# Quantum gravity and gauge neural network

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I fully agree with the concept of gravity based on quantum theory. I offer you your point of view. In general, my work is based on a Cotton flow for a gauge field. Let's see further.

The theory of everything is mainly associated with the general theory of relativity and the standard model. On the one hand, the equivalence principle and on the other hand the gauge principle. The two principles are completely opposite to use, one for space-time geometry, the other for quantum fields. For the union is looking for a way called quantum gravity. Canonical quantization of gravity is called Wheeler equation. However, there are difficulties, lack of time and the inability to combine with quantum fields. The equation is purely wave and geometric. All fundamental laws are usually symmetrical in time, even the gauge fields of the standard model are reversible. However, in the real world, time has a strict direction to the future. This is another problem.

We believe that the quantum gravity equation is not linear in time. This trip is supported by Roger Penrose and Lee Smolin. At the fundamental level on the scale of the Planck, time is real and has an arrow due to the nonlinearity of the quantum gravity equation. In the recent work we generalized the concept of Cotton Flow is not in the form of a metric, but in the form of a gauge field. This equation describes the behavior of nonlinear in the time of the gauge field on the scale of the Planck.

$$\frac{\partial S}{\partial t}= kC$$

$$A_{i}=\partial_{i} S$$

$$K_{in}=\partial_{i} A_{n}+A_{i}A_{n}$$

$$C=e^{inj}C_{inj}=e^{inj}\partial_{i} K_{nj}$$

$$k=\frac{Gh}{c^2}$$

In this equation for the gauge field, the solution itself is interesting in the form of finding the local phase of the wave function.

$$S=S(x,y,z,t)$$

$$\psi=e^{iS}$$

The general solution of the nonlinear equation in time will be

$$S=k\int Cdt + \int A^{i}dx_{i} + f(x,y,z,t)$$

Thus, a series of compounds and splitting of cylindrical pipelines together creates a topological structure of a gauge field as a web or in the form of neural networks on the scale of the Planck. The neural network of the gauge field is subject to a nonlinear equation so that it develops in the future and expanded. This neural network is dynamic in time.

Consider some solutions for special cases.

Gravity and gauge field the scale Planck.

In this chapter, we will show how the gauge neural network on the scale of the Planck creates gravity on a large scale, where there is a classic world.

Consider the equation of the neural field. We make an assumption that on a large scale curvature of the field due to the least

$$\frac{\partial S}{\partial t}=kC=e^{inj} A_{i}\partial_{n} A_{j}$$

Can be determined in the form of a function from the local phase. Decision in the form of a reduction in the rule of differentiation of derivatives

$$\frac{\partial S}{\partial t}=ke^{inj} \partial_{n}S \partial_{n}\partial_{j}S$$

Decision in the form of a reduction in the rule of differentiation of derivatives

$$v_{i}=\frac{dx_{i}}{dt}=ke^{inj} \partial_{n}\partial_{j}S$$

As can be seen, there is some idea of the speed of movement, that is, the initial concept of kinematics.

We introduce the transverse surface in the form of an area

$$dF_{i}=e^{inj} dx_{n}dx_{j}$$

As a result, an additional solution for the local phase of the gauge neural field will be

$$S=k\int Cdt + \int A^{i}dx_{i} +\frac{1}{k} \int v_{i}dF^{i}+ f(x,y,z,t)$$

Moreover, now we will see the appearance of gravity. Consider the kinematic action for the gauge neural network

$$S=\frac{1}{k} \int v_{i}dF^{i}$$

Let the reference system accelerates

$$a_{i}=\int v_{i}dt$$

Then the action will be accelerated

$$S=\frac{1}{k} \int a_{i}dF^{i}dt$$

This definition of action in the form of a function of time, besides, if there is matter in this gauge neural network, the overall action will be

$$S=\frac{1}{k} \int a_{i}dF^{i}dt+ \int Mc^2dt$$

As a result, when variations are obtained, the Gauss theorem is obtained for the source of the gravitational field.

$$\int a_{i}dF^{i} =-4\pi G M$$

Thus, we have the Poisson equation for the gravitational field, which is true in the classical world, when taking into account the signal transmission limit at the speed of light the theory of gravity is described by the general theory relativity. Gravity is a curvature of space-time. On the other hand, our theory also describes gravity as a dynamic state of the gauge neural network. Thus, the source quantum state of space-time is like a neural network on a scale Planck based on a gauge principle. In fact, quantum gravity is a non-linear quantum field theory on the scale of the Planck.

