There is some irony, and perhaps a bit of gallows humor, in opening a paper in this volume with the claim that “applied ethics” is a misnomer. Yet that claim is true in the following sense. What we need for most of the issues that have sparked the contemporary resurgence of moral and political theory is not the application of ethics as we know it, but the revamping of ethics to make it relevant to the issues we face. It (...) is in our concern with major policy programs that ethics and political philosophy are most commonly rejoined to become a unified enquiry after a nearly complete separation through most of this century. Yet, ethical theories may be shaken to their foundations by our effort to apply them to policy problems. I do not propose to revamp ethics here, but only to show that much ethical theory cannot readily be applied to major policy problems. There are at least three important characteristics of major policy issues in general that may give traditional moral theories difficulties. First, such issues can generally be handled only by institutional intervention; they commonly cannot be resolved through uncoordinated individual action. Theories formulated at the individual level must therefore be recast to handle institutional actions and possibilities. Second, major policy issues typically have complicating strategic interactions between individuals at their bases. Third, they are inherently stochastic in the important sense that they affect large numbers with more or less determinable probabilities. C. H. Waddington calls such issues instances of “the problem of the ethics of stochastic processes.”. (shrink)

In an earlier paper by one of us [K.-E. Hellwig (1981)], elements of discrete quantum stochastic processes which arise when the classical probability space is replaced by quantum theory have been considered. In the present paper a general formulation is given and its properties are compared with those of classical stochastic processes. Especially, it is asked whether such processes can be Markovian. An example is given and similarities to methods in quantum statistical thermodynamics (...) are pointed out. (shrink)

We discuss a generalization of the standard notion of probability space and show that the emerging framework, to be called operational probability theory, can be considered as underlying quantal theories. The proposed framework makes special reference to the convex structure of states and to a family of observables which is wider than the familiar set of random variables: it appears as an alternative to the known algebraic approach to quantum probability.

The paper is concerned with the existence and asymptotic character of the nonlinear boundary value problemdG/dt=F ¦ –¦dF/dt=gG =k 1,G=k 2 as ¦– ¦ o+ The discussion is related to the problem of particle-number fluctuations in the theory of cosmic radiation andG andF denote respectively the probability generating functions for the electron distribution in an electron-initiated and a photon-initiated shower.A solution of the system satisfying the boundary conditions is constructed so that specified limiting conditions are fulfilled.

As stochastic independence is essential to the mathematical development of probability theory, it seems that any foundational work on probability should be able to account for this property. Bayesian decision theory appears to be wanting in this respect. Savage’s postulates on preferences under uncertainty entail a subjective expected utility representation, and this asserts only the existence and uniqueness of a subjective probability measure, regardless of its properties. What is missing is a preference condition corresponding (...) to stochastic independence. To fill this significant gap, the article axiomatizes Bayesian decision theory afresh and proves several representation theorems in this novel framework. (shrink)

We formulate from first principles a theory of stochastic processes in configuration space. The fundamental equations of the theory are an equation of motion which generalizes Newton's second law and an equation which expresses the condition of conservation of matter. Two types of stochastic motion are possible, both described by the same general equations, but leading in one case to classical Brownian motion behavior and in the other to quantum mechanical behavior. The Schrödinger equation, which (...) is derived here with no further assumption, is thus shown to describe a specific stochastic process. It is explicitly shown that only in the quantum mechanical process does the superposition of probability amplitudes give rise to interference phenomena; moreover, the presence of dissipative forces in the Brownian motion equations invalidates the superposition principle. At no point are any special assumptions made concerning the physical nature of the underlying stochastic medium, although some suggestions are discussed in the last section. (shrink)

The use of negative probabilities is discussed for certain problems in which a stochastic process approach is indicated. An extension of probability theory to include signed (negative and positive) probabilities is outlined and both philosophical and axiomatic examinations of negative probabilities are presented. Finally, a class of applications illustrates the use and implications of signed probability theory.

