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Linear programming (LP) is an extremely useful tool and has been successfully applied to solve various problems in a wide range of areas, including operations research, engineering, economics, or even more abstract mathematical areas such…

Data Structures and Algorithms · Computer Science 2020-03-19 Agniva Chowdhury , Palma London , Haim Avron , Petros Drineas

In this work, we propose Asynchronous Perception Machine (APM), a computationally-efficient architecture for test-time-training (TTT). APM can process patches of an image one at a time in any order asymmetrically and still encode…

Computer Vision and Pattern Recognition · Computer Science 2025-09-26 Rajat Modi , Yogesh Singh Rawat

Theoretical concepts in condensed matter physics are typically verified and also developed by exploiting computer simulations mostly in simple models. Predictions based on these usually isotropic models are often at odds with measurement…

Soft Condensed Matter · Physics 2020-11-13 K. Koperwas , A. Grzybowski , M. Paluch

Neutral atom quantum computing's great scaling potential has resulted in it emerging as a popular modality in recent years. For state preparation, atoms are loaded stochastically and have to be detected and rearranged at runtime to create a…

Emerging Technologies · Computer Science 2025-09-16 Jonas Winklmann , Martin Schulz

This paper considers the shape formation problem within the 3D hybrid model, where a single agent with a strictly limited viewing range and the computational capacity of a deterministic finite automaton manipulates passive tiles through…

Data Structures and Algorithms · Computer Science 2024-05-15 Kristian Hinnenthal , David Liedtke , Christian Scheideler

We propose a new theoretical model for passively mobile Wireless Sensor Networks, called PM, standing for Passively mobile Machines. The main modification w.r.t. the Population Protocol model is that agents now, instead of being automata,…

Computational Complexity · Computer Science 2010-12-14 Ioannis Chatzigiannakis , Othon Michail , Stavros Nikolaou , Andreas Pavlogiannis , Paul G. Spirakis

Determining the stability of molecules and condensed phases is the cornerstone of atomistic modelling, underpinning our understanding of chemical and materials properties and transformations. Here we show that a machine learning model,…

We propose masked particle modeling (MPM) as a self-supervised method for learning generic, transferable, and reusable representations on unordered sets of inputs for use in high energy physics (HEP) scientific data. This work provides a…

High Energy Physics - Phenomenology · Physics 2024-07-12 Tobias Golling , Lukas Heinrich , Michael Kagan , Samuel Klein , Matthew Leigh , Margarita Osadchy , John Andrew Raine

Arbitrary Pattern Formation (APF) is a fundamental coordination problem in swarm robotics. It requires a set of autonomous robots (mobile computing units) to form an arbitrary pattern (given as input) starting from any initial pattern. This…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-03-28 Avisek Sharma , Satakshi Ghosh , Pritam Goswami , Buddhadeb Sau

Scalable and efficient numerical simulations continue to gain importance, as computation is firmly established as the third pillar of discovery, alongside theory and experiment. Meanwhile, the performance of computing hardware grows through…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-06-26 Pietro Incardona , Antonio Leo , Yaroslav Zaluzhnyi , Rajesh Ramaswamy , Ivo F. Sbalzarini

First principles based exploration of chemical space deepens our understanding of chemistry, and might help with the design of new materials or experiments. Due to the computational cost of quantum chemistry methods and the immens number of…

Chemical Physics · Physics 2020-08-18 Bing Huang , O. Anatole von Lilienfeld

Symmetries impose structure on the Hilbert space of a quantum mechanical model. The mathematical units of this structure are the irreducible representations of symmetry groups and I consider how they function as conceptual units of…

Quantum Physics · Physics 2018-01-29 N. L. Harshman

We study centralized reconfiguration problems for geometric amoebot structures. A set of $n$ amoebots occupy nodes on the triangular grid and can reconfigure via expansion and contraction operations. We focus on the joint movement…

Data Structures and Algorithms · Computer Science 2026-03-12 Manish Kumar , Othon Michail , Andreas Padalkin , Christian Scheideler

Statistical learning algorithms are finding more and more applications in science and technology. Atomic-scale modeling is no exception, with machine learning becoming commonplace as a tool to predict energy, forces and properties of…

Chemical Physics · Physics 2020-12-09 Félix Musil , Michele Ceriotti

The objective of this article is to study the asymptotic behavior of a new particle filtering approach in the context of hidden Markov models (HMMs). In particular, we develop an algorithm where the latent-state sequence is segmented into…

Statistics Theory · Mathematics 2014-09-16 Hock Peng Chan , Chiang Wee Heng , Ajay Jasra

Particle learning (PL) provides state filtering, sequential parameter learning and smoothing in a general class of state space models. Our approach extends existing particle methods by incorporating the estimation of static parameters via a…

Methodology · Statistics 2010-11-05 Carlos M. Carvalho , Michael S. Johannes , Hedibert F. Lopes , Nicholas G. Polson

Amorphous materials are coming within reach of realistic computer simulations, but new approaches are needed to fully understand their intricate atomic structures. Here, we show how machine-learning (ML)-based techniques can give new,…

Jamming is a fundamental transition that governs the mechanical behavior of particulate media, including sand, foam and dense suspensions but also biological tissues: Upon compression, particulate media can change from freely flowing to a…

Soft Condensed Matter · Physics 2022-03-10 Zhaoyu Xie , Timothy J Atherton

Atomic probe tomography (APT), based on the work of Erwin Mueller, is able to generate three-dimensional chemical maps in atomic resolution. The required instruments for APT have evolved over the last 20 years from an experimental to an…

This study explores the age-old quest to construct a geometric model of a quantum particle. While static classical particle models have largely been dismissed, the focus has now shifted to intricate dynamic models that hold the promise of…

General Relativity and Quantum Cosmology · Physics 2024-05-21 Michael Cramer Andersen