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Accurate extrinsic sensor calibration is essential for both autonomous vehicles and robots. Traditionally this is an involved process requiring calibration targets, known fiducial markers and is generally performed in a lab. Moreover, even…

Robotics · Computer Science 2021-03-18 Celyn Walters , Oscar Mendez , Simon Hadfield , Richard Bowden

We introduce a new disordered system, the Super-Potts model, which is a more frustrated version of the Potts glass. Its elementary degrees of freedom are variables that can take M values and are coupled via pair-wise interactions. Its exact…

Disordered Systems and Neural Networks · Physics 2015-01-15 Maria Chiara Angelini , Giulio Biroli

We study numerically the local low-energy excitations in the 3-d Edwards-Anderson model for spin glasses. Given the ground state, we determine the lowest-lying connected cluster of flipped spins with a fixed volume containing one given…

Disordered Systems and Neural Networks · Physics 2009-11-07 J. Lamarcq , J. -P. Bouchaud , O. C. Martin , M. Mezard

We present an algorithm for the exact computer-aided construction of the Voronoi cells of lattices with known symmetry group. Our algorithm scales better than linearly with the total number of faces and is applicable to dimensions beyond…

Information Theory · Computer Science 2025-10-28 Daniel Pook-Kolb , Bruce Allen , Erik Agrell

In the coming years, strong gravitational lens discoveries are expected to increase in frequency by two orders of magnitude. Lens-modelling techniques are being developed to prepare for the coming massive influx of new lens data, and blind…

Astrophysics of Galaxies · Physics 2020-06-18 Philipp Denzel , Sampath Mukherjee , Jonathan P. Coles , Prasenjit Saha

We revisited, by means of numerical simulations, the one dimensional bond diluted Levy Ising spin glasses outside the limit of validity of mean field theories. In these models the probability that two spins at distance $r$ interact (via a…

Disordered Systems and Neural Networks · Physics 2015-02-19 L. Leuzzi , G. Parisi , F. Ricci-Tersenghi , J. J. Ruiz-Lorenzo

Autoregressive Neural Networks based on dense or convolutional layers have recently been shown to be a viable strategy for generating classical spin systems. Unlike these methods, sampling with transformers is commonly considered to be…

Disordered Systems and Neural Networks · Physics 2026-05-01 Piotr Białas , Piotr Korcyl , Tomasz Stebel , Adam Stefański , Dawid Zapolski

Variational tensor network optimization has become a powerful tool for studying classical statistical models in two dimensions. However, its application to three-dimensional systems remains limited, primarily due to the high computational…

Statistical Mechanics · Physics 2025-10-14 Xia-Ze Xu , Tong-Yu Lin , Guang-Ming Zhang

We systematically examine various proposals which aim at increasing the accuracy in the determination of the renormalization of two-fermion lattice operators. We concentrate on three finite quantities which are particularly suitable for our…

High Energy Physics - Lattice · Physics 2011-09-13 M. Crisafulli , V. Lubicz , A. Vladikas

We present an algorithm which calculates groundstates of Ising spin glasses approximately. It works by randomly selecting clusters of spins which exhibit no frustrations. The spins which were not selected, contribute to the local fields of…

Condensed Matter · Physics 2015-06-25 A. K. Hartmann

We report exact numerical diagonalization results of the infinite-range Ising spin glass in a transverse field $\Gamma$ at zero temperature. Eigenvalues and eigenvectors are determined for various strengths of $\Gamma$ and for system sizes…

Statistical Mechanics · Physics 2008-02-03 Parongama Sen , Purusattam ray , Bikas K. Chakrabarti

The central object of this PhD thesis is known under different names in the fields of computer science and statistical mechanics. In computer science, it is called the Maximum Cut problem, one of the famous twenty-one Karp's original…

Machine Learning · Computer Science 2022-08-31 Mikhail Krechetov

We study the interplay of superfluidity, glassy and magnetic orders of hardcore bosons with random frustrating interactions. In the classical limit, this model reduces to a $\pm J$ Edwards-Anderson Ising model with concentration $p$ of the…

Disordered Systems and Neural Networks · Physics 2012-10-16 Derek Larson , Ying-Jer Kao

In this paper, we propose and analyse a family of generalised stochastic composite mirror descent algorithms. With adaptive step sizes, the proposed algorithms converge without requiring prior knowledge of the problem. Combined with an…

Optimization and Control · Mathematics 2022-11-22 Weijia Shao , Fikret Sivrikaya , Sahin Albayrak

Spin-glass systems are universal models for representing many-body phenomena in statistical physics and computer science. High quality solutions of NP-hard combinatorial optimization problems can be encoded into low energy states of…

Disordered Systems and Neural Networks · Physics 2020-01-14 Gavin S. Hartnett , Masoud Mohseni

Singular value decomposition (SVD) and matrix inversion are ubiquitous in scientific computing. Both tasks are computationally demanding for large scale matrices. Existing algorithms can approximatively solve these problems with a given…

Numerical Analysis · Mathematics 2026-01-28 Weiwei Xu , Weijie Shen , Zhengjian Bai , Chen Xu

Renormalization group on hierarchical lattices is often considered a valuable tool to understand the critical behavior of more complicated statistical mechanical models. In presence of quenched disorder, however, in many model cases…

Disordered Systems and Neural Networks · Physics 2014-11-21 F. Antenucci , A. Crisanti , L. Leuzzi

These lecture notes evolve around mathematical concepts arising in inverse problems. We start by introducing inverse problems through examples such as differentiation, deconvolution, computed tomography and phase retrieval. This then leads…

Numerical Analysis · Mathematics 2025-08-26 Danielle Bednarski , Tim Roith

We develop a replicated liquid theory for structural glasses which exhibit spatial variation of physical quantities along one axis, say $z$-axis. The theory becomes exact with infinite transverse dimension $d-1 \to \infty$. It provides an…

Soft Condensed Matter · Physics 2025-11-14 Yukihiro Tomita , Hajime Yoshino

Spin glasses occupy a unique place in condensed matter: they freeze collectively while remaining struc-turally disordered, and they exhibit slow, history-dependent dynamics that reflect an exceptionally rug-ged free-energy landscape. This…

Disordered Systems and Neural Networks · Physics 2025-12-25 Naeimeh Tahriri , Vahid Mahdikhah , Jahanfar Abouie , Daryoosh Vashaee