Edited by Kuyukov Vitaly
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3 hours ago, Kuyukov Vitaly said:

I fully agree with the concept of gravity based on quantum theory. I offer you your point of view. In general, my work is based on a Cotton flow for a gauge field. Let's see further.

The theory of everything is mainly associated with the general theory of relativity and the standard model. On the one hand, the equivalence principle and on the other hand the gauge principle. The two principles are completely opposite to use, one for space-time geometry, the other for quantum fields. For the union is looking for a way called quantum gravity. Canonical quantization of gravity is called Wheeler equation. However, there are difficulties, lack of time and the inability to combine with quantum fields. The equation is purely wave and geometric. All fundamental laws are usually symmetrical in time, even the gauge fields of the standard model are reversible. However, in the real world, time has a strict direction to the future. This is another problem.

We believe that the quantum gravity equation is not linear in time. This trip is supported by Roger Penrose and Lee Smolin. At the fundamental level on the scale of the Planck, time is real and has an arrow due to the nonlinearity of the quantum gravity equation. In the recent work we generalized the concept of Cotton Flow is not in the form of a metric, but in the form of a gauge field. This equation describes the behavior of nonlinear in the time of the gauge field on the scale of the Planck.

St=kC

Ai=iS

Kin=iAn+AiAn

C=einjCinj=einjiKnj

k=Ghc2

In this equation for the gauge field, the solution itself is interesting in the form of finding the local phase of the wave function.

S=S(x,y,z,t)

ψ=eiS

The general solution of the nonlinear equation in time will be

S=kCdt+Aidxi+f(x,y,z,t)

Thus, a series of compounds and splitting of cylindrical pipelines together creates a topological structure of a gauge field as a web or in the form of neural networks on the scale of the Planck. The neural network of the gauge field is subject to a nonlinear equation so that it develops in the future and expanded. This neural network is dynamic in time.

Consider some solutions for special cases.

Gravity and gauge field the scale Planck.

In this chapter, we will show how the gauge neural network on the scale of the Planck creates gravity on a large scale, where there is a classic world.

Consider the equation of the neural field. We make an assumption that on a large scale curvature of the field due to the least

St=kC=einjAinAj

Can be determined in the form of a function from the local phase. Decision in the form of a reduction in the rule of differentiation of derivatives

St=keinjnSnjS

Decision in the form of a reduction in the rule of differentiation of derivatives

vi=dxidt=keinjnjS

As can be seen, there is some idea of the speed of movement, that is, the initial concept of kinematics.

We introduce the transverse surface in the form of an area

dFi=einjdxndxj

As a result, an additional solution for the local phase of the gauge neural field will be

S=kCdt+Aidxi+1kvidFi+f(x,y,z,t)

Moreover, now we will see the appearance of gravity. Consider the kinematic action for the gauge neural network

S=1kvidFi

Let the reference system accelerates

ai=vidt

Then the action will be accelerated

S=1kaidFidt

This definition of action in the form of a function of time, besides, if there is matter in this gauge neural network, the overall action will be

S=1kaidFidt+Mc2dt

As a result, when variations are obtained, the Gauss theorem is obtained for the source of the gravitational field.

aidFi=4πGM

Thus, we have the Poisson equation for the gravitational field, which is true in the classical world, when taking into account the signal transmission limit at the speed of light the theory of gravity is described by the general theory relativity. Gravity is a curvature of space-time. On the other hand, our theory also describes gravity as a dynamic state of the gauge neural network. Thus, the source quantum state of space-time is like a neural network on a scale Planck based on a gauge principle. In fact, quantum gravity is a non-linear quantum field theory on the scale of the Planck.

