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This paper develops a new approach to the estimation of the degree of boundedness or stability of multidimensional nonlinear systems with time-dependent nonperiodic coefficients-an essential task in various engineering and natural science…

Dynamical Systems · Mathematics 2022-06-16 Mark A. Pinsky

From correlations in measurement outcomes alone, can two otherwise isolated parties establish whether such correlations are atemporal? That is, can they rule out that they have been given the same system at two different times? Classical…

Quantum Physics · Physics 2024-09-24 Minjeong Song , Varun Narasimhachar , Bartosz Regula , Thomas J. Elliott , Mile Gu

A scheme is presented to extract detailed dynamical signatures from successive measurements of complex systems. Relative entropy based time series tools are used to quantify the gain in predictive power of increasing past knowledge. By…

Data Analysis, Statistics and Probability · Physics 2008-12-31 Nick S. Jones

Time ordering may be defined by first defining the limit of no time ordering (NTO) in terms of a time average of an external interaction, V(t). Previously, time correlation was defined in terms of a similar limit called the independent time…

Information-processing systems that coordinate multiple agents and objectives face fundamental thermodynamic constraints. We show that solutions with maximum utility to act as coordination focal points have a much higher selection pressure…

Artificial Intelligence · Computer Science 2025-10-16 Atma Anand

The out-of-time-ordered correlators (OTOC) have been established as a fundamental concept for quantifying quantum information scrambling and diagnosing quantum chaotic behavior. Recently, it was theoretically proposed that the OTOC can be…

Quantum Physics · Physics 2020-07-01 Xinfang Nie , Bo-Bo Wei , Xi Chen , Ze Zhang , Xiuzhu Zhao , Chudan Qiu , Yu Tian , Yunlan Ji , Tao Xin , Dawei Lu , Jun Li

The out-of-time-ordered correlation (OTOC) function is an important new probe in quantum field theory which is treated as a significant measure of random quantum correlations. In this paper, with the slogan "Cosmology meets Condensed Matter…

High Energy Physics - Theory · Physics 2020-09-17 Sayantan Choudhury

A model quantum cosmology is used to illustrate how arrows of time emerge in a universe governed by a time-neutral dynamical theory constrained by time asymmetric initial and final boundary conditions represented by initial and final…

General Relativity and Quantum Cosmology · Physics 2020-02-18 James B. Hartle

The outcome of continuously measuring a quantum system is a string of data whose intricate correlation properties reflect the underlying quantum dynamics. In this paper we study the role of these correlation in reconstructing the…

Quantum Physics · Physics 2024-11-14 Joseph A. Smiga , Gabriel T. Landi

Out-of-time-order correlators (OTOC) being explored as a measure of quantum chaos, is studied here in a coupled bipartite system. Each of the subsystems can be chaotic or regular and lead to very different OTOC growths both before and after…

Quantum Physics · Physics 2023-07-19 Ravi Prakash , Arul Lakshminarayan

While the microscopic laws of physics are often symmetric under time reversal, most natural processes that we observe are not. The emergent asymmetry between typical and time-reversed processes is referred to as the arrow of time. In…

Quantum Physics · Physics 2025-12-23 Luis Pedro García-Pintos , Yi-Kai Liu , Alexey V. Gorshkov

Prior work proposed simple test-time scaling, a method for replicating this scaling behavior with models distilled from o1-like models by manually controlling test-time compute: either scaling down by enforcing a maximum length or scaling…

Machine Learning · Computer Science 2025-07-22 Guojun Wu

In this paper we propose the PCP-like theorem for sub-linear time inapproximability. Abboud et al. have devised the distributed PCP framework for proving sub-quadratic time inapproximability. Here we try to go further in this direction.…

Computational Complexity · Computer Science 2024-01-03 Hengzhao Ma , Jianzhong Li

We give a new general approach for designing exact exponential-time algorithms for subset problems. In a subset problem the input implicitly describes a family of sets over a universe of size n and the task is to determine whether the…

Data Structures and Algorithms · Computer Science 2015-12-08 Fedor V. Fomin , Serge Gaspers , Daniel Lokshtanov , Saket Saurabh

Topologically ordered quantum matter exhibits intriguing long-range patterns of entanglement, which reveal themselves in subsystem entropies. However, measuring such entropies, which can be used to certify topological order, on large…

Quantum Physics · Physics 2024-08-26 Robert Ott , Torsten V. Zache , Nishad Maskara , Mikhail D. Lukin , Peter Zoller , Hannes Pichler

Extreme-order statistics is applied to the branches of an observer in a many-worlds framework. A unitary evolution operator for a step of time is constructed, generating pseudostochastic behaviour with a power-law distribution when applied…

Quantum Physics · Physics 2012-04-04 L. Polley

We study variants of the mean problem under the $p$-Dynamic Time Warping ($p$-DTW) distance, a popular and robust distance measure for sequential data. In our setting we are given a set of finite point sequences over an arbitrary metric…

Computational Geometry · Computer Science 2022-05-03 Maike Buchin , Anne Driemel , Koen van Greevenbroek , Ioannis Psarros , Dennis Rohde

We consider statistical methods based on finite samples of locally randomized measurements in order to certify different degrees of multiparticle entanglement in intermediate-scale quantum systems. We first introduce hierarchies of…

Quantum Physics · Physics 2023-06-08 Andreas Ketterer , Satoya Imai , Nikolai Wyderka , Otfried Gühne

Over the last 30 years, extensive work has been devoted to developing central limit theory for partial sums of subordinated long memory linear time series. A much less studied problem, motivated by questions that are ubiquitous in extreme…

Probability · Mathematics 2026-03-24 Ioan Scheffel , Marco Oesting , Gilles Stupfler

Submodular maximization is a general optimization problem with a wide range of applications in machine learning (e.g., active learning, clustering, and feature selection). In large-scale optimization, the parallel running time of an…

Data Structures and Algorithms · Computer Science 2023-04-11 Matthew Fahrbach , Vahab Mirrokni , Morteza Zadimoghaddam