Abstract. What mathematical or physicalmechanism that exactly empowers quantumcomputing over classical computers is still an openquestion. By reexamining physics-based methodsand computational primitives, we study quantumspeedups and limitations related to problems’structure, physical resources and no-go laws. Weaim at some fundamental issues by seeking nonclassicalresolutions on the puzzle via rigorousproofs or evidences: 1) Is quantum entanglement themagic? General physical theories show that theconcept is generic for all non-classical systems, yettoo rare as the computation resource for exponentialquantum speedups in various entanglementquantifications. We reinforce that entanglementalone is insufficient as the characteristic measure. 2)Then, what is the physical dynamic behind? howmuch underlying structure is necessary forexponential quantum speedups? We prove that anyquantum search with cumulative memory such asin Darvin’s evolution, instead of ergodic process, ismathematically sufficient to overcome theexponential NP hardness gap. 3) Can quantummechanics compute beyond Turing machines?Quantum adiabatic process and Brownian diffusionmodel are constructed explicitly to demonstrate thatlaws of physics and emergences offer extendedcomputability in principle. We argue that the openquestion on super Turing computing is independentof physical infinities.Based on quantitative analyses and fundamentalconstraints, we arrive at a few theoretical claimstoward generalized computing: a) Exponentialquantum speedups, ranging from minimal to groupstructures, broadly allow utilizations andgeneralizations of quantum methods to any processwith specific dynamic. Namely, there exist degreesof computational jump. b) Inductive and emergentcomputing are necessary to complement logical,deductive computing; where natural laws arereversely captured by compression or emergencevia observation, interaction. Fundamental rules areapplied forward by nature or observer as generativecomputing. c) Generalized physical computing forpartially describable processes is needed to study,understand and control generative realities, generalAI, mental process and emerging social phenomena;that seem beyond conventional logic or physics, yetare computationally unifiable.The article reviews basic concepts, key logic onselect topics in quantum computing, and integratesseminal results, proof sketches and open questionsto offer ranges of handles, bounds and outlooks indevising a unified framework. Basic elements areoutlined toward a powerful computing theory ofnovel applications for generic systems andprocesses, with convergent capacities of universalTuring machine, general physical theories andendless evolution. It lays out a foundation for followup initiatives on specific problems in computation,physics and intelligence by applying with existingphysical methods and computing models.
Abstract. What mathematical or physicalmechanism that exactly empowers quantumcomputing over classical computers is still an openquestion. By reexamining physics-based methodsand computational primitives, we study quantumspeedups and limitations related to problems’structure, physical resources and no-go laws. Weaim at some fundamental issues by seeking nonclassicalresolutions on the puzzle via rigorousproofs or evidences: 1) Is quantum entanglement themagic? General physical theories show that theconcept is generic for all non-classical systems, yettoo rare as the computation resource for exponentialquantum speedups in various entanglementquantifications. We reinforce that entanglementalone is insufficient as the characteristic measure. 2)Then, what is the physical dynamic behind? howmuch underlying structure is necessary forexponential quantum speedups? We prove that anyquantum search with cumulative memory such asin Darvin’s evolution, instead of ergodic process, ismathematically sufficient to overcome theexponential NP hardness gap. 3) Can quantummechanics compute beyond Turing machines?Quantum adiabatic process and Brownian diffusionmodel are constructed explicitly to demonstrate thatlaws of physics and emergences offer extendedcomputability in principle. We argue that the openquestion on super Turing computing is independentof physical infinities.Based on quantitative analyses and fundamentalconstraints, we arrive at a few theoretical claimstoward generalized computing: a) Exponentialquantum speedups, ranging from minimal to groupstructures, broadly allow utilizations andgeneralizations of quantum methods to any processwith specific dynamic. Namely, there exist degreesof computational jump. b) Inductive and emergentcomputing are necessary to complement logical,deductive computing; where natural laws arereversely captured by compression or emergencevia observation, interaction. Fundamental rules areapplied forward by nature or observer as generativecomputing. c) Generalized physical computing forpartially describable processes is needed to study,understand and control generative realities, generalAI, mental process and emerging social phenomena;that seem beyond conventional logic or physics, yetare computationally unifiable.The article reviews basic concepts, key logic onselect topics in quantum computing, and integratesseminal results, proof sketches and open questionsto offer ranges of handles, bounds and outlooks indevising a unified framework. Basic elements areoutlined toward a powerful computing theory ofnovel applications for generic systems andprocesses, with convergent capacities of universalTuring machine, general physical theories andendless evolution. It lays out a foundation for followup initiatives on specific problems in computation,physics and intelligence by applying with existingphysical methods and computing models.