At Planck scale , spacetime curvature has to follow only locally tangent/locally differentiable planes' segments. Any appropriate response to this  should include, and thus require, gravity, not only the structure of matter, but the structure of space and time itself. The status of thus-arrived-at quasi-local mass, energy-momentum and angular-momentum constructions in general relativity must , consequently ,  not include non-local or borderline tangent planes to discussed manifolds at this level. Quantum fluctuations of space and time at the smallest scale imaginable are , therefore , subject to this rule of locality , if we are to obtain  any scientifically valuable appraisal of  the signal transmission limit at the speed of light.  As a result , the non-linearity of the Q gravity field you refer to , is the most brilliant point of your thesis.

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Thickness axons ( L ) in the neural network limits speed signal transmission

$$v = \frac{Gh}{c^2} \frac{1}{L^2}$$

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Solution for space-time metric

$$S = \frac{dV}{dt}=g_{ik}^|g_{ik}V+ π_{ik}g_{ik}V$$

Edited by Kuyukov Vitaly
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The nature of the time is counterdiced. On the one hand, the disappearance of time in Wheeler's equation. On the other hand, Penrose talks about the reality of time. There is another definition, in the form of a holographic hypothesis

$$t=\frac{Gh}{c^2} \int \frac{dS}{r}$$22.pdf

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17 hours ago, Kuyukov Vitaly said:

Thickness axons ( L ) in the neural network limits speed signal transmission

v=Ghc21L2

Where the balance between structural and dynamical aspects  for obtaining best  signaling efficiency would be, and the design principle(s) that Axons utilize  to maintain  this balance, suggest that the convoluted paths taken by neurons  should reflect a design recompensation by the neuron to slow signaling latencies for purposes of  optimizing  speed(y) signal transmission.  Your formula is all but the same as the one we use in our own laboratories. Nonetheless , the let-go of the signaling event could come before, right at, or after the observation time. The virtual chaocity at interconnects level  emanates at the numerical registering level as the thickness/signal speed ratio. This spells that the axon fiber thickness effect’s power could be brought down from 2 ( as you have written ) to something around 1.3-1.4.

Edited by Prof Reza Sanaye
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Here’s an idea. Try writing in a manner that makes sense to others.

17 minutes ago, Prof Reza Sanaye said:

the convoluted paths taken by neurons  should reflect a design recompensation by the neuron to slow signaling latencies <...> the let-go of the signaling event <...> The virtual chaocity at interconnects level  emanates at the numerical registering level <...> This spells that the axon fiber thickness effect’s power could be brought down from 2

Basically, add units to your numbers, not your words. You’re making up terms and expecting to be understood. This will result in consistent failure. You have been given this feedback over and over and over again some more. You’ve been neg repped over and over and over again. You’ve not taken any of this feedback on board.

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1 hour ago, iNow said:

Here’s an idea. Try writing in a manner that makes sense to others.

Basically, add units to your numbers, not your words. You’re making up terms and expecting to be understood. This will result in consistent failure. You have been given this feedback over and over and over again some more. You’ve been neg repped over and over and over again. You’ve not taken any of this feedback on board.

It is not true that whatever you don't come to understand has some defect in itself. How is it that  YOU  don't try to read more in-depth  AND  even re-read ?? Why do you put the whole hermeneutics of the text on the writer's shoulders ??   !!  It is decades since Roland Barthes made it literally crystal-clear by ample elucidation   that  ANY  text needs to be best digested by the reader before being best written by the author.

Second , why do you  TOTALLY  rule out the probability of your own lack/shortage of expertise in a number of asides and ancillaries and accessory knowledge that are either partially or fully necessary to grasp the point ??  !!