The book develops the necessary background in probability theory underlying diverse treatments of stochastic processes and their wide-ranging applications. With this goal in mind, the pace is lively, yet thorough. Basic notions of independence and conditional expectation are introduced relatively early on in the text, while conditional expectation is illustrated in detail in the context of martingales, Markov property and strong Markov property. Weak convergence of probabilities on metric spaces and Brownian motion are two highlights. The (...) historic role of size-biasing is emphasized in the contexts of large deviations and in developments of Tauberian Theory. The authors assume a graduate level of maturity in mathematics, but otherwise the book will be suitable for students with varying levels of background in analysis and measure theory. In particular, theorems from analysis and measure theory used in the main text are provided in comprehensive appendices, along with their proofs, for ease of reference. Rabi Bhattacharya is Professor of Mathematics at the University of Arizona. Edward Waymire is Professor of Mathematics at Oregon State University. Both authors have co-authored numerous books, including the graduate textbook, Stochastic Processes with Applications. Advanced undergrads and graduate students, analysts. (shrink)

Stochastic independence has a complex status in probability theory. It is not part of the definition of a probability measure, but it is nonetheless an essential property for the mathematical development of this theory. Bayesian decision theorists such as Savage can be criticized for being silent about stochastic independence. From their current preference axioms, they can derive no more than the definitional properties of a probability measure. In a new framework of twofold uncertainty, (...) we introduce preference axioms that entail not only these definitional properties, but also the stochastic independence of the two sources of uncertainty. This goes some way towards filling a curious lacuna in Bayesian decision theory. (shrink)

In recent years, the psychology of reasoning has been undergoing a paradigm shift, with general Bayesian, probabilistic approaches replacing the older, much more restricted binary logic paradigm. At the same time, dual processing theories have been gaining influence. We argue that these developments should be integrated and moreover that such integration is already underway. The new reasoning paradigm should be grounded in dual processing for its algorithmic level of analysis just as it uses Bayesian theory for its computational level (...) of analysis. Moreover, we propose that, within the new paradigm, these levels of analysis reflect on each other. Bayesianism suggests a specific theoretical understanding of dual processing. Just as importantly, the duality in processing carries over to duality in function; although both types of processes compute degrees of belief, they generate different functions. (shrink)

The book considers foundational thinking in quantum theory, focusing on the role the fundamental principles and principle thinking there, including thinking that leads to the invention of new principles, which is, the book contends, one of the ultimate achievements of theoretical thinking in physics and beyond. The focus on principles, prominent during the rise and in the immediate aftermath of quantum theory, has been uncommon in more recent discussions and debates concerning it. The book argues, however, that exploring (...) the fundamental principles and principle thinking is exceptionally helpful in addressing the key issues at stake in quantum foundations and the seemingly interminable debates concerning them. Principle thinking led to major breakthroughs throughout the history of quantum theory, beginning with the old quantum theory and quantum mechanics, the first definitive quantum theory, which it remains within its proper (nonrelativistic) scope. It has, the book also argues, been equally important in quantum field theory, which has been the frontier of quantum theory for quite a while now, and more recently, in quantum information theory, where principle thinking was given new prominence. The approach allows the book to develop a new understanding of both the history and philosophy of quantum theory, from Planck's quantum to the Higgs boson, and beyond, and of the thinking the key founding figures, such as Einstein, Bohr, Heisenberg, Schrödinger, and Dirac, as well as some among more recent theorists. The book also extensively considers the nature of quantum probability, and contains a new interpretation of quantum mechanics, "the statistical Copenhagen interpretation." Overall, the book's argument is guided by what Heisenberg called "the spirit of Copenhagen," which is defined by three great divorces from the preceding foundational thinking in physics-reality from realism, probability from causality, and locality from relativity-and defined the fundamental principles of quantum theory accordingly. (shrink)