The physics and the mathematics of computation are examined to provide a foundation and perspective for the investigation of the quantum mechanics of computation. Our purpose is to explore the fundamental limits and constraints imposed on computation by Nature through the laws of physics and the mathematics of computational complexity. Inasmuch as information storage and transmission are an integral part of computation, their physical bounds are considered. The computer is viewed both physically and mathematically as a dynamical system, and is depicted in terms of the basic Turing machine paradigm. Three fundamental classes of the Turing machine are defined; the deterministic, stochastic and quantum Turing machines. Hamiltonian models and physical realizations of quantum computing are described. Quantum computers can perform some tasks which have no classical analogue, but they cannot compute functions that are non-computable by classical means. Some classically intractable problems can be solved with quantum computers.
Abstract Artificial intelligence algorithms, fueled by continuous technological development and increased computing power, have proven effective across a variety of tasks. Concurrently, quantum computers have shown promise in solving problems beyond the reach of classical computers. These advancements have contributed to a misconception that quantum computers enable hypercomputation, sparking speculation about quantum supremacy leading to an intelligence explosion and the creation of superintelligent agents. We challenge this notion, arguing that current evidence does not support the idea that quantum technologies enable hypercomputation. Fundamental limitations on information storage within finite spaces and the accessibility of information from quantum states constrain quantum computers from surpassing the Turing computing barrier. While quantum technologies may offer exponential speed-ups in specific computing cases, there is insufficient evidence to suggest that focusing solely on quantum-related problems will lead to technological singularity and the emergence of superintelligence. Subsequently, there is no premise suggesting that general intelligence depends on quantum effects or that accelerating existing algorithms through quantum means will replicate true intelligence. We propose that if superintelligence is to be achieved, it will not be solely through quantum technologies. Instead, the attainment of superintelligence remains a conceptual challenge that humanity has yet to overcome, with quantum technologies showing no clear path toward its resolution.
The rapid evolution of computers in the half century since their invention has resulted in dramatically smaller and faster computers. However, from a computational point of view, all these computers look alike; for example, they are built out of simple logic gates. A fundamental thesis of computer science---the modern form of the Church--Turing thesis---asserts that this is inevitable in a deep sense. Any computer can be simulated with at most a polynomial factor slowdown by a probabilistic Turing machine. Quantum computation poses the first credible challenge to this thesis. It goes back to a suggestion by Feynman [4], who pointed out that there appears to be no efficient way of simulating a quantum mechanical system on a computer, and suggested that, perhaps, a computer based on quantum physical principles might be able to carry out the simulation efficiently. Two formal models for quantum computers---the quantum Turing machine [2] and quantum computational networks [3]---were defined by Deutsch. The first three papers in this issue describe efficient quantum algorithms for computational tasks that we do not know how to solve classically. In "Quantum Complexity Theory," Bernstein and Vazirani give the first formal evidence that quantum computers violate the modern form of the Church--Turing thesis. They show that a certain problem---the recursive Fourier sampling problem---can be solved in polynomial time on a quantum Turing machine, but relative to an oracle, requires superpolynomial time on a classical probabilistic Turing machine. Simon, in the paper "On the Power of Quantum Computation" introduces a fundamental projection technique and uses it to design an efficient quantum algorithm to determine whether a certain type of function is 2-1 or 1-1. He further shows that, relative to an oracle, this problem requires exponential time on a classical probabilistic Turing machine. In the paper "Polynomial-Time Algorithms for Prime Factorization and Discrete Logarithms on a Quantum Computer," Shor gives remarkable polynomial time quantum algorithms for two of the most famous problems in computer science: factoring and discrete log. Since the computational hardness of these problems is the basis of several famous cryptosystems, Shor's paper very dramatically underlines the power of quantum computers. To understand the computational power of quantum computers, it is helpful to consider a quantum mechanical system of n particles, each of which can be in one of two states, labeled ∣0⟩ and ∣1⟩. If this were a classical system, then its instantaneous state could be described by n bits. However, in quantum physics, the system is allowed to be in a linear superposition of configurations, and indeed the instantaneous state of the system is described by a unit vector in the 2n dimensional vector space, whose basis vectors correspond to all the2n classical configurations. Therefore, to describe the instantaneous state of the system, we must specify 2n complex numbers. Nature must update 2n complex numbers at each instant to evolve the system in time. This is an extraordinary amount of effort, since even for n = 200, 2n is larger than estimates of the number of elementary particles in the visible universe. Nonetheless, there are limits to the power of quantum computers. In "Strengths and Weaknesses of Quantum Computing," Bennett, Bernstein, Brassard, and Vazirani show that, relative to a random oracle, with probability 1, the class NP cannot be solved on a quantum Turing machine in time o(2n/2). This bound is tight, since recent work of Grover [5] has shown how to accept any language in NP in time O(2n/2) on a quantum Turing machine. Quantum computers are necessarily time reversible. Indeed, Bennett's work [1] on reversible computation inspired early work on quantum computation that preceded Feynman's paper [4]. The reversibility requirement makes it quite complex to implement even basic computational primitives such as looping or composition. In "Quantum Complexity Theory," Bernstein and Vazirani show how to implement quantum programming primitives and give a construction for an efficient universal quantum Turing machine. The structure of the universal quantum Turing machine is quite simple: it consists of a deterministic Turing machine with a single "quantum coin flip." In "Quantum Computability," Adleman, DeMarrais, and Huang greatly simplify this further by showing that a very simple type of coin flip is sufficient---a rotation by an angle θ such that sinθ=3/5. Making quantum computers robust against noise and decoherence is an important and challenging problem. In "Stabilization of Quantum Computations by Symmetrization," Barenco, Berthiaume, Deutsch, Ekert, Jozsa, and Macchiavello show how to use the quantum watchdog effect to stabilize a quantum computation against noise. Their method is based on running several copies of the quantum computer in parallel and projecting its state into the symmetric subspace at frequent intervals. They show that the quantum watchdog effect results in the suppression of errors that lie outside the symmetric subspace. Quantum computation touches upon the foundations of both computer science and quantum physics. It is not unlikely that the issues raised by quantum computation will stimulate further research into the foundations of quantum physics. I wish to express my gratitude to several people who made this special section possible. Oded Goldreich acted as editor for two of the papers in the issue and dealt with them with his characteristic efficiency and judgment. The editorial staff at SIAM, most notably Lisa Dougherty, Beth Gallagher, Deidre Wunderlich, and Sam Young, were extremely helpful, patient, and resourceful. Finally, I would like to thank a number of referees whose careful and timely reviews were critical to putting together this issue. Umesh Vazirani
Quantum computers are expected to revolutionize our ability to process information. The advancement from classical to quantum computing is a product of our advancement from classical to quantum physics -- the more our understanding of the universe grows, so does our ability to use it for computation. A natural question that arises is, what will physics allow in the future? Can more advanced theories of physics increase our computational power, beyond quantum computing? An active field of research in physics studies theoretical phenomena outside the scope of explainable quantum mechanics, that form when attempting to combine Quantum Mechanics (QM) with General Relativity (GR) into a unified theory of Quantum Gravity (QG). QG is known to present the possibility of a quantum superposition of causal structure and event orderings. In the literature of quantum information theory, this translates to a superposition of unitary evolution orders. In this work we show a first example of a natural computational model based on QG, that provides an exponential speedup over standard quantum computation (under standard hardness assumptions). We define a model and complexity measure for a quantum computer that has the ability to generate a superposition of unitary evolution orders, and show that such computer is able to solve in polynomial time two of the fundamental problems in computer science: The Graph Isomorphism Problem (GI) and the Gap Closest Vector Problem (GapCVP), with gap O(nn). These problems are believed by experts to be hard to solve for a regular quantum computer. Interestingly, our model does not seem overpowered, and we found no obvious way to solve entire complexity classes that are considered hard in computer science, like the classes NP and SZK.