Third , I  HAVE  taken on board the hint as about minimally applying fresh terminology. Fresh gushers of science and humanities , however , do have their own new terminology coming with them as they develop. This is verily proven by the history of science and the history of humanities. It's undeniable. It is extremely amazing that you prefer to always remain within the realm of already-one-hundred-times-chewed science and humanities.  There  IS  vital need for very slowly, carefully pushing forward the boundaries of human knowledge.

🤷‍♂️

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9 hours ago, Kuyukov Vitaly said:

The nature of the time is counterdiced. On the one hand, the disappearance of time in Wheeler's equation. On the other hand, Penrose talks about the reality of time. There is another definition, in the form of a holographic hypothesis

t=Ghc2dSr

To get  FULL  grasp of the counterdicing of time , I could not download your attachment (( 22.pdf )).

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I can't make heads or tails of any of this.

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1 hour ago, joigus said:

I can't make heads or tails of any of this.

The membership of that club is getting quite crowded! 😉

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Non-linearity is expected in anything related to gravity off the low-field approximation, ever since 1915.

Much more unexpected is "counterdicing of time." Before trying to get a full grasp of it, what about a rough grasp of it first?

So let's start with a simple question: What is "counterdicing of time"?

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6 hours ago, joigus said:

Non-linearity is expected in anything related to gravity off the low-field approximation, ever since 1915.

Much more unexpected is "counterdicing of time." Before trying to get a full grasp of it, what about a rough grasp of it first?

So let's start with a simple question: What is "counterdicing of time"?

joigus has all rights reserved to demand some sort of explanation from Kuyukov Vitaly. Vitaly is supposed , under such forums' circumstances , to address joigus' questioning. I myself did not get a FULL grasp of the thing ,especially in view of the fact that the respective pdf finally did not arrive. I don't suppose it is my right to talk or write on the part of Vitaly. However , as joigus is senior to me in membership here , I only offer my own ROUGH understanding of the phenomenon.

Time is rigid in quantum physics, not stretchy and interconnected with the dimensionality as in relativity. Moreover, measurements of quantum systems make time irreversible in quantum mechanics, whilst the theory is fully reversible otherwise. Reality does not emerge unless it is measured. And it's only when measurements are taken that their wave-like or particle-like behavior emerges. The Quantum Zeno Effect brings forth  the problematic  in which an unstable particle can never decay if observed continuously. A "conscious observer" cannot obtain knowledge unless new information is recorded irreversibly in the universe. This data can be generated and preserved either in the quantum target system or in the measuring device. It can only then  turn into info in the mind of the observer. The measurement equipment is quantum, not classical. The only way to record the irreversible interaction information is to be statistically determined. If and when ,as an analogy to neuron signaling , the topology of the neural paths covered reverses , then the knowledge in observer’s mind counters the data actually recorded by the measuring apparatus. Statistically/probabilistically countering the time dice cast in this way is sometimes called “ time counterdicing ”.

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3 hours ago, Prof Reza Sanaye said:

Statistically/probabilistically countering the time dice cast in this way is sometimes called “ time counterdicing ”.

"Counterdicing" sounds like something you would do to a potato or an onion, and very dangerous to your fingers.

Edited by joigus
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19 hours ago, joigus said:

"Counterdicing" sounds like something you would do to a potato or an onion, and very dangerous to your fingers.

I am happy that you have only picked on a dozen of my words..............  Not deeply  going thru the whole thing , , , , , , , ,

Happier even , That : You have managed to edit your single hilarious sentence   . . .

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On 3/23/2021 at 3:19 AM, Prof Reza Sanaye said:

Statistically/probabilistically countering the time dice cast in this way is sometimes called “ time counterdicing ”.

My searching and internet skills are only average, but I cannot in any reference, find any use or mention of the term "time counterdicing"

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2 hours ago, beecee said:

My searching and internet skills are only average, but I cannot in any reference, find any use or mention of the term "time counterdicing"

Neither can I. When I reached that point, I decided to go for a joke.

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35 minutes ago, joigus said:

Neither can I. When I reached that point, I decided to go for a joke.

Yeah, I think probably one or two participants in this thread, is trying to play the rest of us as suckers.

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