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We consider a Brownian particle confined by an external potential and subject to stochastic resetting to the origin. Motivated by the repetitive nature of the dynamics, we describe the process as a thermodynamic cycle of thermal expansion…

Statistical Mechanics · Physics 2026-05-28 Oded Farago

A probabilistic framework for studying single-particle diffusion in partially absorbing media has recently been developed in terms of an encounter-based approach. The latter computes the joint probability density (generalized propagator)…

Statistical Mechanics · Physics 2022-10-12 Paul C Bressloff

In this paper, we show how the entropy (including the von Neumann entropy obtained by tracing across various sizes of subsystems, the entanglement gap, as well as different degrees of R\'{e}nyi entropy) of the random reduced density…

Quantum Physics · Physics 2022-11-17 Ruge Lin

The purpose of this work is to study some monotone functionals of the heat kernel on a complete Riemannian manifold with nonnegative Ricci curvature. In particular, we show that on these manifolds, the gradient estimate of Li and Yau, the…

Differential Geometry · Mathematics 2009-11-11 Fabrice Baudoin , Nicola Garofalo

This work studies the spectral convergence of graph Laplacian to the Laplace-Beltrami operator when the graph affinity matrix is constructed from $N$ random samples on a $d$-dimensional manifold embedded in a possibly high dimensional…

Statistics Theory · Mathematics 2025-09-16 Xiuyuan Cheng , Nan Wu

This paper investigates the relationship between categorical entropy and von Neumann entropy of quantum lattices. We begin by studying the von Neumann entropy, proving that the average von Neumann entropy per site converges to the logarithm…

Statistical Mechanics · Physics 2025-05-27 Haiqi Wu , Kai Xu

Numerical study of the one-dimensional Frenkel Hamiltonian with on-site randomness is carried out. We focus on the statistics of the energy levels near the lower exciton band edge, i. e. those determining optical response. We found that the…

Disordered Systems and Neural Networks · Physics 2009-11-07 Andrei V. Malyshev , Victor A. Malyshev

Poly-trees are singly connected causal networks in which variables may arise from multiple causes. This paper develops a method of recovering ply-trees from empirically measured probability distributions of pairs of variables. The method…

Artificial Intelligence · Computer Science 2013-04-11 George Rebane , Judea Pearl

We introduce a constructive framework for assigning thermodynamic structure to an arbitrary data system from its measured microstates. Starting from an empirical distribution over configurations, we first infer a data-driven energy function…

Statistical Mechanics · Physics 2026-04-29 George-Rafael Domenikos , Lock Yue Chew , Victoria Leong

We provide a prescription to construct R\'{e}nyi and von Neumann entropy of a system of interacting fermions from a knowledge of its correlation functions. We show that R\'{e}nyi entanglement entropy of interacting fermions in arbitrary…

Statistical Mechanics · Physics 2024-01-09 Saranyo Moitra , Rajdeep Sensarma

A spectral minimal partition of a manifold is its decomposition into disjoint open sets that minimizes a spectral energy functional. It is known that bipartite spectral minimal partitions coincide with nodal partitions of Courant-sharp…

Analysis of PDEs · Mathematics 2024-06-07 Gregory Berkolaiko , Yaiza Canzani , Graham Cox , Jeremy L. Marzuola

We address the problem of identifying the topology of an unknown weighted, directed network of LTI systems stimulated by wide-sense stationary noises of unknown power spectral densities. We propose several reconstruction algorithms based on…

Systems and Control · Computer Science 2013-08-13 Shahin Shahrampour , Victor M. Preciado

The classical matrix-tree theorem relates the determinant of the combinatorial Laplacian on a graph to the number of spanning trees. We generalize this result to Laplacians on one- and two-dimensional vector bundles, giving a combinatorial…

Probability · Mathematics 2011-12-09 Richard Kenyon

This thesis addresses two persistent and closely related challenges in modern deep learning, reliability and efficiency, through a unified framework grounded in Spectral Geometry and Random Matrix Theory (RMT). As deep networks and large…

Machine Learning · Computer Science 2026-02-27 Davide Ettori

Quantum entanglement plays a crucial role in quantum information, quantum teleportation and quantum computation. The information about the entanglement content between subsystems of the composite system is encoded in the Schmidt…

Statistical Mechanics · Physics 2013-05-07 Santosh Kumar , Akhilesh Pandey

Random forests are one of the most popular machine learning methods due to their accuracy and variable importance assessment. However, random forests only provide variable importance in a global sense. There is an increasing need for such…

Methodology · Statistics 2021-03-25 Joshua Daniel Loyal , Ruoqing Zhu , Yifan Cui , Xin Zhang

A novel approach for non-intrusive uncertainty propagation is proposed. Our approach overcomes the limitation of many traditional methods, such as generalised polynomial chaos methods, which may lack sufficient accuracy when the quantity of…

Numerical Analysis · Mathematics 2018-03-20 Yous van Halder , Benjamin Sanderse , Barry Koren

The meromorphic functional calculus developed in Part I overcomes the nondiagonalizability of linear operators that arises often in the temporal evolution of complex systems and is generic to the metadynamics of predicting their behavior.…

Chaotic Dynamics · Physics 2018-04-18 Paul M. Riechers , James P. Crutchfield

This paper investigates scaling symmetry in thermodynamics by unifying constrained Hamiltonian dynamics with symplectic and contact geometries. Through the mathematical processes of contactization and symplectization, we demonstrate that…

Mathematical Physics · Physics 2026-05-14 M. C. Baldiotti , R. Fresneda

Protein sequences are believed to have been selected to provide the stability of, and reliable renaturation to, an encoded unique spatial fold. In recently proposed theoretical schemes, this selection is modeled as ``minimal frustration,''…

Condensed Matter · Physics 2009-10-28 Vijay S. Pande , Alexander Yu. Grosberg , Toyoichi Tanaka
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