This document discusses the sensitivity of a next generation reactor neutrino experiment to determine the neutrino mass hierarchy. It analyzes factors that affect the sensitivity such as baseline length, neutrino flux, detector size, energy resolution, and uncertainties in the neutrino oscillation parameters. With a 16.5GW thermal power reactor source, 18 kiloton detector, and 5 years of data taking, a reactor neutrino experiment could determine the mass hierarchy at over 3-sigma sensitivity if the energy resolution is less than 3% and 0.5% respectively. Other systematic uncertainties from multiple reactor sites, energy scale uncertainty, and oscillation parameters must also be carefully controlled to achieve this sensitivity.
Systematic Study Multiplicity Production Nucleus – Nucleus Collisions at 4.5 ...IOSRJAP
The correlations between the multiplicity distributions and the projectile fragments, as well as the correlation between the black and grey fragments were given. We observed that the mean number of interacting projectile nucleons increases quickly as the value of heavily ionizing charged particles increase as expected but attains a more or less constant value for extreme central collisions. Finally, there is no distinct correlation between the shower particle production and the target excitation, but the average value of grey particles decreases with the increase of the number of black particles and vice versa. This correlation can also be explained by the fireball model.
Direct detection of a break in the teraelectronvolt cosmic-ray spectrum of el...Sérgio Sacani
High-energy cosmic-ray electrons and positrons (CREs), which
lose energy quickly during their propagation, provide a probe of
Galactic high-energy processes1–7 and may enable the observation
of phenomena such as dark-matter particle annihilation or
decay8–10. The CRE spectrum has been measured directly up to
approximately 2 teraelectronvolts in previous balloon- or spaceborne
experiments11–16, and indirectly up to approximately 5
teraelectronvolts using ground-based Cherenkov γ-ray telescope
arrays17,18. Evidence for a spectral break in the teraelectronvolt
energy range has been provided by indirect measurements17,18,
although the results were qualified by sizeable systematic
uncertainties. Here we report a direct measurement of CREs in the
energy range 25 gigaelectronvolts to 4.6 teraelectronvolts by the
Dark Matter Particle Explorer (DAMPE)19 with unprecedentedly
high energy resolution and low background. The largest part of
the spectrum can be well fitted by a ‘smoothly broken power-law’
model rather than a single power-law model. The direct detection of
a spectral break at about 0.9 teraelectronvolts confirms the evidence
found by previous indirect measurements17,18, clarifies the behaviour
of the CRE spectrum at energies above 1 teraelectronvolt and sheds
light on the physical origin of the sub-teraelectronvolt CREs.
Systematic Study Multiplicity Production Nucleus – Nucleus Collisions at 4.5 ...IOSRJAP
The correlations between the multiplicity distributions and the projectile fragments, as well as the correlation between the black and grey fragments were given. We observed that the mean number of interacting projectile nucleons increases quickly as the value of heavily ionizing charged particles increase as expected but attains a more or less constant value for extreme central collisions. Finally, there is no distinct correlation between the shower particle production and the target excitation, but the average value of grey particles decreases with the increase of the number of black particles and vice versa. This correlation can also be explained by the fireball model.
Direct detection of a break in the teraelectronvolt cosmic-ray spectrum of el...Sérgio Sacani
High-energy cosmic-ray electrons and positrons (CREs), which
lose energy quickly during their propagation, provide a probe of
Galactic high-energy processes1–7 and may enable the observation
of phenomena such as dark-matter particle annihilation or
decay8–10. The CRE spectrum has been measured directly up to
approximately 2 teraelectronvolts in previous balloon- or spaceborne
experiments11–16, and indirectly up to approximately 5
teraelectronvolts using ground-based Cherenkov γ-ray telescope
arrays17,18. Evidence for a spectral break in the teraelectronvolt
energy range has been provided by indirect measurements17,18,
although the results were qualified by sizeable systematic
uncertainties. Here we report a direct measurement of CREs in the
energy range 25 gigaelectronvolts to 4.6 teraelectronvolts by the
Dark Matter Particle Explorer (DAMPE)19 with unprecedentedly
high energy resolution and low background. The largest part of
the spectrum can be well fitted by a ‘smoothly broken power-law’
model rather than a single power-law model. The direct detection of
a spectral break at about 0.9 teraelectronvolts confirms the evidence
found by previous indirect measurements17,18, clarifies the behaviour
of the CRE spectrum at energies above 1 teraelectronvolt and sheds
light on the physical origin of the sub-teraelectronvolt CREs.
