Abstract This chapter considers three ways in which probabilities may be derived from a physical theory without adverting to subjective considerations. The first derives from a fundamentally stochastic dynamics that implies transition chances at the level of natural law. The second is a Humean approach, in which probabilities are deployed as part of a compact system for conveying information about the structure of the Humean mosaic, i.e. the distribution of local physical quantities in space-time. The last employs either deterministic or stochastic dynamics together with a measure of typicality, i.e. a measure of sets of initial conditions that count as extremely large. Probabilities emerge in this setting as typical frequencies, that is, frequencies exhibited by most initial conditions.
Abstract This chapter considers three ways in which probabilities may be derived from a physical theory without adverting to subjective considerations. The first derives from a fundamentally stochastic dynamics that implies transition chances at the level of natural law. The second is a Humean approach, in which probabilities are deployed as part of a compact system for conveying information about the structure of the Humean mosaic, i.e. the distribution of local physical quantities in space-time. The last employs either deterministic or stochastic dynamics together with a measure of typicality, i.e. a measure of sets of initial conditions that count as extremely large. Probabilities emerge in this setting as typical frequencies, that is, frequencies exhibited by most initial conditions.
Abstract Some of the most compelling examples of the existence of truly objective probabilities come from physics, in particular quantum physics and statistical mechanics. So it is crucial to the overall success of HOC that it be compatible with the objective probabilities found in these theories. First, objective probabilities in classical (Boltzmannian) statistical mechanics (SM) are discussed. It is shown that HOC does capture the central probabilistic postulates of SM, and indeed that it may do so in two distinct ways. Second, objective probabilities in standard, non-relativistic quantum mechanics (QM), the context in which the notion that fundamental physics is at bottom chancy first became widely accepted, are discussed. It is shown that HOC is especially apt for capturing the probabilities of QM; other accounts may do equally well (though some clearly do not), but none can do the job better.
Abstract Many theories and models from physics are probabilistic. This observation raises several philosophical questions: What are probabilities in physics? Do they reflect objective chances which exist independently of the human mind? Or do they only express subjective credences and thus capture our own uncertainty about the world? Finally, which metaphysical lessons, if at all, can one draw from the largely probabilistic character of physics? The chapters collected in this volume address these questions and provide a detailed philosophical appraisal of the status of probabilities in all of physics. Particular emphasis is laid upon statistical physics and quantum mechanics. Many chapters reflect a desire to understand probabilities from physics as objective chances. These chances are characterized, e.g., as time-averages, as probabilities from a best system in the terms of David Lewis, or using the Boltzmannian typicality approach. Other chapters are sympathetic to a Bayesian view of probabilities in physics. The chapters about quantum mechanics elucidate the peculiar characteristics of quantum correlations and discuss strategies to justify the Born Rule. Finally, the chapters of this volume demonstrate how closely interpretive issues about probabilities are entangled with other foundational problems of physics such as the Reversibility Paradox, the ontology of the quantum world and the question whether the world is deterministic.
Abstract The conspicuous similarities between interpretive strategies in classical statistical mechanics and in quantum mechanics may be grounded on their employment of common implementations of probability. The objective probabilities which represent the underlying stochasticity of these theories can be naturally associated with three of their common formal features: initial conditions, dynamics, and observables. Various well-known interpretations of the two theories line up with particular choices among these three ways of implementing probability. This perspective has significant application to debates on primitive ontology and to the quantum measurement problem.
