The document presents a theory of Fibonacci dimensional expansion of space to explain the measured rate of spatial expansion (H0). Key points:
1) The theory predicts the empirical value of H0 (74.3 km/sec/mpc) to within 1% using axioms derived from the Fibonacci sequence.
2) Calculations show the theoretical H0 (75.0 km/sec/mpc) matches the measured value, providing evidence the universal volume is expanding proportionally to Fibonacci ratios.
3) While transforming variables, the theory correlates with existing physics equations and can accurately describe observed "dark" expansion forces.
Second application of dimensional analysis
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In engineering and science, dimensional analysis is the analysis of the relationships between different physical quantities by identifying their fundamental dimensions (such as length, mass, time, and electric charge) and units of measure (such as miles vs. kilometers, or pounds vs. kilograms vs. grams) and tracking these dimensions as calculations or comparisons are performed.
Dimensional analysis is one of the important topic of the fluid mechanics. It is useful for transferring data from one system to other system and also useful in reducing complexity of the equation.
Second application of dimensional analysis
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In engineering and science, dimensional analysis is the analysis of the relationships between different physical quantities by identifying their fundamental dimensions (such as length, mass, time, and electric charge) and units of measure (such as miles vs. kilometers, or pounds vs. kilograms vs. grams) and tracking these dimensions as calculations or comparisons are performed.
Dimensional analysis is one of the important topic of the fluid mechanics. It is useful for transferring data from one system to other system and also useful in reducing complexity of the equation.
Dimensional analysis offers a method for reducing complex physical problems to the simplest (that is, most economical) form prior to obtaining a quantitative answer.
Divide and Conquer Algorithms - D&C forms a distinct algorithm design technique in computer science, wherein a problem is solved by repeatedly invoking the algorithm on smaller occurrences of the same problem. Binary search, merge sort, Euclid's algorithm can all be formulated as examples of divide and conquer algorithms. Strassen's algorithm and Nearest Neighbor algorithm are two other examples.
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On Hilbert Space Operator Deformation Analysis in Application to Some Element...BRNSS Publication Hub
The application of abstract results on contraction and extension in the Hilbert space through the concept of spectra in this paper, aims at an analytical survey of some deformation problems in elasticity theory. Results used in achieving this target were fully outlined in sections one and two while the target was realized in the last section.
Dimensional analysis offers a method for reducing complex physical problems to the simplest (that is, most economical) form prior to obtaining a quantitative answer.
Divide and Conquer Algorithms - D&C forms a distinct algorithm design technique in computer science, wherein a problem is solved by repeatedly invoking the algorithm on smaller occurrences of the same problem. Binary search, merge sort, Euclid's algorithm can all be formulated as examples of divide and conquer algorithms. Strassen's algorithm and Nearest Neighbor algorithm are two other examples.
The string matching problem is a classic of algorithms. In this class, we only look at the Rabin-Karpp algorithm as a classic example of the string matching algorithms
Different analytical and numerical methods are commonly used to solve transient heat conduction problems. In this problem, the use of Alternating Direct Implicit scheme (ADI) was adopted to solve temperature variation within an infinitesimal long bar of a square cross-section. The bottom right quadrant of the square cross-section of the bar was selected. The surface of the bar was maintained at constant temperature and temperature variation within the bar was evaluated within a time frame. The Laplace equation governing the 2-dimesional heat conduction was solved by iterative schemes as a result of the time variation. The modelled problem using COMSOL-MULTIPHYSICS software validated the result of the ADI analysis. On comparing the Modelled results from COMSOL MULTIPHYSICS and the results from ADI iterative scheme graphically, there was an high level of agreement between both results.
On Hilbert Space Operator Deformation Analysis in Application to Some Element...BRNSS Publication Hub
The application of abstract results on contraction and extension in the Hilbert space through the concept of spectra in this paper, aims at an analytical survey of some deformation problems in elasticity theory. Results used in achieving this target were fully outlined in sections one and two while the target was realized in the last section.
Громадський благодійний фонд "Виноградів" в рамках проекту "Я волонтер" презентували проект, та провели лекція для учнів шкіл Виноградівського району, Закарпатської області.
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Filtration and enhancement of signals and images by the discrete signal-induced heap transform (DsiHT) is described in this paper. The basic functions of the DsiHT are orthogonal waves that are originated from the signal generating the transform. These waves with their specific motion describe a process of elementary rotations or Givens transformations of the processed signal. Unlike the discrete Fourier transform which performs rotations of all data of the signalon each stage of calculation, the DsiHT sequentially rotates only two components of the data and accumulates a heap in one of the components with the maximum energy. Because of the nature of the heap transform, if the signal under process is mixed with a wave which is similar to the signal-generator then this additive component is eliminated or vanished after applying the heap transformation. This property can effectively be used for noise removal, noise detection, and image enhancement.