27 Double π0 photoproduction on the neutron at GRAAL - Physics Letters B, Jul...Cristian Randieri PhD
Double π0 photoproduction on the neutron at GRAAL - Physics Letters B, Elsevier, July 2007, Vol. 651, N. 2-3, pp. 108-113, ISSN: 0370-2693, doi: 10.1016/j.physletb.2007.06.009
di J. Ajaka, Y. Assafiri, O. Bartalini, V. Bellini, S. Bouchigny, M. Castoldi, A. D'Angelo, J. P. Didelez, R. Di Salvo, A. Fantini, L. Fichen, G. Gervino, F. Ghio, B. Girolami, A. Giusa, M. Guidal, E. Hourany, R. Kunne, A. Lapik, P. Levi Sandri, D. Moricciani, A. Mushkarenkov, V. Nedorezov, C. Randieri, N. Rudnev, G. Russo, C. Schaerf, M. L. Sperduto, M. C. Sutera, A. Turinge (2007)
Abstract
The photoproduction of double π0 on the neutron is studied in the beam energy range of 0.6 up to 1.5 GeV, using a liquid deuterium target. The cross section and the beam asymmetry are extracted and compared to those previously obtained on a proton target. The theoretical interpretation of these results is given using different models.
ACADGILD:: FRONTEND LESSON -Ruby on rails vs groovy on railsPadma shree. T
Have you ever wondered as to what these terms are – Ruby, Groovy, Rail and got confused as to what all this is about? Which one to choose? Which one is better and which is not? Well then here is a blog which I write with the intention of making things clear between Ruby on Rails and Groovy on Rails.
27 Double π0 photoproduction on the neutron at GRAAL - Physics Letters B, Jul...Cristian Randieri PhD
Double π0 photoproduction on the neutron at GRAAL - Physics Letters B, Elsevier, July 2007, Vol. 651, N. 2-3, pp. 108-113, ISSN: 0370-2693, doi: 10.1016/j.physletb.2007.06.009
di J. Ajaka, Y. Assafiri, O. Bartalini, V. Bellini, S. Bouchigny, M. Castoldi, A. D'Angelo, J. P. Didelez, R. Di Salvo, A. Fantini, L. Fichen, G. Gervino, F. Ghio, B. Girolami, A. Giusa, M. Guidal, E. Hourany, R. Kunne, A. Lapik, P. Levi Sandri, D. Moricciani, A. Mushkarenkov, V. Nedorezov, C. Randieri, N. Rudnev, G. Russo, C. Schaerf, M. L. Sperduto, M. C. Sutera, A. Turinge (2007)
Abstract
The photoproduction of double π0 on the neutron is studied in the beam energy range of 0.6 up to 1.5 GeV, using a liquid deuterium target. The cross section and the beam asymmetry are extracted and compared to those previously obtained on a proton target. The theoretical interpretation of these results is given using different models.
ACADGILD:: FRONTEND LESSON -Ruby on rails vs groovy on railsPadma shree. T
Have you ever wondered as to what these terms are – Ruby, Groovy, Rail and got confused as to what all this is about? Which one to choose? Which one is better and which is not? Well then here is a blog which I write with the intention of making things clear between Ruby on Rails and Groovy on Rails.
Neutral Electronic Excitations: a Many-body approach to the optical absorptio...Claudio Attaccalite
Neutral Electronic Excitations: a Many-body approach to the optical absorption spectra.
Introduction to Bethe-Salpeter equation and linear response theory.
International Journal of Computational Engineering Research(IJCER)ijceronline
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
Study of size dependence of Raman scattering in Carbon nanotubes.
To Study Temperature dependence of Raman spectra
To Study spatial distribution of temperature during laser processing
To Study Temperature rise in CNTs as a function of laser power
Theoretically calculated Vs Experimental Raman temperature
Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...Sérgio Sacani
Since volcanic activity was first discovered on Io from Voyager images in 1979, changes
on Io’s surface have been monitored from both spacecraft and ground-based telescopes.
