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Related papers: Towards a Matrix Product Ansatz in Two Dimensions

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A fundamental problem in modern supervised learning is computing reliable conditional prediction intervals in high-dimensional settings: existing methods often rely on restrictive modelling assumptions, do not scale as predictor dimension…

Machine Learning · Statistics 2026-02-24 Daniel Salnikov , Dan Leonte , Kevin Michalewicz

A totally asymmetric exclusion process on a ring with $\nu$ non-conserved internal degrees of freedom, where particles hop forward with a rate that depends on their internal state, has been studied. We show, using a mapping of the model to…

Statistical Mechanics · Physics 2010-11-16 Urna Basu , P. K. Mohanty

Principal Component Analysis (PCA) is a fundamental tool for data visualization, denoising, and dimensionality reduction. It is widely popular in Statistics, Machine Learning, Computer Vision, and related fields. However, PCA is well-known…

Machine Learning · Statistics 2023-07-21 Debolina Paul , Saptarshi Chakraborty , Swagatam Das

Matrix product states play an important role in quantum information theory to represent states of many-body systems. They can be seen as low-dimensional subvarieties of a high-dimensional tensor space. In these notes, we consider two…

Representation Theory · Mathematics 2023-12-05 Tim Seynnaeve

Modern approaches to generative modeling of continuous data using tensor networks incorporate compression layers to capture the most meaningful features of high-dimensional inputs. These methods, however, rely on traditional Matrix Product…

Machine Learning · Computer Science 2024-12-11 Danylo Kolesnyk , Yelyzaveta Vodovozova

Inspired from modern out-of-equilibrium statistical physics models, a matrix product based framework permits the formal definition of random vectors (and random time series) whose desired joint distributions are a priori prescribed. Its key…

Statistical Mechanics · Physics 2012-03-21 Florian Angeletti , Eric Bertin , Patrice Abry

A generic algorithm for the extraction of probabilistic (Bayesian) information about model parameters from data is presented. The algorithm propagates an ensemble of particles in the product space of model parameters and outputs. Each…

Computation · Statistics 2015-09-18 Carlo Albert

A fundamental objective of materials modeling is identifying atomic structures that align with experimental observables. Conventional approaches for disordered materials involve sampling from thermodynamic ensembles and hoping for an…

Materials Science · Physics 2025-09-30 Tigany Zarrouk , Miguel A. Caro

The asymmetric simple exclusion process (ASEP) is a paradigm for non-equilibrium physics that appears as a building block to model various low-dimensional transport phenomena, ranging from intracellular traffic to quantum dots. We review…

Statistical Mechanics · Physics 2015-05-27 Kirone Mallick

We study the statistics of thermodynamic quantities in two related systems with quenched disorder: A (1+1)-dimensional planar lattice of elastic lines in a random potential and the 2-dimensional random bond dimer model. The first system is…

Disordered Systems and Neural Networks · Physics 2009-11-10 Simon Bogner , Thorsten Emig , Ahmed Taha , Chen Zeng

Towards the efficient simulation of near-term quantum devices using tensor network states, we introduce an improved real-space parallelizable matrix-product state (MPS) compression method. This method enables efficient compression of all…

Quantum Physics · Physics 2024-09-02 Rong-Yang Sun , Tomonori Shirakawa , Seiji Yunoki

In many important cellular processes, including mRNA translation, gene transcription, phosphotransfer, and intracellular transport, biological "particles" move along some kind of "tracks". The motion of these particles can be modeled as a…

Subcellular Processes · Quantitative Biology 2017-11-01 Yoram Zarai , Michael Margaliot , Tamir Tuller

We present a general scheme to realize a cold-atom quantum simulator of bidimensional atomic crystals. Our model is based on the use of two independently trapped atomic species: the first one, subject to a strong in-plane confinement,…

Quantum Gases · Physics 2014-09-19 Nicola Bartolo , Mauro Antezza

In this article, we introduce a new parameterized family of topological descriptors, taking the form of candidate decompositions, for multi-parameter persistence modules, and we identify a subfamily of these descriptors, that we call…

Algebraic Topology · Mathematics 2025-10-30 David Loiseaux , Mathieu Carrière , Andrew J. Blumberg

The equivalence of thermodynamic ensembles is at the heart of statistical mechanics and central to our understanding of equilibrium states of matter. Recently, it has been shown that there is a formal connection between the dynamics of open…

Quantum Physics · Physics 2015-07-29 Jukka Kiukas , Madalin Guta , Igor Lesanovsky , Juan P. Garrahan

Condensates of active particles such as cells form almost-crystalline lattices which play a central role in many biological systems. Typically, their properties have been determined merely by analogy to the rather trivial one-dimensional…

Soft Condensed Matter · Physics 2025-12-02 Connor Roberts , Gunnar Pruessner

It is known that when the steady state of a one-dimensional multispecies system, which evolves via a random-sequential updating mechanism, is written in terms of a linear combination of Bernoulli shock measures with random-walk dynamics, it…

Statistical Mechanics · Physics 2009-06-06 F. H. Jafarpour , S. R. Masharian

We study the $J_1$-$J_2$ spin-$1/2$ chain using a path integral constructed over matrix product states (MPS). By virtue of its non-trivial entanglement structure, the MPS ansatz captures the key phases of the model even at a semi-classical,…

Strongly Correlated Electrons · Physics 2025-02-21 F. Azad , Adam J. McRoberts , Chris Hooley , A. G. Green

The selection of an equilibrium state by maximising the entropy of a system, subject to certain constraints, is often powerfully motivated as an exercise in logical inference, a procedure where conclusions are reached on the basis of…

Statistical Mechanics · Physics 2015-12-03 Ian J. Ford

A novel mathematical model for fiber-reinforced materials is proposed. It is based on a 1-dimensional beam model for the thin fiber structures, a flexible and general 3-dimensional elasticity model for the matrix and an overlapping domain…

Computational Engineering, Finance, and Science · Computer Science 2021-05-12 Ustim Khristenko , Stefan Schuß , Melanie Krüger , Felix Schmidt , Barbara Wohlmuth , Christian Hesch