Partial orders have been used to model several experimental setups, going from classical thermodynamics and general relativity to the quantum realm with its resource theories. In order to study such experimental setups, one typically characterizes them via a (numerical) representation, that is, a set of real-valued functions. In the context of resource theory, it is customary to use \textbf{mathematical} representations, i.e. a set of \textbf{measurement outcomes} which characterize the achievable transitions within the experimental setup. However, in line with the minimum energy and maximum entropy principles in classical mechanics and thermodynamics, respectively, one would expect an optimization interpretation for a representation to be called \textbf{physical}. More specifically, a physical representation could consist of a set of competing \textbf{optimization principles} such that a transition happens provided they are all optimized by it. Somewhat surprisingly, we show that this distinction can result in an \textbf{infinite information gap}, with some partial orders having mathematical representations that involve a finite amount of information and requiring infinite information to build a physical representation. We connect this phenomenon with well-known resource-theoretic scenarios like majorization, and develop notions of partial order dimension that run in parallel to the representations that we consider. Our results improve on the classification of preordered spaces in terms of real-valued functions.
Partial orders have been used to model several experimental setups, going from classical thermodynamics and general relativity to the quantum realm with its resource theories. In order to study such experimental setups, one typically characterizes them via a (numerical) representation, that is, a set of real-valued functions. In the context of resource theory, it is customary to use \textbf{mathematical} representations, i.e. a set of \textbf{measurement outcomes} which characterize the achievable transitions within the experimental setup. However, in line with the minimum energy and maximum entropy principles in classical mechanics and thermodynamics, respectively, one would expect an optimization interpretation for a representation to be called \textbf{physical}. More specifically, a physical representation could consist of a set of competing \textbf{optimization principles} such that a transition happens provided they are all optimized by it. Somewhat surprisingly, we show that this distinction can result in an \textbf{infinite information gap}, with some partial orders having mathematical representations that involve a finite amount of information and requiring infinite information to build a physical representation. We connect this phenomenon with well-known resource-theoretic scenarios like majorization, and develop notions of partial order dimension that run in parallel to the representations that we consider. Our results improve on the classification of preordered spaces in terms of real-valued functions.
The Infinite Gap (ε∞) as a Model-Dependent Structural Principle in Physics: Conceptual Framework, Dynamical Bounds, and Experimental Signatures
#Description: This work introduces the concept of the *Infinite Gap* (ε∞) as a model-dependent structural principle capturing the fundamental mismatch between idealized mathematical descriptions and physically realized states. Rather than defining ε∞ as a single universal observable, we formulate it as a family of gap functionals whose explicit representation depends on the physical framework under consideration. The concept is developed across multiple domains, including cosmology, quantum mechanics, and information theory, providing a unifying perspective on discrepancies between theoretical predictions and empirical observations. In the quantum context, the Infinite Gap is directly related to measurable quantities such as state purity, defined by 1−Tr(ρ2), and is shown to obey dynamical inequalities under Lindblad evolution, reflecting the irreversible growth of decoherence. This establishes a direct bridge between the conceptual framework and experimentally accessible systems. We further introduce a structural contribution, δstruct, representing an irreducible component of the gap that cannot be attributed to noise, entropy, or decoherence. This term is proposed as a hypothesis capturing intrinsic limitations in the representation of physical reality by mathematical models. The framework also provides testable implications in controlled quantum systems, where deviations from idealized purity can be experimentally quantified, as well as in cosmology, where large-scale observational tensions may be interpreted within this perspective. Overall, this work aims to establish a conceptual and semi-quantitative bridge between ideal theoretical constructs and the limitations inherent in their physical realization, positioning the Infinite Gap as a candidate structural feature of physical theory. # Keywords: * Infinite Gap * Structural Principle in Physics * Quantum Decoherence * Density Matrix * Purity * Entropy * Lindblad Equation * Cosmology * Model-Dependent Framework * Effective Theories * Information Theory * Foundations of Physics