Here, we present the highest spatial resolution images of Io ever obtained from a groundbased telescope. These images, acquired by the SHARK-VIS instrument on the Large
Binocular Telescope, show evidence of a major resurfacing event on Io’s trailing hemisphere. When compared to the most recent spacecraft images, the SHARK-VIS images
show that a plume deposit from a powerful eruption at Pillan Patera has covered part
of the long-lived Pele plume deposit. Although this type of resurfacing event may be common on Io, few have been detected due to the rarity of spacecraft visits and the previously low spatial resolution available from Earth-based telescopes. The SHARK-VIS instrument ushers in a new era of high resolution imaging of Io’s surface using adaptive
optics at visible wavelengths.
Introduction:
RNA interference (RNAi) or Post-Transcriptional Gene Silencing (PTGS) is an important biological process for modulating eukaryotic gene expression.
It is highly conserved process of posttranscriptional gene silencing by which double stranded RNA (dsRNA) causes sequence-specific degradation of mRNA sequences.
dsRNA-induced gene silencing (RNAi) is reported in a wide range of eukaryotes ranging from worms, insects, mammals and plants.
This process mediates resistance to both endogenous parasitic and exogenous pathogenic nucleic acids, and regulates the expression of protein-coding genes.
What are small ncRNAs?
micro RNA (miRNA)
short interfering RNA (siRNA)
Properties of small non-coding RNA:
Involved in silencing mRNA transcripts.
Called “small” because they are usually only about 21-24 nucleotides long.
Synthesized by first cutting up longer precursor sequences (like the 61nt one that Lee discovered).
Silence an mRNA by base pairing with some sequence on the mRNA.
Discovery of siRNA?
The first small RNA:
In 1993 Rosalind Lee (Victor Ambros lab) was studying a non- coding gene in C. elegans, lin-4, that was involved in silencing of another gene, lin-14, at the appropriate time in the
development of the worm C. elegans.
Two small transcripts of lin-4 (22nt and 61nt) were found to be complementary to a sequence in the 3' UTR of lin-14.
Because lin-4 encoded no protein, she deduced that it must be these transcripts that are causing the silencing by RNA-RNA interactions.
Types of RNAi ( non coding RNA)
MiRNA
Length (23-25 nt)
Trans acting
Binds with target MRNA in mismatch
Translation inhibition
Si RNA
Length 21 nt.
Cis acting
Bind with target Mrna in perfect complementary sequence
Piwi-RNA
Length ; 25 to 36 nt.
Expressed in Germ Cells
Regulates trnasposomes activity
MECHANISM OF RNAI:
First the double-stranded RNA teams up with a protein complex named Dicer, which cuts the long RNA into short pieces.
Then another protein complex called RISC (RNA-induced silencing complex) discards one of the two RNA strands.
The RISC-docked, single-stranded RNA then pairs with the homologous mRNA and destroys it.
THE RISC COMPLEX:
RISC is large(>500kD) RNA multi- protein Binding complex which triggers MRNA degradation in response to MRNA
Unwinding of double stranded Si RNA by ATP independent Helicase
Active component of RISC is Ago proteins( ENDONUCLEASE) which cleave target MRNA.
DICER: endonuclease (RNase Family III)
Argonaute: Central Component of the RNA-Induced Silencing Complex (RISC)
One strand of the dsRNA produced by Dicer is retained in the RISC complex in association with Argonaute
ARGONAUTE PROTEIN :
1.PAZ(PIWI/Argonaute/ Zwille)- Recognition of target MRNA
2.PIWI (p-element induced wimpy Testis)- breaks Phosphodiester bond of mRNA.)RNAse H activity.
MiRNA:
The Double-stranded RNAs are naturally produced in eukaryotic cells during development, and they have a key role in regulating gene expression .
Cancer cell metabolism: special Reference to Lactate PathwayAADYARAJPANDEY1
Normal Cell Metabolism:
Cellular respiration describes the series of steps that cells use to break down sugar and other chemicals to get the energy we need to function.