We introduce a framework that can be used to model both mathematics and human reasoning about mathematics. This framework involves stochastic mathematical systems (SMSs), which are stochastic processes that generate pairs of questions and associated answers (with no explicit referents). We use the SMS framework to define normative conditions for mathematical reasoning, by defining a “calibration” relation between a pair of SMSs. The first SMS is the human reasoner, and the second is an “oracle” SMS that can (...) be interpreted as deciding whether the question–answer pairs of the reasoner SMS are valid. To ground thinking, we understand the answers to questions given by this oracle to be the answers that would be given by an SMS representing the entire mathematical community in the infinite long run of the process of asking and answering questions. We then introduce a slight extension of SMSs to allow us to model both the physical universe and human reasoning about the physical universe. We then define a slightly different calibration relation appropriate for the case of scientific reasoning. In this case the first SMS represents a human scientist predicting the outcome of future experiments, while the second SMS represents the physical universe in which the scientist is embedded, with the question–answer pairs of that SMS being specifications of the experiments that will occur and the outcome of those experiments, respectively. Next we derive conditions justifying two important patterns of inference in both mathematical and scientific reasoning: (i) the practice of increasing one’s degree of belief in a claim as one observes increasingly many lines of evidence for that claim, and (ii) abduction, the practice of inferring a claim’s probability of being correct from its explanatory power with respect to some other claim that is already taken to hold for independent reasons. (shrink)

Probability and indeterminism have always been core philosophical themes. This paper aims to contribute to understanding probability and indeterminism in biology. To provide the background for the paper, it will first be argued that an omniscient being would not need the probabilities of evolutionary theory to make predictions about biological processes. However, despite this, one can still be a realist about evolutionary theory, and then the probabilities in evolutionary theory refer to real features of (...) the world. This prompts the question of how to interpret biological probabilities which correspond to real features of the world but are in principle dispensable for predictive purposes. This paper will suggest three possible interpretations. The first interpretation is a propensity interpretation of kinds of systems. It will be argued that backward probabilities in biology do not present a problem for this propensity interpretation. The second interpretation is the frequency interpretation. Third, I will suggest Humean chances are a new interpretation of probability in evolutionary theory. Finally, this paper discusses Sansom’s argument that biological processes are indeterministic because probabilities in evolutionary theory refer to real features of the world. It will be argued that Sansom’s argument is not conclusive, and that the question whether biological processes are deterministic or indeterministic is still with us. (shrink)

We develop the concept of quantum probability based on ideas of R. Feynman. The general guidelines of quantum probability are translated into rigorous mathematical definitions. We then compare the resulting framework with that of operational statistics. We discuss various relationship between measurements and define quantum stochastic processes. It is shown that quantum probability includes both conventional probability theory and traditional quantum mechanics. Discrete quantum systems, transition amplitudes, and discrete Feynman amplitudes are treated. We (...) close with some examples that illustrate previously defined concepts. (shrink)

This book presents a multidisciplinary perspective on chance, with contributions from distinguished researchers in the areas of biology, cognitive neuroscience, economics, genetics, general history, law, linguistics, logic, mathematical physics, statistics, theology and philosophy. The individual chapters are bound together by a general introduction followed by an opening chapter that surveys 2500 years of linguistic, philosophical, and scientific reflections on chance, coincidence, fortune, randomness, luck and related concepts. A main conclusion that can be drawn is that, even after all this time, (...) we still cannot be sure whether chance is a truly fundamental and irreducible phenomenon, in that certain events are simply uncaused and could have been otherwise, or whether it is always simply a reflection of our ignorance. Other challenges that emerge from this book include a better understanding of the contextuality and perspectival character of chance (including its scale-dependence), and the curious fact that, throughout history (including contemporary science), chance has been used both as an explanation and as a hallmark of the absence of explanation. As such, this book challenges the reader to think about chance in a new way and to come to grips with this endlessly fascinating phenomenon. (shrink)

Objective probability in quantum mechanics is often thought to involve a stochastic process whereby an actual future is selected from a range of possibilities. Everett’s seminal idea is that all possible definite futures on the pointer basis exist as components of a macroscopic linear superposition. I demonstrate that these two conceptions of what is involved in quantum processes are linked via two alternative interpretations of the mind-body relation. This leads to a fission, rather than divergence, interpretation of (...) Everettian theory and to a novel explanation of why a principle of indifference does not apply to self-location uncertainty for a post-measurement, pre-observation subject, just as Sebens and Carroll claim. Their Epistemic Separability Principle is shown to arise out of this explanation and the derivation of the Born rule for Everettian theory is thereby put on a firmer footing. (shrink)

