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Accurate measurement of shock wave motion parameters with high spatiotemporal resolution is essential for applications such as power field testing and damage assessment. However, significant challenges are posed by the fast, uneven…

Computer Vision and Pattern Recognition · Computer Science 2025-12-30 Taihang Lei , Banglei Guan , Minzu Liang , Pengju Sun , Jing Tao , Yang Shang , Qifeng Yu

Since a number of years the QGSJET model has been successfully used by different groups in the field of high energy cosmic rays. Current work is devoted to the first general update of the model. The key improvement is connected to an…

High Energy Physics - Phenomenology · Physics 2015-06-25 S. Ostapchenko

We review the basic concepts of all-order calculations in Quantum Chromodynamics (QCD) and their application to collider phenomenology. We start by discussing the factorization properties of QCD amplitudes and cross-sections in the soft and…

High Energy Physics - Phenomenology · Physics 2017-10-11 Gionata Luisoni , Simone Marzani

Recent developments in computer vision have enabled the availability of segmented images across various domains, such as medicine, where segmented radiography images play an important role in diagnosis-making. As prediction problems are…

Methodology · Statistics 2025-08-22 Issam-Ali Moindjié , Marie-Hélène Descary , Cédric Beaulac

We introduce a new event shape observable -- event isotropy -- that quantifies how close the radiation pattern of a collider event is to a uniform distribution. This observable is based on a normalized version of the energy mover's…

High Energy Physics - Phenomenology · Physics 2020-08-19 Cari Cesarotti , Jesse Thaler

Predicting the subsequent event for an existing event context is an important but challenging task, as it requires understanding the underlying relationship between events. Previous methods propose to retrieve relational features from event…

Computation and Language · Computer Science 2022-05-24 Li Du , Xiao Ding , Yue Zhang , Kai Xiong , Ting Liu , Bing Qin

Predicting extreme events in nonlinear dynamical systems is challenging due to a limited understanding of their statistical properties. This study numerically and theoretically investigates the statistical properties of infinite-modal maps…

Chaotic Dynamics · Physics 2026-04-07 Masaki Nakagawa

Topological effects continue to fascinate physicists since more than three decades. One of their main applications are high-precision measurements of the resistivity. We propose to make also use of the spatially separated edge states. It is…

Mesoscale and Nanoscale Physics · Physics 2016-06-01 Götz S. Uhrig

QCD predictions for moments of parton multiplicity distributions are discussed. The next-to-leading terms and conservation law give rise to the peculiar oscillating shape of some ratio of the moments. The similar shape has been found by…

High Energy Physics - Phenomenology · Physics 2007-05-23 I. M. Dremin

Topological phases are characterised by a topological invariant that remains unchanged by deformations in the Hamiltonian. Materials exhibiting topological phases include topological insulators, superconductors exhibiting strong spin-orbit…

Mesoscale and Nanoscale Physics · Physics 2019-07-08 Dimitrie Culcer , Attila Geresdi

We study fully three-dimensional droplets that slide down an incline by employing a thin-film equation that accounts for capillarity, wettability, and a lateral driving force in small-gradient (or long-wave) approximation. In particular, we…

Fluid Dynamics · Physics 2016-12-15 Sebastian Engelnkemper , Markus Wilczek , Svetlana V. Gurevich , Uwe Thiele

Some rigorous results can be derived using a very simple approach to hadron spectroscopy, in which a static potential is associated with non-relativistic kinematics. Several regularities of the experimental spectrum are explained by such…

Nuclear Theory · Physics 2009-11-06 Jean-Marc Richard

In real-world scenario, many phenomena produce a collection of events that occur in continuous time. Point Processes provide a natural mathematical framework for modeling these sequences of events. In this survey, we investigate…

Quantum gas microscopy has developed into a powerful tool to explore strongly correlated quantum systems. However, discerning phases with topological or off-diagonal long range order requires the ability to extract these correlations from…

Strongly Correlated Electrons · Physics 2024-08-09 Bo Xiao , Javier Robledo Moreno , Matthew Fishman , Dries Sels , Ehsan Khatami , Richard Scalettar

Disordered systems like liquids, gels, glasses, or granular materials are not only ubiquitous in daily life and in industrial applications but they are also crucial for the mechanical stability of cells or the transport of chemical and…

Disordered Systems and Neural Networks · Physics 2019-04-30 Zhen Zhang , Walter Kob

Symbolic event recognition systems have been successfully applied to a variety of application domains, extracting useful information in the form of events, allowing experts or other systems to monitor and respond when significant events are…

Artificial Intelligence · Computer Science 2013-08-16 Anastasios Skarlatidis , Georgios Paliouras , Alexander Artikis , George A. Vouros

Structural quantities such as order parameters and correlation functions are often employed to gain insight into the physical behavior and properties of condensed matter systems. While standard quantities for characterizing structure exist,…

Soft Condensed Matter · Physics 2017-08-23 Aaron S. Keys , Christopher R. Iacovella , Sharon C. Glotzer

The orbital angular momentum of light, unlike spin, is an infinite-dimensional discrete variable and may hence offer enhanced performances for encoding, transmitting, and processing information in the quantum regime. Hitherto, this degree…

Quantum Physics · Physics 2019-07-24 A. Pecoraro , F. Cardano , L. Marrucci , A. Porzio

Continuous-time event data are common in applications such as individual behavior data, financial transactions, and medical health records. Modeling such data can be very challenging, in particular for applications with many different types…

Machine Learning · Statistics 2020-11-09 Alex Boyd , Robert Bamler , Stephan Mandt , Padhraic Smyth

Training a model to detect patterns of interrelated events that form situations of interest can be a complex problem: such situations tend to be uncommon, and only sparse data is available. We propose a hybrid neuro-symbolic architecture…