SlideShare a Scribd company logo
arXiv:2405.04560v1
[astro-ph.IM]
7
May
2024
Draft version May 9, 2024
Typeset using L
A
TEX default style in AASTeX63
Detectability of Solar Panels as a Technosignature
Ravi Kopparapu,1, 2, 3
Vincent Kofman,1, 2, 4
Jacob Haqq-Misra,5, 3
Vivaswan Kopparapu,6
and Manasvi Lingam7
1NASA Goddard Space Flight Center, 8800 Greenbelt Road, Greenbelt, MD 20771, USA
2SEEC, Sellers Exoplanet Environment Collaboration, NASA Goddard Space Flight Center, 8800 Greenbelt Road, Greenbelt, MD 20771,
USA
3CHAMPs, Consortium on Habitability and Atmospheres of M-dwarf Planets
4American University, 4400 Massachusetts Avenue, NW, Washington, DC, 20016, USA
5Blue Marble Space Institute of Science, Seattle, WA, USA
6Atholton High School, Columbia, MD 21044, USA
7Department of Aerospace, Physics and Space Sciences, Florida Institute of Technology, Melbourne, FL 32901, USA
Submitted to ApJ
ABSTRACT
In this work, we assess the potential detectability of solar panels made of silicon on an Earth-like
exoplanet as a potential technosignature. Silicon-based photovoltaic cells have high reflectance in the
UV-VIS and in the near-IR, within the wavelength range of a space-based flagship mission concept
like the Habitable Worlds Observatory (HWO). Assuming that only solar energy is used to provide
the 2022 human energy needs with a land cover of ∼ 2.4%, and projecting the future energy demand
assuming various growth-rate scenarios, we assess the detectability with an 8 m HWO-like telescope.
Assuming the most favorable viewing orientation, and focusing on the strong absorption edge in the
ultraviolet-to-visible (0.34 − 0.52 µm), we find that several 100s of hours of observation time is needed
to reach a SNR of 5 for an Earth-like planet around a Sun-like star at 10pc, even with a solar panel
coverage of ∼ 23% land coverage of a future Earth. We discuss the necessity of concepts like Kardeshev
Type I/II civilizations and Dyson spheres, which would aim to harness vast amounts of energy. Even
with much larger populations than today, the total energy use of human civilization would be orders of
magnitude below the threshold for causing direct thermal heating or reaching the scale of a Kardashev
Type I civilization. Any extraterrrestrial civilization that likewise achieves sustainable population
levels may also find a limit on its need to expand, which suggests that a galaxy-spanning civilization
as imagined in the Fermi paradox may not exist.
Keywords: Exoplanet atmospheric composition, technosignatures
1. INTRODUCTION
The search for extraterrestrial life has primarily focused on detecting biosignatures, which are remote obser-
vations of atmospheric or ground-based spectral features that indicate signs of life on an exoplanet. More re-
cently, “technosignatures” referring to any observational manifestations of extraterrestrial technology that could
be detected or inferred through astronomical searches has received increased attention (Tarter 2007). While the
search for extra-terrestrial intelligence (SETI) through radio observations has been popular for decades, recent stud-
ies have proposed alternate searches for technosignatures in the UV to mid-infrared part of the spectrum: see
NASA Technosignatures Workshop Participants (2018); Lingam & Loeb (2019, 2021); Socas-Navarro et al. (2021);
Haqq-Misra et al. (2022c) for a comprehensive description.
Specifically, methods to detect technosignatures through spectral signatures from exoplanets have been proposed
as a means to utilize existing techniques and telescope facilities. These include nitrogen dioxide (NO2) pollu-
Corresponding author: Ravi Kopparapu
ravikumar.kopparapu@nasa.gov
2 Kopparapu et al.
tion (Kopparapu et al. 2021), fluorinated compounds such as chloroflorocarbons (CFCs, Owen 1980; Lin et al. 2014;
Haqq-Misra et al. 2022b), or nitrogen trifluoride (NF3) and sulfur hexafluoride (SF6) (Seager et al. 2023), night-side
city lights (Beatty 2022) and agricultural signatures on exoplanets (Haqq-Misra et al. 2022a). In this work, we focus
on another potential technosignature: silicon solar panels.
Technological civilizations may harness their host star’s radiation for their energy needs, just like our civilization has
commenced with large scale solar photovoltaics. Most solar cells use silicon in different forms. Lingam & Loeb (2017)
outlined three primary motivations for employing silicon-based solar panels, which might be broadly applicable. The
first is the relatively high cosmic abundance of silicon compared to the elements utilized in other types of photovoltaics
such as germanium, gallium, or arsenic. Second, the electronic structure of silicon (specifically its band gap) is well-
suited for harnessing the radiation emitted by Sun-like stars (Rühle 2016). Third, silicon is also cost effective in terms
of refining, processing and manufacturing solar cells (Bazilian et al. 2013).1
Based on these arguments, Lingam & Loeb (2017) suggest that the existence of large-scale silicon solar cells could
produce artificial spectral “edges” in some UV wavelength bands when observing the atmosphere of an exoplanet in
reflected spectroscopy because of the steep change in the reflectance of silicon. This artificial spectral edge may be sim-
ilar to the vegetation red “edge” (VRE) seen between 0.70−0.75 µm that can be noticed in the reflected light spectrum
of Earth (Sagan et al. 1993; Arnold et al. 2002; Woolf et al. 2002). The “edge” refers to the noticeable increase in the
reflectance of the material under consideration when a reflected light spectrum is taken of the planet. In the VRE
case, the high reflectance arises due to the contrast between chlorophyll absorption at red wavelengths (0.65–0.70 µm)
and the scattering properties of the cellular and leaf structures at NIR wavelengths (0.75 − 1.1 µm): see, for exam-
ple, Seager et al. (2005); Turnbull et al. (2006); Schwieterman et al. (2018); O’Malley-James & Kaltenegger (2018) for
more details. Detecting VRE on an exoplanet would provide contextual information about the type of widespread
biological life (e.g., autotrophy), and corresponding atmospheric properties relevant for habitability. Lingam & Loeb
(2017) suggest that a similar artificial edge, if manifested, could provide some contextual information about the kind
of technological activity on a planet.
Could we detect surface reflectance features of solar panels on exoplanets as technosignatures? While Lingam & Loeb
(2017) suggested this possibility, they did not conduct any quantitative assessment of their detectablity. In this work,
we will consider the detectability of solar panels on an Earth-like planet around a Sun-like star with a LUVOIR-B (8
meter) class space telescope. The paper is structured as following: §2 discusses the methods and models used in this
work. In §3, we estimate the area of land that would need to be covered to provide human civilization with its energy
needs today and in future scenarios. The potential detectability is then assessed in §4. A discussion section and a
summary of our findings follows in §5.
2. METHODS
The methods to assess the detectability of photovoltaics as a signature for the presence of advanced civilizations
are described here. In order to constrain the spectral signal, the following needs to be assessed: 1) The reflectivity
of photovoltaics panels. 2) The panels need to be included in a suitable location on an Earth-ground map 3) The
spectroscopic signal from the panels need to be compared to simulations without the panels, and the signal-to-noise
that can be attributed to the panels should be computed.
2.1. Silicon and the reflectivity as as spectral signature
Pure silicon is not as well-suited (as a material) to be used in a photovoltaic cell since it is highly reflective in the
ultraviolet-to-visible range. As electric energy is generated by absorbing a photon to promote an electron across the
PN junction, any light that is reflected leads to a reduction in efficiency. To minimize reflection of light, photovoltaic
cells are either subjected to texturing (Campbell & Green 1987; Macdonald et al. 2004; Kim et al. 2020) or coated in
anti-reflective coatings, often TiO2 or Si3N4 (Zhao & Green 1991; Raut et al. 2011; Sarkın et al. 2020); the coating
results in the typical dark color seen on solar panels.
In the scenario with the above anti-reflective coating, the artificial edge is still apparent, but less pronounced and
deeper in the ultraviolet (with respect to pure silicon), when realistic materials are assumed for photovoltaic cells. For
this work, the reflectance spectrum shown in Fig. 1 is adopted. This explains a major source of divergence between
Lingam & Loeb (2017) and our work, because the former emphasized greater surface coverage by pure silicon solar
1 https://www.energy.gov/eere/solar/solar-photovoltaic-cell-basics
Silicon Technosignatures 3
panels that could compensate for reduced efficiency, whereas we consider potentially more realistic photovoltaic cells
endowed with higher efficiency, thereby warranting lower coverage.
2.2. Generating the surface model containing solar panels
Based on the estimated surface area required for the current energy use discussed in §3, a ground map is generated
that hosts roughly 2.4% of land coverage. The Sahara desert was fiducially chosen to host the solar panels. This region
is both close to the equator, where a comparatively greater amount of solar energy would be available throughout the
year, and has minimal cloud coverage. However, dust storms are also prevalent, and have been increasing in frequency
over the past four decades (see Fig.4, Varga 2020). Average events are ∼ 20 per year with varying severity. Such
events may reduce the available sunlight, further restricting the energy generated. We recognize and caution that no
significant area of the Earth is uninhabited, and even the placement of solar farms in seemingly barren deserts has
been contentious due to the destruction of the extremely fragile ecosystems that may consequently arise. However,
our goal in this work is to assess the detectability of solar panels on an exoplanet, and as such, the most “optimal”
land location in term of solar energy generation is chosen for this purpose.
The ground surface model that is used for this study is based on the data products from the moderate resolution
imaging spectroradiometer (MODIS), which is hosted on both the Terra and AQUA satellites operated by NASA
Goddard Space Flight Center2
. The MODIS-MCD12C1 maps provide yearly average coverage at high spatial resolution
of 18 different land types across the entire planet. For this paper, ground coverage is reduced to 5 different types: ocean,
snow/ice, grass, forest, and bare soil. The spatial resolution is binned down to 2.5 by 2 degree (longitude/latitude).
The ground albedo, or the fraction of light that is reflected as a function of wavelength for the different surface types,
are adopted from the United States Geological Survey database (Kokaly et al. 2017). Subsequently, solar panels are
added as a sixth category, which are described with the reflectivity from RELAB (Reflectance Experiments Laboratory
(Pieters & Hiroi 2004), and placed on the surface map at the chosen locations.
2.3. Assessing the contribution to the reflectivity from silicon
In order for a spectral feature to be detectable, it needs to satisfy two conditions. It has to be sufficiently strong,
and its spectral signal needs to uniquely identifiable with the source molecule or in this case, ground coverage. The
detectability of photovoltaic panels was proposed to be in the UV-VIS region of the spectrum, which is the range
where the spectral feature of the panels are most uniquely identifiable. The infrared region is not suitable because
the difference in the reflectivity here does not correspond to a spectrally unique feature: the features overlap with
much stronger signals from the other surface components. This study is constructed so as to focus on the maximum
detectability of the technosignature. This does not indicate that the signal may be fully uniquely attributed to
the panels, which would require a follow-up study utilizing retrieval methods and an exhaustive search for possible
overlapping signals (i.e. Rayleigh scattering, absorption by O3 or hazes). The first step in assessing the detectability
is finding the potential signal strength in the most optimistic case, which is pursued here.
It should also be noted that the placement of the panels in the desert is fortunate in terms of the detectability as
well, because from the ground coverage components shown in Fig.1, the contrast exhibited with soil is the second
highest (after snow/ice).
3. PHOTOVOLTAIC REQUIREMENTS FOR EARTH
At present, the power density (i.e., power generated per unit ground area) of solar energy is estimated to be
5.4 W m−2
(Miller & Keith 2018). Ignoring the effect on a habitable planet environment, if the total land area of
Earth3
is 149 ×106
km2
, then the total power that could be generated if all the land were covered by solar panels
would be 5.4 W m−2
× 149 × 106
km2
= 804 Tera Watts, or 25,374 exajoules per year. In 2022, the world power
consumption from all primary energy sources (including commercially-traded fuels and modern renewables used to
generate electricity) was 604 exajoules.4
Clearly, all land need not be covered: only ∼ 2.4% of land coverage by solar
panels would be needed to match the world energy consumption in 2022.
Figure 2 shows historic annual world energy use in Joules, and projected energy usage under various growth-rate
scenarios. This plot is similar to the growth rate figure shown in Mullan & Haqq-Misra (2019), where the authors
2 https://modis.gsfc.nasa.gov/about/
3 https://ourworldindata.org/land-use
4 Page 8, “Primary energy consumption”, https://www.energyinst.org/statistical-review
4 Kopparapu et al.
0.25 0.50 0.75 1.00 1.25 1.50 1.75 2.00
Wavelength in microns
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
Reflectance
Soil
Forest
Ocean
Snow
Grass
Silicon
Figure 1. Reflectance of different surface components on a planet as a function of wavelength. The reflectance
of silicon-based photovoltaics is shown as dashed curve. The ground model is based on the data from MODIS dataset
https://modis.gsfc.nasa.gov/about/. The solar cell reflectivity data is from RELAB (Reflectance Experiments Laboratory
(Pieters & Hiroi 2004).
discussed the implications of population growth as related to the energy usage. Two data sets are shown: one from
the Organization for Economic Cooperation and Development (OECD) data5
from 1850–2015, and another curve from
the Energy Institute6
from 1965–2022. The purpose of representing both datasets is to show that the two datasets
generally agree, apart from a small systematic difference. Projected energy usage in 2030 is based on estimates from
the US Energy Information Administration7
(678×1015
Btu ≈ 715 exajoules), and the corresponding land coverage
needed (2.8%) to power the world entirely on solar panels is also shown.
Future projections are shown in Figure 2 by assuming scenarios of constant growth of 7% yr−1
, 2.6% yr−1
, 2% yr−1
,
and 1% yr−1
based on the 2022 world energy consumption estimate of 604 exajoules from the Energy Institute, and
assuming a fixed solar power density value of 5.4 W m−2
. The historical period from 1850–2022 shows an average
growth rate of about 2.6% yr−1
, although this growth rate decreased to about 2% yr−1
during the more recent 1965–
2022 period. A growth rate of 7% yr−1
was used by Von Hoerner (1975) in a previous analysis of limits to growth;
such a projection was consistent with the more rapid growth rate observed from the period of about 1950–1975. These
scenarios, along with a more conservative 1% yr−1
scenario and a toy logistic scenario, serve to illustrate the range
and inherent uncertainties in making such projections about the future.
Figure 2 also indicates the point on each projection where the energy demands would require a solar panel coverage
of 23% of Earth’s land—about the size of Africa—with an annual energy use of 5840 exajoules. This magnitude of
energy use would occur by 2056 for the 7% yr−1
scenario, by 2110 for the 2.6% yr−1
scenario, by 2137 for the 2% yr−1
scenario, and by 2250 for the 1% yr−1
scenario. The idea of covering such a large fraction of Earth’s surface with
solar panels would inevitably have many undesirable consequences on climate and local environments; nevertheless,
this 23% land coverage limit will be used as an upper limit in the detectability calculations in §4.
It is also worth noting that the energy output from 23% land coverage would far surpass that required to provide
all people with a high standard of living. The analysis by Jackson et al. (2022) found that human well-being may
peak at a per capita energy use of 75 gigajoules per person,8
so the 5840 exajoules generated by 23% land coverage
would be more than adequate to sustain a population of 10 billion people (corresponding to 750 exajoules, or 3% land
coverage)—which is approximately the maximum human population predicted by most United Nations models. For
5 https://www.oecd-ilibrary.org/energy/primary-energy-supply/indicator/english 1b33c15a-en
6 Page 8, “Primary energy consumption” https://www.energyinst.org/statistical-review
7 https://www.eia.gov/outlooks/archive/ieo09/world.html
8 Many other studies have also concluded that an annual energy consumption of . 100 GJ per person should suffice to achieve a high standard
of living (Arto et al. 2016; Millward-Hopkins et al. 2020; Vogel et al. 2021).
Silicon Technosignatures 5
Figure 2. Historic and projected annual world energy use in Joules (left axis) and in the corresponding fraction of Earth’s land
coverage by solar panels that would be required (right axis). Historic data are from the OECD (1850–2015, grey) and Energy
Institute (1965-2022, black). The historic 2022 value is shown in an open circle and a projection for 2030 from the US Energy
Information Administration is shown as a filled circle. Colored lines show future projections with constant growth at 7% yr−1
(green), 2.6% yr−1
(yellow), 2% yr−1
(blue), and 1% yr−1
(red). A hypothetical scenario of 23% land coverage by solar panels is
shown as open squares on each of these four future projections. An additional Toy logistic projection (violet) follows a 1% yr−1
growth rate up to the maximum energy use required to sustain a population of 30 billion people at a high standard of living,
with the maximum value of the logistic function shown as an open triangle. Horizontal dashed grey lines indicate threshold
values for causing direct heating of Earth’s atmosphere (∼ 1023
and reaching the Kardashev Type I limit (i.e. harvesting all
available solar energy). Calculations assume a fixed 5.4 W m−2
solar panel power density.
the purpose of illustration in this study, the energy use of a human population of 30 billion people (2250 exajoules,
8.9% land coverage) is used as the upper bound of the toy logistic function in Figure 2. This toy logistic function
serves to demonstrate the possibility of a nonlinear trajectory in future energy use, which may even reach a stable
equilibrium. For human civilization today, it is encouraging to consider the possibility that 8.9% solar panel coverage
of Earth’s land—approximately the size of China and India combined—would be more than enough to provide a high
quality of life in the future. The implications of this possibility for technosignatures will be discussed in §5.
4. DETECTABILITY REQUIREMENTS FOR PHOTOVOLTAICS
We performed simulations with the Planetary Spectrum Generator (PSG: Villanueva et al. 2018, 2022) to generate
reflected light spectra, and then calculated the required signal-to-noise ratio (SNR) to detect the signature of solar
panels in the 0.34 µm–0.52 µm range, which overlaps with the UV and optical spectral region for HWO. We selected
this particular region because of the following reason: Fig. 1 shows that the reflectance of Silicon solar panel has
peaks below ∼ 0.4 µm and between 1-2 µm. However, these signatures strongly overlap with features from other
surface materials. Any change in the coverage of solar panels will be obscured by changes in the relative amount of
ocean versus soil or vegetation coverage, as can be see in Fig. 3. Fig. 3a shows the spectral contrast ratio versus
wavelength for different viewing angles from the point of view of an observer. The contrast ratio is greater than 1
because we are presuming a coronagraph which blocks most of the starlight. The changes in the spectra beyond 0.8 µm
are predominantly changes in the reflectivity of the ground coverage. Any contribution from the silicon is blended into
the overall spectra in this wavelength region; note that the overlap of the silicon features with molecular absorption
features is not the focus of our investigation. Our analysis provides an upper limit to the signal that may originate
6 Kopparapu et al.