This is a unique volume by a unique scientist, which combines conceptual, formal, and engineering approaches in a way that is rarely seen. Its core is the relation between ways of learning and knowing on the one hand and different modes of time on the other. Partial Boolean logic and the associated notion of complementarity are used to express this relation, and mathematical tools of fundamental physics are used to formalize it. Along the way many central philosophical problems are touched (...) and addressed, above all the mind-body problem. Completed only shortly before the death of the author, the text has been edited and annotated by the author's close collaborator Harald Atmanspacher. (shrink)

Nelson’s stochastic quantum mechanics provides an ideal arena to test how the Born rule is established from an initial probability distribution that is not identical to the square modulus of the wavefunction. Here, we investigate numerically this problem for three relevant cases: a double-slit interference setup, a harmonic oscillator, and a quantum particle in a uniform gravitational field. For all cases, Nelson’s stochastic trajectories are initially localized at a definite position, thereby violating the Born rule. For the (...) double slit and harmonic oscillator, typical quantum phenomena, such as interferences, always occur well after the establishment of the Born rule. In contrast, for the case of quantum particles free-falling in the gravity field of the Earth, an interference pattern is observed before the completion of the quantum relaxation. This finding may pave the way to experiments able to discriminate standard quantum mechanics, where the Born rule is always satisfied, from Nelson’s theory, for which an early subquantum dynamics may be present before full quantum relaxation has occurred. Although the mechanism through which a quantum particle might violate the Born rule remains unknown to date, we speculate that this may occur during fundamental processes, such as beta decay or particle-antiparticle pair production. (shrink)

We consider probability theories in general. In the first part of the paper, various constraints are imposed and classical probability and quantum theory are recovered as special cases. Quantum theory follows from a set of five reasonable axioms. The key axiom which gives us quantum theory rather than classical probability theory is the continuity axiom, which demands that there exists a continuous reversible transformation between any pair of pure states. In the second part (...) of this paper, we consider in detail how the measurement process works in both the classical and the quantum case. The key differences and similarities are elucidated. It is shown how measurement in the classical case can be given a simple ontological interpretation which is not open to us in the quantum case. On the other hand, it is shown that the measurement process can be treated mathematically in the same way in both theories even to the extent that the equations governing the state update after measurement are identical. The difference between the two cases is seen to be due not to something intrinsic to the measurement process itself but, rather, to the nature of the set of allowed states and, therefore, ultimately to the continuity axiom. (shrink)

In Probability Designs, Karin Kukkonen presents the predictive processing model of cognition as a means of exploring narrative structure and reader experience. Utilizing the literary canon of various cultures, Kukkonen combines theory and cognitive science to analyze how reader expectation and prediction shape literature, and how literature accomplishes cognitive feats that determine the human capacity for free, exploratory thought.

Studies on the development of cell populations are often based on results of the theory of stochastic birth- and death-processes (continuous or discrete (seee.g. references inVogel, Niewisch &Matioli (1969), in some cases, death may be interpreted not as actual death of the cell bute.g. as a recruitment of the cell considered into another cell compartment, etc.). It is usually assumed that the conditions for the development are homogeneous,i.e. that the probabilities of births and deaths are independent on (...) the time. However, in most situations, this assumption is not fulfilled (owing to the maturation and differentiation of cells, changes of the microenvironment, inducing factors, etc.). Then it is necessary to study the development of cell populations under non-homogeneous conditions. In this paper, some properties of appropriate birth- and death-processes under nonhomogeneous conditions are studied; formulae given in section 4 permit calculation of some characteristics describing the cell population size distribution at individual discrete epochs (at individual generations) during the development of the cell population considered. (shrink)

The aim of this paper is to study the monotonicity properties with respect to the probability distribution of the state processes, of optimal decisions in bandit decision problems. Orderings of dynamic discrete projects are provided by extending the notion of stochastic dominance to stochastic processes.

