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We discuss different approaches for studying the influence of disorder in the three-dimensional Ising model. From the theoretical point of view, renormalisation group calculations provide quite accurate results. Experiments carried out on…

Statistical Mechanics · Physics 2007-05-23 Bertrand Berche , Pierre-Emmanuel Berche , Christophe Chatelain , Wolfhard Janke

On locally tree-like random graphs, we relate the random cluster model with external magnetic fields and $q\geq 2$ to Ising models with vertex-dependent external fields. The fact that one can formulate general random cluster models in terms…

Probability · Mathematics 2025-03-25 Van Hao Can , Remco van der Hofstad

We study the ability of Transformer models to learn sequences generated by Permuted Congruential Generators (PCGs), a widely used family of pseudo-random number generators (PRNGs). PCGs introduce substantial additional difficulty over…

Machine Learning · Computer Science 2026-02-18 Tao Tao , Maissam Barkeshli

A major challenge facing existing sequential Monte-Carlo methods for parameter estimation in physics stems from the inability of existing approaches to robustly deal with experiments that have different mechanisms that yield the results…

Quantum Physics · Physics 2017-09-13 Christopher Granade , Nathan Wiebe

Deep neural networks (DNNs) offer a means of addressing the challenging task of clustering high-dimensional data. DNNs can extract useful features, and so produce a lower dimensional representation, which is more amenable to clustering…

Machine Learning · Computer Science 2021-07-23 Louis Mahon , Thomas Lukasiewicz

Applications of reversible circuits can be found in the fields of low-power computation, cryptography, communications, digital signal processing, and the emerging field of quantum computation. Furthermore, prototype circuits for low-power…

Quantum Physics · Physics 2007-05-23 Ketan N. Patel , John P. Hayes , Igor L. Markov

This paper addresses the problem of unsupervised clustering which remains one of the most fundamental challenges in machine learning and artificial intelligence. We propose the clustered generator model for clustering which contains both…

Machine Learning · Statistics 2019-11-20 Dandan Zhu , Tian Han , Linqi Zhou , Xiaokang Yang , Ying Nian Wu

Monte Carlo criticality simulations are widely used in nuclear safety demonstrations, as they offer an arbitrarily precise estimation of global and local tallies while making very few assumptions. However, since the inception of such…

Statistical Mechanics · Physics 2023-01-11 Kévin Fröhlicher , Eric Dumonteil , Loïc Thulliez , Julien Taforeau , Mariya Brovchenko

The field of device-independent quantum cryptography has seen enormous success in the past several years, including security proofs for key distribution and random number generation that account for arbitrary imperfections in the devices…

Quantum Physics · Physics 2018-05-11 Carl A. Miller

Device-independent quantum random number generators (DI-QRNGs) are crucial for information processing, ensuring certified quantumness and genuine randomness. However, existing implementations often face low bit rates due to quantumness…

Quantum Physics · Physics 2025-03-25 Ayan Kumar Nai , Vimlesh Kumar , M. Ebrahim-Zadeh , G. K. Samanta

Numerical simulation is an important method for verifying the quantum circuits used to simulate low-energy nuclear states. However, real-world applications of quantum computing for nuclear theory often generate deep quantum circuits that…

Quantum Physics · Physics 2024-06-06 Ang Li , Alessandro Baroni , Ionel Stetcu , Travis S. Humble

Nuclear clustering describes the appearance of structures resembling smaller nuclei such as alpha particles (4He nuclei) within the interior of a larger nucleus. While clustering is important for several well-known examples, much remains to…

In recent decades, quantum technologies have made significant strides toward achieving quantum utility. However, practical applications are hindered by challenges related to scaling the number of qubits and the depth of circuits. In this…

Quantum Physics · Physics 2025-10-01 Pingal Pratyush Nath , Aninda Sinha , Urbasi Sinha

This paper provides a user's guide to the general theory of approximate randomization tests developed in Canay, Romano, and Shaikh (2017) when specialized to linear regressions with clustered data. An important feature of the methodology is…

Econometrics · Economics 2022-03-16 Yong Cai , Ivan A. Canay , Deborah Kim , Azeem M. Shaikh

We define two a priori tests of pseudo-random number generators for the class of linear matrix-recursions. The first desirable property of a random number generator is the smallness of serial or lagged correlations between generated…

Data Analysis, Statistics and Probability · Physics 2018-04-06 Spyros Konitopoulos , Konstantin G. Savvidy

The optimizations of the track fittings require complex simulations of silicon strip detectors to be compliant with the fundamental properties of the hit heteroscedasticity. Many different generations of random numbers must be available…

Instrumentation and Detectors · Physics 2023-09-06 Gregorio Landi , Giovanni E. Landi

We propose a simple simulation of nonlocal quantum correlations among $N$ qubits using a local hidden variable source with a positive probability distribution, given that each the $N$ observers has access to a local negative bit. Notably,…

Quantum Physics · Physics 2023-09-08 Kelvin Onggadinata , Pawel Kurzynski , Dagomir Kaszlikowski

Monte Carlo event generators are in a modern terminology the digital twins of collider-based particle physics experiment. We give an introduction into the application of MC generators for particle physics, discuss their different components…

High Energy Physics - Phenomenology · Physics 2025-09-29 Jürgen Reuter

Entanglement of high-dimensional quantum systems has become increasingly important for quantum communication and experimental tests of nonlocality. However, many effects of high-dimensional entanglement can be simulated by using multiple…

Quantum Physics · Physics 2018-02-09 Tristan Kraft , Christina Ritz , Nicolas Brunner , Marcus Huber , Otfried Gühne

In cluster tomography, we propose measuring the number of clusters $N$ intersected by a line segment of length $\ell$ across a finite sample. As expected, the leading order of $N(\ell)$ scales as $a\ell$, where $a$ depends on microscopic…

Disordered Systems and Neural Networks · Physics 2024-02-13 Helen S. Ansell , Samuel J. Frank , István A. Kovács