from photovoltaic panels. The potential overlap with molecular features would be the next step in the investigation
in case the signal would be detectable.
Fig. 3b shows the SNR values of different land coverage of solar panels as a function of observation time for a
8m HWO-like telescope. The model instrument set is similar to the LUVOIR concept study telescope, as the design
of HWO mission is currently ongoing. As both LUVOIR-B and the HWO are concepts for off-axis telescopes, the
LUVOIR-B concept is the current best approximation. It has an internal coronagraph with the key goal of direct
exoplanet observations (Juanola-Parramon et al. 2022). It is equipped with three channels: NUV (0.2–0.525 µm),
visible (0.515–1.030 µm) and NIR (1.0–2.0 µm). The NUV channel is capable of high-contrast imaging only, with an
effective spectral resolution of R∼ 7. The optical channel contains an imaging camera and integral field spectrograph
(IFS) with R=140. The planet is kept at a quadrature phase (in our simulation, an orbital phase angle of 270◦
). This
is an Earth-like planet at an Earth-like distance around a Sun-like star at distance of 10 pc.
The wavelength dependent SNR is calculated as the difference between the spectra with and without the solar panels
divided by the noise simulated by PSG for the instrument under consideration (see section 5.3 of Villanueva et al.
(2018), chapter 8 in Villanueva et al. (2022), and also the PSG website,9
where the noise model is discussed in detail).
The “net SNR” is calculated by summing the squares of the individual SNRs at each wavelength within a given band
(either NUV or VIS), and then taking the square root. This methodology is largely robust to SNR, as long as the
feature is resolved by the spectrum. The SNR is calculated at different longitudinal views of an Earth-like planet from
observer’s view point. Only three longitudinal views are shown for illustrative purpose. A 0◦
longitude represents
a viewing angle where the placement of the solar cells are only visible partially from the observer’s view point. A
315◦
longitudinal view indicates the placement of solar cells in almost the full view of the observer. A 90◦
longitude
represents a viewing angle where solar cells are not visible to the observer.
Fig. 3b indicates that even with the most ambitious land coverage (≈ 23%), and with a favorable viewing perspective
to the observer (planet longitude of 315◦
), it would take several hundred hours of observation time in reflected light
spectra with an 8 m size telescope to reach SNR ∼ 5 (solid purple curve). This result can be understood from inspecting
Fig. 4, where the spectra in planet-star contrast ratio are plotted for three cases: 2.4% (blue solid), 23% (red solid) and
zero (dashed green) land coverage of silicon panels. Because we have chosen the 0.34 µm–0.52 µm range to calculate
the impact of silicon panels on the reflectance spectra, the difference between a planet with and without silicon is not
markedly different, even with 23% land cover, as can be seen from Fig. 4. This suggests that the artificial silicon
edge suggested by Lingam & Loeb (2017) may not be detectable. The discrepancy partly stems from the choice of
photovoltaic cell properties, as indicated in Section 2.1, because the reflectance of realistic solar cells is less pronounced
than pure silicon, the latter of which was evaluated in Lingam & Loeb (2017). A larger coverage than 23% would result
in slightly lower observation times; however, refer to Section 5 for the implications of larger coverage by photovoltaic
cells.
5. DISCUSSION
The results from the previous section seem to indicate that even ambitious deployment of solar panels (constructed
with silicon and hosting anti-reflective coatings) covering a significant land area of an Earth-like exoplanet may not be
enough to be detectable with a 8 m HWO-like telescope. These calculations presumed a fixed-present day efficiency
for solar panels, so any technological improvements in efficiency would only decrease the required land coverage, and
consequently decrease detectability.
Lingam & Loeb (2017) conjectured that tidally locked planets around M-dwarfs might be a suitable place to start
looking for photovoltaic cells. Unfortunately, due to the close proximity of planets in the habitable zone around M-
dwarfs – which poses issue for spatially resolving the planet – currently there is no technological pathway to directly
observing these types of planets. In the case that this setup would be possible though, the detectability of the silicon
UV edge on planets around M-dwarfs would be further diminished, since the stellar emission in the relevant range
(0.34 − 0.52 µm) is significantly lower.
Note that we have performed all of the SNR calculations based on an orbital phase angle of 270◦
with edge-on
orbital configuration (i.e., inclination = 90◦
). Additional calculations varying the phase angle, varying the inclination
angle, and so forth are needed to fully assess the potential detectability. Furthermore, we have not explored the
extent of the effect of varying mirror size on the SNR, or a different stellar host spectral type (like a K-dwarf star).
9 https://psg.gsfc.nasa.gov/helpmodel.php
Silicon Technosignatures 7
0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8
Wavelength (micron)
0
0.2
0.4
0.6
0.8
1
1.2
1.4
contrast
(planet/star)
23% land cover of solar panels
Longitude 0
Longitude 90
Longitude 315
(a)
0 500 1000 1500 2000
Observation time (hours)
0
1
2
3
4
5
6
7
8
SNR
23% land cover, Long0
2.4% land cover, Long0
2.4% land cover Long90
23% land cover Long90
2.4% Land cover Long315
23% land cover Long315
(b)
Figure 3. (a) Reflectance spectra (expressed in terms of the planet to star contrast ratio) for different planetary orientations
with respect to the observer for a 23% land cover of solar panels. We choose the 0.34−0.52µm range to estimate the detectability
of Si-based solar panels, as discussed in §4 and shown in Fig.1. Within this range, there is a noticeable difference in the spectra,
which contributes to higher SNR for an observing longitude of 315◦
(fully visible panel coverage). (b) SNR of detecting silicon
solar panels as a function of observation time with a 8m class LUVOIR-B-like telescope for different orientations of the planet
towards the observer. A longitudinal orientation of 315◦
yields a higher SNR because the solar panels on the planet are better
oriented towards the observer, as compared to a longitude of 90◦
(partially visible).
0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8
Wavelength (micron)
0
0.2
0.4
0.6
0.8
1
1.2
1.4
contrast
(planet/star)
2.4% land cover
23% land cover
No silicon
Figure 4. Planet-star contrast ratio as a function of wavelength for 2.4% (blue solid), 23% (red solid) and 0% (green dashed)
land coverage of solar panels. The planet longitudinal orientation is 315◦
, where the solar panels are oriented towards the
observer. Only the 23% land cover displays any significant variation in the spectrum. This trend is also manifested in the SNR
curve of Fig.3, where the maximum SNR is obtained for a 23% land cover oriented at 315◦
planet longitude.
Berdyugina & Kuhn (2019) generated composite maps of orbiting photovoltaic power sources if they were situated
around a planet like Proxima Centauri b. Specific simulations and the corresponding SNR estimates relevant for HWO
from such orbiting structures needs to be undertaken. These additional considerations are left for future work.
8 Kopparapu et al.
As Earth remains the only example of an inhabited planet with a technosphere, future trajectories of Earth can
provide insight into the constraints that might also apply to extraterrestrial technospheres. It is worth reiterating
that only 3% land coverage by solar panels would be needed to support a population of 10 billion people at a high
standard of living, and the toy logistic curve shown in Figure 2 indicates that even a population of 30 billion people at
a high standard of living would require far less energy than the power output of the 23% land coverage scenario used in
these detectability calculations. These estimates not only do not account for increased efficiency due to technological
innovations, but they also do not account for other sources of energy. Hence, the actual solar requirements for Earth
would likely be much reduced, especially in case controlled nuclear fusion becomes viable. For Earth, these results
suggest the possibility of a future in which the energy needs of even a larger-than-predicted population could be fully
met with known technology.
If Earth is taken as an example in the search for technosignatures, then this raises the question: Is the large-scale
deployment of solar panels on a planetary surface ever needed? Any actual large-scale deployment would certainly
raise numerous issues regarding the feasibility of such a deployment or the logistical challenges in global distribution of
energy, but a more fundamental unknown is whether a technological civilization would ever require such large energy
demands to justify a scenario such as 23% land coverage or greater. Several of the projections shown in Figure 2
reach a time at which dissipation from energy use exceeds the threshold for contributing significant direct heating to
Earth’s climate (∼ 3 × 1023
J), which occurs in the year 2265 for the 2.6% yr−1
growth rate scenario and 2338 for
the 2% yr−1
growth rate scenario. Yet, it is not evident that such vast energy requirements will ever be necessary on
Earth: the energy requirements for the global human population to afford a high standard of living fall several orders
of magnitude below the direct heating threshold. The motivation to prevent direct heating of the atmosphere may
serve as an additional deterrent to avoid such scenarios, and further suggests that only modest-scale deployment of
solar panels would ever be needed to achieve sustainable development goals on Earth.
Speculating even further shows that these scenario projections will reach the limit of a Kardashev Type I civilization
(Kardashev 1964), which is a civilization that uses all available energy on its planet (i.e., all starlight incident at
the top of the atmosphere). This Type I threshold (∼ 5 × 1024
J) occurs in the year 2377 for the 2.6% yr−1
growth
rate scenario and 2482 for the 2% yr−1
growth rate scenario. The equivalent land area required to meet such energy
demands with solar power exceeds 100% in these cases, which indicate that other sources of power—possibly including
space-based solar power—would be required in these scenarios. Such speculative scenarios suggest images of “Dyson
spheres/swarms” (e.g., Dyson 1960; Wright 2020) of solar collectors that expand a civilization’s ability to capture the
energy output of its host star.
Kardashev (1964) even imagined a Type II civilization as one that utilizes the entirety of its host star’s output;
however, such speculations are based primarily on the assumption of a fixed growth rate in world energy use. But
such vast energy reserves would be unnecessary even under cases of substantial population growth, especially if fusion
and other renewable sources are available to supplement solar energy. The concept of a Type I or Type II civilization
then becomes an exercise in imagining the possible uses that a civilization would have for such vast energy reserves.
Even activities such as large-scale physics experiments and (relativistic) interstellar space travel (cf. Lingam & Loeb
2021, Chapter 10) might not be enough to explain the need for a civilization to harness a significant fraction of its
entire planetary or stellar output. In contrast, if human civilization can meet its own energy demands with only a
modest deployment of solar panels, then this expectation might also suggest that concepts like Dyson spheres would
be rendered unnecessary in other technospheres.
These results also have implications for the problem known as the Fermi paradox (Webb 2015; Ćirković 2018; Forgan
2019) or Great Silence (Brin 1983): if extraterrestrial expansion through the galaxy is relatively easy, then where are
they? In the context of limits to growth, the recognition that human civilization could reach a sustainable equilibrium
in its population and energy use that falls well below the Type I threshold suggests that extraterrestrial civilizations
may not be compelled to expand for reasons of subsistence. This conclusion mirrors the “sustainability solution”
to the Fermi paradox (e.g., Haqq-Misra & Baum 2009; Mullan & Haqq-Misra 2019), which suggests that any extant
extraterrestrial civilizations only expand proportionally with their planet’s carrying capacity. Any civilization that is
able to achieve sustainable population levels with high standard of living may also settle on a limit on any need to
expand, which may likewise constrain the magnitude of any potential technosignatures generated by such a civilization.
Underlying this discussion are two competing philosophical positions regarding the tendency of life to expand. The
first position assumes that (a) life will evolve to utilize the maximum energy available in its environment, while the
second assumes that (b) life will evolve to utilize as much energy as needed in its environment to reach an optimal level
Silicon Technosignatures 9
of existence. To the extent that the environment will always impose thermodynamic limits, the second option (b) may
probably be favored by life. But does life tend to expand up to such thermodynamic limits if unopposed, or will life
tend to optimize its consumption of resources rather than maximize them? Such interdisciplinary questions highlight
the intersection of technosignature science with concepts from ecology (e.g., Meurer et al. 2024), and further scrutiny
of the proposed general tendency of life to expand may be useful for thinking about and enivisioning the particular
tendencies for technospheres to expand.
6. CONCLUSION
We analyzed the detectability of silicon-based solar panels (with anti-reflective coatings) as a signature of extrater-
restrial technology. Assuming a 8-meter HWO-like telescope, focusing on the reflection edge in the UV-VIS, and
considering varying land coverage of solar panels on an Earth-like exoplanet that match the present and projected
energy needs, we estimate that several hundreds of hours of observation time is needed to reach a SNR of ∼ 5 for a
high land coverage of ∼ 23%.
We subsequently assessed the need for the deployment of such large-scale solar panels, taking into consideration
various projected growth rates of future energy consumption. We find that, even with significant population growth,
the energy needs of human civilization would be several orders of magnitude below the energy threshold for a Kardashev
Type I civilization, or a Dyson sphere/swarm which harnesses the energy of a star. This line of inquiry reexamines
the utility of such concepts, and potentially addresses one crucial aspect of the Fermi paradox: we have not discovered
any large scale engineering yet, conceivably because advanced technologies may not need them.
ACKNOWLEDGMENTS
J.H.M., M.L., and R.K.K. gratefully acknowledge support from the NASA Exobiology program under grant
80NSSC22K1009. The authors also acknowledge support from the Goddard Space Flight Center (GSFC) Sellers
Exoplanet Environments Collaboration (SEEC), which is supported by the NASA Planetary Science Division’s Re-
search Program. Any opinions, findings, and conclusions or recommendations expressed in this material are those of
the authors and do not necessarily reflect the views of their employers or NASA.
REFERENCES
Arnold, L., Gillet, S., Lardière, O., Riaud, P., & Schneider,
J. 2002, Astronomy & Astrophysics, 392, 231
Arto, I., Capellán-Pérez, I., Lago, R., Bueno, G., &
Bermejo, R. 2016, Energy for Sustainable Development,
33, 1
Bazilian, M., Onyeji, I., Liebreich, M., et al. 2013,
Renewable Energy, 53, 329
Beatty, T. G. 2022, Monthly Notices of the Royal
Astronomical Society, 513, 2652
Berdyugina, S., & Kuhn, J. 2019, The Astronomical
Journal, 158, 246
Brin, G. D. 1983, Quarterly Journal of the Royal
Astronomical Society, Vol. 24, NO. 3, P. 283-309, 1983,
24, 283
Campbell, P., & Green, M. A. 1987, Journal of Applied
Physics, 62, 243, doi: 10.1063/1.339189
Ćirković, M. M. 2018, The great silence: Science and
philosophy of Fermi’s paradox (Oxford University Press)
Dyson, F. J. 1960, Science, 131, 1667
Forgan, D. H. 2019, Solving Fermi’s paradox, Vol. 10
(Cambridge University Press)
Haqq-Misra, J., & Baum, S. 2009, Journal of the British
Interplanetary Society, 62, 47
Haqq-Misra, J., Fauchez, T. J., Schwieterman, E. W., &
Kopparapu, R. 2022a, The Astrophysical Journal Letters,
929, L28
Haqq-Misra, J., Kopparapu, R., Fauchez, T. J., et al.
2022b, The Planetary Science Journal, 3, 60
Haqq-Misra, J., Schwieterman, E. W., Socas-Navarro, H.,
et al. 2022c, Acta Astronautica, 198, 194
Jackson, R. B., Ahlström, A., Hugelius, G., et al. 2022,
Ecosphere, 13, e3978
Juanola-Parramon, R., Zimmerman, N. T., Pueyo, L., et al.
2022, Journal of Astronomical Telescopes, Instruments,
and Systems, 8, 034001, doi: 10.1117/1.JATIS.8.3.034001
Kardashev, N. S. 1964, Soviet Ast., 8, 217
Kim, M. S., Lee, J. H., & Kwak, M. K. 2020, International
Journal of Precision Engineering and Manufacturing, 21,
1389
10 Kopparapu et al.
Kokaly, R. F., Clark, R. N., Swayze, G. A., et al. 2017,
USGS Spectral Library Version 7, Tech. Rep. 1035, U.S.
Geological Survey, doi: 10.3133/ds1035
Kopparapu, R., Arney, G., Haqq-Misra, J., Lustig-Yaeger,
J., & Villanueva, G. 2021, The Astrophysical Journal,
908, 164
Lin, H. W., Gonzalez Abad, G., & Loeb, A. 2014, ApJL,
792, L7, doi: 10.1088/2041-8205/792/1/L7
Lingam, M., & Loeb, A. 2017, MNRAS, 470, L82,
doi: 10.1093/mnrasl/slx084
—. 2019, Astrobiology, 19, 28, doi: 10.1089/ast.2018.1936
—. 2021, Life in the Cosmos: From Biosignatures to
Technosignatures (Cambridge: Harvard University Press)
Macdonald, D. H., Cuevas, A., Kerr, M. J., et al. 2004,
Solar Energy, 76, 277, doi: 10.1016/j.solener.2003.08.019
Meurer, J. C., Haqq-Misra, J., & de Souza Mendonça, M.
2024, International Journal of Astrobiology, 23, e3
Miller, L. M., & Keith, D. W. 2018, Environmental
Research Letters, 13, 104008
Millward-Hopkins, J., Steinberger, J. K., Rao, N. D., &
Oswald, Y. 2020, Global Environmental Change, 65,
102168
Mullan, B., & Haqq-Misra, J. 2019, Futures, 106, 4
NASA Technosignatures Workshop Participants. 2018,
arXiv e-prints, arXiv:1812.08681,
doi: 10.48550/arXiv.1812.08681
O’Malley-James, J. T., & Kaltenegger, L. 2018,
Astrobiology, 18, 1123
Owen, T. 1980, in Strategies for the Search for Life in the
Universe (Springer), 177–185
Pieters, C. M., & Hiroi, T. 2004, in Lunar and Planetary
Science Conference, ed. S. Mackwell & E. Stansbery,
Lunar and Planetary Science Conference, 1720
Raut, H. K., Ganesh, V. A., Nair, A. S., & Ramakrishna, S.
2011, Energy & Environmental Science, 4, 3779
Rühle, S. 2016, Solar Energy, 130, 139,
doi: 10.1016/j.solener.2016.02.015
Sagan, C., Thompson, W. R., Carlson, R., Gurnett, D., &
Hord, C. 1993, Nature, 365, 715
Sarkın, A. S., Ekren, N., & Sağlam, Ş. 2020, Solar Energy,
199, 63, doi: 10.1016/j.solener.2020.01.084
Schwieterman, E. W., Kiang, N. Y., Parenteau, M. N., et al.
2018, Astrobiology, 18, 663, doi: 10.1089/ast.2017.1729
Seager, S., Petkowski, J. J., Huang, J., et al. 2023, Scientific
Reports, 13, 13576
Seager, S., Turner, E. L., Schafer, J., & Ford, E. B. 2005,
Astrobiology, 5, 372, doi: 10.1089/ast.2005.5.372
Socas-Navarro, H., Haqq-Misra, J., Wright, J. T., et al.
2021, Acta Astronaut., 182, 446,
doi: 10.1016/j.actaastro.2021.02.029
Tarter, J. C. 2007, Highlights of Astronomy, 14, 14,
doi: 10.1017/S1743921307009829
Turnbull, M. C., Traub, W. A., Jucks, K. W., et al. 2006,
The Astrophysical Journal, 644, 551
Varga, G. 2020, Environment international, 139, 105712
Villanueva, G. L., Liuzzi, G., Faggi, S., et al. 2022,
Fundamentals of the Planetary Spectrum Generator
(Greenbelt, Maryland: NASA Goddard Space Flight
Center)
Villanueva, G. L., Smith, M. D., Protopapa, S., Faggi, S., &
Mandell, A. M. 2018, JQSRT, 217, 86,
doi: 10.1016/j.jqsrt.2018.05.023
Vogel, J., Steinberger, J. K., O’Neill, D. W., Lamb, W. F.,
& Krishnakumar, J. 2021, Global Environmental Change,
69, 102287
Von Hoerner, S. J. 1975, Journal of the British
Interplanetary Society, 28, 691
Webb, S. 2015, If the universe is teeming with aliens...
where is everybody?: seventy-five solutions to the fermi
paradox and the problem of extraterrestrial life
(Springer)
Woolf, N. J., Smith, P. S., Traub, W. A., & Jucks, K. W.
2002, The Astrophysical Journal, 574, 430
Wright, J. T. 2020, Serbian Astronomical Journal, 1
Zhao, J., & Green, M. A. 1991, IEEE Transactions on
Electron Devices, 38, 1925, doi: 10.1109/16.119035
This figure "cg_throughput.png" is available in "png" format from:
http://arxiv.org/ps/2405.04560v1
This figure "counts.png" is available in "png" format from:
http://arxiv.org/ps/2405.04560v1
0.5 1.0 1.5 2.0 2.5
Wavelength in microns[um]
0.12
0.14
0.16
0.18
0.20
0.22
Reflectance