Following up on previous results by Falmagne, this paper investigates possible mechanisms explaining how preference relations are created and how they evolve over time. We postulate a preference relation which is initially empty and becomes increasingly intricate under the influence of a random environment delivering discrete tokens of information concerning the alternatives. The framework is that of a class of real-time stochastic processes having interlinked Markov and Poisson components. Specifically, the occurence of the tokens is governed by a (...) Poisson process, while the succession of preference relations is a Markov process. In an example case, the preference relations are the various possible semiorders on the set of alternatives. Asymptotic results are obtained in the form of the limit probabilities of any semiorder. The arguments extend to a much more general situation including interval orders, biorders and partial orders. The results provide (up to a small number of parameters) complete quantitative predictions for panel data of a standard type, in which the same sample of subjects has been asked to compare the alternatives a number of times. (shrink)

The aim of this paper is to study the monotonicity properties with respect to the probability distribution of the state processes, of optimal decisions in bandit decision problems. Orderings of dynamic discrete projects are provided by extending the notion of stochastic dominance to stochastic processes.

Table of Contents: Preface.- 1. Introduction; Mauricio Suárez.- PART I: PROBABILITIES.- 2. Probability and time symmetry in classical Markov processes; Guido Bacciagaluppi.- 3. Probability assignments and the principle of indifference: An examination of two eliminative strategies; Sorin Bangu.- 4. Why typicality does not explain the approach to equilibrium; Roman Frigg; PART II: CAUSES.- 5. From metaphysics to physics and back: The example of causation; Federico Laudisa.- 6. On explanation in retro-causal interpretations of quantum mechanics; Joseph Berkovitz.- 7. (...) Causal completeness in general probability theories; Balasz Gyenis, Miklós Rédei.- 8. Causal Markov, robustness and the quantum correlations; Mauricio Suárez, Iñaki San Pedro.- PART III: PROPENSITIES.- 9. Do dispositions and propensities have a role in the ontology of quantum mechanics? Some critical remarks; Mauro Dorato.- 10. Is the quantum world composed of propensitons?; Nicholas Maxwell.- 11. Derivative dispositions and multiple derivative levels; Ian Thompson. (shrink)

I review the role of probability in contemporary physics and the origin of probabilistic time asymmetry, beginning with the pre-quantum case but concentrating on quantum theory. I argue that quantum mechanics radically changes the pre-quantum situation and that the philosophical nature of objective probability in physics, and of probabilistic asymmetry in time, is dependent on the correct resolution of the quantum measurement problem.

A lot of research in cognition and decision making suffers from a lack of formalism. The quantum probability program could help to improve this situation, but we wonder whether it would provide even more added value if its presumed focus on outcome models were complemented by process models that are, ideally, informed by ecological analyses and integrated into cognitive architectures.

What follows shall provide an introduction to a predominantly philosophical and polemical, but historically revealing, paper on the foundations of the theory of probability. The leading Russian probabilist Aleksandr Yakovlevich Khinchin wrote the paper in the late 1930s, commenting on a slightly older, but still competing approach to probability theory by Richard von Mises. Together with the even more influential Andrey Nikolayevich Kolmogorov, who was nine years his junior, Khinchin had revolutionized probability theory around (...) 1930 by introducing the modern measure-theoretic approach, which is still standard today and which allowed for a sufficiently general treatment of important new notions such as “stochastic processes.” This development had its first culmination in Kolmogorov's booklet, Grundbegriffe der Wahrscheinlichkeitsrechnung, written in German in 1933, which has exerted an enormous influence world wide. (shrink)

The central thesis of this book is that the argument that probability is insufficient to handle uncertainty in artificial intelligence (AI) is metaphysical in nature. Piscopo calls this argument against probability the non-adequacy claim and provides this summary of it [which first appeared in (Piscopo and Birattari 2008)]:Probability theory is not suitable to handle uncertainty in AI because it has been developed to deal with intrinsically stochastic phenomena, while in AI, uncertainty has an epistemic nature. (...) (Piscopo (3))Piscopo uses the term “metaphysical” in the Popperian sense: the non-adequacy claim is metaphysical (rather than scientific) since it cannot be disproved (much less established) by observation or experiment.In Chapter 2, Piscopo recounts some of the relevant history and issues in philosophy of science. There is little that is controversial here. One problem is that when addressing the question of how a particular probabilistic model is tested, Piscopo limits herself .. (shrink)