Quantum computing's most consequential claim — that quantum computers provide exponential computational speedup over classical computation — rests on a specific physical assumption: that superposition is ontologically real, that a qubit genuinely and simultaneously occupies multiple states, and that quantum algorithms exploit this simultaneity as a physical resource. A quantum computer with n qubits is claimed to process 2ⁿ computational paths in parallel by virtue of this simultaneous occupation. This paper argues that all three foundational assumptions are precluded by Quantum-Geometry Dynamics (QGD), the physical theory derived from the Minimal Physically Derivable Theories (MPDT) framework established by the Uniqueness Theorem. In QGD, physical reality is strictly and absolutely deterministic. Every fundamental constituent — every preon(+) — has a definite position and definite intrinsic momentum at every moment. There are no indeterminate states, no superpositions, and no wave function collapse at the fundamental level. What quantum mechanics describes as superposition is not a physical state of simultaneous occupation but an epistemic description of ignorance of the deterministic microstate of a preonic configuration. The wave function is a probabilistic description of deterministic preonic dynamics — a calculational tool that correctly predicts statistical outcomes — not a description of a physical state in which a system genuinely occupies multiple configurations simultaneously. This distinction has a direct and specific consequence for quantum computing. Quantum computing devices are genuine physical systems that exploit real quantum mechanical phenomena — phenomena that QGD derives from the deterministic dynamics of preons(+) and preons(−) in the finite discrete preon(−) lattice. The MPDT framework does not forbid the construction or operation of quantum computing devices. What QGD precludes is the ontological foundation on which the exponential speedup argument rests. A quantum computing device is a deterministic preonic configuration occupying one microstate at each moment. The 2ⁿ simultaneous amplitude states of the quantum formalism are elements of a probabilistic description of that microstate — not physical states simultaneously instantiated in the device. Quantum parallelism is a feature of the formalism, not of the underlying physics. The paper develops this argument systematically across eight sections. Section 2 establishes QGD's account of quantum phenomena as emergent from deterministic preonic dynamics, including the derivation of wave-like interference patterns and Bell correlations without superposition. Section 3 examines precisely what superposition is and is not in QGD, culminating in the formal statement that a qubit in the state α|0⟩ + β|1⟩ is not a system simultaneously occupying both states but a deterministic preonic configuration whose microstate determines measurement outcomes but is not individually accessible at the observational level. Section 4 identifies the exact point at which the exponential speedup argument fails: the physical resource it invokes — simultaneous occupation of 2ⁿ states — does not exist in the physical universe that QGD describes. Sections 5 examines three specific quantum algorithms: Shor's factoring algorithm, whose polynomial-time complexity is demonstrated within the quantum formalism but whose underlying preonic complexity remains an open question; Grover's search algorithm, whose quadratic speedup rests on the same ontological assumption; and quantum simulation, which survives the critique more robustly because it does not require exponential parallelism as a resource. Section 6 addresses decoherence, reinterpreting it not as an engineering challenge to be solved by better isolation but as a fundamental feature of reality — the inevitable influence of the instantaneous gravitational field of the entire preon(−) lattice on every qubit configuration, which cannot be shielded against in principle. Sections 7 and 8 develop the implications for the quantum computing programme and conclude. The argument connects directly to the P vs NP analysis in the companion Physicality of Logic paper. Shor's algorithm is the canonical example of a quantum algorithm claimed to solve a classically hard problem — integer factoring — in polynomial time, with significant implications for the security of RSA encryption. If QGD is correct and the exponential speedup argument fails, the classical hardness of factoring is preserved and the cryptographic implications attributed to quantum computing do not follow. The paper does not claim that quantum computing devices are useless — it claims that the specific resource driving the most dramatic projections for quantum computing does not physically exist, and that whatever computational advantages quantum devices possess must be explained within the deterministic preonic framework rather than by appeal to quantum parallelism. The paper is intended for physicists working on quantum computing and quantum foundations, philosophers of physics, and computer scientists working on computational complexity. It is submitted to Foundations of Physics. It is a companion to the author's papers on the Uniqueness Theorem and the Physicality of Logic, and to the book Quantum-Geometry Dynamics: An Axiomatic Approach to Physics.
