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Related papers: Algorithmic Randomness and Capacity of Closed Sets

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Consider a quantum cat map $M$ associated to a matrix $A\in\mathop{\mathrm{Sp}}(2n,\mathbb Z)$, which is a common toy model in quantum chaos. We show that the mass of eigenfunctions of $M$ on any nonempty open set in the position-frequency…

Analysis of PDEs · Mathematics 2023-04-25 Semyon Dyatlov , Malo Jézéquel

Computational feasibility is a widespread concern that guides the framing and modeling of biological and artificial intelligence. The specification of cognitive system capacities is often shaped by unexamined intuitive assumptions about the…

Artificial Intelligence · Computer Science 2022-05-12 Federico Adolfi , Todd Wareham , Iris van Rooij

Although there is a somewhat standard formalization of computability on countable sets given by Turing machines, the same cannot be said about uncountable sets. Among the approaches to define computability in these sets, order-theoretic…

Logic in Computer Science · Computer Science 2022-09-07 Pedro Hack , Daniel A. Braun , Sebastian Gottwald

The study of the boundary between classically simulable and computationally complex quantum dynamics is fundamental to understanding which physical resources may enable enhanced information-processing capabilities. We investigate this…

Quantum Physics · Physics 2026-05-08 Moein N. Ivaki , Matias Karjula , Tapio Ala-Nissila

Scalable quantum technologies will present challenges for characterizing and tuning quantum devices. This is a time-consuming activity, and as the size of quantum systems increases, this task will become intractable without the aid of…

This paper is a comment on the paper "Quantum Mechanics and Algorithmic Randomness" was written by Ulvi Yurtsever \cite{Yurtsever} and the briefly explanation of the algorithmic randomness of quantum measurements results. There are…

Quantum Physics · Physics 2017-04-07 Mohammad Shahbazi

We study the empirical meaning of randomness with respect to a family of probability distributions $P_\theta$, where $\theta$ is a real parameter, using algorithmic randomness theory. In the case when for a computable probability…

Machine Learning · Computer Science 2009-06-25 Vladimir V'yugin

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

Computational pseudorandomness studies the extent to which a random variable $\bf{Z}$ looks like the uniform distribution according to a class of tests $\cal{F}$. Computational entropy generalizes computational pseudorandomness by studying…

Computational Complexity · Computer Science 2020-11-13 Russell Impagliazzo , Sam McGuire

We analyze tight informationally complete measurements for arbitrarily large multipartite systems and study their configurations of entanglement. We demonstrate that tight measurements cannot be exclusively composed neither of fully…

Quantum Physics · Physics 2018-06-26 Jakub Czartowski , Dardo Goyeneche , Karol Życzkowski

We study algorithmic randomness properties for probability measures on Cantor space. We say that a measure $\mu$ on the space of infinite bit sequences is ML absolutely continuous if the non-ML-random bit sequences form a null set with…

Logic · Mathematics 2020-10-19 Andre Nies , Frank Stephan

We show, under natural assumptions for qubit systems, that measurement-based quantum computations (MBQCs) which compute a non-linear Boolean function with high probability are contextual. The class of contextual MBQCs includes an example…

Quantum Physics · Physics 2013-08-28 Robert Raussendorf

In this work, we aim at augmenting the decisions output by quantum models with "error bars" that provide finite-sample coverage guarantees. Quantum models implement implicit probabilistic predictors that produce multiple random decisions…

Quantum Physics · Physics 2023-10-24 Sangwoo Park , Osvaldo Simeone

We consider capacity (fuzzy measure, non-additive probability) on a compactum as a monotone cooperative normed game. We introduce topological analogues of well known class of exact games and show that these classes form subfunctors of the…

General Topology · Mathematics 2026-05-04 Taras Radul

We study the question, ``For which reals $x$ does there exist a measure $\mu$ such that $x$ is random relative to $\mu$?'' We show that for every nonrecursive $x$, there is a measure which makes $x$ random without concentrating on $x$. We…

Logic · Mathematics 2007-07-11 Jan Reimann , Theodore Slaman

Motivated by results on generic-case complexity in group theory, we apply the ideas of effective Baire category and effective measure theory to study complexity classes of functions which are "fractionally computable" by a partial…

Group Theory · Mathematics 2007-06-30 Ilya Kapovich , Paul Schupp

We present results for Choquet integrals with minimal assumptions on the monotone set function through which they are defined. They include the equivalence of sublinearity and strong subadditivity independent of regularity assumptions on…

Functional Analysis · Mathematics 2023-02-24 Augusto C. Ponce , Daniel Spector

We develop a systematic approach to quantum probability as a theory of rational betting in quantum gambles. In these games of chance the agent is betting in advance on the outcomes of several (finitely many) incompatible measurements. One…

Quantum Physics · Physics 2007-05-23 I. Pitowsky

Bounds analogous to entropic uncertainty relations allow one to design practical tests to detect quantum entanglement by a collective measurement performed on several copies of the state analyzed. This approach, initially worked out for…

Quantum Physics · Physics 2013-01-04 Łukasz Rudnicki , Zbigniew Puchała , Paweł Horodecki , Karol Życzkowski

We give a general unified method that can be used for $L_1$ {\em closeness testing} of a wide range of univariate structured distribution families. More specifically, we design a sample optimal and computationally efficient algorithm for…

Data Structures and Algorithms · Computer Science 2015-08-25 Ilias Diakonikolas , Daniel M. Kane , Vladimir Nikishkin