Contents: PART 1. MODELS IN SCIENTIFIC PROCESSES. Joseph AGASSI: Why there is no theory of models. Ma??l??gorzata CZARNOCKA: Models and symbolic nature of knowledge. Adam GROBLER: The representational and the non-representational in models of scientific theories. Stephan HARTMANN: Models as a tool for the theory construction; some strategies of preliminary physics. William HERFEL: Nonlinear dynamical models as concrete construction. Elzbieta KA??L??USZY??N??SKA: Styles of thinking. Stathis PSILLOS: The cognitive interplay between theories and models: the case of 19th century (...) optics. PART 2. TOOLS OF SCIENCE. Nancy D. CARTWRIGHT, Towfic SHOMAR, Maricio SUAREZ: The tool-box of science. Javier ECHEVERRIA: The four contexts of scientific activity. Katline HAVAS: Continuity and change; kinds of negation in scientific progress. Matthias KAISER: The independence of scientific phenomena. W??l??adys??l??aw KRAJEWSKI: Scientific meta-philosophy. Ilkka NIINILUOTO: The emergence if scientific specialities: six models. Leszek NOWAK: Antirealism, realism and idealization. Rinat M. NUGAYEV: Classic, modern and postmodern scientific unification. Veikko RANTALA: Translation and scientific change. Gerhard SCHURZ: Theories and their applications - a case of nonmonotonic reasoning. Witold STRAWI??N??SKI: The unity of science today. Vardan TOROSIAN: Are the ethic and logic of science compatible. PART 3. UNSHARP APPROACHES IN SCIENCE. Ernest W. ADAMS: Problems and prospects in a theory of inexact first-order theories. Wolfgang BALZER and Gerhard ZOUBEK: On the comparison of approximative empirical claims. Gianpierro CATTANEO, Maria Luisa DALLA CHIARA, Roberto GIUNTINI: The unsharp approaches to quantum theory. Theo A.F. KUIPERS: Falsification versus efficient truth approximation. Bernhard LAUTH: Limiting decidability and probability. Jaros??l??aw PYKACZ: Many-valued logics in foundations of quantum mechanics. Roman R. ZAPATRIN: Logico-algebraic approach to spacetime quantization. (shrink)

In this paper I present both a critical appraisal of Humphreys' probabilistic theory of causality and a sketch of an alternative view of the relationship between the notions of probability and of cause. Though I do not doubt that determinism is false, I claim that the examples used to motivate Humphreys' theory typically refer to subjective rather than objective chance. Additionally, I argue on a number of grounds that Humphreys' suggestion that linear regression models be used as (...) a canonical form for the description of causal relations is untenable. I conclude by exploring the variety of ways in which probabilistic elements can be embedded into the structure of causal mechanisms. This investigation suggests both that deterministic mechanisms can produce stochastic behavior and stochastic mechanisms can produce deterministic behavior. Note: Link is to the article in a subscription database available to users affiliated with Butler University. Appropriate login information will be required for access. Users not affiliated with Butler University should contact their local librarian for assistance in locating a copy of this article. (shrink)

In this paper I present both a critical appraisal of Humphreys' probabilistic theory of causality and a sketch of an alternative view of the relationship between the notions of probability and of cause. Though I do not doubt that determinism is false, I claim that the examples used to motivate Humphreys' theory typically refer to subjective rather than objective chance. Additionally, I argue on a number of grounds that Humphreys' suggestion that linear regression models be used as (...) a canonical form for the description of causal relations is untenable. I conclude by exploring the variety of ways in which probabilistic elements can be embedded into the structure of causal mechanisms. This investigation suggests both that deterministic mechanisms can produce stochastic behavior and stochastic mechanisms can produce deterministic behavior. (shrink)