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11 - 3
Experiment 11
Simple Harmonic Motion
Questions
How are swinging pendulums and masses on springs related? Why are these types of
problems so important in Physics? What is a spring’s force constant and how can you measure
it? What is linear regression? How do you use graphs to ascertain physical meaning from
equations? Again, how do you compare two numbers, which have errors?
Note: This week all students must write a very brief lab report during the lab period. It is
due at the end of the period. The explanation of the equations used, the introduction and the
conclusion are not necessary this week. The discussion section can be as little as three sentences
commenting on whether the two measurements of the spring constant are equivalent given the
propagated errors. This mini-lab report will be graded out of 50 points
Concept
When an object (of mass m) is suspended from the end of a spring, the spring will stretch
a distance x and the mass will come to equilibrium when the tension F in the spring balances the
weight of the body, when F = - kx = mg. This is known as Hooke's Law. k is the force constant
of the spring, and its units are Newtons / meter. This is the basis for Part 1.
In Part 2 the object hanging from the spring is allowed to oscillate after being displaced
down from its equilibrium position a distance -x. In this situation, Newton's Second Law gives
for the acceleration of the mass:
Fnet = m a or
The force of gravity can be omitted from this analysis because it only serves to move the
equilibrium position and doesn’t affect the oscillations. Acceleration is the second time-
derivative of x, so this last equation is a differential equation.
To solve: we make an educated guess:
Here A and w are constants yet to be determined. At t = 0 this solution gives x(t=0) = A,
which indicates that A is the initial distance the spring stretches before it oscillates. If friction is
negligible, the mass will continue to oscillate with amplitude A. Now, does this guess actually
solve the (differential) equation? A second time-derivative gives:
Comparing this equation to the original differential equation, the correct solution was
chosen if w2 = k / m. To understand w, consider the first derivative of the solution:
−kx = ma
a = −
k
m
⎛
⎝
⎜⎜⎜⎜
⎞
⎠
⎟⎟⎟⎟
x
d 2x
dt 2
= −
k
m
x x(t) = A cos(ωt)
d 2x(t)
dt 2
= −Aω2 cos(ωt) = −ω2x(t)
James Gering
Florida Institute of Technology
11 - 4
Integrating gives
We assume the object completes one oscillation in a certain period of time, T. This helps
set the limits of integration. Initially, we pull the object a distance A from equilibrium and
release it. So at t = 0 and x = A. (one.
1. Theory of
Fibonacci Dimensional Expansion of Space
Abstract
The rate of measured spatial expansion, as defined by the measured constant H0, is
predicted by a theory of sequential events to within 1% of the empirical centric value
74.3 (+/- 2.1) km sec-1 mpc-1.
Introduction
The measured (empirical) rate of spatial expansion is best described as the expansion
constant H0 1. This measured constant is accurately correlated to the theory of
Fibonacci dimensional spatial expansion. The mathematics of the prediction are
presented as evidence of correlation, and the calculated theoretical explanation is
shown to match remarkably well with observation. The theory’s principle axioms are
defined and explained. Calculations for H0 are justified and compared with
measurement. Mathematics defining the theory are shown in Appendix A.
Suggesting a directional sequence of expanding events requires a transformation of
variables, and a transformation of physical units, which can be reversely transformed
back into standard nomenclature and standard physical units. The theory
mathematically treats time as an effective expansion through mathematics of the
Fibonacci infinite sequence. Definitions (Appx. A) and units (Appx. C.)