Energy is stored in the bonds of glucose and when glucose is broken down, much of that energy is released.
Cell utilize energy in the form of ATP.
The first step of respiration is called glycolysis. In a series of steps, glycolysis breaks glucose into two smaller molecules - a chemical called pyruvate. A small amount of ATP is formed during this process.
Most healthy cells continue the breakdown in a second process, called the Kreb's cycle. The Kreb's cycle allows cells to “burn” the pyruvates made in glycolysis to get more ATP.
The last step in the breakdown of glucose is called oxidative phosphorylation (Ox-Phos).
It takes place in specialized cell structures called mitochondria. This process produces a large amount of ATP. Importantly, cells need oxygen to complete oxidative phosphorylation.
If a cell completes only glycolysis, only 2 molecules of ATP are made per glucose. However, if the cell completes the entire respiration process (glycolysis - Kreb's - oxidative phosphorylation), about 36 molecules of ATP are created, giving it much more energy to use.
IN CANCER CELL:
Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful.
Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation.
This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive.
Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful.
Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation.
This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive.
introduction to WARBERG PHENOMENA:
WARBURG EFFECT Usually, cancer cells are highly glycolytic (glucose addiction) and take up more glucose than do normal cells from outside.
Otto Heinrich Warburg (; 8 October 1883 – 1 August 1970) In 1931 was awarded the Nobel Prize in Physiology for his "discovery of the nature and mode of action of the respiratory enzyme.
WARNBURG EFFECT : cancer cells under aerobic (well-oxygenated) conditions to metabolize glucose to lactate (aerobic glycolysis) is known as the Warburg effect. Warburg made the observation that tumor slices consume glucose and secrete lactate at a higher rate than normal tissues.
Slide 1: Title Slide
Extrachromosomal Inheritance
Slide 2: Introduction to Extrachromosomal Inheritance
Definition: Extrachromosomal inheritance refers to the transmission of genetic material that is not found within the nucleus.
Key Components: Involves genes located in mitochondria, chloroplasts, and plasmids.
Slide 3: Mitochondrial Inheritance
Mitochondria: Organelles responsible for energy production.
Mitochondrial DNA (mtDNA): Circular DNA molecule found in mitochondria.
Inheritance Pattern: Maternally inherited, meaning it is passed from mothers to all their offspring.
Diseases: Examples include Leber’s hereditary optic neuropathy (LHON) and mitochondrial myopathy.
Slide 4: Chloroplast Inheritance
Chloroplasts: Organelles responsible for photosynthesis in plants.
Chloroplast DNA (cpDNA): Circular DNA molecule found in chloroplasts.
Inheritance Pattern: Often maternally inherited in most plants, but can vary in some species.
Examples: Variegation in plants, where leaf color patterns are determined by chloroplast DNA.
Slide 5: Plasmid Inheritance
Plasmids: Small, circular DNA molecules found in bacteria and some eukaryotes.
Features: Can carry antibiotic resistance genes and can be transferred between cells through processes like conjugation.
Significance: Important in biotechnology for gene cloning and genetic engineering.
Slide 6: Mechanisms of Extrachromosomal Inheritance
Non-Mendelian Patterns: Do not follow Mendel’s laws of inheritance.
Cytoplasmic Segregation: During cell division, organelles like mitochondria and chloroplasts are randomly distributed to daughter cells.
Heteroplasmy: Presence of more than one type of organellar genome within a cell, leading to variation in expression.
Slide 7: Examples of Extrachromosomal Inheritance
Four O’clock Plant (Mirabilis jalapa): Shows variegated leaves due to different cpDNA in leaf cells.
Petite Mutants in Yeast: Result from mutations in mitochondrial DNA affecting respiration.
Slide 8: Importance of Extrachromosomal Inheritance
Evolution: Provides insight into the evolution of eukaryotic cells.
Medicine: Understanding mitochondrial inheritance helps in diagnosing and treating mitochondrial diseases.
Agriculture: Chloroplast inheritance can be used in plant breeding and genetic modification.
Slide 9: Recent Research and Advances
Gene Editing: Techniques like CRISPR-Cas9 are being used to edit mitochondrial and chloroplast DNA.