We study the informational underpinnings of thermodynamics and statistical mechanics, using an abstract framework, general probabilistic theories, capable of describing arbitrary physical theories. This allows one to abstract the informational content of a theory from the concrete details of its formalism. In this framework, we extend the treatment of microcanonical thermodynamics, namely the thermodynamics of systems with a well-defined energy, beyond the known cases of classical and quantum theory, formulating two necessary requirements for a well-defined thermodynamics. We adopt the recent approach of resource theories, where one studies the transitions between states that can be accomplished with a restricted set of physical operations. We formulate three different resource theories, differing in the choice of the restricted set of physical operations. To bridge the gap between the objective dynamics of particles and the subjective world of probabilities, one of the core issues in the foundations of statistical mechanics, we propose four information-theoretic axioms. They are satisfied by quantum theory and more exotic alternatives, including a suitable extension of classical theory where classical systems interact with each other creating entangled states. The axioms identify a class of theories where every mixed state can be modelled as the reduced state of a pure entangled state. In these theories it is possible to introduce well-behaved notions of majorisation, entropy, and Gibbs states, allowing for an information-theoretic derivation of Landauer's principle. The three resource theories define the same notion of resource if and only if, on top of the four axioms, the dynamics of the underlying theory satisfy a condition called "unrestricted reversibility". Under this condition we derive a duality between microcanonical thermodynamics and pure bipartite entanglement.
In these decades, it has been revealed that there is rich information-theoretic structure in thermodynamics of out-of-equilibrium systems in both the classical and quantum regimes. This has led to the fruitful interplay among statistical physics, quantum information theory, and mathematical theories including matrix analysis and asymptotic probability theory. The main purpose of this book is to clarify how information theory works behind thermodynamics and to shed modern light on it. We focus on both of purely information-theoretic concepts and their physical implications: We present self-contained and rigorous proofs of several fundamental properties of entropies, divergences, and majorization. We also discuss the modern formulations of thermodynamics, especially from the perspectives of stochastic thermodynamics and resource theory of thermodynamics. Resource theory is a recently-developed field as a branch of quantum information theory in order to quantify (energetically or information-theoretically) "useful resources." We show that resource theory has an intrinsic connection to various fundamental ideas of mathematics and information theory. This book is not intended to be a comprehensive review of the field, but would serve as a concise introduction to several important ingredients of the information-theoretic formulation of thermodynamics.
All physical systems register bits of information, whether it be an atom, an electrical current, the location of a billiard ball, or a switch. Information can be classical, quantum, or a hybrid of both, depending on the system. For example, an atom or an electron or a superconducting system can register quantum information because the quantum theory applies to each of these systems, but we can safely argue that the location of a billiard ball registers classical information only. These atoms or electrons or superconducting systems can also register classical bits because it is always possible for a quantum system to register classical bits. The term information , in the context of information theory, has a precise meaning that is somewhat different from our prior “everyday” experience with it. Recall that the notion of the physical bit refers to the physical representation of a bit, and the information bit is a measure of how much we learn from the outcome of a random experiment. Perhaps the word “surprise” better captures the notion of information as it applies in the context of information theory. This chapter begins our formal study of classical information. Recall that Chapter 2 reviewed some of the major operational tasks in classical information theory. Here, our approach is somewhat different because our aim is to provide an intuitive understanding of information measures, in terms of the parties who have access to the classical systems. We define precise mathematical formulas that measure the amount of information encoded in a single physical system or in multiple physical systems. The advantage of developing this theory is that we can study information in its own right without having to consider the details of the physical system that registers it. We first introduce the entropy in Section 10.1 as the expected surprise of a random variable. We extend this basic notion of entropy to develop other measures of information in Sections 10.2–10.6 that prove useful as intuitive informational measures, but also, and perhaps more importantly, these measures are the answers to operational tasks that one might wish to perform using noisy resources. While introducing these quantities, we discuss and prove several mathematical results concerning them that are important tools for the practicing information theorist.