More Related Content

Similar to Detectability of Solar Panels as a Technosignature

GRIPS_first_flight_2016
GRIPS_first_flight_2016GRIPS_first_flight_2016
GRIPS_first_flight_2016
Nicole Duncan
 
Iaetsd rf controlled sailing robot for oceanic missions
Iaetsd rf controlled sailing robot for oceanic missionsIaetsd rf controlled sailing robot for oceanic missions
Iaetsd rf controlled sailing robot for oceanic missions
Iaetsd Iaetsd
 
Wireless+power+transmission+via+solar+power+satellite
Wireless+power+transmission+via+solar+power+satelliteWireless+power+transmission+via+solar+power+satellite
Wireless+power+transmission+via+solar+power+satellite
niteshmishra05
 
Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...
Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...
Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...
Sérgio Sacani
 
Aa15425 10
Aa15425 10Aa15425 10
Aa15425 10
Sérgio Sacani
 
The Possible Tidal Demise of Kepler’s First Planetary System
The Possible Tidal Demise of Kepler’s First Planetary SystemThe Possible Tidal Demise of Kepler’s First Planetary System
The Possible Tidal Demise of Kepler’s First Planetary System
Sérgio Sacani
 
Major mergers host_the_most_luminous_red_quasars_at_z2_a_hubble_space_telesco...
Major mergers host_the_most_luminous_red_quasars_at_z2_a_hubble_space_telesco...Major mergers host_the_most_luminous_red_quasars_at_z2_a_hubble_space_telesco...
Major mergers host_the_most_luminous_red_quasars_at_z2_a_hubble_space_telesco...
Sérgio Sacani
 
Geoelectric energy
Geoelectric energyGeoelectric energy
Geoelectric energy
oilandgas24
 
