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Macroscopic fluctuations have become an essential tool to understand physics far from equilibrium due to the link between their statistics and nonequilibrium ensembles. The optimal path leading to a fluctuation encodes key information on…

Statistical Mechanics · Physics 2017-03-13 N. Tizón-Escamilla , P. I. Hurtado , P. L. Garrido

Symmetry-informed machine learning can exhibit advantages over machine learning which fails to account for symmetry. In the context of continuous symmetry detection, current state of the art experiments are largely limited to detecting…

Machine Learning · Statistics 2025-11-13 Ben Shaw , Sasidhar Kunapuli , Abram Magner , Kevin R. Moon

Dissipative phenomena manifest in multiple mechanical systems. In this dissertation, different geometric frameworks for modelling non-conservative dynamics are considered. The objective is to generalize several results from conservative…

Mathematical Physics · Physics 2024-09-19 Asier López-Gordón

This paper defines the basis of a new hierarchical framework for segmentation algorithms based on energy minimization schemes. This new framework is based on two formal tools. First, a combinatorial pyramid encode efficiently a hierarchy of…

Computer Vision and Pattern Recognition · Computer Science 2009-06-16 Martin Braure De Calignon , Luc Brun , Jacques-Olivier Lachaud

We propose a novel framework for learning a low-dimensional representation of data based on nonlinear dynamical systems, which we call dynamical dimension reduction (DDR). In the DDR model, each point is evolved via a nonlinear flow towards…

Machine Learning · Statistics 2022-04-19 Ryeongkyung Yoon , Braxton Osting

The solid-on-solid model provides a commonly used framework for the description of surfaces. In the last years it has been extended in order to investigate the effect of defects in the bulk on the roughness of the surface. The determination…

Condensed Matter · Physics 2009-10-28 U. Blasum , W. Hochstättler , C. Moll , H. Rieger

Advancements in cytometry technologies have led to a remarkable increase in the number of markers that can be analyzed simultaneously, presenting significant challenges in data analysis. Traditional approaches, such as dimensional reduction…

Quantitative Methods · Quantitative Biology 2025-07-01 Masahiro Ono

A computational framework is presented for the sampling of the energy surface of magnetic systems via the systematic identification of first-order saddle points that determine connectivity of metastable states and define the mechanisms of…

Materials Science · Physics 2025-12-09 Hendrik Schrautzer , Tim Drevelow , Hannes Jónsson , Pavel F. Bessarab

Some recent experimental and theoretical work on 1) charge symmetry-breaking, 2) parity non-conservation, and 3) searches for breaking of time reversal invariance are reviewed. The examples illustrate the uses of symmetry to learn about…

Nuclear Theory · Physics 2009-09-25 Ernest M. Henley

Periodic frameworks with crystallographic symmetry are investigated from the perspective of a general deformation theory of periodic bar-and-joint structures in $R^d$. It is shown that natural parametrizations provide affine section…

Metric Geometry · Mathematics 2011-10-24 Ciprian S. Borcea , Ileana Streinu

We present a pedagogical, but by no means complete, review of weak scale supersymmetry phenomenology. After a general introduction to the new particles that must be present in any supersymmetric framework, we describe how to write down…

High Energy Physics - Phenomenology · Physics 2008-02-03 Xerxes Tata

We develop a method combining machine learning (ML) and density functional theory (DFT) to predict low-energy polymorphs by introducing physics-guided descriptors based on structural distortion modes. We systematically generate crystal…

Materials Science · Physics 2022-09-07 Bastien F. Grosso , Nicola A. Spaldin , Aria Mansouri Tehrani

Topology is a fundamental aspect of quantum physics, and it has led to key breakthroughs and results in various fields of quantum materials. In condensed matters, this has culminated in the recent discovery of symmetry-protected topological…

Materials Science · Physics 2023-10-24 Baokai Wang , Yi-Chun Hung , Xiaoting Zhou , Tzen Ong , Hsin Lin

The design space of discrete-space diffusion or flow generative models are significantly less well-understood than their continuous-space counterparts, with many works focusing only on a simple masked construction. In this work, we aim to…

In geometry processing, symmetry is a universal type of high-level structural information of 3D models and benefits many geometry processing tasks including shape segmentation, alignment, matching, and completion. Thus it is an important…

Graphics · Computer Science 2021-09-15 Lin Gao , Ling-Xiao Zhang , Hsien-Yu Meng , Yi-Hui Ren , Yu-Kun Lai , Leif Kobbelt

These are intended to be review notes on emergent symmetries, i.e., symmetries which manifest themselves in specific sectors of energy in many systems. The emphasis is on the physical aspects rather than computation methods. We include some…

High Energy Physics - Theory · Physics 2016-03-17 Pedro R. S. Gomes

In this paper, we give a new framework for the stochastic shortest path problem in finite state and action spaces. Our framework generalizes both the frameworks proposed by Bertsekas and Tsitsikli and by Bertsekas and Yu. We prove that the…

Discrete Mathematics · Computer Science 2017-02-13 Matthieu Guillot , Gautier Stauffer

An introduction to the minimal supersymmetric Standard Model (MSSM) is given. The motivation for ``low-energy'' supersymmetry is reviewed, and the structure of the MSSM is outlined. In its most general form, the MSSM can be viewed as a…

High Energy Physics - Phenomenology · Physics 2008-02-03 Howard E. Haber

A new minimal coupling method is introduced. A general dissipative quantum system is investigated consistently and systematically. Some coupling functions describing the interaction between the system and the environment are introduced.…

Quantum Physics · Physics 2007-05-23 F. Kheirandish , M. Amooshahi

Symmetry in differential equations reveals invariances and offers a powerful means to reduce model complexity. Lie group analysis characterizes these symmetries through infinitesimal generators, which provide a local, linear criterion for…

Numerical Analysis · Mathematics 2025-11-14 Max Kreider , John Harlim , Daning Huang