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Consider a compact metric space $(M, d_M)$ and $X = M^{\mathbb{N}}$. We prove a Ruelle's Perron Frobenius Theorem for a class of compact subshifts with Markovian structure introduced in [Bull. Braz. Math. Soc. 45 (2014), pp. 53-72] which…

Dynamical Systems · Mathematics 2021-11-12 Rafael Rigão Souza , Victor Vargas

If a quantum system interacts with the environment, then the Hamiltonian acquires a correction known as the Lamb-shift term. There are two other corrections to the Hamiltonian, related to the stationary state. Namely, the stationary state…

Quantum Physics · Physics 2025-01-28 Marcin Łobejko , Marek Winczewski , Gerardo Suárez , Robert Alicki , Michał Horodecki

A pedagogical approach for deriving the statistical mechanical partition function, in a manner that emphasizes the key role of entropy in connecting the microscopic states to thermodynamics, is introduced. The connections between the…

Statistical Mechanics · Physics 2013-09-10 Jonathan L. Belof , Brian Space

We show how the renormalization group approach can be used to prove quantitative central limit theorems (CLTs) in the setting of free, Boolean, bi-free and bi-Boolean independence under finite third moment assumptions. The proofs rely on…

Probability · Mathematics 2026-03-30 Jad Hamdan

Rains' bound is arguably the best known upper bound of the distillable entanglement by operations completely preserving positivity of partial transpose (PPT) and was conjectured to be additive and coincide with the asymptotic relative…

Quantum Physics · Physics 2017-06-28 Xin Wang , Runyao Duan

We show that classical density functional theory can be based on the constrained search method [M. Levy, Proc. Natl. Acad. Sci. 76, 6062 (1979)]. From the Gibbs inequality one first derives a variational principle for the grand potential as…

Statistical Mechanics · Physics 2011-04-21 Wipsar Sunu Brams Dwandaru , Matthias Schmidt

To investigate the consequences of component confinement such as at a glass transition and the well-known energy or enthalpy gap (between the glass and the perfect crystal at absolute zero, see text), we follow our previous approach [Phys.…

Statistical Mechanics · Physics 2015-03-17 P. D. Gujrati

We introduce a variational algorithm based on Matrix Product States that is trained by minimizing a generalized free energy defined using Tsallis entropy instead of the standard Gibbs entropy. As a result, our model can generate the…

Statistical Mechanics · Physics 2024-09-16 Pablo Díez-Valle , Fernando Martínez-García , Juan José García-Ripoll , Diego Porras

Quantum many-body states that frequently appear in physics often obey an entropy scaling law, meaning that an entanglement entropy of a subsystem can be expressed as a sum of terms that scale linearly with its volume and area, plus a…

Quantum Physics · Physics 2021-05-26 Isaac H. Kim

The aim of the present paper is to present a careful and accessible discussion of the formal aspects of Boltzmann-Gibbs and Tsallis entropies. We begin with a brief overview of Boltzmann-Gibbs entropy, highlighting its main properties and…

Statistical Mechanics · Physics 2025-10-23 Kelvin dos Santos Alves , Rogerio Teixeira Cavalcanti

In periodic structures such as photonic crystal (PhC) slabs, a bound state in the continuum (BIC) is always surrounded by resonant states with their $Q$-factor following $Q\sim 1/|{\bm \beta}-{\bm \beta}_*|^{2p}$, where ${\bm \beta}$ and…

Optics · Physics 2025-05-02 Nan Zhang , Ya Yan Lu

In this paper we apply the formalism of translation invariant (continuous) matrix product states in the thermodynamic limit to $(1+1)$ dimensional critical models. Finite bond dimension bounds the entanglement entropy and introduces an…

Quantum Physics · Physics 2015-06-18 Vid Stojevic , Jutho Haegeman , I. P. McCulloch , L. Tagliacozzo , Frank Verstraete

We prove a Bernstein-type bound for the difference between the average of negative log-likelihoods of independent discrete random variables and the Shannon entropy, both defined on a countably infinite alphabet. The result holds for the…

Information Theory · Computer Science 2021-06-24 Yunpeng Zhao

We study constrained reinforcement learning (CRL) from a novel perspective by setting constraints directly on state density functions, rather than the value functions considered by previous works. State density has a clear physical and…

Machine Learning · Computer Science 2021-06-25 Zengyi Qin , Yuxiao Chen , Chuchu Fan

We propose a compositional approach to synthesize policies for networks of continuous-space stochastic control systems with unknown dynamics using model-free reinforcement learning (RL). The approach is based on implicitly abstracting each…

Systems and Control · Electrical Eng. & Systems 2022-08-09 Abolfazl Lavaei , Mateo Perez , Milad Kazemi , Fabio Somenzi , Sadegh Soudjani , Ashutosh Trivedi , Majid Zamani

We analytically derive, in the context of the replica formalism, the first finite size corrections to the average optimal cost in the random assignment problem for a quite generic distribution law for the costs. We show that, when moving…

Disordered Systems and Neural Networks · Physics 2017-05-18 Sergio Caracciolo , Matteo P. D'Achille , Enrico M. Malatesta , Gabriele Sicuro

The marginal likelihood or evidence in Bayesian statistics contains an intrinsic penalty for larger model sizes and is a fundamental quantity in Bayesian model comparison. Over the past two decades, there has been steadily increasing…

Statistics Theory · Mathematics 2020-08-12 Anirban Bhattacharya , Debdeep Pati , Sean Plummer

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

Clinical decision-making often involves selecting tests that are costly, invasive, or time-consuming, motivating individualized, sequential strategies for what to measure and when to stop ascertaining. We study the problem of learning…

Machine Learning · Statistics 2026-04-16 Doudou Zhou , Yiran Zhang , Dian Jin , Yingye Zheng , Lu Tian , Tianxi Cai

We introduce a method to reconstruct an element of a Hilbert space in terms of an arbitrary finite collection of linearly independent reconstruction vectors, given a finite number of its samples with respect to any Riesz basis. As we…

Numerical Analysis · Mathematics 2010-12-01 Ben Adcock , Anders C. Hansen