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Related papers: Subcomputable Schnorr Randomness

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We extend in a natural way the operation of Turing machines to infinite ordinal time, and investigate the resulting supertask theory of computability and decidability on the reals. The resulting computability theory leads to a notion of…

Logic · Mathematics 2007-05-23 Joel David Hamkins , Andy Lewis

A state $\rho=(\rho_n)_{n=1}^{\infty}$ is a sequence such that $\rho_n$ is a density matrix on $n$ qubits. It formalizes the notion of an infinite sequence of qubits. The von Neumann entropy $H(d)$ of a density matrix $d$ is the Shannon…

Quantum Physics · Physics 2025-04-15 Tejas Bhojraj

We answer a question of Ambos-Spies and Ku\v{c}era in the affirmative. They asked whether, when a real is low for Schnorr randomness, it is already low for Schnorr tests.

Logic · Mathematics 2014-08-14 Bjørn Kjos-Hanssen , André Nies , Frank Stephan

In a prequential approach to algorithmic randomness, probabilities for the next outcome can be forecast `on the fly' without the need for fully specifying a probability measure on all possible sequences of outcomes, as is the case in the…

Probability · Mathematics 2023-04-26 Floris Persiau , Gert de Cooman

Computational mechanics, an approach to structural complexity, defines a process's causal states and gives a procedure for finding them. We show that the causal-state representation--an $\epsilon$-machine--is the minimal one consistent with…

Statistical Mechanics · Physics 2022-02-17 Cosma Rohilla Shalizi , James P. Crutchfield

Resonance counting is an intuitive and widely used tool in Random Matrix Theory and Anderson Localization. Its undoubted advantage is its simplicity: in principle, it is easily applicable to any random matrix ensemble. On the downside, the…

Disordered Systems and Neural Networks · Physics 2025-03-12 Anton Kutlin , Carlo Vanoni

The aim of this short note is to draw attention to a method by which the partition function and marginal probabilities for a certain class of random fields on complete graphs can be computed in polynomial time. This class includes Ising…

Machine Learning · Computer Science 2013-06-19 Boris Flach

Under mild assumptions, we prove that any random multifunction can be represented as the set of minimizers of an infinitely many differentiable normal integrand, which preserves the convexity of the random multifunction. We provide several…

Optimization and Control · Mathematics 2021-08-06 Juan Guillermo Garrido , Pedro Pérez-Aros , Emilio Vilches

Invariance properties of semimartingales on Lie groups under a family of random transformations are defined and investigated, generalizing the random rotations of the Brownian motion. A necessary and sufficient explicit condition…

Probability · Mathematics 2018-12-31 Sergio Albeverio , Francesco C. De Vecchi , Paola Morando , Stefania Ugolini

We consider the notion of the matrix (tensor) distribution of a measurable function of several variables. On the one hand, it is an invariant of this function with respect to a certain group of transformations of variables; on the other…

Dynamical Systems · Mathematics 2023-11-03 A. Vershik

We discuss the application of random projections to conic programming: notably linear, second-order and semidefinite programs. We prove general approximation results on feasibility and optimality using the framework of formally real Jordan…

Optimization and Control · Mathematics 2021-01-13 Leo Liberti , Pierre-Louis Poirion , Ky Vu

The notion of random self-decomposability is generalized further. The notion is then extended to non-negative integer-valued distributions.

Probability · Mathematics 2010-10-05 S Satheesh , E Sandhya

For the space of functions that can be approximated by linear chirps, we prove a reconstruction theorem by random sampling at arbitrary rates.

Probability · Mathematics 2010-08-31 Eric Carlen , R. Vilela Mendes

A computer code can simulate a system's propagation of variation from random inputs to output measures of quality. Our aim here is to estimate a critical output tail probability or quantile without a large Monte Carlo experiment. Instead,…

Machine Learning · Statistics 2019-08-16 Hao Chen , William J. Welch

A new class of functions is presented. The structure of the algorithm, particularly the selection criteria (branching), is used to define the fundamental property of the new class. The most interesting property of the new functions is that…

Computational Complexity · Computer Science 2020-02-25 Rade Vuckovac

We introduce the notion of almost realizability, an arithmetic generalization of realizability for integer sequences, which is the property of counting periodic points for some map. We characterize the intersection between the set of…

Number Theory · Mathematics 2025-08-18 Piotr Miska , Tom Ward

Although algorithmic randomness with respect to various non-uniform computable measures is well-studied, little attention has been paid to algorithmic randomness with respect to computable \emph{trivial} measures, where a measure $\mu$ on…

Logic · Mathematics 2015-03-24 Christopher P. Porter

In this paper we introduce the notion of linear computability as a method of finding the Waring rank of forms. We use this notion to find infinitely many new examples which satisfy Strassen's Conjecture.

Commutative Algebra · Mathematics 2015-06-15 Enrico Carlini , Maria Virginia Catalisano , Luca Chiantini , Anthony V. Geramita , Youngho Woo

A randomised trapezoidal quadrature rule is proposed for continuous functions which enjoys less regularity than commonly required. Indeed, we consider functions in some fractional Sobolev space. Various error bounds for this randomised rule…

Numerical Analysis · Mathematics 2020-12-03 Yue Wu

We propose a notion of autoreducibility for infinite time computability and explore it and its connection with a notion of randomness for infinite time machines.

Logic · Mathematics 2014-02-06 Merlin Carl