Dear Robert,

certainly I plan to read your essay. It looks very interesting and I must dig deeper...

Thanks for your words and voting

All the best and good luck for the contest

Torsten

Hi Torsten,

Your idea is similar to the idea of deep learning in AI via Renormalization group. Googling will get you many papers. As a matter of fact my system generates RG automatically.

You have seen my system before but in my new essay which is short and sweet:) I derive Newtons gravitation(long distance) law from the SAME system that generate all the quantum mechanical results. Moreover, the simulations that predict the electron and the proton now I find an analog of it in the standard physics via Helmann potential which is a combination of Coulomb and Yukawa potentials. Thanks for your attention.

last year essay

your this year essay

see gravity,p2

gravity

    Torsten,

    I see. General Relativity and Gravitation sponsored by GRF. Any affiliation with eventual LIGO efforts to approach BB waves?

    Jim

    Sorry, that should be gravity "P" energy in the results. thanks

    Torsten,

    A great essay as usual, right on topic, well written and more importantly for me correctly identifying the quantum scale mechanisms, layered (fractal) and feedback based architecture producing the - almost 'illusion', of aims, intent and even consciousness.

    Of course I would think all that as my essay describes and concludes exactly the same components and structure, so is very complementary, though where you more thoroughly cover the key point I also identify important related matters at the highest and lowest ends of the scale. I hope you may particularly comment on my identifcation of a classical derivation of QM's 'probability' distribution, built wearing last years red & green socks!

    I gather yours too has been hit by '1's. Mines had 11! but I've refused to retaliate. I think yours is worth far more than it's current placing suggests. Close now to final scoring so I hope you'll get to read mine and confirm you agree with my analysis of our complementarity or raise any issues.

    Very well done, again, and best of luck.

    Peter

      Dear Torsten,

      A very well written technical essay, that makes some very interesting points. While I grasped the larger ideas of feedback loops, top-down effects and the results you obtained on fractal curves, I can see the devil is in the details. I wish my knowledge of topology was better to better appreciate some of the results and insights here, but I intend to change that and come back to this paper again once I have a better grasp of related concepts (PS: If you can suggest some kind of good resource for someone who is beginning to study topology, I would be very grateful. I rather not start with some of the advanced references in your submission).

      Please know that I appreciate the mathematical rigor of your work, for I think it is important to not be wishy washy when dealing with issues of learning and intuition. My submission shows that our learning is intricately tied to feedback-feedforward models. I also agree on the idea of top-down causation (though I prefer that Ellis is now referring it to as top-down realization). It is heartening to see that over the course of the various submissions, there seems to be a growing consensus emerging on what some of the important ideas to probe further are.

      This is great work and focuses on the important questions. I have rated it highly so that it can make it to the final deservedly, and can be judged fairly for its proper technical content. I now look forward to going back and reading your past winning essays on this forum. Thanks and good luck in the contest!!

      Cheers

      Natesh

      PS: My email is nganesh@umass.edu. Please feel free to reach out. I would love to see where you go further on this line of work. Hopefully I will gain more understanding on this area of math, as I dive deeper. I am particularly interested in understanding strange non-chaotic attractors.

        Hi adel sadeq,

        thanks for your hint. I think my approach is a little bit more general and flexible then renormalization group approach. In particular, I'm not limited to the Ising model. But again, thanks for the hint. I will study more work in this direction.

        Now to your work: honestly I had some problems to understand it (including your last year essay). It was not obvious to me how you will get the quantum mechanics? In this year essay, how did you get the Hellman potential? Did you assume it?

        Best wishes and good luck with the contest

        Torsten

        Dear Peter,

        thanks for your words and the voting (which I really need).

        Today I had a chance to look into your essay. Interestingly I had a kind of deja vu. You got also similar structures (like SU(2) etc.). So, I agree that our essays are complementary. In particular, your essay is the background of my essay and vice verse.

        Well done, Peter.

        Of course I will comment on your interpretation of QM but better on your comment area.

        All the bestfor you and good luck in the contest

        Torsten

        PS: That speaks in your favour that you don't retaliate. I also don't do it.

        Thanks Torsten,

        I have a friend Jolanda who was form many years a Civil Engineer and now has a degree and practice in Environmental Law. She may have some insights or information relevant to our writing about human/nature boundaries and to quantify changes in fractal dimension before and after development.

        All the Best,

        Jonathan

        It is good to see that..

        If the qualifying round ended right now, you and I would both be in the finals. I wish you luck now and into the future Torsten. I left another brief reply/comment above.

        All the Best,

        Jonathan

        Torsten,

        I'm glad you agree on our agreement. I think we're both right on topic and get straight to the heart (and brain!) of the matter and it's dynamics. Certainly some 10's around here I think! I hope you'll also check out my video.Classic QM on vimeo. I'm also always up for collaboration. Loners can't penetrate doctrine and few have all the skills.

        I'm scoring yours now. Very well done. Do please comment on/criticise the video.

        Peter

        Dear Natesh,

        at first thanks for this reply (and of course for the upvoting, I'm gonna need it)

        I agree completely with your summarize of the contest. Top-down causation is one idea that admits growing consensus in many essays.