E0371025028
E0371025028E0371025028
E0371025028
ijceronline
 
SPACE BASED SOLAR POWER (2019)
SPACE BASED SOLAR POWER (2019)SPACE BASED SOLAR POWER (2019)
SPACE BASED SOLAR POWER (2019)
anjana_rasheed
 
Simulation of the Earth’s radio-leakage from mobile towers as seen from selec...
Simulation of the Earth’s radio-leakage from mobile towers as seen from selec...Simulation of the Earth’s radio-leakage from mobile towers as seen from selec...
Simulation of the Earth’s radio-leakage from mobile towers as seen from selec...
Sérgio Sacani
 
Intra cluster light_at_the_frontier_abell_2744
Intra cluster light_at_the_frontier_abell_2744Intra cluster light_at_the_frontier_abell_2744
Intra cluster light_at_the_frontier_abell_2744
Sérgio Sacani
 
The exceptional soft_x_ray_halo_of_the_galaxy_merger_ngc6240
The exceptional soft_x_ray_halo_of_the_galaxy_merger_ngc6240The exceptional soft_x_ray_halo_of_the_galaxy_merger_ngc6240
The exceptional soft_x_ray_halo_of_the_galaxy_merger_ngc6240
Sérgio Sacani
 
2583
25832583
2583
loyalj
 
An almost dark galaxy with the mass of the Small Magellanic Cloud
An almost dark galaxy with the mass of the Small Magellanic CloudAn almost dark galaxy with the mass of the Small Magellanic Cloud
An almost dark galaxy with the mass of the Small Magellanic Cloud
Sérgio Sacani
 
Satellite based solar power using witricity
Satellite based solar power using witricitySatellite based solar power using witricity
Satellite based solar power using witricity
shiyabuddin Gk
 
power transmismission via solar power satellite
power transmismission via solar power satellitepower transmismission via solar power satellite
power transmismission via solar power satellite
Doddoji Adharvana
 
A Simultaneous dual-site technosignature search using international LOFAR sta...
A Simultaneous dual-site technosignature search using international LOFAR sta...A Simultaneous dual-site technosignature search using international LOFAR sta...
A Simultaneous dual-site technosignature search using international LOFAR sta...
Sérgio Sacani
 
Aa17123 11
Aa17123 11Aa17123 11
Aa17123 11
Sérgio Sacani
 
A new spin_of_the_first_stars
A new spin_of_the_first_starsA new spin_of_the_first_stars
A new spin_of_the_first_stars
Sérgio Sacani
 

Similar to Detectability of Solar Panels as a Technosignature (20)

GRIPS_first_flight_2016
GRIPS_first_flight_2016GRIPS_first_flight_2016
GRIPS_first_flight_2016
 
Iaetsd rf controlled sailing robot for oceanic missions
Iaetsd rf controlled sailing robot for oceanic missionsIaetsd rf controlled sailing robot for oceanic missions
Iaetsd rf controlled sailing robot for oceanic missions
 
Wireless+power+transmission+via+solar+power+satellite
Wireless+power+transmission+via+solar+power+satelliteWireless+power+transmission+via+solar+power+satellite
Wireless+power+transmission+via+solar+power+satellite
 
Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...
Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...
Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...
 
Aa15425 10
Aa15425 10Aa15425 10
Aa15425 10
 
The Possible Tidal Demise of Kepler’s First Planetary System
The Possible Tidal Demise of Kepler’s First Planetary SystemThe Possible Tidal Demise of Kepler’s First Planetary System
The Possible Tidal Demise of Kepler’s First Planetary System
 
Major mergers host_the_most_luminous_red_quasars_at_z2_a_hubble_space_telesco...
Major mergers host_the_most_luminous_red_quasars_at_z2_a_hubble_space_telesco...Major mergers host_the_most_luminous_red_quasars_at_z2_a_hubble_space_telesco...
Major mergers host_the_most_luminous_red_quasars_at_z2_a_hubble_space_telesco...
 
Geoelectric energy
Geoelectric energyGeoelectric energy
Geoelectric energy
 
E0371025028
E0371025028E0371025028
E0371025028
 
SPACE BASED SOLAR POWER (2019)
SPACE BASED SOLAR POWER (2019)SPACE BASED SOLAR POWER (2019)
SPACE BASED SOLAR POWER (2019)
 
Simulation of the Earth’s radio-leakage from mobile towers as seen from selec...
Simulation of the Earth’s radio-leakage from mobile towers as seen from selec...Simulation of the Earth’s radio-leakage from mobile towers as seen from selec...
Simulation of the Earth’s radio-leakage from mobile towers as seen from selec...
 
Intra cluster light_at_the_frontier_abell_2744
Intra cluster light_at_the_frontier_abell_2744Intra cluster light_at_the_frontier_abell_2744
Intra cluster light_at_the_frontier_abell_2744
 
The exceptional soft_x_ray_halo_of_the_galaxy_merger_ngc6240
The exceptional soft_x_ray_halo_of_the_galaxy_merger_ngc6240The exceptional soft_x_ray_halo_of_the_galaxy_merger_ngc6240
The exceptional soft_x_ray_halo_of_the_galaxy_merger_ngc6240
 
2583
25832583
2583
 
An almost dark galaxy with the mass of the Small Magellanic Cloud
An almost dark galaxy with the mass of the Small Magellanic CloudAn almost dark galaxy with the mass of the Small Magellanic Cloud
An almost dark galaxy with the mass of the Small Magellanic Cloud
 
Satellite based solar power using witricity
Satellite based solar power using witricitySatellite based solar power using witricity
Satellite based solar power using witricity
 
power transmismission via solar power satellite
power transmismission via solar power satellitepower transmismission via solar power satellite
power transmismission via solar power satellite
 
A Simultaneous dual-site technosignature search using international LOFAR sta...
A Simultaneous dual-site technosignature search using international LOFAR sta...A Simultaneous dual-site technosignature search using international LOFAR sta...
A Simultaneous dual-site technosignature search using international LOFAR sta...
 
Aa17123 11
Aa17123 11Aa17123 11
Aa17123 11
 
A new spin_of_the_first_stars
A new spin_of_the_first_starsA new spin_of_the_first_stars
A new spin_of_the_first_stars
 

More from Sérgio Sacani

Signatures of wave erosion in Titan’s coasts
Signatures of wave erosion in Titan’s coastsSignatures of wave erosion in Titan’s coasts
Signatures of wave erosion in Titan’s coasts
Sérgio Sacani
 
SDSS1335+0728: The awakening of a ∼ 106M⊙ black hole⋆
SDSS1335+0728: The awakening of a ∼ 106M⊙ black hole⋆SDSS1335+0728: The awakening of a ∼ 106M⊙ black hole⋆
SDSS1335+0728: The awakening of a ∼ 106M⊙ black hole⋆
Sérgio Sacani
 
Discovery of An Apparent Red, High-Velocity Type Ia Supernova at 𝐳 = 2.9 wi...
Discovery of An Apparent Red, High-Velocity Type Ia Supernova at  𝐳 = 2.9  wi...Discovery of An Apparent Red, High-Velocity Type Ia Supernova at  𝐳 = 2.9  wi...
Discovery of An Apparent Red, High-Velocity Type Ia Supernova at 𝐳 = 2.9 wi...
Sérgio Sacani
 
Evidence of Jet Activity from the Secondary Black Hole in the OJ 287 Binary S...
Evidence of Jet Activity from the Secondary Black Hole in the OJ 287 Binary S...Evidence of Jet Activity from the Secondary Black Hole in the OJ 287 Binary S...
Evidence of Jet Activity from the Secondary Black Hole in the OJ 287 Binary S...
Sérgio Sacani
 
Candidate young stellar objects in the S-cluster: Kinematic analysis of a sub...
Candidate young stellar objects in the S-cluster: Kinematic analysis of a sub...Candidate young stellar objects in the S-cluster: Kinematic analysis of a sub...
Candidate young stellar objects in the S-cluster: Kinematic analysis of a sub...
Sérgio Sacani
 
JAMES WEBB STUDY THE MASSIVE BLACK HOLE SEEDS
JAMES WEBB STUDY THE MASSIVE BLACK HOLE SEEDSJAMES WEBB STUDY THE MASSIVE BLACK HOLE SEEDS
JAMES WEBB STUDY THE MASSIVE BLACK HOLE SEEDS
Sérgio Sacani
 
Anti-Universe And Emergent Gravity and the Dark Universe
Anti-Universe And Emergent Gravity and the Dark UniverseAnti-Universe And Emergent Gravity and the Dark Universe
Anti-Universe And Emergent Gravity and the Dark Universe
Sérgio Sacani
 
The binding of cosmological structures by massless topological defects
The binding of cosmological structures by massless topological defectsThe binding of cosmological structures by massless topological defects
The binding of cosmological structures by massless topological defects
Sérgio Sacani
 
EWOCS-I: The catalog of X-ray sources in Westerlund 1 from the Extended Weste...
EWOCS-I: The catalog of X-ray sources in Westerlund 1 from the Extended Weste...EWOCS-I: The catalog of X-ray sources in Westerlund 1 from the Extended Weste...
EWOCS-I: The catalog of X-ray sources in Westerlund 1 from the Extended Weste...
Sérgio Sacani
 
The debris of the ‘last major merger’ is dynamically young
The debris of the ‘last major merger’ is dynamically youngThe debris of the ‘last major merger’ is dynamically young
The debris of the ‘last major merger’ is dynamically young
Sérgio Sacani
 
Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...
Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...
Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...
Sérgio Sacani
 
THE IMPORTANCE OF MARTIAN ATMOSPHERE SAMPLE RETURN.
THE IMPORTANCE OF MARTIAN ATMOSPHERE SAMPLE RETURN.THE IMPORTANCE OF MARTIAN ATMOSPHERE SAMPLE RETURN.
THE IMPORTANCE OF MARTIAN ATMOSPHERE SAMPLE RETURN.
Sérgio Sacani
 
Multi-source connectivity as the driver of solar wind variability in the heli...
Multi-source connectivity as the driver of solar wind variability in the heli...Multi-source connectivity as the driver of solar wind variability in the heli...
Multi-source connectivity as the driver of solar wind variability in the heli...
Sérgio Sacani
 
Gliese 12 b: A Temperate Earth-sized Planet at 12 pc Ideal for Atmospheric Tr...
Gliese 12 b: A Temperate Earth-sized Planet at 12 pc Ideal for Atmospheric Tr...Gliese 12 b: A Temperate Earth-sized Planet at 12 pc Ideal for Atmospheric Tr...
Gliese 12 b: A Temperate Earth-sized Planet at 12 pc Ideal for Atmospheric Tr...
Sérgio Sacani
 
Gliese 12 b, a temperate Earth-sized planet at 12 parsecs discovered with TES...
Gliese 12 b, a temperate Earth-sized planet at 12 parsecs discovered with TES...Gliese 12 b, a temperate Earth-sized planet at 12 parsecs discovered with TES...
Gliese 12 b, a temperate Earth-sized planet at 12 parsecs discovered with TES...
Sérgio Sacani
 
The importance of continents, oceans and plate tectonics for the evolution of...
The importance of continents, oceans and plate tectonics for the evolution of...The importance of continents, oceans and plate tectonics for the evolution of...
The importance of continents, oceans and plate tectonics for the evolution of...
Sérgio Sacani
 
A Giant Impact Origin for the First Subduction on Earth
A Giant Impact Origin for the First Subduction on EarthA Giant Impact Origin for the First Subduction on Earth
A Giant Impact Origin for the First Subduction on Earth
Sérgio Sacani
 
Climate extremes likely to drive land mammal extinction during next supercont...
Climate extremes likely to drive land mammal extinction during next supercont...Climate extremes likely to drive land mammal extinction during next supercont...
Climate extremes likely to drive land mammal extinction during next supercont...
Sérgio Sacani
 
Constraints on Neutrino Natal Kicks from Black-Hole Binary VFTS 243
Constraints on Neutrino Natal Kicks from Black-Hole Binary VFTS 243Constraints on Neutrino Natal Kicks from Black-Hole Binary VFTS 243
Constraints on Neutrino Natal Kicks from Black-Hole Binary VFTS 243
Sérgio Sacani
 
Jet reorientation in central galaxies of clusters and groups: insights from V...
Jet reorientation in central galaxies of clusters and groups: insights from V...Jet reorientation in central galaxies of clusters and groups: insights from V...
Jet reorientation in central galaxies of clusters and groups: insights from V...
Sérgio Sacani
 

More from Sérgio Sacani (20)

Signatures of wave erosion in Titan’s coasts
Signatures of wave erosion in Titan’s coastsSignatures of wave erosion in Titan’s coasts
Signatures of wave erosion in Titan’s coasts
 
SDSS1335+0728: The awakening of a ∼ 106M⊙ black hole⋆
SDSS1335+0728: The awakening of a ∼ 106M⊙ black hole⋆SDSS1335+0728: The awakening of a ∼ 106M⊙ black hole⋆
SDSS1335+0728: The awakening of a ∼ 106M⊙ black hole⋆
 
Discovery of An Apparent Red, High-Velocity Type Ia Supernova at 𝐳 = 2.9 wi...
Discovery of An Apparent Red, High-Velocity Type Ia Supernova at  𝐳 = 2.9  wi...Discovery of An Apparent Red, High-Velocity Type Ia Supernova at  𝐳 = 2.9  wi...
Discovery of An Apparent Red, High-Velocity Type Ia Supernova at 𝐳 = 2.9 wi...
 
Evidence of Jet Activity from the Secondary Black Hole in the OJ 287 Binary S...
Evidence of Jet Activity from the Secondary Black Hole in the OJ 287 Binary S...Evidence of Jet Activity from the Secondary Black Hole in the OJ 287 Binary S...
Evidence of Jet Activity from the Secondary Black Hole in the OJ 287 Binary S...
 
