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Transcript of G.J. Chaitin's 2 March 2000 Carnegie Mellon University School of Computer Science Distinguished Lecture. The notion of randomness is taken from physics and applied to pure mathematics in order to shed light on the…

Chaotic Dynamics · Physics 2007-05-23 G. J. Chaitin

We derive a master equation describing the evolution of a quantum system subjected to a sequence of observations. These measurements occur randomly at a given rate and can be of a very general form. As an example, we analyse the effects of…

Quantum Physics · Physics 2009-11-13 James D. Cresser , Stephen M. Barnett , John Jeffers , David T. Pegg

Randomized controlled trials are susceptible to imbalance on covariates predictive of the outcome. Rerandomization and deterministic treatment assignment are two proposed solutions. This paper explores the relationship between…

Methodology · Statistics 2023-10-03 Connor T. Jerzak , Rebecca Goldstein

Inference on the parametric part of a semiparametric model is no trivial task. If one approximates the infinite dimensional part of the semiparametric model by a parametric function, one obtains a parametric model that is in some sense…

Statistics Theory · Mathematics 2025-09-23 Adam Lee , Emil A. Stoltenberg , Per A. Mykland

We introduce the E-measure: a measure-like generalization of the E-value to a class of hypotheses. Unlike classical measures, E-measures are closed under infimums instead of addition. They arise from a compatibility axiom with logical…

Statistics Theory · Mathematics 2026-04-23 Nick W. Koning

We consider the space of complete and separable metric spaces which are equipped with a probability measure. A notion of convergence is given based on the philosophy that a sequence of metric measure spaces converges if and only if all…

Probability · Mathematics 2008-06-13 Andreas Greven , Peter Pfaffelhuber , Anita Winter

We describe algebraic certificates of positivity for functions belonging to a finitely generated algebra of Borel measurable functions, with particular emphasis to algebras generated by semi-algebraic functions. In which case the standard…

Optimization and Control · Mathematics 2010-04-20 Jean-Bernard Lasserre , Mihai Putinar

A number of issues related to measurement show that self-consistency is lacking in quantum mechanics as this theory has been generally understood. Each issue is presented as a point in this paper. Each point can be resolved by incorporating…

General Physics · Physics 2007-05-23 D. M. Snyder

We prove that the Hilbert space description of all joint von Neumann measurements on a quantum state can be reproduced in terms of a single measure space ({\Omega}, F, {\mu}) with a normalized real-valued measure {\mu}, that is, in terms of…

Quantum Physics · Physics 2012-10-12 Elena R. Loubenets

Measurements of quantum systems can be used to generate classical data that is truly unpredictable for every observer. However, this true randomness needs to be discriminated from randomness due to ignorance or lack of control of the…

Quantum Physics · Physics 2017-06-14 Felix Bischof , Hermann Kampermann , Dagmar Bruß

We use machine learning to provide a tractable measure of the amount of predictable variation in the data that a theory captures, which we call its "completeness." We apply this measure to three problems: assigning certain equivalents to…

Theoretical Economics · Economics 2019-10-17 Drew Fudenberg , Jon Kleinberg , Annie Liang , Sendhil Mullainathan

Let f be a computable function from finite sequences of 0's and 1's to real numbers. We prove that strong f-randomness implies strong f-randomness relative to a PA-degree. We also prove: if X is strongly f-random and Turing reducible to Y…

Randomized measurements are useful for analyzing quantum systems especially when quantum control is not fully perfect. However, their practical realization typically requires multiple rotations in the complex space due to the adoption of…

Quantum Physics · Physics 2025-08-28 Jin-Min Liang , Satoya Imai , Shuheng Liu , Shao-Ming Fei , Otfried Gühne , Qiongyi He

Both classical and respectively quantum observables can be modeled as somewhat similar examples of random variables. In such a model the associated measurements preserve the values spectrum of an observable but change the corresponding…

Statistical Mechanics · Physics 2008-03-20 S. Dumitru , A. Boer

We analyze the notion that physical theories are quantitative and testable by observations in experiments. This leads us to propose a new, Bayesian, interpretation of probabilities in physics that unifies their current use in classical…

Quantum Physics · Physics 2007-05-23 Francis G. Perey

To begin with, it is pointed out that the form of the quantum probabil- ity formula originates in the very initial state of the object system as seen when the state is expanded with the eigen-projectors of the measured ob- servable. Making…

Quantum Physics · Physics 2016-10-23 Fedor Herbut

We consider a random tree and introduce a metric in the space of trees to define the ``mean tree'' as the tree minimizing the average distance to the random tree. When the resulting metric space is compact we have laws of large numbers and…

Probability · Mathematics 2007-05-23 David Balding , Pablo A. Ferrari , Ricardo Fraiman , Mariela Sued

Martin-L\"of (ML)-reducibility compares $K$-trivial sets by examining the Martin-L\"of random sequences that compute them. We show that every $K$-trivial set is computable from a c.e.\ set of the same ML-degree. We investigate the interplay…

Logic · Mathematics 2022-02-11 Noam Greenberg , Joseph S. Miller , Andre Nies , Daniel Turetsky

Reduction is shown to be a possible consequence of the basic principles of quantum mechanics, involving no branching of the quantum state of the universe. The key feature of a measurement is attributed to the creation of macroscopic germs…

Quantum Physics · Physics 2008-02-19 Roland Omnès

Solomonoff unified Occam's razor and Epicurus' principle of multiple explanations to one elegant, formal, universal theory of inductive inference, which initiated the field of algorithmic information theory. His central result is that the…

Machine Learning · Computer Science 2011-11-09 Marcus Hutter