We propose the quantum field formalism as a new type of stochastic Markov process determined by local configuration. Our proposed Markov process is different with the classical one, in which the transition probability is determined by the state labels related to the character of state. In the new quantum Markov process, the transition probability is determined not only by the state character, but also by the occupation of the state. Due to the probability occupation of the (...) state, the classical relation between the probability and condition probability at different times is no more valid. We have formulated the chain relation of successive transition for transition probability of the quantum Markov process instead of classical Chapman–Kolmogorov equation. The master equation is valid only in a classical Markov process. We have derived Euler-Lagrange equation in operator form as a characteristic equation of motion for the evolution of particle states as a Markov process. (shrink)

Fuzzy amplitude densities are employed to obtain probability distributions for measurements that are not perfectly accurate. The resulting quantum probability theory is motivated by the path integral formalism for quantum mechanics. Measurements that are covariant relative to a symmetry group are considered. It is shown that the theory includes traditional as well as stochastic quantum mechanics.

The idea that quantum randomness can be reduced to randomness of classical fields (fluctuating at time and space scales which are essentially finer than scales approachable in modern quantum experiments) is rather old. Various models have been proposed, e.g., stochastic electrodynamics or the semiclassical model. Recently a new model, so called prequantum classical statistical field theory (PCSFT), was developed. By this model a “quantum system” is just a label for (so to say “prequantum”) classical random field. Quantum averages (...) can be represented as classical field averages. Correlations between observables on subsystems of a composite system can be as well represented as classical correlations. In particular, it can be done for entangled systems. Creation of such classical field representation demystifies quantum entanglement. In this paper we show that quantum dynamics (given by Schrödinger’s equation) of entangled systems can be represented as the stochastic dynamics of classical random fields. The “effect of entanglement” is produced by classical correlations which were present at the initial moment of time, cf. views of Albert Einstein. (shrink)

This NATO Advanced Study Institute centered on large-scale molecular systems: Quantum mechanics, although providing a general framework for the description of matter, is not easily applicable to many concrete systems of interest; classical statistical methods, on the other hand, allow only a partial picture of the behaviour of large systems. The aim of the ASI was to present both aspects of the subject matter and to foster interaction between the scientists working in these important areas of theoretical physics and theoretical (...) chemistry. The quantum-mechanical part was mostly based on the operator-algebraic formulation of quantum mechanics and comprised quantum statistics of infinite systems with special em phasis on macroscopic observables, equilibrium conditions, irreversibility on the one hand, symmetry breaking for molecules in the radiation field and macroscopic quantum phenomena in the theory of superconductivity (BCS-theory) on the other hand. In addition, phase-space methods for many-body systems were also presented. Statistical physics was the main topic in the other lectures of the School; much emphasis was put on the statistical features of macros copic ("large") systems, the lectures dealt with mass and energy transport im polymers, in gels and in microemulsions, with aggregation and growth phenomena, with relaxation in complex, correlated systems, with conduction and optical properties of polymers, and with the means of describing disordered systems, above all fractals and related hierarchical models. (shrink)

This paper investigates dynamical relaxation to quantum equilibrium in the stochastic de Broglie–Bohm–Bell formulation of quantum mechanics. The time-dependent probability distributions are computed as in a Markov process with slowly varying transition matrices. Numerical simulations, supported by exact results for the large-time behavior of sequences of (slowly varying) transition matrices, confirm previous findings that indicate that de Broglie–Bohm–Bell dynamics allows an arbitrary initial probability distribution to relax to quantum equilibrium; i.e., there is no need to make the (...) ad-hoc assumption that the initial distribution of particle locations has to be identical to the initial probability distribution prescribed by the system’s initial wave function. The results presented in this paper moreover suggest that the intrinsically stochastic nature of Bell’s formulation, which is arguable most naturally formulated on an underlying discrete space-time, is sufficient to ensure dynamical relaxation to quantum equilibrium for a large class of quantum systems without the need to introduce coarse-graining or any other modification in the formulation. (shrink)