Candidate young stellar objects in the S-cluster: Kinematic analysis of a sub...
Candidate young stellar objects in the S-cluster: Kinematic analysis of a sub...Candidate young stellar objects in the S-cluster: Kinematic analysis of a sub...
Candidate young stellar objects in the S-cluster: Kinematic analysis of a sub...
 
JAMES WEBB STUDY THE MASSIVE BLACK HOLE SEEDS
JAMES WEBB STUDY THE MASSIVE BLACK HOLE SEEDSJAMES WEBB STUDY THE MASSIVE BLACK HOLE SEEDS
JAMES WEBB STUDY THE MASSIVE BLACK HOLE SEEDS
 
Anti-Universe And Emergent Gravity and the Dark Universe
Anti-Universe And Emergent Gravity and the Dark UniverseAnti-Universe And Emergent Gravity and the Dark Universe
Anti-Universe And Emergent Gravity and the Dark Universe
 
The binding of cosmological structures by massless topological defects
The binding of cosmological structures by massless topological defectsThe binding of cosmological structures by massless topological defects
The binding of cosmological structures by massless topological defects
 
EWOCS-I: The catalog of X-ray sources in Westerlund 1 from the Extended Weste...
EWOCS-I: The catalog of X-ray sources in Westerlund 1 from the Extended Weste...EWOCS-I: The catalog of X-ray sources in Westerlund 1 from the Extended Weste...
EWOCS-I: The catalog of X-ray sources in Westerlund 1 from the Extended Weste...
 
The debris of the ‘last major merger’ is dynamically young
The debris of the ‘last major merger’ is dynamically youngThe debris of the ‘last major merger’ is dynamically young
The debris of the ‘last major merger’ is dynamically young
 
Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...
Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...
Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...
 
THE IMPORTANCE OF MARTIAN ATMOSPHERE SAMPLE RETURN.
THE IMPORTANCE OF MARTIAN ATMOSPHERE SAMPLE RETURN.THE IMPORTANCE OF MARTIAN ATMOSPHERE SAMPLE RETURN.
THE IMPORTANCE OF MARTIAN ATMOSPHERE SAMPLE RETURN.
 
Multi-source connectivity as the driver of solar wind variability in the heli...
Multi-source connectivity as the driver of solar wind variability in the heli...Multi-source connectivity as the driver of solar wind variability in the heli...
Multi-source connectivity as the driver of solar wind variability in the heli...
 
Gliese 12 b: A Temperate Earth-sized Planet at 12 pc Ideal for Atmospheric Tr...
Gliese 12 b: A Temperate Earth-sized Planet at 12 pc Ideal for Atmospheric Tr...Gliese 12 b: A Temperate Earth-sized Planet at 12 pc Ideal for Atmospheric Tr...
Gliese 12 b: A Temperate Earth-sized Planet at 12 pc Ideal for Atmospheric Tr...
 
Gliese 12 b, a temperate Earth-sized planet at 12 parsecs discovered with TES...
Gliese 12 b, a temperate Earth-sized planet at 12 parsecs discovered with TES...Gliese 12 b, a temperate Earth-sized planet at 12 parsecs discovered with TES...
Gliese 12 b, a temperate Earth-sized planet at 12 parsecs discovered with TES...
 
The importance of continents, oceans and plate tectonics for the evolution of...
The importance of continents, oceans and plate tectonics for the evolution of...The importance of continents, oceans and plate tectonics for the evolution of...
The importance of continents, oceans and plate tectonics for the evolution of...
 
A Giant Impact Origin for the First Subduction on Earth
A Giant Impact Origin for the First Subduction on EarthA Giant Impact Origin for the First Subduction on Earth
A Giant Impact Origin for the First Subduction on Earth
 
Climate extremes likely to drive land mammal extinction during next supercont...
Climate extremes likely to drive land mammal extinction during next supercont...Climate extremes likely to drive land mammal extinction during next supercont...
Climate extremes likely to drive land mammal extinction during next supercont...
 
Constraints on Neutrino Natal Kicks from Black-Hole Binary VFTS 243
Constraints on Neutrino Natal Kicks from Black-Hole Binary VFTS 243Constraints on Neutrino Natal Kicks from Black-Hole Binary VFTS 243
Constraints on Neutrino Natal Kicks from Black-Hole Binary VFTS 243
 
Jet reorientation in central galaxies of clusters and groups: insights from V...
Jet reorientation in central galaxies of clusters and groups: insights from V...Jet reorientation in central galaxies of clusters and groups: insights from V...
Jet reorientation in central galaxies of clusters and groups: insights from V...
 

Recently uploaded

Farming systems analysis: what have we learnt?.pptx
Farming systems analysis: what have we learnt?.pptxFarming systems analysis: what have we learnt?.pptx
Farming systems analysis: what have we learnt?.pptx
Frédéric Baudron
 
CLASS 12th CHEMISTRY SOLID STATE ppt (Animated)
CLASS 12th CHEMISTRY SOLID STATE ppt (Animated)CLASS 12th CHEMISTRY SOLID STATE ppt (Animated)
CLASS 12th CHEMISTRY SOLID STATE ppt (Animated)
eitps1506
 
MICROBIAL INTERACTION PPT/ MICROBIAL INTERACTION AND THEIR TYPES // PLANT MIC...
MICROBIAL INTERACTION PPT/ MICROBIAL INTERACTION AND THEIR TYPES // PLANT MIC...MICROBIAL INTERACTION PPT/ MICROBIAL INTERACTION AND THEIR TYPES // PLANT MIC...
MICROBIAL INTERACTION PPT/ MICROBIAL INTERACTION AND THEIR TYPES // PLANT MIC...
ABHISHEK SONI NIMT INSTITUTE OF MEDICAL AND PARAMEDCIAL SCIENCES , GOVT PG COLLEGE NOIDA
 
Compexometric titration/Chelatorphy titration/chelating titration
Compexometric titration/Chelatorphy titration/chelating titrationCompexometric titration/Chelatorphy titration/chelating titration
Compexometric titration/Chelatorphy titration/chelating titration
Vandana Devesh Sharma
 
Alternate Wetting and Drying - Climate Smart Agriculture
Alternate Wetting and Drying - Climate Smart AgricultureAlternate Wetting and Drying - Climate Smart Agriculture
Alternate Wetting and Drying - Climate Smart Agriculture
International Food Policy Research Institute- South Asia Office
 
在线办理(salfor毕业证书)索尔福德大学毕业证毕业完成信一模一样
在线办理(salfor毕业证书)索尔福德大学毕业证毕业完成信一模一样在线办理(salfor毕业证书)索尔福德大学毕业证毕业完成信一模一样
在线办理(salfor毕业证书)索尔福德大学毕业证毕业完成信一模一样
vluwdy49
 
AJAY KUMAR NIET GreNo Guava Project File.pdf
AJAY KUMAR NIET GreNo Guava Project File.pdfAJAY KUMAR NIET GreNo Guava Project File.pdf
AJAY KUMAR NIET GreNo Guava Project File.pdf
AJAY KUMAR
 
GBSN - Biochemistry (Unit 6) Chemistry of Proteins
GBSN - Biochemistry (Unit 6) Chemistry of ProteinsGBSN - Biochemistry (Unit 6) Chemistry of Proteins
GBSN - Biochemistry (Unit 6) Chemistry of Proteins
Areesha Ahmad
 
Physiology of Nervous System presentation.pptx
Physiology of Nervous System presentation.pptxPhysiology of Nervous System presentation.pptx
Physiology of Nervous System presentation.pptx
fatima132662
 
23PH301 - Optics - Optical Lenses.pptx
23PH301 - Optics  -  Optical Lenses.pptx23PH301 - Optics  -  Optical Lenses.pptx
23PH301 - Optics - Optical Lenses.pptx
RDhivya6
 
Juaristi, Jon. - El canon espanol. El legado de la cultura española a la civi...
Juaristi, Jon. - El canon espanol. El legado de la cultura española a la civi...Juaristi, Jon. - El canon espanol. El legado de la cultura española a la civi...
Juaristi, Jon. - El canon espanol. El legado de la cultura española a la civi...
frank0071
 
LEARNING TO LIVE WITH LAWS OF MOTION .pptx
LEARNING TO LIVE WITH LAWS OF MOTION .pptxLEARNING TO LIVE WITH LAWS OF MOTION .pptx
LEARNING TO LIVE WITH LAWS OF MOTION .pptx
yourprojectpartner05
 
Describing and Interpreting an Immersive Learning Case with the Immersion Cub...
Describing and Interpreting an Immersive Learning Case with the Immersion Cub...Describing and Interpreting an Immersive Learning Case with the Immersion Cub...
Describing and Interpreting an Immersive Learning Case with the Immersion Cub...
Leonel Morgado
 
Sexuality - Issues, Attitude and Behaviour - Applied Social Psychology - Psyc...
Sexuality - Issues, Attitude and Behaviour - Applied Social Psychology - Psyc...Sexuality - Issues, Attitude and Behaviour - Applied Social Psychology - Psyc...
Sexuality - Issues, Attitude and Behaviour - Applied Social Psychology - Psyc...
PsychoTech Services
 
cathode ray oscilloscope and its applications
cathode ray oscilloscope and its applicationscathode ray oscilloscope and its applications
cathode ray oscilloscope and its applications
sandertein
 
Randomised Optimisation Algorithms in DAPHNE
Randomised Optimisation Algorithms in DAPHNERandomised Optimisation Algorithms in DAPHNE
Randomised Optimisation Algorithms in DAPHNE
University of Maribor
 
Immersive Learning That Works: Research Grounding and Paths Forward
Immersive Learning That Works: Research Grounding and Paths ForwardImmersive Learning That Works: Research Grounding and Paths Forward
Immersive Learning That Works: Research Grounding and Paths Forward
Leonel Morgado
 
Pests of Storage_Identification_Dr.UPR.pdf
Pests of Storage_Identification_Dr.UPR.pdfPests of Storage_Identification_Dr.UPR.pdf
Pests of Storage_Identification_Dr.UPR.pdf
PirithiRaju
 
Introduction_Ch_01_Biotech Biotechnology course .pptx
Introduction_Ch_01_Biotech Biotechnology course .pptxIntroduction_Ch_01_Biotech Biotechnology course .pptx
Introduction_Ch_01_Biotech Biotechnology course .pptx
QusayMaghayerh
 
ESA/ACT Science Coffee: Diego Blas - Gravitational wave detection with orbita...
ESA/ACT Science Coffee: Diego Blas - Gravitational wave detection with orbita...ESA/ACT Science Coffee: Diego Blas - Gravitational wave detection with orbita...
ESA/ACT Science Coffee: Diego Blas - Gravitational wave detection with orbita...
Advanced-Concepts-Team
 

Recently uploaded (20)

Farming systems analysis: what have we learnt?.pptx
Farming systems analysis: what have we learnt?.pptxFarming systems analysis: what have we learnt?.pptx
Farming systems analysis: what have we learnt?.pptx
 
CLASS 12th CHEMISTRY SOLID STATE ppt (Animated)
CLASS 12th CHEMISTRY SOLID STATE ppt (Animated)CLASS 12th CHEMISTRY SOLID STATE ppt (Animated)
CLASS 12th CHEMISTRY SOLID STATE ppt (Animated)
 
MICROBIAL INTERACTION PPT/ MICROBIAL INTERACTION AND THEIR TYPES // PLANT MIC...
MICROBIAL INTERACTION PPT/ MICROBIAL INTERACTION AND THEIR TYPES // PLANT MIC...MICROBIAL INTERACTION PPT/ MICROBIAL INTERACTION AND THEIR TYPES // PLANT MIC...
MICROBIAL INTERACTION PPT/ MICROBIAL INTERACTION AND THEIR TYPES // PLANT MIC...
 
Compexometric titration/Chelatorphy titration/chelating titration
Compexometric titration/Chelatorphy titration/chelating titrationCompexometric titration/Chelatorphy titration/chelating titration
Compexometric titration/Chelatorphy titration/chelating titration
 
Alternate Wetting and Drying - Climate Smart Agriculture
Alternate Wetting and Drying - Climate Smart AgricultureAlternate Wetting and Drying - Climate Smart Agriculture
Alternate Wetting and Drying - Climate Smart Agriculture
 
在线办理(salfor毕业证书)索尔福德大学毕业证毕业完成信一模一样
在线办理(salfor毕业证书)索尔福德大学毕业证毕业完成信一模一样在线办理(salfor毕业证书)索尔福德大学毕业证毕业完成信一模一样
在线办理(salfor毕业证书)索尔福德大学毕业证毕业完成信一模一样
 
AJAY KUMAR NIET GreNo Guava Project File.pdf
AJAY KUMAR NIET GreNo Guava Project File.pdfAJAY KUMAR NIET GreNo Guava Project File.pdf
AJAY KUMAR NIET GreNo Guava Project File.pdf
 
GBSN - Biochemistry (Unit 6) Chemistry of Proteins
GBSN - Biochemistry (Unit 6) Chemistry of ProteinsGBSN - Biochemistry (Unit 6) Chemistry of Proteins
GBSN - Biochemistry (Unit 6) Chemistry of Proteins
 
Physiology of Nervous System presentation.pptx
Physiology of Nervous System presentation.pptxPhysiology of Nervous System presentation.pptx
Physiology of Nervous System presentation.pptx
 
23PH301 - Optics - Optical Lenses.pptx
23PH301 - Optics  -  Optical Lenses.pptx23PH301 - Optics  -  Optical Lenses.pptx
23PH301 - Optics - Optical Lenses.pptx
 
Juaristi, Jon. - El canon espanol. El legado de la cultura española a la civi...
Juaristi, Jon. - El canon espanol. El legado de la cultura española a la civi...Juaristi, Jon. - El canon espanol. El legado de la cultura española a la civi...
Juaristi, Jon. - El canon espanol. El legado de la cultura española a la civi...
 
