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Phase retrieval (PR) is a popular research topic in signal processing and machine learning. However, its performance degrades significantly when the measurements are corrupted by noise or outliers. To address this limitation, we propose a…

Optimization and Control · Mathematics 2025-05-30 Jun Fan , Ailing Yan , Xianchao Xiu , Wanquan Liu

Reliable experimental demonstrations of violations of local realism are highly desirable for fundamental tests of quantum mechanics. One can quantify the violation witnessed by an experiment in terms of a statistical p-value, which can be…

Quantum Physics · Physics 2011-12-30 Yanbao Zhang , Scott Glancy , Emanuel Knill

Machine-learning techniques have become fundamental in high-energy physics and, for new physics searches, it is crucial to know their performance in terms of experimental sensitivity, understood as the statistical significance of the…

High Energy Physics - Phenomenology · Physics 2022-11-10 Ernesto Arganda , Xabier Marcano , Víctor Martín Lozano , Anibal D. Medina , Andres D. Perez , Manuel Szewc , Alejandro Szynkman

Statistical tests are needed to determine experimentally whether a hypothetical theory based on local realism can be an acceptable alternative to quantum mechanics. It is impossible to rule out local realism by a single test, as often…

Quantum Physics · Physics 2017-04-26 Asher Peres

In a local realist world view, physical properties are defined prior to and independent of measurement, and no physical influence can propagate faster than the speed of light. Proper experimental violation of a Bell inequality would show…

The Clauser-Horne-Shimony and Holt inequality applies when measurements with binary outcomes are performed on physical systems under the assumption of local realism. Testing such inequalities in the quantum realm usually involves either…

Quantum Physics · Physics 2015-04-28 A. Ketterer , A. Keller , T. Coudreau , P. Milman

Bell or Clauser-Horne-Shimony-Holt (CHSH) tests on superconducting quantum processors are commonly interpreted under the assumption that repeated circuit executions sample a single, stationary preparation ensemble. Here we show that this…

Quantum Physics · Physics 2026-01-14 Prosanta Pal , Shubhanshu Karoliya , Gargee Sharma , Ramakrishna Podila

Bell inequalities provide a fundamental tool for probing nonlocal correlations, yet their quantum bound, that is, the maximal value attainable through quantum strategies, is rarely accessible analytically. In this work, we introduce a…

Quantum Physics · Physics 2025-11-25 Patryk Michalski , Arturo Konderak , Wojciech Bruzda , Remigiusz Augusiak

In a sequence of papers, Marian Kupczynski has argued that Bell's theorem can be circumvented if one takes correct account of contextual setting-dependent parameters describing measuring instruments. We show that this is not true. Despite…

Quantum Physics · Physics 2023-06-05 Richard D. Gill , Justo Pastor Lambare

Bell inequalities are an important tool in device-independent quantum information processing because their violation can serve as a certificate of relevant quantum properties. Probably the best known example of a Bell inequality is due to…

This chapter demystifies P-values, hypothesis tests and significance tests, and introduces the concepts of local evidence and global error rates. The local evidence is embodied in \textit{this} data and concerns the hypotheses of interest…

Other Statistics · Statistics 2019-10-07 Michael J. Lew

Rehearsal-based continual learning (CL) mitigates catastrophic forgetting by maintaining a subset of samples from previous tasks for replay. Existing studies primarily focus on optimizing memory storage through coreset selection strategies.…

Machine Learning · Computer Science 2026-04-13 Minh-Duong Nguyen , Thien-Thanh Dao , Le-Tuan Nguyen , Dung D. Le , Kok-Seng Wong

One of the most striking non-classical features of quantum mechanics is in the correlations it predicts between spatially separated measurements. In local hidden variable theories, correlations are constrained by Bell inequalities, but…

Quantum Physics · Physics 2011-09-16 Matty J. Hoban , Dan E. Browne

We develop a framework for certifying randomness from Bell-test trials based on directly estimating the probability of the measurement outcomes with adaptive test supermartingales. The number of trials need not be predetermined, and one can…

Quantum Physics · Physics 2020-09-30 Emanuel Knill , Yanbao Zhang , Peter Bierhorst

A simple classical non-local dynamical system with random initial conditions and an output projecting the state variable on selected axes has been defined to mimic a two-channel quantum coincidence experiment. Non-locality is introduced by…

General Physics · Physics 2018-02-23 Renzo Mosetti

As a way of saving quantum resources, recycling of Bell nonlocality has been experimentally studied, but restricted to sequential unsharp measurements. However, it has been theoretically shown recently that projective measurements are…

Quantum Physics · Physics 2022-12-08 Ya Xiao , Yan-Xin Rong , Xin-Hong Han , Shuo Wang , Xuan Fan , Wei-Chen Li , Yong-Jian Gu

We report on a test of Bell inequalities using a non-maximally entangled state, which represents an important step in the direction of eliminating the detection loophole. The experiment is based on the creation of a polarisation entangled…

Quantum Physics · Physics 2007-05-23 G. Brida , M. Genovese , C. Novero , E. Predazzi

Entanglement, describing the inseparability of a quantum multiparty system, is one of the most intriguing features of quantum mechanics. Violation of Bell inequality, for ruling out the possibility of local hidden variable theories, is…

Quantum Physics · Physics 2017-04-21 Xianxin Guo , Yefeng Mei , Shengwang Du

This paper studies convergence of empirical risks in reproducing kernel Hilbert spaces (RKHS). A conventional assumption in the existing research is that empirical training data do not contain any noise but this may not be satisfied in some…

Optimization and Control · Mathematics 2020-05-19 Shaoyan Guo , Huifu Xu , Liwei Zhang

Most existing temporal point process models are characterized by conditional intensity function. These models often require numerical approximation methods for likelihood evaluation, which potentially hurts their performance. By directly…

Machine Learning · Computer Science 2024-05-03 Bingqing Liu
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