What is information? A short answer could be: Anything that changes our minds and states of thinking! Information is virtual. It can be carried by speech, an image, scratches on a stone, patterns in a photon field, the connections of neurons in our brains or even by the wavefunction of an electron. Information does not depend on the actual means of transmission nor does its identity change when changing the carrier. Information is physical. It needs to be sustained by a physical substrate and rearranging that substrate to contain the wanted information requires to spend energy or work. Without a physical world, information can not be stored, processed, or transmitted. Our world is permeated with different representations of information. Actually Information about the physical laws governing our Universe can be found everywhere and in everything. Could it then be that the real fundamental elements of this world are tiny bits of information? Could we get it from bit?1 A number of researcher investigate this possibility, and several of their attempts to recover physical laws from the principles governing information are reported about in this special issue on physics of information. The articles by Gregg Jaeger,2 by Ariel Caticha,3 and by John Skilling and Kevin Knuth4 address the reconstruction of quantum mechanics from information theory. Furthermore, Kevin Knuth and James Walsh5 show how to recover space-time from particles sending each others signals in an initially geometry-free setting. A central element of most works on information is the concept of a probability. Probabilities can be defined via various routes. Most familiar might be their definitions by the frequentists school as relative frequencies of events (in the limit of infinite amounts of such). A more general definition of probabilities is the Bayesians' one, which regards probabilities as quantifiers of statements, expressing how much those should be expected to be true. Although this definition looks subjective on the first glance, it rests on a solid mathematical theorem by Richard Cox6 that any extension of binary logic to a continuum of single valued truthfulness quantifier that respects a minimum of requirements must be isomorphic to probability theory. And this definition turns out to embrace the frequentists' definition in case that infinite numbers of comparable events are actually available and can be counted. The majority of authors of this special issues seem to favor the Bayesian perspective, which is probably a result of our own, the guest editors', preference and not necessarily a reflection of the prevailing position of contemporary scientists. The different views on probabilities of frequentists and Bayesians are addressed by the article of Allen Caldwell.7 He builds a bridge between these antagonistic camps by explaining frequentists' constructions in a Bayesian language. In particular, his argumentation why the omnipresent p-value in statistical and experimental literature might often capture a relevant signal of model misfit is reassuring, given that a large fraction of our medical system is based on decisions backed up by p-values. A Bayesian might add that it would be even more reassuring, if a system rigorously build on logic and its continuous extension would be used for decisions affecting live-or-death questions. The laws governing probabilities themselves seem to reflect that of more elementary mathematical structures. Kevin Knuth shows how these emerge from lattice theory, which deals with relations in partially ordered sets like that of collections of possibilities.8 The sum rule of probability theory is a direct consequence of the underlying lattice structure. Interestingly, a number of other theories are resting also on such lattices and therefore exhibit their own versions of sum rules: measures of sets, mutual information, the Euler characteristics of topological spaces, as well as quantum mechanical interactions that are quantified by pairs of numbers, the real and imaginary parts of complex probability amplitudes (see also4). The theory of information has very practical application in physics and elsewhere. Manfred Opper discusses how the solutions of stochastic differential equations can be inferred via variational methods, which have their origin in thermodynamics.9 Torsten Enßlin introduces information field theory (IFT), the information theory for fields, as a means to infer the configuration of a physical field from incomplete and noisy data.10 The mathematical apparatus for this is that of quantum field theory (QFT), just with ordinary probabilities instead of complex probability amplitudes as in the latter. Could it be that the difference between IFT and QFT is just be the same as between classical information theory and quantum mechanics, the transition from real valued to complex valued quantifier for statements? Anyhow, any practical inference machinery, be it for dynamical systems or for fields, requires sophisticated numerical methods. Michael Betancourt reviews Markov Chain Monte Carlo Methods to calculate expectation values over high dimensional probabilities.11 Theo Steininger and coworkers present the NIFTy3 software package for numerical information field theory calculations, which can handle very high dimensional field inference problems.12 Finally, in an article focused on the subtleties of the Monty Hall problem and mostly aiming at information theoretical entertainment, Torsten Enßlin and Margret Westercamp investigate the possibility that human intuition might be more rational than contemporary psychology thinks.13 A number of possible topics for an issue on physics of information are not addressed here. We would have loved to have articles on Landauer's principle, which states that erasing information has to cost energy, on QBism, a Bayesian version of quantum mechanics, on artificial and biological neural networks, as well as any other aspect of the information-soaked biological world. What has a reader of this special issue to be equipped with in order to follow the lines of thoughts? In addition to the usual physicist's education, the minimal additional equipment are the basics of probability theory and the concept of entropy. Most of the other concepts used in the articles rest on those and are introduced there. Let A, B, and C be propositions (or possibilities). The probability P ( A | B ) of A being true assuming that B is true is a number between 0 and 1, with P ( A | B ) = 1 expressing certainty of A under B ( B ⇒ A ) and P ( A | B ) = 0 expressing certainty of not A being the case under B ( B ⇒ ¬ A ).
