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We develop a maximum relative entropy formalism to generate optimal approximations to probability distributions. The central results consist in (a) justifying the use of relative entropy as the uniquely natural criterion to select a…

Statistical Mechanics · Physics 2008-10-17 Chih-Yuan Tseng , Ariel Caticha

For a positive integer $k$ and a graph $H$ on $k$ vertices, we are interested in the inducibility of $H$, denoted $\mathrm{ind}(H)$, which is defined as the maximum possible probability that choosing $k$ vertices uniformly at random from a…

Combinatorics · Mathematics 2024-11-27 Richard Ueltzen

We show that the existence of a homomorphism from an $n$-vertex graph $G$ to an $h$-vertex graph $H$ can be decided in time $2^{O(n)}h^{O(1)}$ and polynomial space if $H$ comes from a family of graphs that excludes a topological minor. The…

Computational Complexity · Computer Science 2026-02-27 Clément Carbonnel

A sofic approximation to a countable group is a sequence of partial actions on finite sets that asymptotically approximates the action of the group on itself by left-translations. A group is sofic if it admits a sofic approximation. Sofic…

Dynamical Systems · Mathematics 2021-08-18 Dylan Airey , Lewis Bowen , Frank Lin

We present a new approach for the approximate K-nearest neighbor search based on navigable small world graphs with controllable hierarchy (Hierarchical NSW, HNSW). The proposed solution is fully graph-based, without any need for additional…

Data Structures and Algorithms · Computer Science 2018-08-16 Yu. A. Malkov , D. A. Yashunin

The concept of independence entropy for symbolic dynamical systems was introduced in [LMP13]. This notion of entropy measures the extent to which one can freely insert symbols in positions without violating the constraints defined by the…

Dynamical Systems · Mathematics 2022-03-01 Bashir Abu Khalil

The hierarchy of pure states (HOPS) is a wavefunction-based method which can be used for numerically modeling open quantum systems. Formally, HOPS recovers the exact system dynamics for an infinite depth of the hierarchy. However,…

Chemical Physics · Physics 2018-04-18 P. -P. Zhang , C. D. B. Bentley , A. Eisfeld

Hypergraph neural networks (HGNN) have recently become attractive and received significant attention due to their excellent performance in various domains. However, most existing HGNNs rely on first-order approximations of hypergraph…

Artificial Intelligence · Computer Science 2024-01-11 Maolin Wang , Yaoming Zhen , Yu Pan , Yao Zhao , Chenyi Zhuang , Zenglin Xu , Ruocheng Guo , Xiangyu Zhao

We examine the phase behavior of a quasi-one-dimensional system of hard squares with side-length $\sigma$, where the particles are confined between two parallel walls and only nearest neighbor interactions occur. As in our previous work…

Statistical Mechanics · Physics 2017-05-03 Peter Gurin , Gerardo Odriozola , Szabolcs Varga

The unadjusted Langevin algorithm is widely used for sampling from complex high-dimensional distributions. It is well known to be biased, with the bias typically scaling linearly with the dimension when measured in squared Wasserstein…

Machine Learning · Statistics 2025-09-11 Daniel Lacker , Fuzhong Zhou

The square lattice with central forces between nearest neighbors is isostatic with a subextensive number of floppy modes. It can be made rigid by the random addition of next-nearest neighbor bonds. This constitutes a rigidity percolation…

Statistical Mechanics · Physics 2011-12-06 Wouter G. Ellenbroek , Xiaoming Mao

The entanglement entropy of a subsystem $A$ of a quantum system is expressed, in the replica method, through analytic continuation with respect to n of the trace of the n-th power of the reduced density matrix $\tr\rho_A^n$. We study the…

Statistical Mechanics · Physics 2010-03-25 F. Gliozzi , L. Tagliacozzo

We study the complexity of approximating complex zero sets of certain $n$-variate exponential sums. We show that the real part, $R$, of such a zero set can be approximated by the $(n-1)$-dimensional skeleton, $T$, of a polyhedral…

Algebraic Geometry · Mathematics 2021-04-22 Alperen Ergür , Grigoris Paouris , J. Maurice Rojas

We perform Transition matrix Monte Carlo simulations to evaluate the entropy of rhombus tilings with fixed polygonal boundaries and 2D-fold rotational symmetry. We estimate the large-size limit of this entropy for D=4 to 10. We confirm…

Statistical Mechanics · Physics 2009-11-11 Nicolas Destainville

In many high-impact applications, it is important to ensure the quality of output of a machine learning algorithm as well as its reliability in comparison with the complexity of the algorithm used. In this paper, we have initiated a…

Machine Learning · Computer Science 2023-03-03 Katarina Doctor , Tong Mao , Hrushikesh Mhaskar

For a given graph $G$, a "hopset" $H$ with hopbound $\beta$ and stretch $\alpha$ is a set of edges such that between every pair of vertices $u$ and $v$, there is a path with at most $\beta$ hops in $G \cup H$ that approximates the distance…

Data Structures and Algorithms · Computer Science 2025-05-08 Michael Dinitz , Ama Koranteng , Yasamin Nazari

We introduce a new class of countably infinite random geometric graphs, whose vertices are points in a metric space, and vertices are adjacent independently with probability p if the metric distance between the vertices is below a given…

Combinatorics · Mathematics 2012-08-28 Anthony Bonato , Jeannette Janssen

Uniform random intersection graphs have received much interest and been used in diverse applications. A uniform random intersection graph with $n$ nodes is constructed as follows: each node selects a set of $K_n$ different items uniformly…

Physics and Society · Physics 2015-02-03 Jun Zhao , Osman Yağan , Virgil Gligor

Universal logarithmic terms in the entanglement entropy appear at quantum critical points (QCPs) in one dimension (1D) and have been predicted in 2D at QCPs described by 2D conformal field theories. The entanglement entropy in a strip…

Strongly Correlated Electrons · Physics 2017-12-13 Michael P. Zaletel , Jens H. Bardarson , Joel E. Moore

The k-nearest neighbors (kNN) algorithm is a cornerstone of non-parametric classification in artificial intelligence, yet its deployment in large-scale applications is persistently constrained by the computational trade-off between…

Machine Learning · Computer Science 2026-01-26 Jiaye Li , Gang Chen , Hang Xu , Shichao Zhang
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