LEARNING TO LIVE WITH LAWS OF MOTION .pptx
LEARNING TO LIVE WITH LAWS OF MOTION .pptxLEARNING TO LIVE WITH LAWS OF MOTION .pptx
LEARNING TO LIVE WITH LAWS OF MOTION .pptx
 
Describing and Interpreting an Immersive Learning Case with the Immersion Cub...
Describing and Interpreting an Immersive Learning Case with the Immersion Cub...Describing and Interpreting an Immersive Learning Case with the Immersion Cub...
Describing and Interpreting an Immersive Learning Case with the Immersion Cub...
 
Sexuality - Issues, Attitude and Behaviour - Applied Social Psychology - Psyc...
Sexuality - Issues, Attitude and Behaviour - Applied Social Psychology - Psyc...Sexuality - Issues, Attitude and Behaviour - Applied Social Psychology - Psyc...
Sexuality - Issues, Attitude and Behaviour - Applied Social Psychology - Psyc...
 
cathode ray oscilloscope and its applications
cathode ray oscilloscope and its applicationscathode ray oscilloscope and its applications
cathode ray oscilloscope and its applications
 
Randomised Optimisation Algorithms in DAPHNE
Randomised Optimisation Algorithms in DAPHNERandomised Optimisation Algorithms in DAPHNE
Randomised Optimisation Algorithms in DAPHNE
 
Immersive Learning That Works: Research Grounding and Paths Forward
Immersive Learning That Works: Research Grounding and Paths ForwardImmersive Learning That Works: Research Grounding and Paths Forward
Immersive Learning That Works: Research Grounding and Paths Forward
 
Pests of Storage_Identification_Dr.UPR.pdf
Pests of Storage_Identification_Dr.UPR.pdfPests of Storage_Identification_Dr.UPR.pdf
Pests of Storage_Identification_Dr.UPR.pdf
 
Introduction_Ch_01_Biotech Biotechnology course .pptx
Introduction_Ch_01_Biotech Biotechnology course .pptxIntroduction_Ch_01_Biotech Biotechnology course .pptx
Introduction_Ch_01_Biotech Biotechnology course .pptx
 
ESA/ACT Science Coffee: Diego Blas - Gravitational wave detection with orbita...
ESA/ACT Science Coffee: Diego Blas - Gravitational wave detection with orbita...ESA/ACT Science Coffee: Diego Blas - Gravitational wave detection with orbita...
ESA/ACT Science Coffee: Diego Blas - Gravitational wave detection with orbita...
 