Quantum mechanics is the study of uncertainty. But what does uncertainty mean within the structure of physical reality? From Newton onward, mathematical physics has largely approached motion by specifying a state, identifying the laws governing its evolution, and determining the subsequent behavior of the system. Fourier extended this program to heat, Maxwell to electromagnetic fields, Navier and Stokes to fluids, Hamilton and Lagrange to variational and canonical mechanics, Einstein to spacetime, and quantum mechanics to the evolution and measurement of the quantum state. Across these theories, increasingly powerful mathematics has described what a physical system may do and how its state may evolve. This work asks a logically prior question: Does everything that is mathematically accessible participate equally in physical realization? We propose that it does not. The central distinction developed in this work is between accessibility, admissibility, participation, and realization. A mathematical representation may contain a large space of possible states, trajectories, modes, or outcomes. Physical realization, however, need not occupy that space uniformly. We propose that relational structure establishes an admissible geometry within the accessible space; that geometry determines which possibilities participate strongly or weakly; and probability subsequently quantifies the residual uncertainty among physically supported realizations. The resulting ordering is: Potentiality → Relations → Structure → Geometry → Admissibility → Participation → Realization → Evolution. Under this interpretation, probability is not abolished. Superposition is not abolished. Quantum mechanics is not rejected. Rather, their physical ordering is reconsidered. Superposition describes what the mathematical representation can contain; relational geometry determines how strongly those possibilities can participate; probability describes the uncertainty remaining within that structured support; and observation records the realization that occurs. The NIST loophole-free two-photon Bell experiment provides the principal empirical test developed in this work. Beginning from the experimentally characterized entangled state—not from subsequently observed outcome counts—we construct a relational geometry and the corresponding outcome-dependent participation and information-cost landscapes. The NIST measurement configurations then become experimental sampling coordinates on a geometry determined independently from the later event records. The resulting analysis identifies several mutually reinforcing features: strong inequality among the participation of mathematically accessible Bell outcomes; a corresponding hierarchy of geometric information cost; concentration of experimental variation into reduced effective dimensions; agreement between predicted geometric support and held-out experimental records; preservation of Bell-inequality violation on the reduced realization geometry; compatibility with no-signalling; and robustness tests against multinomial, temporal, detector, and other alternative explanations. The interpretation is not a restoration of Bell-local hidden variables and does not require superluminal signalling. Bell's theorem continues to exclude the relevant locally factorized descriptions. Instead, the observed correlations are interpreted as local measurements of a common non-separable relational structure. Spatial separation does not imply relational or informational separability. This distinction also reframes the quantum measurement problem. Wave-function collapse need not be regarded as the event that creates the physical structure responsible for an outcome. The framework instead proposes that admissibility constrains participation prior to observation, with measurement revealing a realization from an already structured physical domain. A definitive replacement for the standard measurement postulate will require discriminating predictions beyond those already shared with conventional quantum mechanics. The broader implication concerns the theory of motion itself. Newtonian mechanics, Hamiltonian dynamics, Maxwell's equations, Fourier transport, Navier–Stokes flow, relativity, and quantum mechanics employ very different evolution equations, yet all operate upon structured physical domains. The admissibility framework proposes that their deeper commonality lies not in a single dynamical equation but in an ontological ordering: the laws of motion govern how reality evolves; admissibility governs the structure within which reality can become realized. This has consequences beyond quantum foundations. In engineering and computational physics, enormous mathematical state spaces are routinely explored through CFD, finite-element simulation, optimization, Monte Carlo methods, and digital twins. If physically significant behavior occupies a substantially smaller admissible geometry, computation can be redirected