        As you statedin your comment, I like mathematical models with some level of rigor and I'm very glad that we agree in this point.

        I will ceratinly send you some literature by email.

        Thanks again for the voting and all the best as well good luck in the contest!

        Torsten

        Hi Torsten,

        Thank you for reviewing my essay. As you know my system is based on a simulation of a mathematical structure that is based on random numbers that lead to known physics result , so it was natural for me to try to connect it(or somehow convert it) to standard methods in physics. During such a search I stumbled on the Helmann potential and noticed that it pretty much produced similar curves to my simulation. Of course such potential has a different use in standard physics, however, it seems that the original Yukawa interpretation of "force particles" might not have been a good idea! Also, it was natural that at distances longer than Compton wavelength the Coulomb potential should take over. In another word, to interpret Yukawa's potential the same as Coulomb i.e. two particles(actual) interacting as in chirality!

        As to the idea itself, I understand that people don't have all the time or inclination to examine other ideas to a great extend. But I have shown in numerous examples and simulations with NUMBERS how the QM/QFT phenomenology arises from such structure.

        My best hope is to give people a quick taste of the idea. And at least I hope people spend few minutes to run the simulations, especially the Newton's gravity law generation.

        Thanks again.

        additional advertising:)

        You can see how the system is so coherent, it naturally derives , or let say realities aspects emerge from simple random numbers. This is very similar to constructing endless geometrical structures from the simple line segments combinations. Space and matter emerge naturally as in your theory! The theory is inherently non-local, EPR is very natural.

        Moreover, there are no unnatural 12 fields on top of each other being scalar, spinor, vectors,vector bosons!, tensors........on and on. No virtual particles(exist, no don't exist just mathematical), and many other concepts that try to push an elephant into a needles's eye. I am not saying that the present models are wrong, they are just so twisted because of the historical developments.

        Dear Torsten,

        With great interest I read your essay, which of course is worthy of high rating. Excellently written.

        Your work is related to my interests

        «My current work is in direction of quantum gravity and cosmology. There, I used mathematical methods from topology to understand quantum gravity.»

        «I had the feeling that the loop hypothesis is correct. I was thing that there is an interaction between neurons which can be not directly realized (so that it forms a loop).»

        The cycles you already have, they are connected to your torus loops

        «the two generators of non-contractable loops of the torus (or doughnut) as example.»

        About how torus loops function from a physical point of view and how they form large loops by which they interact with each other at resonant frequencies, is shown in my essay.

        I wish you success in the contest.

        Kind regards,

        Vladimir

        Dear Torsten,

        you propose an intriguing new way of looking at neural networks in terms of topologically stable structures---feedback loops. I'm not sure, however, I understand it fully. I would see an analogy to (topological) error correction here: the whole network, i.e. the detailed states (firing or not-firing) of all the neurons, yields the codespace, while only the topologically protected structures encode information; that way, the information is robust to small, random fluctuations within the network, i.e. noise. Is this somewhat close?

        I'm not sure, then, what exactly you mean by the 'strength' and 'phase' of a signal. Are you referring to the signal carried by a given feedback loop? If so, is the strength related to the rate of firing, and the phase to the timing?

        In the end, it's an interesting proposal, which however I feel could benefit from a more in-depth treatment (but of course, that's hard to do within the length constraints of this essay contest).

        Hope you do well!

        Cheers,

        Jochen

          Dear Sirs!

          Physics of Descartes, which existed prior to the physics of Newton returned as the New Cartesian Physic and promises to be a theory of everything. To tell you this good news I use «spam».

          New Cartesian Physic based on the identity of space and matter. It showed that the formula of mass-energy equivalence comes from the pressure of the Universe, the flow of force which on the corpuscle is equal to the product of Planck's constant to the speed of light.

          New Cartesian Physic has great potential for understanding the world. To show it, I ventured to give "materialistic explanations of the paranormal and supernatural" is the title of my essay.

          Visit my essay, you will find there the New Cartesian Physic and make a short entry: "I believe that space is a matter" I will answer you in return. Can put me 1.

          Sincerely,

          Dizhechko Boris

          Dear Jochen,

          thanks for your words and for reading my essay.

          you are right that the whole approach is invariant for small fluctuations because of the topological structure. You are also right that strngth is the rate of firing and phase is the timing (I thought that I wrote at some place).

          In principle, I describe the topological structure of the space of neuron firing. Also this topologicval structure is robust w.r.t. fluctuations.

          Here is also where the structure change happens: for higher rates of firing and long time, this structure changes from a network (as picture of the brain network) into a tree.

          You are right I have to present more details but there was not room. Furthermore, the math is not so easy to present.

          So thanks again

          Best

          Torsten

          Dear Torsten,

          Your description of the dynamic loops reminded me of the dynamic theory of consciousness by T Fekete and S Edelman (e.g. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4961712/). I like the approach. What always bothered me a bit is that there is no good examples of the consequences of their proposal. A good model often goes a long way and maybe your work could be a good starting point for that!

          All the best!

          Larissa