In a deterministic theory, one can deduce the state of the universe at any one time from the dynamical laws that govern its evolution and its state at any other time.In particular, one can deduce from the conditions that obtained at some early boundary condition for the universe, its state at all subsequent times.It is a piece of well-received philosophical common sense that there is no room in a deterministic theory for objective probabilities.Arguments will be given below that this piece of philosophical common sense is mistaken, and that a probability measure over the space of physically possible trajectories is an indispensable component of any theory -deterministic or otherwise -that can be used as a basis for prediction or receive confirmation from the evidence.Phase space is the central representational space in physics.It is the space within which all of the states pertaining to a system are represented, and it encodes all of the general information that we have about those states.To take an obvious example (less obvious examples will be given below) the fact that a pair of quantities are represented by different dimensions in phase space encodes the fact that they represent separate degrees of freedom.Physically possible histories are represented by trajectories through phase space and in a deterministic theory, when dealing with a closed system, there is (no more than) one trajectory through each point.Since the universe as a whole is the only truly closed system, this means there is one trajectory through each point in the phase space of the universe.Probabilities may be invoked in applications of theory, when the state of a system or the values of external variables are not known with full precision, but they are eliminable given complete knowledge.And they don't appear in the statement of the laws.The laws serve simply to identify the physically allowable trajectories.About Newtonian dynamics, Laplace famously said "given for one instant an intelligence which could comprehend all the forces by which nature is animated and the respective situation of the beings who compose it -an intelligence sufficiently vast to submit these data to analysis -it would embrace in the same formula the movements of the greatest bodies of the universe and those of the lightest atom; for it, nothing would be uncertain and the future, and the past, would be present to its eyes."ii It is a short step from this to the idea that probabilities invoked in classical contexts are subjective rather than objective.If they represent anything, it is facts about our epistemic states, not facts about the world.iii Popper, and Lewis, and other influential figures have endorsed this view, categorically rejecting any role for objective probabilities indeterministic contexts.In Popper's words:
Chapter 1: On the existence of quantum representations for two dichotomic measurements. Under which conditions do outcome probabilities of measurements possess a quantum-mechanical model? This kind of problem is solved here for the case of two dichotomic von Neumann measurements which can be applied repeatedly to a quantum system with trivial dynamics. The solution uses methods from the theory of operator algebras and the theory of moment problems. The ensuing conditions reveal surprisingly simple relations between certain quantum-mechanical probabilities. It also shown that generally, none of these relations holds in general probabilistic models. This result might facilitate further experimental discrimination between quantum mechanics and other general probabilistic theories. Chapter 2: Possibilistic Physics. I try to outline a framework for fundamental physics where the concept of probability gets replaced by the concept of possibility. Whereas a probabilistic theory assigns a state-dependent probability value to each outcome of each measurement, a possibilistic theory merely assigns one of the state-dependent labels "possible to occur" or "impossible to occur" to each outcome of each measurement. It is argued that Spekkens' combinatorial toy theory of quantum mechanics is inconsistent in a probabilistic framework, but can be regarded as possibilistic. Then, I introduce the concept of possibilistic local hidden variable models and derive a class of possibilistic Bell inequalities which are violated for the possibilistic Popescu-Rohrlich boxes. The chapter ends with a philosophical discussion on possibilistic vs. probabilistic. It can be argued that, due to better falsifiability properties, a possibilistic theory has higher predictive power than a probabilistic one. Chapter 3: The quantum region for von Neumann measurements with postselection. It is determined under which conditions a probability distribution on a finite set can occur as the outcome distribution of a quantum-mechanical von Neumann measurement with hyphenation given that the scalar product between the initial and the final state is known as well as the success probability of the postselection. An intermediate von Neumann measurement can enhance transition probabilities between states such that the error probability shrinks by a factor of up to 2. Chapter 4: A presentation of the category of stochastic matrices. This chapter gives generators and relations for the strict monoidal category of probabilistic maps on finite cardinals (i.e., stochastic matrices). Chapter 5: Convex Spaces: Definition and Examples. We try to promote convex spaces as an abstract concept of convexity which was introduced by Stone as "barycentric calculus''. A convex space is a set where one can take convex combinations in a consistent way. By identifying the corresponding Lawvere theory as the category from chapter 4 and using the results obtained there, we give a different proof of a result of Swirszcz which shows that convex spaces can be identified with algebras of a finitary version of the Giry monad. After giving an extensive list of examples of convex sets as they appear throughout mathematics and theoretical physics, we note that there also exist convex spaces that cannot be embedded into a vector space: semilattices are a class of examples of purely combinatorial type. In an information-theoretic interpretation, convex subsets of vector spaces are probabilistic, while semilattices are possibilistic. Convex spaces unify these two concepts.