Therapies: Development of mitochondrial replacement therapy (MRT) for preventing mitochondrial diseases.
Slide 10: Conclusion
Summary: Extrachromosomal inheritance involves the transmission of genetic material outside the nucleus and plays a crucial role in genetics, medicine, and biotechnology.
Future Directions: Continued research and technological advancements hold promise for new treatments and applications.
Slide 11: Questions and Discussion
Invite Audience: Open the floor for any questions or further discussion on the topic.
(May 29th, 2024) Advancements in Intravital Microscopy- Insights for Preclini...Scintica Instrumentation
Intravital microscopy (IVM) is a powerful tool utilized to study cellular behavior over time and space in vivo. Much of our understanding of cell biology has been accomplished using various in vitro and ex vivo methods; however, these studies do not necessarily reflect the natural dynamics of biological processes. Unlike traditional cell culture or fixed tissue imaging, IVM allows for the ultra-fast high-resolution imaging of cellular processes over time and space and were studied in its natural environment. Real-time visualization of biological processes in the context of an intact organism helps maintain physiological relevance and provide insights into the progression of disease, response to treatments or developmental processes.
In this webinar we give an overview of advanced applications of the IVM system in preclinical research. IVIM technology is a provider of all-in-one intravital microscopy systems and solutions optimized for in vivo imaging of live animal models at sub-micron resolution. The system’s unique features and user-friendly software enables researchers to probe fast dynamic biological processes such as immune cell tracking, cell-cell interaction as well as vascularization and tumor metastasis with exceptional detail. This webinar will also give an overview of IVM being utilized in drug development, offering a view into the intricate interaction between drugs/nanoparticles and tissues in vivo and allows for the evaluation of therapeutic intervention in a variety of tissues and organs. This interdisciplinary collaboration continues to drive the advancements of novel therapeutic strategies.
This pdf is about the Schizophrenia.
For more details visit on YouTube; @SELF-EXPLANATORY;
https://www.youtube.com/channel/UCAiarMZDNhe1A3Rnpr_WkzA/videos
Thanks...!
THE IMPORTANCE OF MARTIAN ATMOSPHERE SAMPLE RETURN.Sérgio Sacani
The return of a sample of near-surface atmosphere from Mars would facilitate answers to several first-order science questions surrounding the formation and evolution of the planet. One of the important aspects of terrestrial planet formation in general is the role that primary atmospheres played in influencing the chemistry and structure of the planets and their antecedents. Studies of the martian atmosphere can be used to investigate the role of a primary atmosphere in its history. Atmosphere samples would also inform our understanding of the near-surface chemistry of the planet, and ultimately the prospects for life. High-precision isotopic analyses of constituent gases are needed to address these questions, requiring that the analyses are made on returned samples rather than in situ.
Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...Sérgio Sacani
We characterize the earliest galaxy population in the JADES Origins Field (JOF), the deepest
imaging field observed with JWST. We make use of the ancillary Hubble optical images (5 filters
spanning 0.4−0.9µm) and novel JWST images with 14 filters spanning 0.8−5µm, including 7 mediumband filters, and reaching total exposure times of up to 46 hours per filter. We combine all our data
at > 2.3µm to construct an ultradeep image, reaching as deep as ≈ 31.4 AB mag in the stack and
30.3-31.0 AB mag (5σ, r = 0.1” circular aperture) in individual filters. We measure photometric
redshifts and use robust selection criteria to identify a sample of eight galaxy candidates at redshifts
z = 11.5 − 15. These objects show compact half-light radii of R1/2 ∼ 50 − 200pc, stellar masses of
M⋆ ∼ 107−108M⊙, and star-formation rates of SFR ∼ 0.1−1 M⊙ yr−1
. Our search finds no candidates
at 15 < z < 20, placing upper limits at these redshifts. We develop a forward modeling approach to
infer the properties of the evolving luminosity function without binning in redshift or luminosity that
marginalizes over the photometric redshift uncertainty of our candidate galaxies and incorporates the
impact of non-detections. We find a z = 12 luminosity function in good agreement with prior results,
and that the luminosity function normalization and UV luminosity density decline by a factor of ∼ 2.5
from z = 12 to z = 14. We discuss the possible implications of our results in the context of theoretical
models for evolution of the dark matter halo mass function.
