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The tacnode process is a universal determinantal point process arising from non-intersecting particle systems and tiling problems. It is the aim of this work to explore the integrable structure and large gap asymptotics for the gap…

Mathematical Physics · Physics 2023-07-13 Luming Yao , Lun Zhang

We introduce a model for stochastic transport on a one-dimensional substrate with particles assuming different conformations during their stepping cycles. These conformations correspond to different footprints on the substrate: in order to…

Statistical Mechanics · Physics 2019-06-26 Yvan Rousset , Luca Ciandrini , Norbert Kern

We study algorithmic randomness notions via effective versions of almost-everywhere theorems from analysis and ergodic theory. The effectivization is in terms of objects described by a computably enumerable set, such as lower semicomputable…

Logic · Mathematics 2016-03-22 Kenshi Miyabe , André Nies , Jing Zhang

These are the lecture notes of a course taught at the Park City Mathematics Institute in June 2017. They are intended to review some recent results, obtained in large part with Thomas Lebl\'e, on the statistical mechanics of systems of…

Mathematical Physics · Physics 2017-09-14 Sylvia Serfaty

Elements of the pomeron phenomenology within the Regge pole exchange picture are recalled. This includes discussion of the high energy behaviour of total cross-sections, the triple pomeron limit of the diffractive dissociation and the…

High Energy Physics - Phenomenology · Physics 2007-05-23 J. Kwiecinski

These notes cover and expand upon the material for two summer schools: The first, which was held at CIRM, Marseille, France, July 10-14, 2023, as part of "Renormalization and Visualization for packing, billiard and surfaces", was titled…

Number Theory · Mathematics 2024-12-04 Katherine E. Stange

We use computer simulations to test a simple idea for mapping between long-time self diffusivities obtained from molecular and Brownian dynamics. The strategy we explore is motivated by the behavior of fluids comprising particles that…

Soft Condensed Matter · Physics 2011-10-25 Mark J. Pond , Jeffrey R. Errington , Thomas M. Truskett

These are notes for a mini-course of 3 lectures given at the St. Petersburg School in Probability and Statistical Physics (June 2012). My aim was to explain, on the example of a particular model, how ideas from the representation theory of…

Probability · Mathematics 2016-07-19 Grigori Olshanski

We describe birational representations of discrete groups generated by involutions, having their origin in the theory of exactly solvable vertex-models in lattice statistical mechanics. These involutions correspond respectively to two kinds…

High Energy Physics - Theory · Physics 2009-10-28 S. Boukraa , J-M. Maillard , G. Rollet

This paper investigates second-order representations in the sense of Kawamura and Cook for spaces of integrable functions that regularly show up in analysis. It builds upon prior work about the space of continuous functions on the unit…

Computational Complexity · Computer Science 2019-03-14 Florian Steinberg

Folding and aggregation of proteins, the interaction between proteins and membranes, as well as the adsorption of organic soft matter to inorganic solid substrates belong to the most interesting challenges in understanding structure and…

Soft Condensed Matter · Physics 2007-12-06 Michael Bachmann , Wolfhard Janke

The authors have been using a largely algebraic form of ``computational discovery'' in various undergraduate classes at their respective institutions for some decades now to teach pure mathematics, applied mathematics, and computational…

History and Overview · Mathematics 2024-07-31 Neil J. Calkin , Eunice Y. S. Chan , Robert M. Corless

The expansiveness of compositional phase space is too vast to fully search using current theoretical tools for many emergent problems in condensed matter physics. The reliance on a deep chemical understanding is one method to identify local…

Superconductivity · Physics 2023-01-26 Lazar Novakovic , Ashkan Salamat , Keith V. Lawler

Machine learning potentials (MLPs) are becoming powerful tools for performing accurate atomistic simulations and crystal structure optimizations. An approach to developing MLPs employs a systematic set of polynomial invariants including…

Computational Physics · Physics 2020-11-18 Atsuto Seko

The O'Connell process is a softened version (a geometric lifting with a parameter $a>0$) of the noncolliding Brownian motion such that neighboring particles can change the order of positions in one dimension within the characteristic length…

Probability · Mathematics 2012-10-30 Makoto Katori

We introduce the idea of {\it collisional models} for Brownian particles, in which a particle is sequentially placed in contact with distinct thermal environments and external forces. Thermodynamic properties are exactly obtained,…

Statistical Mechanics · Physics 2020-10-07 Angel L. L. Stable , Carlos E. F. Noa , William G. C. Oropesa , C. E. Fiore

These notes originated in a series of lectures I gave in Marseille in May, 2013. I was invited to give an introduction to the isomorphism theorems, originating with Dynkin, which connect Markov local times and Gaussian processes. This is an…

Probability · Mathematics 2014-07-08 Jay Rosen

We present a detailed phenomenological study of $J/\psi$ polarization in semi-inclusive deep inelastic scattering processes, focusing on the kinematics accessible at the future Electron-Ion Collider. We show theoretical estimates for the…

High Energy Physics - Phenomenology · Physics 2023-06-14 Umberto D'Alesio , Luca Maxia , Francesco Murgia , Cristian Pisano , Sangem Rajesh

It came to the attention of myself and the coauthors of (S., Rozowski, Silva, Rot, 2022) that a number of process calculi can be obtained by algebraically presenting the branching structure of the transition systems they specify. Labelled…

Logic · Mathematics 2022-10-25 Todd Schmid

Probabilistic argumentation allows reasoning about argumentation problems in a way that is well-founded by probability theory. However, in practice, this approach can be severely limited by the fact that probabilities are defined by adding…

Artificial Intelligence · Computer Science 2019-03-07 Nico Potyka
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