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One-dimensional scattering mediated by non-Hermitian Hamiltonians is studied. A schematic set of models is used which simulate two point interactions at a variable strength and distance. The feasibility of the exact construction of the…

Quantum Physics · Physics 2008-06-26 Miloslav Znojil

In this work we study the interleaving distance between merge trees from a combinatorial point of view. We use a particular type of matching between trees to obtain a novel formulation of the distance. With such formulation, we tackle the…

Combinatorics · Mathematics 2024-11-11 Matteo Pegoraro

We discuss the computational complexity of random 2D Ising spin glasses, which represent an interesting class of constraint satisfaction problems for black box optimization. Two extremal cases are considered: (1) the +/- J spin glass, and…

Neural and Evolutionary Computing · Computer Science 2009-09-29 Martin Pelikan , Jiri Ocenasek , Simon Trebst , Matthias Troyer , Fabien Alet

A collective spin model is used to describe two species of mutually interacting ultracold bosonic atoms confined to a toroidal trap. The system is modeled by a Hamiltonian that can be split into two components, a linear part and a quadratic…

Quantum Gases · Physics 2024-06-05 Allison Brattley , Tomáš Opatrný , Kunal K. Das

We study the problem of algorithmically optimizing the Hamiltonian $H_N$ of a spherical or Ising mixed $p$-spin glass. The maximum asymptotic value $\mathsf{OPT}$ of $H_N/N$ is characterized by a variational principle known as the Parisi…

Probability · Mathematics 2022-09-13 Brice Huang , Mark Sellke

Fitting distances to tree metrics and ultrametrics are two widely used methods in hierarchical clustering, primarily explored within the context of numerical taxonomy. Given a positive distance function…

Data Structures and Algorithms · Computer Science 2025-04-25 Amir Carmel , Debarati Das , Evangelos Kipouridis , Evangelos Pipis

Motivated by the duality between site-centered spin and bond-centered spin in one-dimensional system, which connects two different constructions of fermions from the same set of Majorana fermions, we show that two-dimensional models with…

Strongly Correlated Electrons · Physics 2008-11-26 Han-Dong Chen , Jiangping Hu

We propose and study an algorithm for computing a nearest passive system to a given non-passive linear time-invariant system (with much freedom in the choice of the metric defining `nearest', which may be restricted to structured…

Numerical Analysis · Mathematics 2021-03-04 Antonio Fazzi , Nicola Guglielmi , Christian Lubich

We study four particular 3-dimensional natural Hamiltonian systems defined in conformally Euclidean spaces. We prove their superintegrability and we obtain, in the four cases, the maximal number of functionally independent integrals of…

Mathematical Physics · Physics 2021-09-13 Jose F. Carinena , Manuel F. Ranada , Mariano Santander

Josephson junctions in a two-dimensional electron gas with spin-orbit coupling are a promising candidate to realize topological superconductivity. While it is known that the geometry of the junction strongly influences the size of the…

Mesoscale and Nanoscale Physics · Physics 2023-03-22 André Melo , Tanko Tanev , Anton R. Akhmerov

We study strongly isochronous Hamiltonians that generate periodic time evolution with the same basic period for a dense set of initial values. We explain that all such Hamiltonians are maximally superintegrable, and show that if the system…

Mathematical Physics · Physics 2024-12-19 L. Feher

Recent tensor-network samplings of modified Nishimori spin glasses have revealed robust finite-temperature critical transitions in two dimensions, defying the standard Edwards-Anderson lower critical dimension boundary ($d_{l}\approx2.5$).…

Disordered Systems and Neural Networks · Physics 2026-04-14 Alok Yadav

Near-integrability is usually associated with smooth small perturbations of smooth integrable systems. Studying integrable mechanical Hamiltonian flows with impacts that respect the symmetries of the integrable structure provides an…

Chaotic Dynamics · Physics 2020-11-24 Michal Pnueli , Vered Rom-Kedar

In this paper we propose and study a new complexity model for approximation algorithms. The main motivation are practical problems over large data sets that need to be solved many times for different scenarios, e.g., many multicast trees…

Data Structures and Algorithms · Computer Science 2010-06-18 Marek Cygan , Lukasz Kowalik , Marcin Mucha , Marcin Pilipczuk , Piotr Sankowski

If we have a system of binary variables and we measure the pairwise correlations among these variables, then the least structured or maximum entropy model for their joint distribution is an Ising model with pairwise interactions among the…

Disordered Systems and Neural Networks · Physics 2014-09-12 Michele Castellana , William Bialek

The central object of this PhD thesis is known under different names in the fields of computer science and statistical mechanics. In computer science, it is called the Maximum Cut problem, one of the famous twenty-one Karp's original…

Machine Learning · Computer Science 2022-08-31 Mikhail Krechetov

Tree projections provide a unifying framework to deal with most structural decomposition methods of constraint satisfaction problems (CSPs). Within this framework, a CSP instance is decomposed into a number of sub-problems, called views,…

Artificial Intelligence · Computer Science 2017-11-15 Georg Gottlob , Gianlugi Greco , Francesco Scarcello

This study examines the time complexities of the unbalanced optimal transport problems from an algorithmic perspective for the first time. We reveal which problems in unbalanced optimal transport can/cannot be solved efficiently.…

Machine Learning · Computer Science 2021-01-11 Ryoma Sato , Makoto Yamada , Hisashi Kashima

We consider fixed-point equations for probability distributions on isometry classes of measured metric spaces. The construction is required to be recursive and tree-like, but we allow loops for the geodesics between points in the support of…

Probability · Mathematics 2022-04-25 Lucas Iziquel

We consider a high-dimensional random constrained optimization problem in which a set of binary variables is subjected to a linear system of equations. The cost function is a simple linear cost, measuring the Hamming distance with respect…

Disordered Systems and Neural Networks · Physics 2022-11-23 Alfredo Braunstein , Louise Budzynski , Stefano Crotti , Federico Ricci-Tersenghi