The increased availability of biomedical data, particularly in the public domain, offers the opportunity to better understand human health and to develop effective therapeutics for a wide range of unmet medical needs. However, data scientists remain stymied by the fact that data remain hard to find and to productively reuse because data and their metadata i) are wholly inaccessible, ii) are in non-standard or incompatible representations, iii) do not conform to community standards, and iv) have unclear or highly restricted terms and conditions that preclude legitimate reuse. These limitations require a rethink on data can be made machine and AI-ready - the key motivation behind the FAIR Guiding Principles. Concurrently, while recent efforts have explored the use of deep learning to fuse disparate data into predictive models for a wide range of biomedical applications, these models often fail even when the correct answer is already known, and fail to explain individual predictions in terms that data scientists can appreciate. These limitations suggest that new methods to produce practical artificial intelligence are still needed.
In this talk, I will discuss our work in (1) building an integrative knowledge infrastructure to prepare FAIR and "AI-ready" data and services along with (2) neurosymbolic AI methods to improve the quality of predictions and to generate plausible explanations. Attention is given to standards, platforms, and methods to wrangle knowledge into simple, but effective semantic and latent representations, and to make these available into standards-compliant and discoverable interfaces that can be used in model building, validation, and explanation. Our work, and those of others in the field, creates a baseline for building trustworthy and easy to deploy AI models in biomedicine.
Bio
Dr. Michel Dumontier is the Distinguished Professor of Data Science at Maastricht University, founder and executive director of the Institute of Data Science, and co-founder of the FAIR (Findable, Accessible, Interoperable and Reusable) data principles. His research explores socio-technological approaches for responsible discovery science, which includes collaborative multi-modal knowledge graphs, privacy-preserving distributed data mining, and AI methods for drug discovery and personalized medicine. His work is supported through the Dutch National Research Agenda, the Netherlands Organisation for Scientific Research, Horizon Europe, the European Open Science Cloud, the US National Institutes of Health, and a Marie-Curie Innovative Training Network. He is the editor-in-chief for the journal Data Science and is internationally recognized for his contributions in bioinformatics, biomedical informatics, and semantic technologies including ontologies and linked data.
Professional air quality monitoring systems provide immediate, on-site data for analysis, compliance, and decision-making.
Monitor common gases, weather parameters, particulates.
4. PMT
Reactor
neutrino
experiment
e
Reactor
Detector
Inside
Detector
Evis
Inverse
Beta
Decay
(IBD)
2 1020
neutrinos/GW/sec
L
5. Energy
distribu'on
e
@
detector
e
near
dNfar
dEvis
=
NpT
4 L2
Ethr
dE (E ) Pee IBD G(E , Evis)
Pee
far
L
Neutrino
oscilla;on
6. How
to
dis'nguish
Mass
Hierarchy?
Detect
the
sign
of
( m2
32)m2
31
m1
m2
m3
m3
m1
m2
NH
IH
The
informa'on
of
mass^2
difference
are
in
Oscilla'on
Probabili'es.
7. MH
difference
in
spectrum
10000
20000
30000
40000
30 km NH
IH
2000
6000
10000
14000 40 km NH
IH
1000
3000
5000
7000
dN/dE[1/MeV]
50 km NH
IH
0
1000
2000
3000
4000
2 3 4 5 6 7 8
E [MeV]
60 km NH
IH
e
9.
analysis
2
The
theore;cal
predic;on
is
fiBed
to
the
Data,
assuming
NH
or
IH.