Axiomatic Suggested Facts from Theory
Three results (axioms,) directly from the Fibonacci derived theory, are required for
calculation:
Axioms
𝐸
𝐸 𝐵
= 𝑚𝑉𝐵
lim
𝐷→∞
𝑅 𝐷 = 𝑅 𝐿𝑂𝐺 = (𝛾 -1)(1/𝛾) = 12.42
𝑟𝐶𝐿 = 𝑟𝐵𝑜ℎ𝑟 = 5.29E-11 meter
2. where:
rBohr = Bohr radius
D is a Fibonacci number
𝛾 = infinite Fibonacci limit Fn-2 / Fn = 0.382
EB and VB represent boundaries between sequential events
Definitions (Appx. A)
Units (Appx. C)
Mathematics
Calculus of Spatial Growth Rate
Result of calculation is detailed numerically in Appx. B
H0 (theory) = 75.0 km sec-1 mpc-1
H0 (measured) = 74.3 +/- 2.1 km sec-1 mpc-1
Math
𝐸
𝐸 𝐵
= 𝑚𝑉𝐵
𝑑
𝑑𝑡
(
𝐸
𝐸 𝐵
) =
𝑑
𝑑𝑡
( 𝑚𝑉𝐵)
Substituting:
mu c2
𝑑
𝑑𝑡
(
1
𝐸 𝐵
) = mu (
𝑑𝑉𝑢𝐵
𝑑𝑡
)
𝑑
𝑑𝑡
(
1
𝐸 𝐵
) =
1
𝑐2 (
𝑑𝑉𝑢𝐵
𝑑𝑡
)
For 𝑟𝑢 = 𝑟𝑢(t):
𝑑𝑉𝑢𝐵
𝑑𝑡
=
𝑑
𝑑𝑡
𝑑
𝑑𝑟 𝑢
[ 4
3
π (ru + Δr)3
-
4
3
π 𝑟𝑢
3
] (see boundary units below)
4. For Fibonacci dimensional expansion:
We perceive 𝑥3 =
𝑥5
(1+𝑅 𝐸
5/3
)
but we have calculated with 𝑥5
and
𝑥5
𝑥3
= (1 + 𝑅 𝐸
5/3
).
We have also calculated (using H0) implying an effective diameter
= 2 𝑥 𝑟𝑎𝑑𝑖𝑢𝑠.
For comparison to measured (perceived) H0:
H0 (as perceived) =
𝐻0 𝑐𝑎𝑙𝑐𝑢𝑙𝑎𝑡𝑒𝑑
(1+𝑅 𝐸
5/3
𝑥 2)
Then H0 from theory (perceived) = 75.0 km s-1
mpc-1
H0 (empirical) = 74.3 +/- 2.1 km s-1
mpc-1
H0 (theory) = 75.0 km s-1
mpc-1
Correlation of Fibonacci Dimensional Expansion Theory to Existing Empirical Physics
The theory agrees with all existing physical equations and empirical results because the
theory can be precisely described as a mathematical transformation of variables.
Appendix C expands this assertion.
Physical Suggestion
Fibonacci dimensional spatial expansion, while correlating with existing physics, both
relativistic and quantum mechanical, also accurately predicts and explains the effects
of dark matter forces that have been observed.
5. Conclusion
The observed spatial expansion, attributed to a “dark” force, is significant evidence of
the main Fibonacci dimensional theory. The universal volume appears to be expanding
at a rate directly proportional to ratios of the Fibonacci infinite sequence.
Reference:
1. Speed of Universe’s Expansion Measured Better than Ever; Moskowitz,
SPACE.com; 10/03/2012.
Appendix A
For Fibonacci dimensional spatial growth, we need to rewrite the velocity
c = 2.998E+8 met sec-1
as:
2.998E+8 physical events per meter (using MKS units) where a single (one) physical
event has the one-dimensional spatial dimension b3 = 1.111E-17 meter.
Such that:
c (event 1/2
) =
1
√ 𝑏3
and 𝑏3(meter) =
1
𝑐2 (event -1
) (meter)
For radius r:
𝑟𝐷 =
𝑟(𝐷+1𝐷)
(1+𝑅 𝐸
(𝐷+1𝐷)
𝐷 )
e.g. 𝑟3 =
𝑟5
(1+𝑅 𝐸
5/3
)
where
𝑅 𝐿𝑂𝐺 = lim
𝑛→∞
𝑅 𝐷(𝑛) (Appx. D)
{𝑅 𝐷} = { (1/1)1/1, (1/1)5/2, (5/2)8/3, (8/3)13/5, ... }
𝑅 𝐿𝑂𝐺 = (𝛾 -1
)(1/𝛾) = 12.42 =
1
𝑅 𝐸
(nomenclature)
6. We know:
∫
1
𝑡
𝑑𝑡
𝑒
1
= 1 where lim
𝑛→∞
(1 +
1
𝑛
)
𝑛
= 𝑒
and where ϕ = lim
𝑛→∞
𝐹 𝑛−1
𝐹 𝑛
= 0.618
𝛾 = lim
𝑛→∞
𝐹 𝑛−2
𝐹 𝑛
= 0.382
and 1 = ϕ + 𝛾
Then:
𝑟𝐶𝐿 =
𝑐𝑏3
2𝜋3(1+𝑅 𝐸
5/3
)
= 𝑟𝐵𝑜ℎ𝑟 for a closed geometry, and
𝐸
𝐸 𝐵
= 𝑚𝑉𝐵 where 1 (radial) Boundary event =
1
𝑏3
(meter -1
)
Appendix B
Excel Result.pdf
<Calc for H0>
Excel Show Formula.pdf
<Calc for H0 Show Formula>
7. Appendix C
Agreement with Existing Physics
The definitions in Appendix A can be rewritten as a transformation of variables:
t(sec) = c(event) x B(sec event -1)
and the resulting expression
E / EB = mVB
where:
t represents time in seconds
c is the numerical value of the “speed of light” using the dimension (event)
B is the number of seconds per event, and
EB has the units; energy mass -1
meter -3
(we choose the MKS system of measure.)