from exhaustive exploration toward the structures in which realizable behavior is concentrated. This provides a theoretical basis for reduced-order physical prediction, targeted simulation, transport localization, and deterministic Physics Intelligence. In AI infrastructure and high-performance computing, the same principle suggests that workloads, thermal transport, energy utilization, routing, scheduling, and hardware states need not be treated as equally relevant points within enormous combinatorial spaces. Identifying admissible low-dimensional structure before exhaustive computation offers a route toward reduced search complexity, improved orchestration, higher computational and energy efficiency, and physics-informed predictive control. In aerospace, energy, advanced manufacturing, climate systems, and data-center infrastructure, the framework similarly motivates identifying the geometry of physically participating transport before expending computational resources resolving the entire mathematically accessible domain. The work therefore proposes a common principle extending from fundamental physics to computational engineering: Mathematical possibility is larger than physical realization. Uncertainty may remain genuine at the level of an individual event without implying an absence of antecedent structure. The results presented here provide empirical evidence consistent with the proposition that physical realization is organized by relational geometry prior to probability, while identifying the further tests required to establish whether this ordering constitutes a fundamental law of quantum and classical motion. The next decisive tests include prospective Bell predictions, multipartite and contextuality experiments, Lorentz-covariant formulation, recovery of the classical limit, and extension to quantum field theory and curved spacetime. Nature need not explore everything mathematics permits. Motion is the realization of what physical structure admits. That description captures the actual architecture of the finished 130-page work: it preserves Bell's theorem rather than attempting to evade it, explicitly separates mathematical accessibility from physical participation, and treats the NIST comparison as evidence for the proposed framework while acknowledging that a distinctive prediction beyond standard quantum mechanics remains necessary for a physical replacement of collapse. Principal Implications What This Means for Bell’s Inequality Bell's theorem remains intact. The present framework does not attempt to restore Bell-local hidden variables, weaken Bell's result, or explain the observed correlations through faster-than-light signalling. Bell establishes that the correlations observed between Alice and Bob cannot be reproduced by the relevant locally factorized description. The question developed here begins after that result: if Bell-local separability fails, what physical structure carries the correlations? The proposed answer is relational geometry. Alice and Bob remain spatially separated and perform local measurements, but their outcomes arise from different interrogations of a common non-separable quantum structure. Spatial separation therefore does not imply informational or relational separability. The correlation need not be interpreted as something transmitted from Alice to Bob at the moment of measurement; it can instead be understood as a property of the joint structure to which both measurements belong. The NIST analysis gives this interpretation a quantitative form. The characterized entangled state determines the relational geometry before the subsequent detector records are used for evaluation. Alice's and Bob's measurement settings sample different regions of that geometry. The resulting Bell outcomes exhibit strongly unequal participation, while Bell violation and no-signalling are preserved. The proposed implication is therefore: Bell violation demonstrates the failure of Bell-local factorization; admissibility proposes a geometry for the non-separable physical structure that remains. This reframes the familiar intuition of "action at a distance." The deeper question may not be how information crosses the distance between Alice and Bob, but why spatial distance should require the relational information defining their joint state to become separable in the first place. What This Means for Wave-Function Collapse The framework does not discard wave-function collapse as an operational rule for updating the quantum state after an observation. It changes the proposed ontological role assigned to collapse. In the conventional collapse-centered picture, the quantum state contains multiple possible outcomes and measurement marks the transition to a definite result. This leaves a foundational question: what physically distinguishes the outcome that becomes real from those that do not? Admissibility inserts a structural stage before observation. The accessible quantum