2
min(NH) 2
min(IH)
Nfit
i = dEvis
NpT
4 L2
Ethr
dE (E ) Pee IBD G(E , Evis)
FiFng
parameters
are
12, 13, m2
21, | m2
31|, fsys
Penalty
term
Nfit
i
10. 0
2
4
6
8
10
12
14
16
18
20
22
24
10 20 30 40 50 60 70 80 90 100
(2
)min
L [km]
a = 2% NH
3% NH
4% NH
5% NH
6% NH
Sensi'vity
to
the
Mass
hierarchy
16.5GW
10kton
5yrs
Current
value
NH
a 7%
E
E
=
a
E
2
+ b2
( m2
31)
11. Effects
of
to
the
sensi'vity
| m2
31|
L
=
30km
| m2
31|
| m2
31|
L
=
50km
Baseline
should
be
long
enough
| m2
31|+2
fit
2
fit | m2
31|+
12. 0
2
4
6
8
10
12
14
16
18
20
22
24
10 20 30 40 50 60 70 80 90 100
(2
)min
L [km]
a = 2% NH
3% NH
4% NH
5% NH
6% NH
Sensi'vity
to
the
Mass
hierarchy
16.5GW
10kton
5yrs
Current
value
NH
a 7%
E
E
=
a
E
13. Effect
of
Energy
Resolu'on
a
=
0
a
=
6%
Evergy
Resolu'on
affects
the
sensi'vity
significantly.
E = 0
E
E
=
a
E
14. Expected Energy Resolution
PMT coverage : 67% (15,000 20” PMTs)
PMT coverage : 67% (15,000 20” PMTs)
+ Attenuation length : 25 m
+ QE : 35%
J.S.
Park,
S.B.
Kim
15.
Effect
of
Energy
Resolu'on
2
16.5GW
10kton
5yrs
E
E
=
a
E
2
+ b2
•
Sensi'vity
is
reduced
by
~
40%
•
Op'mized
L
is
shortened
by
~
5
km
b
=
0%
b
=
1%
a
=
2%
a
=
3%
0
1
2
3
4
5
6
7
8
10 20 30 40 50 60 70 80 90 100
(
2
)min
L [km]
(a, b) = (3, 0) NH
(3, 0.5) NH
(3, 0.75) NH
(3, 1) NH
0
2
4
6
8
10
12
14
16
18
20
22
24
10 20 30 40 50 60 70 80 90 100
(
2
)min
L [km]
(a, b) = (2, 0) NH
(2, 0.5) NH
(2, 0.75) NH
(2, 1) NH
17. Mul'-‐reactor
interference
L1
L2
E.
Ciuffoli,
J.
Evslin,
X.
Zhang:
1302.0624
Y-‐F.
Li,
J.
Cao,
Y.
Wang,
L.
Zhan:
1303.6733
Baseline
difference
should
be
small.
ΔL
=
L1
–
L2
18. Mul'-‐reactor
interference
Other
reactor
sites
influence
the
sensi'vity.
All
Reactors
16.5GW
10kton
5yrs
a
=
3%,
b
=
0.5%
E
E
=
a
E
2
+ b2
YongGwang
only
0
1
2
3
4
5
6
7
8
9
10
11
( 2)min
19. Mul'-‐reactor
interference
All
Reactors
0
1
2
3
4
5
6
7
8
9
10
11
( 2
)min
16.5GW
10kton
5yrs
a
=
3%,
b
=
0.5%
E
E
=
a
E
2
+ b2
RENO
site
In
latest
RENO-‐50
proposeal:
Site
changed
18
kton
detector
20. Energy
scale
uncertainty
Energy
scale
uncertainty
is
controlled
~
1%
for
RENO
detector.
J.
Evslin
et.al.
arXiv:
1308.0591
No
E
scale
Unc.
Unknown
E
scale
(worst
case)
Effect
of
E
scale
Uncertainty
21. Schedule
for
MH
determina'on
2010
2030
2020
RENO-‐50
DayaBay
II
LBNE
LBNO
PINGU
INO
NOvA
(Opera;ng)
(Approved)
Hyper
K
2015
2025
*
rough
es;mate
2
sigma
3
sigma
4
sigma
5
sigma
22.
Summary
RENO50-‐like
Experiment
for
MH
determina=on.
With
16.5GW
18kton,
a
<
3%
b
<
0.5%
of
Energy
Resolu=on
is
required
>
2
~
3-‐sigma
determina;on
within
5
years.
E
E
=
a
E
2
+ b2
Interference
among
reactor
cores
significantly
affects
the
sensi;vity.
Energy
Scale
uncertainty
should
be
controlled
very
Carefully.
Many
Efforts
for
MH
determina;on
have
started
!