This is a difficult and abstract concept, but it is nothing more than a mathematical
transformation of variables.
In the transformation, one second of time t is replaced by c events. In other words, time
is not fully continuous in this model, and one second of time t is treated as c
(2.998E+08) discrete events in MKS units.
To the extent that c (2.998E+08) is a large enough number to provide mathematical
continuity for the quantity e = lim(ninfinity) (1 + 1/n)n
, then the expression t=cB is
nothing more than a mathematical transformation of variables. Every physical equation
regarding time t could undergo a transformation of the variable t, and subsequently go
through the transformation back into t, with exactly the same physical result whether it
be a classical, quantum mechanical, or relativistic expression of physics.
There is no deviation from any existing empirical result while the Fibonacci dimensional
theory predicts the value of observed spatial expansion.
8. Appendix D
The reason for exploring this Fibonacci model of time is that the model should logically
lead to the physical expansion of our 3-dimensional space (universe) as a function of
time t.
It seems the concept of time could also be described as a directional motion of the
(Fibonacci number) 3 dimensions of space progressing through the (Fibonacci number)
5 dimensions of space. The physical units would need to be transformed, but physical
results would be exactly the same in this model and could be transformed back into the
variable t anytime as desired.
This Fibonacci model of time could be further explored by postulating that 5
spatial dimensions would then mathematically require an alternate value of:
e = lim
𝑛→∞
(1 +
1
𝑛
) 𝑛
because the corresponding statement:
∫
1
𝑥
𝑒
1
𝑑𝑥 = 1
suggests that the number 1 in 3-dimensions should be different from the number 1 in
5-dimensions and should no longer represent a 2-dimensional area but perhaps would
represent a 3-dimensional volume instead.
If we continue the mathematical exercise for time t, we would need to assume that, if
3-dimensions were mathematically traversing through 5-dimensions, then 5-
dimensions would need to be similarly traversing through 8-dimensions, and so on into
Fibonacci infinity.
9. In the infinite Fibonacci limit, then (as shown below) the logarithmic base should be
continually increasing at the rate:
(1/𝛾)^(1/𝛾) = 12.42
and to continue the mathematical model, then the number 1 would appear to be
increasing throughout higher Fibonacci dimensions by the factor:
(
1
12.42
)F(n+1)/F(n)
= (0.08)F(n+1)/F(n)
or about (8%) x [(F(n+1)/ F(n)] or 8% (Fn+1 / Fn) for each successive higher dimension
from the dimension Fn ( e.g. F3+1 / F3 =
5
3
)
where, regarding each adjacent dimension to Fn
𝛾 = lim
𝑛→∞
𝐹 𝑛−2
𝐹 𝑛
= 0.382
and, e.g.
F2 / F4 =
2
5
adjacent to F3 (where Dn = 3)
F3 / F5 =
3
8
adjacent to F4 (where Dn = 5)
and so on.
Then the figurative 5-dimensional number 1 should look more like the number 1.08 as
mathematically perceived in 3-dimensions, and we would determine:
10. e1 = 0
e2 = e0
e3 = e1
e5 = e3
(5/2)
e8 = e5
(8/3)
e13 = e8
(13/5)
and the sequence of dimensional logarithmic base:
{LD} = {0, 1, e, e5/2
, e5
8/3
, e8
13/5
, … }
where the rate of dimensional increase for the logarithmic base:
RLOG = lim
𝑛→∞
𝑅 𝐷(𝑛)
{RD} = { (1/1)1/1, (1/1)5/2, (5/2)8/3, (8/3)13/5, ... }
RLOG = (1/𝛾)^(1/𝛾) = 12.42
The reason for exploring this Fibonacci model of time is that the model should logically
lead to the physical expansion of our 3-dimensional space (universe) as a function of
time t.
To be a worthwhile mathematical exercise, there would need to be a correlation
between the mathematical growth rate of the logarithmic base and the observed
physical expansion of 3-dimensional space as perceived through telescopes, and the
like, while we attempt to measure the Hubble value H0.