We critically examine the role and status probabilities, as they enter via the Quantum Equilibrium Hypothesis, play in the standard, deterministic interpretation of deBroglie’s and Bohm’s Pilot Wave Theory (dBBT), by considering interpretations of probabilities in terms of ignorance, typicality and Humean Best Systems, respectively. We argue that there is an inherent conflict between dBBT and probabilities, thus construed. The conflict originates in dBBT’s deterministic nature, rooted in the Guidance Equation. Inquiring into the latter’s role within dBBT, we find (...) it explanatorily redundant (in particular for dBBT’s solution of the Measurement Problem, which only requires that the corpuscles possess definite positions), and subject to a number of difficulties. Following a suggestion from Bell, we propose to abandon the Guidance Equation, whilst retaining dBBT’s point particle-based Primitive Ontology, with positions as local beables. The resultant theory, which we identify as a stochastic, minimally deBroglie-Bohmian theory, describes a random walk through configuration space. Its probabilities, we propose, are best understood as dispositions of possible corpuscle configurations to manifest themselves. We subsequently evaluate the merits of sdBBT vis-à-vis dBBT, such as the justification of the Symmetrisation Postulate and the violation of the Action-Reaction Principle. Not only is sdBBT an attractive Bohmian theory that, whilst retaining dBBT's virtues, overcomes many of its shortcomings; it also sparks off a number of exciting follow-up questions, such as a comparison between sdBBT and other stochastic hidden-variable theories, e.g. Nelson Stochastics, or between sdBBT and the Everett interpretation. (shrink)

While Aby Warburg, in his younger years, advocated a completely rational, mathematical understanding of the world, he lost confidence in this scientific ideal later on. This article proposes that this crucial shift in perspective, redefining Warburg’s opinions about empiricism, rationality and thus cultural evolution as a whole, took place very early on, namely in the summer of 1890. The present article studies, for the first time, an unpublished student essay by Warburg on probability theory. While discussing stochastic (...) and the possibility of mathematical prediction of future events, Warburg’s belief in the infallible exactitude of numerical sciences got first cracks. (shrink)

The idea that the Creator has a plan for creation is deeply rooted in the Christian notion of Providence. This notion seems to suggest that the history of creation must be the execution of the providential plan of God. Such an understanding of divine providence expects science to confirm that cosmic history is under supernatural guidance, that evolution is therefore oriented toward a goal—to bring forth human beings, for example. The problem is, however, that science finds evidence for neither supernatural (...) guidance nor teleology in nature. To address this problem, I understand Niels H. Gregersen to suggest that God is involved in the creative process. The reason science cannot demonstrate God's supernatural guidance of evolution is that the Creator structures the process from within. Gregersen argues that God is involved in the process of creation by changing the overall probability pattern of evolving systems.In my view, such a model of how God interacts with creation is supported neither by orthodox Christianity nor by modern science. After a critique of Gregersen's argument and a brief history of the relationship between Christianity and science, I shall suggest an alternative. It is that the freedom of creation to create itself is implicit in the fundamental dogma of Christianity that God is love. (shrink)

This is a comprehensive discussion of complexity as it arises in physical, chemical, and biological systems, as well as in mathematical models of nature. Common features of these apparently unrelated fields are emphasised and incorporated into a uniform mathematical description, with the support of a large number of detailed examples and illustrations. The quantitative study of complexity is a rapidly developing subject with special impact in the fields of physics, mathematics, information science, and biology. Because of the variety of the (...) approaches, no comprehensive discussion has previously been attempted. This book will be of interest to graduate students and researchers in physics (nonlinear dynamics, fluid dynamics, solid-state, cellular automata, stochastic processes, statistical mechanics and thermodynamics), mathematics (dynamical systems, ergodic and probability theory), information and computer science (coding, information theory and algorithmic complexity), electrical engineering and theoretical biology. (shrink)

With many Hamiltonians one can naturally associate a |Ψ|2-distributed Markov process. For nonrelativistic quantum mechanics, this process is in fact deterministic, and is known as Bohmian mechanics. For the Hamiltonian of a quantum field theory, it is typically a jump process on the configuration space of a variable number of particles. We define these processes for regularized quantum field theories, thereby generalizing previous work of John S. Bell [3] and of ourselves [11]. We introduce a formula expressing the (...) jump rates in terms of the interaction Hamiltonian, and establish a condition for finiteness of the rates. (shrink)