Detectability of Solar Panels as a Technosignature

  • 1. arXiv:2405.04560v1 [astro-ph.IM] 7 May 2024 Draft version May 9, 2024 Typeset using L A TEX default style in AASTeX63 Detectability of Solar Panels as a Technosignature Ravi Kopparapu,1, 2, 3 Vincent Kofman,1, 2, 4 Jacob Haqq-Misra,5, 3 Vivaswan Kopparapu,6 and Manasvi Lingam7 1NASA Goddard Space Flight Center, 8800 Greenbelt Road, Greenbelt, MD 20771, USA 2SEEC, Sellers Exoplanet Environment Collaboration, NASA Goddard Space Flight Center, 8800 Greenbelt Road, Greenbelt, MD 20771, USA 3CHAMPs, Consortium on Habitability and Atmospheres of M-dwarf Planets 4American University, 4400 Massachusetts Avenue, NW, Washington, DC, 20016, USA 5Blue Marble Space Institute of Science, Seattle, WA, USA 6Atholton High School, Columbia, MD 21044, USA 7Department of Aerospace, Physics and Space Sciences, Florida Institute of Technology, Melbourne, FL 32901, USA Submitted to ApJ ABSTRACT In this work, we assess the potential detectability of solar panels made of silicon on an Earth-like exoplanet as a potential technosignature. Silicon-based photovoltaic cells have high reflectance in the UV-VIS and in the near-IR, within the wavelength range of a space-based flagship mission concept like the Habitable Worlds Observatory (HWO). Assuming that only solar energy is used to provide the 2022 human energy needs with a land cover of ∼ 2.4%, and projecting the future energy demand assuming various growth-rate scenarios, we assess the detectability with an 8 m HWO-like telescope. Assuming the most favorable viewing orientation, and focusing on the strong absorption edge in the ultraviolet-to-visible (0.34 − 0.52 µm), we find that several 100s of hours of observation time is needed to reach a SNR of 5 for an Earth-like planet around a Sun-like star at 10pc, even with a solar panel coverage of ∼ 23% land coverage of a future Earth. We discuss the necessity of concepts like Kardeshev Type I/II civilizations and Dyson spheres, which would aim to harness vast amounts of energy. Even with much larger populations than today, the total energy use of human civilization would be orders of magnitude below the threshold for causing direct thermal heating or reaching the scale of a Kardashev Type I civilization. Any extraterrrestrial civilization that likewise achieves sustainable population levels may also find a limit on its need to expand, which suggests that a galaxy-spanning civilization as imagined in the Fermi paradox may not exist. Keywords: Exoplanet atmospheric composition, technosignatures 1. INTRODUCTION The search for extraterrestrial life has primarily focused on detecting biosignatures, which are remote obser- vations of atmospheric or ground-based spectral features that indicate signs of life on an exoplanet. More re- cently, “technosignatures” referring to any observational manifestations of extraterrestrial technology that could be detected or inferred through astronomical searches has received increased attention (Tarter 2007). While the search for extra-terrestrial intelligence (SETI) through radio observations has been popular for decades, recent stud- ies have proposed alternate searches for technosignatures in the UV to mid-infrared part of the spectrum: see NASA Technosignatures Workshop Participants (2018); Lingam & Loeb (2019, 2021); Socas-Navarro et al. (2021); Haqq-Misra et al. (2022c) for a comprehensive description. Specifically, methods to detect technosignatures through spectral signatures from exoplanets have been proposed as a means to utilize existing techniques and telescope facilities. These include nitrogen dioxide (NO2) pollu- Corresponding author: Ravi Kopparapu ravikumar.kopparapu@nasa.gov
  • 2. 2 Kopparapu et al. tion (Kopparapu et al. 2021), fluorinated compounds such as chloroflorocarbons (CFCs, Owen 1980; Lin et al. 2014; Haqq-Misra et al. 2022b), or nitrogen trifluoride (NF3) and sulfur hexafluoride (SF6) (Seager et al. 2023), night-side city lights (Beatty 2022) and agricultural signatures on exoplanets (Haqq-Misra et al. 2022a). In this work, we focus on another potential technosignature: silicon solar panels. Technological civilizations may harness their host star’s radiation for their energy needs, just like our civilization has commenced with large scale solar photovoltaics. Most solar cells use silicon in different forms. Lingam & Loeb (2017) outlined three primary motivations for employing silicon-based solar panels, which might be broadly applicable. The first is the relatively high cosmic abundance of silicon compared to the elements utilized in other types of photovoltaics such as germanium, gallium, or arsenic. Second, the electronic structure of silicon (specifically its band gap) is well- suited for harnessing the radiation emitted by Sun-like stars (Rühle 2016). Third, silicon is also cost effective in terms of refining, processing and manufacturing solar cells (Bazilian et al. 2013).1 Based on these arguments, Lingam & Loeb (2017) suggest that the existence of large-scale silicon solar cells could produce artificial spectral “edges” in some UV wavelength bands when observing the atmosphere of an exoplanet in reflected spectroscopy because of the steep change in the reflectance of silicon. This artificial spectral edge may be sim- ilar to the vegetation red “edge” (VRE) seen between 0.70−0.75 µm that can be noticed in the reflected light spectrum of Earth (Sagan et al. 1993; Arnold et al. 2002; Woolf et al. 2002). The “edge” refers to the noticeable increase in the reflectance of the material under consideration when a reflected light spectrum is taken of the planet. In the VRE case, the high reflectance arises due to the contrast between chlorophyll absorption at red wavelengths (0.65–0.70 µm) and the scattering properties of the cellular and leaf structures at NIR wavelengths (0.75 − 1.1 µm): see, for exam- ple, Seager et al. (2005); Turnbull et al. (2006); Schwieterman et al. (2018); O’Malley-James & Kaltenegger (2018) for more details. Detecting VRE on an exoplanet would provide contextual information about the type of widespread biological life (e.g., autotrophy), and corresponding atmospheric properties relevant for habitability. Lingam & Loeb (2017) suggest that a similar artificial edge, if manifested, could provide some contextual information about the kind of technological activity on a planet. Could we detect surface reflectance features of solar panels on exoplanets as technosignatures? While Lingam & Loeb (2017) suggested this possibility, they did not conduct any quantitative assessment of their detectablity. In this work, we will consider the detectability of solar panels on an Earth-like planet around a Sun-like star with a LUVOIR-B (8 meter) class space telescope. The paper is structured as following: §2 discusses the methods and models used in this work. In §3, we estimate the area of land that would need to be covered to provide human civilization with its energy needs today and in future scenarios. The potential detectability is then assessed in §4. A discussion section and a summary of our findings follows in §5. 2. METHODS The methods to assess the detectability of photovoltaics as a signature for the presence of advanced civilizations are described here. In order to constrain the spectral signal, the following needs to be assessed: 1) The reflectivity of photovoltaics panels. 2) The panels need to be included in a suitable location on an Earth-ground map 3) The spectroscopic signal from the panels need to be compared to simulations without the panels, and the signal-to-noise that can be attributed to the panels should be computed. 2.1. Silicon and the reflectivity as as spectral signature Pure silicon is not as well-suited (as a material) to be used in a photovoltaic cell since it is highly reflective in the ultraviolet-to-visible range. As electric energy is generated by absorbing a photon to promote an electron across the PN junction, any light that is reflected leads to a reduction in efficiency. To minimize reflection of light, photovoltaic cells are either subjected to texturing (Campbell & Green 1987; Macdonald et al. 2004; Kim et al. 2020) or coated in anti-reflective coatings, often TiO2 or Si3N4 (Zhao & Green 1991; Raut et al. 2011; Sarkın et al. 2020); the coating results in the typical dark color seen on solar panels. In the scenario with the above anti-reflective coating, the artificial edge is still apparent, but less pronounced and deeper in the ultraviolet (with respect to pure silicon), when realistic materials are assumed for photovoltaic cells. For this work, the reflectance spectrum shown in Fig. 1 is adopted. This explains a major source of divergence between Lingam & Loeb (2017) and our work, because the former emphasized greater surface coverage by pure silicon solar 1 https://www.energy.gov/eere/solar/solar-photovoltaic-cell-basics
  • 3. Silicon Technosignatures 3 panels that could compensate for reduced efficiency, whereas we consider potentially more realistic photovoltaic cells endowed with higher efficiency, thereby warranting lower coverage. 2.2. Generating the surface model containing solar panels Based on the estimated surface area required for the current energy use discussed in §3, a ground map is generated that hosts roughly 2.4% of land coverage. The Sahara desert was fiducially chosen to host the solar panels. This region is both close to the equator, where a comparatively greater amount of solar energy would be available throughout the year, and has minimal cloud coverage. However, dust storms are also prevalent, and have been increasing in frequency over the past four decades (see Fig.4, Varga 2020). Average events are ∼ 20 per year with varying severity. Such events may reduce the available sunlight, further restricting the energy generated. We recognize and caution that no significant area of the Earth is uninhabited, and even the placement of solar farms in seemingly barren deserts has been contentious due to the destruction of the extremely fragile ecosystems that may consequently arise. However, our goal in this work is to assess the detectability of solar panels on an exoplanet, and as such, the most “optimal” land location in term of solar energy generation is chosen for this purpose. The ground surface model that is used for this study is based on the data products from the moderate resolution imaging spectroradiometer (MODIS), which is hosted on both the Terra and AQUA satellites operated by NASA Goddard Space Flight Center2 . The MODIS-MCD12C1 maps provide yearly average coverage at high spatial resolution of 18 different land types across the entire planet. For this paper, ground coverage is reduced to 5 different types: ocean, snow/ice, grass, forest, and bare soil. The spatial resolution is binned down to 2.5 by 2 degree (longitude/latitude). The ground albedo, or the fraction of light that is reflected as a function of wavelength for the different surface types, are adopted from the United States Geological Survey database (Kokaly et al. 2017). Subsequently, solar panels are added as a sixth category, which are described with the reflectivity from RELAB (Reflectance Experiments Laboratory (Pieters & Hiroi 2004), and placed on the surface map at the chosen locations. 2.3. Assessing the contribution to the reflectivity from silicon In order for a spectral feature to be detectable, it needs to satisfy two conditions. It has to be sufficiently strong, and its spectral signal needs to uniquely identifiable with the source molecule or in this case, ground coverage. The detectability of photovoltaic panels was proposed to be in the UV-VIS region of the spectrum, which is the range where the spectral feature of the panels are most uniquely identifiable. The infrared region is not suitable because the difference in the reflectivity here does not correspond to a spectrally unique feature: the features overlap with much stronger signals from the other surface components. This study is constructed so as to focus on the maximum detectability of the technosignature. This does not indicate that the signal may be fully uniquely attributed to the panels, which would require a follow-up study utilizing retrieval methods and an exhaustive search for possible overlapping signals (i.e. Rayleigh scattering, absorption by O3 or hazes). The first step in assessing the detectability is finding the potential signal strength in the most optimistic case, which is pursued here. It should also be noted that the placement of the panels in the desert is fortunate in terms of the detectability as well, because from the ground coverage components shown in Fig.1, the contrast exhibited with soil is the second highest (after snow/ice). 3. PHOTOVOLTAIC REQUIREMENTS FOR EARTH At present, the power density (i.e., power generated per unit ground area) of solar energy is estimated to be 5.4 W m−2 (Miller & Keith 2018). Ignoring the effect on a habitable planet environment, if the total land area of Earth3 is 149 ×106 km2 , then the total power that could be generated if all the land were covered by solar panels would be 5.4 W m−2 × 149 × 106 km2 = 804 Tera Watts, or 25,374 exajoules per year. In 2022, the world power consumption from all primary energy sources (including commercially-traded fuels and modern renewables used to generate electricity) was 604 exajoules.4 Clearly, all land need not be covered: only ∼ 2.4% of land coverage by solar panels would be needed to match the world energy consumption in 2022. Figure 2 shows historic annual world energy use in Joules, and projected energy usage under various growth-rate scenarios. This plot is similar to the growth rate figure shown in Mullan & Haqq-Misra (2019), where the authors 2 https://modis.gsfc.nasa.gov/about/ 3 https://ourworldindata.org/land-use 4 Page 8, “Primary energy consumption”, https://www.energyinst.org/statistical-review
  • 4. 4 Kopparapu et al. 0.25 0.50 0.75 1.00 1.25 1.50 1.75 2.00 Wavelength in microns 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 Reflectance Soil Forest Ocean Snow Grass Silicon Figure 1. Reflectance of different surface components on a planet as a function of wavelength. The reflectance of silicon-based photovoltaics is shown as dashed curve. The ground model is based on the data from MODIS dataset https://modis.gsfc.nasa.gov/about/. The solar cell reflectivity data is from RELAB (Reflectance Experiments Laboratory (Pieters & Hiroi 2004). discussed the implications of population growth as related to the energy usage. Two data sets are shown: one from the Organization for Economic Cooperation and Development (OECD) data5 from 1850–2015, and another curve from the Energy Institute6 from 1965–2022. The purpose of representing both datasets is to show that the two datasets generally agree, apart from a small systematic difference. Projected energy usage in 2030 is based on estimates from the US Energy Information Administration7 (678×1015 Btu ≈ 715 exajoules), and the corresponding land coverage needed (2.8%) to power the world entirely on solar panels is also shown. Future projections are shown in Figure 2 by assuming scenarios of constant growth of 7% yr−1 , 2.6% yr−1 , 2% yr−1 , and 1% yr−1 based on the 2022 world energy consumption estimate of 604 exajoules from the Energy Institute, and assuming a fixed solar power density value of 5.4 W m−2 . The historical period from 1850–2022 shows an average growth rate of about 2.6% yr−1 , although this growth rate decreased to about 2% yr−1 during the more recent 1965– 2022 period. A growth rate of 7% yr−1 was used by Von Hoerner (1975) in a previous analysis of limits to growth; such a projection was consistent with the more rapid growth rate observed from the period of about 1950–1975. These scenarios, along with a more conservative 1% yr−1 scenario and a toy logistic scenario, serve to illustrate the range and inherent uncertainties in making such projections about the future. Figure 2 also indicates the point on each projection where the energy demands would require a solar panel coverage of 23% of Earth’s land—about the size of Africa—with an annual energy use of 5840 exajoules. This magnitude of energy use would occur by 2056 for the 7% yr−1 scenario, by 2110 for the 2.6% yr−1 scenario, by 2137 for the 2% yr−1 scenario, and by 2250 for the 1% yr−1 scenario. The idea of covering such a large fraction of Earth’s surface with solar panels would inevitably have many undesirable consequences on climate and local environments; nevertheless, this 23% land coverage limit will be used as an upper limit in the detectability calculations in §4. It is also worth noting that the energy output from 23% land coverage would far surpass that required to provide all people with a high standard of living. The analysis by Jackson et al. (2022) found that human well-being may peak at a per capita energy use of 75 gigajoules per person,8 so the 5840 exajoules generated by 23% land coverage would be more than adequate to sustain a population of 10 billion people (corresponding to 750 exajoules, or 3% land coverage)—which is approximately the maximum human population predicted by most United Nations models. For 5 https://www.oecd-ilibrary.org/energy/primary-energy-supply/indicator/english 1b33c15a-en 6 Page 8, “Primary energy consumption” https://www.energyinst.org/statistical-review 7 https://www.eia.gov/outlooks/archive/ieo09/world.html 8 Many other studies have also concluded that an annual energy consumption of . 100 GJ per person should suffice to achieve a high standard of living (Arto et al. 2016; Millward-Hopkins et al. 2020; Vogel et al. 2021).
  • 5. Silicon Technosignatures 5 Figure 2. Historic and projected annual world energy use in Joules (left axis) and in the corresponding fraction of Earth’s land coverage by solar panels that would be required (right axis). Historic data are from the OECD (1850–2015, grey) and Energy Institute (1965-2022, black). The historic 2022 value is shown in an open circle and a projection for 2030 from the US Energy Information Administration is shown as a filled circle. Colored lines show future projections with constant growth at 7% yr−1 (green), 2.6% yr−1 (yellow), 2% yr−1 (blue), and 1% yr−1 (red). A hypothetical scenario of 23% land coverage by solar panels is shown as open squares on each of these four future projections. An additional Toy logistic projection (violet) follows a 1% yr−1 growth rate up to the maximum energy use required to sustain a population of 30 billion people at a high standard of living, with the maximum value of the logistic function shown as an open triangle. Horizontal dashed grey lines indicate threshold values for causing direct heating of Earth’s atmosphere (∼ 1023 and reaching the Kardashev Type I limit (i.e. harvesting all available solar energy). Calculations assume a fixed 5.4 W m−2 solar panel power density. the purpose of illustration in this study, the energy use of a human population of 30 billion people (2250 exajoules, 8.9% land coverage) is used as the upper bound of the toy logistic function in Figure 2. This toy logistic function serves to demonstrate the possibility of a nonlinear trajectory in future energy use, which may even reach a stable equilibrium. For human civilization today, it is encouraging to consider the possibility that 8.9% solar panel coverage of Earth’s land—approximately the size of China and India combined—would be more than enough to provide a high quality of life in the future. The implications of this possibility for technosignatures will be discussed in §5. 4. DETECTABILITY REQUIREMENTS FOR PHOTOVOLTAICS We performed simulations with the Planetary Spectrum Generator (PSG: Villanueva et al. 2018, 2022) to generate reflected light spectra, and then calculated the required signal-to-noise ratio (SNR) to detect the signature of solar panels in the 0.34 µm–0.52 µm range, which overlaps with the UV and optical spectral region for HWO. We selected this particular region because of the following reason: Fig. 1 shows that the reflectance of Silicon solar panel has peaks below ∼ 0.4 µm and between 1-2 µm. However, these signatures strongly overlap with features from other surface materials. Any change in the coverage of solar panels will be obscured by changes in the relative amount of ocean versus soil or vegetation coverage, as can be see in Fig. 3. Fig. 3a shows the spectral contrast ratio versus wavelength for different viewing angles from the point of view of an observer. The contrast ratio is greater than 1 because we are presuming a coronagraph which blocks most of the starlight. The changes in the spectra beyond 0.8 µm are predominantly changes in the reflectivity of the ground coverage. Any contribution from the silicon is blended into the overall spectra in this wavelength region; note that the overlap of the silicon features with molecular absorption features is not the focus of our investigation. Our analysis provides an upper limit to the signal that may originate