The Origin of Probability: A Complete Derivation in Three Parts is the collected edition of a three-part theoretical investigation into the structural origin of probability within a deterministic closed-description framework. The work asks a deliberately narrow but foundational question: under what conditions can a system whose underlying description remains deterministic acquire a lawful probability-bearing description without inserting primitive randomness, probabilistic axioms, or the Born rule at the beginning of the construction? The trilogy develops that question cumulatively. Each part establishes a distinct layer of the argument, and later results depend on structures and limitations established earlier. The collected edition therefore preserves the full dependency order rather than treating the three papers as independent essays. It also includes a narrative overview and terminology guide intended to make the architecture of the complete derivation easier to follow. Part I, Finite Recurrent Stability Before Spacetime: Collapse, Emergence, Horizons, and Recurrence as Recoverability Boundaries, develops the realization-neutral structural foundation. It begins from persistent relational distinction and recoverability rather than assuming spacetime, metric distance, clock time, energy, probability, or quantum measurement. Within a declared finite-stability regime it distinguishes contraction, correction, carry-through, collapse, emergence, recurrence, cycle structure, and horizon-like boundaries by their effects on recoverable relational structure. Collapse and emergence appear as distinct lower- and upper-bound failures of one finite recurrent-stability architecture. Weak oscillatory form is subsequently obtained only at structural scope, without promoting recurrence into a physical wave, temporal oscillation, or cosmological mechanism. Part II, Stability, Boundary Observability, and Emergent Probability in Deterministic Systems, develops the transition from deterministic structural dynamics to probability-bearing description. Its central problem is not whether deterministic evolution can simply be renamed probabilistic, but whether loss of recoverability at an admissible boundary can support a lawful reduced description of unresolved alternatives. The paper therefore separates Boundary Loss from probability itself and distinguishes quotient formation, reduced observability, scalar closure, finite measure, normalization, and predictive interpretation as separate derivational burdens. A normalized set of branch weights is not treated as probability merely because it sums to one. Probability status is admitted only after the additional structural and interpretive conditions required for predictive use have been isolated. Part III, Boundary Loss and the Born Rule: The Origin of Probability, carries the construction into a bounded physical realization framework. Boundary Loss supplies unresolved alternatives but does not itself supply numerical probability. The derivation therefore proceeds through source-grounded scalar residues, finite positive total measure, normalization, local predictive admission, and independent source-state and event bridges into Hilbert-space representation. A minimum compatibility condition is then isolated, explicitly adopted at the appropriate stage, and applied separately. At the resulting local source-linked scope, the construction reaches the exact Born form p_i = ⟨J(Ψ), P_i J(Ψ)⟩ = ||P_i J(Ψ)||². The significance of the trilogy lies as much in the separation of these stages as in the terminal equation. Boundary Loss is not equated with probability. Scalarization is not assumed to be probability. Normalization is not treated as sufficient for probability. Hilbert-space representation is not allowed to retroactively supply the earlier structural derivation. Compatibility required for the final Born-form application is distinguished from structures already derived. The dependency chain is therefore designed so that later mathematical convenience cannot be silently imported backward as an earlier premise. Across the three parts, the argument develops the following bounded sequence: ordered dependence → recoverable distinction → finite recurrent stability → collapse/emergence boundary structure → boundary observability → Boundary Loss → unresolved alternatives → scalar closure → finite measure → normalization → predictive probability → Hilbert-space source and event bridges → minimum compatibility → exact local source-linked Born form. The collected edition is intended to function as the canonical integrated research record for this derivation. It contains the trilogy overview followed by Part I Version 4, Part II Version 3, and Part III Version 2. Internal bookmarks and navigation link the overview directly to the title page of each constituent work, while the individual papers remain separately citable publications with their own persistent identifiers. Constituent works: Part I: Finite Recurrent Stability Before Spacetime: Collapse, Emergence, Horizons, and Recurrence as Recoverability BoundariesDOI: 10.5281/zenodo.19966230 Part II: Stability, Boundary Observability, and Emergent Probability in Deterministic SystemsDOI: 10.5281/zenodo.19966289 Part III: Boundary Loss and the Born Rule: The Origin of ProbabilityDOI: 10.5281/zenodo.20102172 Taken as a whole, the trilogy proposes a disciplined route from recoverability and deterministic boundary structure to probability and, at its final declared scope, to the Born form. Its central methodological requirement is that every transition be earned at the layer where it is used, with unresolved burdens, adopted conditions, nonclaims, and realization boundaries kept explicit rather than compressed into the final result.