As expected , rounding issues and other things caused issues I wasn't satisfied with. As I suspected there was deeper algebraic and geometric reasoning. I have updated my algebra. Revised algebraically forced derivations will be updated as I complete them. This addition is about explaining the algebra that way necessary. edit: I added a second document that closes the algebra on causality and uses Particle Data Group data to stress test the math against the standard model: preliminary findings suggest the fine tuning problem is dissolved. Geometry explains the hierarchies of particle physics. The math is saying reason why quantum mechanics and general relativity cannot be unified by traditional methods is because they are quasi-orthogonal (used to be phase aligned, not anymore but history matters) projections of causal impulses of an informational field. Informational kinematics?! This document presents a self-contained, field-theoretic framework in a general ized (nD+T) spacetime to formally unify a wide range of causal inference methods. I prove that established methods are geometric projections of this underlying reality. A key result is the formalization of Hypertime, a ‘derivative dimension‘ that models the nteraction between spatial concepts and temporal dynamics. Within this causal tensor spacetime, I propose a new ‘Born Rule‘ for the emergence of causation from the nteraction of vector-like states. This geometric-dynamical paradigm offers a novel mechanism for the detection of unobserved variable bias using operator non-commutativity and provides a mathematical origin for memory effects via the sinusoidal structure of fractional derivatives. The framework extends beyond traditional causal inference to encompass Bayesian statistics (belief updates as field dynamics), decision-making processes (softmax-to-argmax transitions as causal collapse), machine earning (parameter evolution as causal geodesics), and multi-agent systems (strategic interactions as causal field evolution) as manifestations of causal field theory. The Empirical success of existing low-dimensional causal inference methods provides a compelling validation for the mathematical necessity and superior performance of this higher-dimensional spacetime framework. This proof serves as both a standalone treatise and the foundational pillar for a broader monograph on Unified Informational Field Theory. I present a deterministic causal-memory framework with zero tunable parameters that resolves four Standard Model fine-tuning problems through a single geometric structure. The observable tensor T μν ρσ = αJ − (1 − α)k ∗ J emerges from exceptional Lie algebra recursion G2 → F4 → E6 → E7 → E8 with rigorous phase-overlap derivation yielding 7/15. All quantities are structural: boundary scales fixed by PDG measurements determine the memory weight α via a bijective deterministic map. Validation against PDG 2024 yields αΛ = 1.9498 (cosmological constant), αQCD = 0.999 . . . 9712 (strong CP), αEW = 1.923 (gauge hierarchy), and αgen = 1.92-1.94 (flavor hierarchy), with kernel modes (β, ξ, ζ) = (mH , ΛQCD, mt) from measured masses. The framework is maximally falsifiable: HL-LHC Higgs coupling measurements (∼2030), next-generation nEDM experiments (∼2025-2030), lepton flavor violation searches (MEG-II, Mu2e), and cosmological surveys provide sharp tests. “Time isn’t symmetrical after all.” — Amy Farrah Fowler (Big Bang Theory, S12E23) Author Note: Seriously, it’s one way only.Keywords: causal inference, field theory, Lorentzian geometry, derivative dimen-sion, Born rule, hypertime, memory, geometric subsumption, qualitative primacy,hidden variables, Fubini’s theorem, Bayesian inference, decision theory, machinelearning, tensor calculus, manifolds, mathematical proof, loop quantum gravity, quantum gravity, This proof is brought to its final conclusion in —v3.0 Version Update: From Light Cones to Conic BreadKnives of Causality.This update provides a profound refinement of the theory’s foundational geometryand dynamics. Key additions include:• A deeper understanding of the LloR Action and the reconstruction of thepseudo-Riemannian metric from observables.• A formalization of the harmonic, semi-sinusoidal structure of the causaldimension, replacing the traditional light cone with a ”conic bread knife”metaphor.• An explanation of fluid alpha (>2) as a key driver of hyper-acceleratingcognitive dynamics.