  • 6. 6 Kopparapu et al. from photovoltaic panels. The potential overlap with molecular features would be the next step in the investigation in case the signal would be detectable. Fig. 3b shows the SNR values of different land coverage of solar panels as a function of observation time for a 8m HWO-like telescope. The model instrument set is similar to the LUVOIR concept study telescope, as the design of HWO mission is currently ongoing. As both LUVOIR-B and the HWO are concepts for off-axis telescopes, the LUVOIR-B concept is the current best approximation. It has an internal coronagraph with the key goal of direct exoplanet observations (Juanola-Parramon et al. 2022). It is equipped with three channels: NUV (0.2–0.525 µm), visible (0.515–1.030 µm) and NIR (1.0–2.0 µm). The NUV channel is capable of high-contrast imaging only, with an effective spectral resolution of R∼ 7. The optical channel contains an imaging camera and integral field spectrograph (IFS) with R=140. The planet is kept at a quadrature phase (in our simulation, an orbital phase angle of 270◦ ). This is an Earth-like planet at an Earth-like distance around a Sun-like star at distance of 10 pc. The wavelength dependent SNR is calculated as the difference between the spectra with and without the solar panels divided by the noise simulated by PSG for the instrument under consideration (see section 5.3 of Villanueva et al. (2018), chapter 8 in Villanueva et al. (2022), and also the PSG website,9 where the noise model is discussed in detail). The “net SNR” is calculated by summing the squares of the individual SNRs at each wavelength within a given band (either NUV or VIS), and then taking the square root. This methodology is largely robust to SNR, as long as the feature is resolved by the spectrum. The SNR is calculated at different longitudinal views of an Earth-like planet from observer’s view point. Only three longitudinal views are shown for illustrative purpose. A 0◦ longitude represents a viewing angle where the placement of the solar cells are only visible partially from the observer’s view point. A 315◦ longitudinal view indicates the placement of solar cells in almost the full view of the observer. A 90◦ longitude represents a viewing angle where solar cells are not visible to the observer. Fig. 3b indicates that even with the most ambitious land coverage (≈ 23%), and with a favorable viewing perspective to the observer (planet longitude of 315◦ ), it would take several hundred hours of observation time in reflected light spectra with an 8 m size telescope to reach SNR ∼ 5 (solid purple curve). This result can be understood from inspecting Fig. 4, where the spectra in planet-star contrast ratio are plotted for three cases: 2.4% (blue solid), 23% (red solid) and zero (dashed green) land coverage of silicon panels. Because we have chosen the 0.34 µm–0.52 µm range to calculate the impact of silicon panels on the reflectance spectra, the difference between a planet with and without silicon is not markedly different, even with 23% land cover, as can be seen from Fig. 4. This suggests that the artificial silicon edge suggested by Lingam & Loeb (2017) may not be detectable. The discrepancy partly stems from the choice of photovoltaic cell properties, as indicated in Section 2.1, because the reflectance of realistic solar cells is less pronounced than pure silicon, the latter of which was evaluated in Lingam & Loeb (2017). A larger coverage than 23% would result in slightly lower observation times; however, refer to Section 5 for the implications of larger coverage by photovoltaic cells. 5. DISCUSSION The results from the previous section seem to indicate that even ambitious deployment of solar panels (constructed with silicon and hosting anti-reflective coatings) covering a significant land area of an Earth-like exoplanet may not be enough to be detectable with a 8 m HWO-like telescope. These calculations presumed a fixed-present day efficiency for solar panels, so any technological improvements in efficiency would only decrease the required land coverage, and consequently decrease detectability. Lingam & Loeb (2017) conjectured that tidally locked planets around M-dwarfs might be a suitable place to start looking for photovoltaic cells. Unfortunately, due to the close proximity of planets in the habitable zone around M- dwarfs – which poses issue for spatially resolving the planet – currently there is no technological pathway to directly observing these types of planets. In the case that this setup would be possible though, the detectability of the silicon UV edge on planets around M-dwarfs would be further diminished, since the stellar emission in the relevant range (0.34 − 0.52 µm) is significantly lower. Note that we have performed all of the SNR calculations based on an orbital phase angle of 270◦ with edge-on orbital configuration (i.e., inclination = 90◦ ). Additional calculations varying the phase angle, varying the inclination angle, and so forth are needed to fully assess the potential detectability. Furthermore, we have not explored the extent of the effect of varying mirror size on the SNR, or a different stellar host spectral type (like a K-dwarf star). 9 https://psg.gsfc.nasa.gov/helpmodel.php
  • 7. Silicon Technosignatures 7 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 Wavelength (micron) 0 0.2 0.4 0.6 0.8 1 1.2 1.4 contrast (planet/star) 23% land cover of solar panels Longitude 0 Longitude 90 Longitude 315 (a) 0 500 1000 1500 2000 Observation time (hours) 0 1 2 3 4 5 6 7 8 SNR 23% land cover, Long0 2.4% land cover, Long0 2.4% land cover Long90 23% land cover Long90 2.4% Land cover Long315 23% land cover Long315 (b) Figure 3. (a) Reflectance spectra (expressed in terms of the planet to star contrast ratio) for different planetary orientations with respect to the observer for a 23% land cover of solar panels. We choose the 0.34−0.52µm range to estimate the detectability of Si-based solar panels, as discussed in §4 and shown in Fig.1. Within this range, there is a noticeable difference in the spectra, which contributes to higher SNR for an observing longitude of 315◦ (fully visible panel coverage). (b) SNR of detecting silicon solar panels as a function of observation time with a 8m class LUVOIR-B-like telescope for different orientations of the planet towards the observer. A longitudinal orientation of 315◦ yields a higher SNR because the solar panels on the planet are better oriented towards the observer, as compared to a longitude of 90◦ (partially visible). 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 Wavelength (micron) 0 0.2 0.4 0.6 0.8 1 1.2 1.4 contrast (planet/star) 2.4% land cover 23% land cover No silicon Figure 4. Planet-star contrast ratio as a function of wavelength for 2.4% (blue solid), 23% (red solid) and 0% (green dashed) land coverage of solar panels. The planet longitudinal orientation is 315◦ , where the solar panels are oriented towards the observer. Only the 23% land cover displays any significant variation in the spectrum. This trend is also manifested in the SNR curve of Fig.3, where the maximum SNR is obtained for a 23% land cover oriented at 315◦ planet longitude. Berdyugina & Kuhn (2019) generated composite maps of orbiting photovoltaic power sources if they were situated around a planet like Proxima Centauri b. Specific simulations and the corresponding SNR estimates relevant for HWO from such orbiting structures needs to be undertaken. These additional considerations are left for future work.
  • 8. 8 Kopparapu et al. As Earth remains the only example of an inhabited planet with a technosphere, future trajectories of Earth can provide insight into the constraints that might also apply to extraterrestrial technospheres. It is worth reiterating that only 3% land coverage by solar panels would be needed to support a population of 10 billion people at a high standard of living, and the toy logistic curve shown in Figure 2 indicates that even a population of 30 billion people at a high standard of living would require far less energy than the power output of the 23% land coverage scenario used in these detectability calculations. These estimates not only do not account for increased efficiency due to technological innovations, but they also do not account for other sources of energy. Hence, the actual solar requirements for Earth would likely be much reduced, especially in case controlled nuclear fusion becomes viable. For Earth, these results suggest the possibility of a future in which the energy needs of even a larger-than-predicted population could be fully met with known technology. If Earth is taken as an example in the search for technosignatures, then this raises the question: Is the large-scale deployment of solar panels on a planetary surface ever needed? Any actual large-scale deployment would certainly raise numerous issues regarding the feasibility of such a deployment or the logistical challenges in global distribution of energy, but a more fundamental unknown is whether a technological civilization would ever require such large energy demands to justify a scenario such as 23% land coverage or greater. Several of the projections shown in Figure 2 reach a time at which dissipation from energy use exceeds the threshold for contributing significant direct heating to Earth’s climate (∼ 3 × 1023 J), which occurs in the year 2265 for the 2.6% yr−1 growth rate scenario and 2338 for the 2% yr−1 growth rate scenario. Yet, it is not evident that such vast energy requirements will ever be necessary on Earth: the energy requirements for the global human population to afford a high standard of living fall several orders of magnitude below the direct heating threshold. The motivation to prevent direct heating of the atmosphere may serve as an additional deterrent to avoid such scenarios, and further suggests that only modest-scale deployment of solar panels would ever be needed to achieve sustainable development goals on Earth. Speculating even further shows that these scenario projections will reach the limit of a Kardashev Type I civilization (Kardashev 1964), which is a civilization that uses all available energy on its planet (i.e., all starlight incident at the top of the atmosphere). This Type I threshold (∼ 5 × 1024 J) occurs in the year 2377 for the 2.6% yr−1 growth rate scenario and 2482 for the 2% yr−1 growth rate scenario. The equivalent land area required to meet such energy demands with solar power exceeds 100% in these cases, which indicate that other sources of power—possibly including space-based solar power—would be required in these scenarios. Such speculative scenarios suggest images of “Dyson spheres/swarms” (e.g., Dyson 1960; Wright 2020) of solar collectors that expand a civilization’s ability to capture the energy output of its host star. Kardashev (1964) even imagined a Type II civilization as one that utilizes the entirety of its host star’s output; however, such speculations are based primarily on the assumption of a fixed growth rate in world energy use. But such vast energy reserves would be unnecessary even under cases of substantial population growth, especially if fusion and other renewable sources are available to supplement solar energy. The concept of a Type I or Type II civilization then becomes an exercise in imagining the possible uses that a civilization would have for such vast energy reserves. Even activities such as large-scale physics experiments and (relativistic) interstellar space travel (cf. Lingam & Loeb 2021, Chapter 10) might not be enough to explain the need for a civilization to harness a significant fraction of its entire planetary or stellar output. In contrast, if human civilization can meet its own energy demands with only a modest deployment of solar panels, then this expectation might also suggest that concepts like Dyson spheres would be rendered unnecessary in other technospheres. These results also have implications for the problem known as the Fermi paradox (Webb 2015; Ćirković 2018; Forgan 2019) or Great Silence (Brin 1983): if extraterrestrial expansion through the galaxy is relatively easy, then where are they? In the context of limits to growth, the recognition that human civilization could reach a sustainable equilibrium in its population and energy use that falls well below the Type I threshold suggests that extraterrestrial civilizations may not be compelled to expand for reasons of subsistence. This conclusion mirrors the “sustainability solution” to the Fermi paradox (e.g., Haqq-Misra & Baum 2009; Mullan & Haqq-Misra 2019), which suggests that any extant extraterrestrial civilizations only expand proportionally with their planet’s carrying capacity. Any civilization that is able to achieve sustainable population levels with high standard of living may also settle on a limit on any need to expand, which may likewise constrain the magnitude of any potential technosignatures generated by such a civilization. Underlying this discussion are two competing philosophical positions regarding the tendency of life to expand. The first position assumes that (a) life will evolve to utilize the maximum energy available in its environment, while the second assumes that (b) life will evolve to utilize as much energy as needed in its environment to reach an optimal level
  • 9. Silicon Technosignatures 9 of existence. To the extent that the environment will always impose thermodynamic limits, the second option (b) may probably be favored by life. But does life tend to expand up to such thermodynamic limits if unopposed, or will life tend to optimize its consumption of resources rather than maximize them? Such interdisciplinary questions highlight the intersection of technosignature science with concepts from ecology (e.g., Meurer et al. 2024), and further scrutiny of the proposed general tendency of life to expand may be useful for thinking about and enivisioning the particular tendencies for technospheres to expand. 6. CONCLUSION We analyzed the detectability of silicon-based solar panels (with anti-reflective coatings) as a signature of extrater- restrial technology. Assuming a 8-meter HWO-like telescope, focusing on the reflection edge in the UV-VIS, and considering varying land coverage of solar panels on an Earth-like exoplanet that match the present and projected energy needs, we estimate that several hundreds of hours of observation time is needed to reach a SNR of ∼ 5 for a high land coverage of ∼ 23%. We subsequently assessed the need for the deployment of such large-scale solar panels, taking into consideration various projected growth rates of future energy consumption. We find that, even with significant population growth, the energy needs of human civilization would be several orders of magnitude below the energy threshold for a Kardashev Type I civilization, or a Dyson sphere/swarm which harnesses the energy of a star. This line of inquiry reexamines the utility of such concepts, and potentially addresses one crucial aspect of the Fermi paradox: we have not discovered any large scale engineering yet, conceivably because advanced technologies may not need them. ACKNOWLEDGMENTS J.H.M., M.L., and R.K.K. gratefully acknowledge support from the NASA Exobiology program under grant 80NSSC22K1009. The authors also acknowledge support from the Goddard Space Flight Center (GSFC) Sellers Exoplanet Environments Collaboration (SEEC), which is supported by the NASA Planetary Science Division’s Re- search Program. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of their employers or NASA. REFERENCES Arnold, L., Gillet, S., Lardière, O., Riaud, P., & Schneider, J. 2002, Astronomy & Astrophysics, 392, 231 Arto, I., Capellán-Pérez, I., Lago, R., Bueno, G., & Bermejo, R. 2016, Energy for Sustainable Development, 33, 1 Bazilian, M., Onyeji, I., Liebreich, M., et al. 2013, Renewable Energy, 53, 329 Beatty, T. G. 2022, Monthly Notices of the Royal Astronomical Society, 513, 2652 Berdyugina, S., & Kuhn, J. 2019, The Astronomical Journal, 158, 246 Brin, G. D. 1983, Quarterly Journal of the Royal Astronomical Society, Vol. 24, NO. 3, P. 283-309, 1983, 24, 283 Campbell, P., & Green, M. A. 1987, Journal of Applied Physics, 62, 243, doi: 10.1063/1.339189 Ćirković, M. M. 2018, The great silence: Science and philosophy of Fermi’s paradox (Oxford University Press) Dyson, F. J. 1960, Science, 131, 1667 Forgan, D. H. 2019, Solving Fermi’s paradox, Vol. 10 (Cambridge University Press) Haqq-Misra, J., & Baum, S. 2009, Journal of the British Interplanetary Society, 62, 47 Haqq-Misra, J., Fauchez, T. J., Schwieterman, E. W., & Kopparapu, R. 2022a, The Astrophysical Journal Letters, 929, L28 Haqq-Misra, J., Kopparapu, R., Fauchez, T. J., et al. 2022b, The Planetary Science Journal, 3, 60 Haqq-Misra, J., Schwieterman, E. W., Socas-Navarro, H., et al. 2022c, Acta Astronautica, 198, 194 Jackson, R. B., Ahlström, A., Hugelius, G., et al. 2022, Ecosphere, 13, e3978 Juanola-Parramon, R., Zimmerman, N. T., Pueyo, L., et al. 2022, Journal of Astronomical Telescopes, Instruments, and Systems, 8, 034001, doi: 10.1117/1.JATIS.8.3.034001 Kardashev, N. S. 1964, Soviet Ast., 8, 217 Kim, M. S., Lee, J. H., & Kwak, M. K. 2020, International Journal of Precision Engineering and Manufacturing, 21, 1389
  • 10. 10 Kopparapu et al. Kokaly, R. F., Clark, R. N., Swayze, G. A., et al. 2017, USGS Spectral Library Version 7, Tech. Rep. 1035, U.S. Geological Survey, doi: 10.3133/ds1035 Kopparapu, R., Arney, G., Haqq-Misra, J., Lustig-Yaeger, J., & Villanueva, G. 2021, The Astrophysical Journal, 908, 164 Lin, H. W., Gonzalez Abad, G., & Loeb, A. 2014, ApJL, 792, L7, doi: 10.1088/2041-8205/792/1/L7 Lingam, M., & Loeb, A. 2017, MNRAS, 470, L82, doi: 10.1093/mnrasl/slx084 —. 2019, Astrobiology, 19, 28, doi: 10.1089/ast.2018.1936 —. 2021, Life in the Cosmos: From Biosignatures to Technosignatures (Cambridge: Harvard University Press) Macdonald, D. H., Cuevas, A., Kerr, M. J., et al. 2004, Solar Energy, 76, 277, doi: 10.1016/j.solener.2003.08.019 Meurer, J. C., Haqq-Misra, J., & de Souza Mendonça, M. 2024, International Journal of Astrobiology, 23, e3 Miller, L. M., & Keith, D. W. 2018, Environmental Research Letters, 13, 104008 Millward-Hopkins, J., Steinberger, J. K., Rao, N. D., & Oswald, Y. 2020, Global Environmental Change, 65, 102168 Mullan, B., & Haqq-Misra, J. 2019, Futures, 106, 4 NASA Technosignatures Workshop Participants. 2018, arXiv e-prints, arXiv:1812.08681, doi: 10.48550/arXiv.1812.08681 O’Malley-James, J. T., & Kaltenegger, L. 2018, Astrobiology, 18, 1123 Owen, T. 1980, in Strategies for the Search for Life in the Universe (Springer), 177–185 Pieters, C. M., & Hiroi, T. 2004, in Lunar and Planetary Science Conference, ed. S. Mackwell & E. Stansbery, Lunar and Planetary Science Conference, 1720 Raut, H. K., Ganesh, V. A., Nair, A. S., & Ramakrishna, S. 2011, Energy & Environmental Science, 4, 3779 Rühle, S. 2016, Solar Energy, 130, 139, doi: 10.1016/j.solener.2016.02.015 Sagan, C., Thompson, W. R., Carlson, R., Gurnett, D., & Hord, C. 1993, Nature, 365, 715 Sarkın, A. S., Ekren, N., & Sağlam, Ş. 2020, Solar Energy, 199, 63, doi: 10.1016/j.solener.2020.01.084 Schwieterman, E. W., Kiang, N. Y., Parenteau, M. N., et al. 2018, Astrobiology, 18, 663, doi: 10.1089/ast.2017.1729 Seager, S., Petkowski, J. J., Huang, J., et al. 2023, Scientific Reports, 13, 13576 Seager, S., Turner, E. L., Schafer, J., & Ford, E. B. 2005, Astrobiology, 5, 372, doi: 10.1089/ast.2005.5.372 Socas-Navarro, H., Haqq-Misra, J., Wright, J. T., et al. 2021, Acta Astronaut., 182, 446, doi: 10.1016/j.actaastro.2021.02.029 Tarter, J. C. 2007, Highlights of Astronomy, 14, 14, doi: 10.1017/S1743921307009829 Turnbull, M. C., Traub, W. A., Jucks, K. W., et al. 2006, The Astrophysical Journal, 644, 551 Varga, G. 2020, Environment international, 139, 105712 Villanueva, G. L., Liuzzi, G., Faggi, S., et al. 2022, Fundamentals of the Planetary Spectrum Generator (Greenbelt, Maryland: NASA Goddard Space Flight Center) Villanueva, G. L., Smith, M. D., Protopapa, S., Faggi, S., & Mandell, A. M. 2018, JQSRT, 217, 86, doi: 10.1016/j.jqsrt.2018.05.023 Vogel, J., Steinberger, J. K., O’Neill, D. W., Lamb, W. F., & Krishnakumar, J. 2021, Global Environmental Change, 69, 102287 Von Hoerner, S. J. 1975, Journal of the British Interplanetary Society, 28, 691 Webb, S. 2015, If the universe is teeming with aliens... where is everybody?: seventy-five solutions to the fermi paradox and the problem of extraterrestrial life (Springer) Woolf, N. J., Smith, P. S., Traub, W. A., & Jucks, K. W. 2002, The Astrophysical Journal, 574, 430 Wright, J. T. 2020, Serbian Astronomical Journal, 1 Zhao, J., & Green, M. A. 1991, IEEE Transactions on Electron Devices, 38, 1925, doi: 10.1109/16.119035
  • 11. This figure "cg_throughput.png" is available in "png" format from: http://arxiv.org/ps/2405.04560v1
  • 12. This figure "counts.png" is available in "png" format from: http://arxiv.org/ps/2405.04560v1
  • 13. 0.5 1.0 1.5 2.0 2.5 Wavelength in microns[um] 0.12 0.14 0.16 0.18 0.20 0.22 Reflectance