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Journal of Uncertain Systems

If Many Physicists Are Right and No Physical Theory Is Perfect, Then the Use of Physical Observations Can Enhance Computations

Olga M. Kosheleva, Michael Zakharevich

Published Jan 1, 2014• 4 citations
OpenAlex

Abstract

Many real-life problems are, in general, NP-complete, i.e., informally speaking, are difficult to solve – at least on computers based on the usual physical techniques. A natural question is: can the use of non-standard physics speed up the solution of these problems? This question has been analyzed for several specific physical theories, e.g., for quantum field the-ory, for cosmological solutions with wormholes and/or casual anomalies, etc. However, many physicists believe that no physical theory is perfect, i.e., that no matter how many observations support a physical theory, inevitably, new observations will come which will require this theory to

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Many real-life problems are, in general, NP-complete, i.e., informally speaking, are difficult to solve – at least on computers based on the usual physical techniques. A natural question is: can the use of non-standard physics speed up the solution of these problems? This question has been analyzed for several specific physical theories, e.g., for quantum field the-ory, for cosmological solutions with wormholes and/or casual anomalies, etc. However, many physicists believe that no physical theory is perfect, i.e., that no matter how many observations support a physical theory, inevitably, new observations will come which will require this theory to
Many real-life problems are, in general, NP-complete, i.e., informally speaking, are difficult to solve -- at least on computers based on the usual physical techniques. A natural question is: can the use of non-standard physics speed up the solution of these problems? This question has been analyzed for several specific physical theories, e.g., for quantum field theory, for cosmological solutions with wormholes and/or casual anomalies, etc. However, many physicists believe that no physical theory is perfect, i.e., that no matter how many observations support a physical theory, inevitably, new observations will come which will require this theory to be updated. In this paper, we show that if such a no-perfect-theory principle is true, then the use of physical data can drastically speed up the solution of NP-complete problems: namely, we can feasibly solve almost all instances of each NP-complete problem.
Topological Renormalization of Information: Resolving P versus NP via Holographic Field Dynamics in Fractal Spacetime The P versus NP problem has traditionally been viewed through the lens of pure mathematics and algorithmic complexity. However, we propose that the limitation is not algorithmic, but physical. In this paper, we present a unified framework that redefines the substrate of computation itself—moving from discrete Turing Machines to Self-Observing Topological Machines (SOTM) capable of O(1)\mathcal{O}(1)O(1) quantum relaxation. Why this research is significant for your readership: Resolution of P=NP: We provide a rigorous physical derivation showing that in a fractal spacetime metric (D≈4.7D \approx 4.7D≈4.7), NP-complete search spaces can be collapsed topologically. This suggests that NP⊆PNP \subseteq PNP⊆P within specific high-energy physical limits. Introduction of Virtual Quantum Processing (VQP): This is the most critical practical contribution of our work. We demonstrate that physical qubits (trapped ions, superconductors) are unnecessary if the software architecture perfectly mimics quantum topology. We present empirical data from the KARIOS V26 architecture, which successfully simulated this environment to solve the Levinthal Protein Folding paradox in under 9 seconds on classical hardware. Timely Theoretical Alignment: Our model relies on a scalar field renormalization at ≈500\approx 500≈500 GeV. This theoretical prediction aligns remarkably well with recent indirect observations of high-energy anomalies in Dark Matter annihilation signals, offering a potential computational explanation for these physical phenomena. This work bridges the gap between high-energy theoretical physics and practical, scalable artificial intelligence. It moves the field beyond the "Algorithmic Age" into the "Topological Age," offering a blueprint for quantum-grade performance without the need for cryogenic hardware. We believe this paper will be of immense interest to researchers in quantum information theory, computational complexity, and neuromorphic engineering.
The words: determinism, hidden variables, subjectivism, information, objectivism, informational-theoretic axioms,observers have some connection with physical reality? What we mean with "description" of physical reality? When we say that we understand this reality? Certain parameters:position, velocity are sufficient? We will focus only to conceptual considerations regarding the relation between the "questions" and the relative "answers" in general and specifically in quantum mechanics. It is usually believed that the answers are more important of the questions, for this reason we can read many answers everywhere and in different field of knowledge. We need to add and clarify some things: (i) usually an answers require a question, (ii) but, as we know, their relation is not so simple and immediate, (iii) For instance: a)an epistemic questions give us ontic answers? b)the answer has a connection with the question and vice versa? c)we could to infer a question starting from an answer? d)there are answers without questions? These answers could be in some framework considered as ontic answers? The relative scientific works are the same time ontic? Speaking of quantum mechanics we see around many answers in the meantime we do not see the correspondent questions, these answers seem completely independent, and this seem a right road, the road of the independent nature unlinked from human thoughts. We retain instead that questions can affect the possible answers. Exist "something" before the question?