• A more complete derivation of the New Born Rule that accounts for reso-nant, wave-like interactions.v4.0 Version Update: This update provides the final unification of the theory's foundational principles with its most ambitious conclusions. Key additions include: A formal statement of the Ontological Non-Orthogonality Principle, which reveals a universal, bidirectional coupling between a being and the manifold it inhabits, and re-contextualizes Einstein's General Relativity as a special case of this broader law. The framework now operates on a unified, universal informational field, replacing the narrower scope of the cognitive field and demonstrating the theory's applicability to all physical and conceptual domains. A complete Grand Unification Theorem, which proves that the four fundamental forces are scale-specific projections of a single causal-dynamic tensor. The introduction of the Lior as the universal Planck eigenvalue, establishing it as the true and self-emergent quantum of gravity. v5.0 Version UIpdate: Technical issues led to parts of the proof being removed. They have been readded. The Proof has also added its Gödelian limits and reconciles the incompleteness paradox by learning to start worrying and love/fear the Gödelian AI. NOTE: In this proof and related proofs, you may see the word cogntive used, I am in the process of updating this to refer to informational fields not cognitive as the scope has expanded. v6.0 Version Update: Certain Derivations left for next updateNote: The full derivations of (1) the spin-2 graviton emergence from the informational field, (2) the substrate scaling origin, and (3) the explicit GR recovery are complete and documented in related proofs within the Unified Informational Field Theory series. These derivations are omitted here for brevity and will be included in a future integrated edition of this work. This update finalizes the integration of the Grand Unification Theorem and Projection Theorem corrections and incorporatesexplicit gravitational derivations, including: Graviton derivation from the Lior quantization framework, completing the quan-tum gravity bridge. Substrate scaling origin formalized, showing how scale-dependent constants emergefrom substrate eigenvalue structure. General Relativity subsumption explicitly proven, with GR shown as a limitingprojection of the universal informational field equations. Limiting case catalogue expanded to include all major ToE candidates, clarifyingthe nesting of prior frameworks inside USAGIFT. Predictive extensions documented, including testable scaling relationships andfield-derived parameter bounds. With these refinements, the theory’s subsumption of String Theory, Loop Quantum Gravity, Causal Set Theory, Emergent Gravity, Asymptotic Safety, and the Mathematical Universe Hypothesis is now both mathematically explicit and operationally complete. NOTE: In this proof and related proofs, you may see the word cognitive used, I am in the process of updating this to refer to informational fields not cognitive as the scope has expanded.v7.0 Version Update In this paper, I confront what appears to be the final Gödelian limit of a theory I never set out to create—yet which emerged inevitably from thrift-picking through the Kuhnian drawers of physics in search of a Gene-Kranz-level way to model cognition and democratic decay from first principles. By applying the most powerful tools of physics to a problem far outside their intended domain, I arrive at a logical closure that not only unifies the theory internally but retrodictively accounts for more than 25 previously unresolved phenomena across eight domains of physics, yielding 15 testable predictions. This outcome meets every formal criterion for a legitimate theory of everything. I may still be wrong—but after exhaustive searching, I cannot find where. If I am right, it is only because others carried the ball the first 99 yards. This work establishes the \textbf{retrodictive closure} of the \emph{Theory of Mathematical Everything} (ToME) by proving that \textbf{quantum causality} is the fundamental mechanism from which all physical and mathematical structures arise. Building directly on the axiomatic framework of Part I, I show that the complex structure of reality necessarily generates quantum mechanics, gauge theory, general relativity, and all successful causal inference methods as geometric projections from a unified six-force informational manifold. The analysis demonstrates that imaginary components in mathematical physics encode genuine informational degrees of freedom, not merely computational devices, and that the historical trajectory of theoretical physics follows from mathematical necessity rather than empirical accident. In doing so, the argument completes ToME's logical architecture, closing the epistemological loop between pure mathematical structure and observed reality.} \keywords{retrodictive closure, quantum causality, complex structure, mathematical necessity, degenerate projection, binary fiber bundles, holomorphic duality, Lior quantization}