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Quantum graphs without interaction which contain equilateral cycles possess "topological" bound states which do not correspond to zeroes of one of the two variants of the secular equation for quantum graphs. Instead, their eigenvalues lie…

Spectral Theory · Mathematics 2024-05-01 Evans M. Harrell , Anna V. Maltsev

Gibbs sampling methods are standard tools to perform posterior inference for mixture models. These have been broadly classified into two categories: marginal and conditional methods. While conditional samplers are more widely applicable…

Methodology · Statistics 2023-02-21 Pierpaolo De Blasi , María F. Gil-Leyva

We develop a novel method to separate the components of a diffuse emission process based on an association with the energy spectra. Most of the existing methods use some information about the spatial distribution of components, e.g.,…

Instrumentation and Methods for Astrophysics · Physics 2012-02-07 Dmitry Malyshev

Introduced in 1963, Glauber dynamics is one of the most practiced and extensively studied methods for sampling the Ising model on lattices. It is well known that at high temperatures, the time it takes this chain to mix in $L^1$ on a system…

Probability · Mathematics 2015-05-14 Eyal Lubetzky , Allan Sly

Studying independent sets of maximum size is equivalent to considering the hard-core model with the fugacity parameter $\lambda$ tending to infinity. Finding the independence ratio of random $d$-regular graphs for some fixed degree $d$ has…

Combinatorics · Mathematics 2023-02-15 Viktor Harangi

We introduce efficient algorithms for approximate sampling from symmetric Gibbs distributions on the sparse random (hyper)graph. The examples we consider include (but are not restricted to) important distributions on spin systems and…

Discrete Mathematics · Computer Science 2024-03-20 Charilaos Efthymiou

The topology transition problem of transmission networks is becoming increasingly crucial with topological flexibility more widely leveraged to promote high renewable penetration. This paper proposes a novel methodology to address this…

Systems and Control · Electrical Eng. & Systems 2022-09-20 Tong Han , Yue Song , David J. Hill

Gibbs sampling is a common procedure used to fit finite mixture models. However, it is known to be slow to converge when exploring correlated regions of a parameter space and so blocking correlated parameters is sometimes implemented in…

Statistics Theory · Mathematics 2024-11-04 David Michael Swanson

We consider Ising models on the hypercube with a general interaction matrix $J$, and give a polynomial time sampling algorithm when all but $O(1)$ eigenvalues of $J$ lie in an interval of length one, a situation which occurs in many models…

Data Structures and Algorithms · Computer Science 2022-02-21 Frederic Koehler , Holden Lee , Andrej Risteski

The Finite Difference (FD) and the Spectral Boundary Integral (SBI) methods have been used extensively to model spontaneously propagating shear cracks in a variety of engineering and geophysical applications. In this paper, we propose a new…

Geophysics · Physics 2017-08-09 Setare Hajaroalsvadi , Ahmed Elbanna

Recently, a one-to-one correspondence between non-trivial non-Hermitian topology and directional amplification has been demonstrated, theoretically and experimentally, for the case of one complex band. Here, we extend our framework to…

Mesoscale and Nanoscale Physics · Physics 2025-09-25 Clara C. Wanjura , Andreas Nunnenkamp

Gibbs samplers are preeminent Markov chain Monte Carlo algorithms used in computational physics and statistical computing. Yet, their most fundamental properties, such as relations between convergence characteristics of their various…

Computation · Statistics 2024-07-11 Iwona Chlebicka , Krzysztof Łatuszyński , Błażej Miasojedow

We study the statistical distribution of the closest encounter between generic smooth observations computed along different trajectories of a rapidly mixing dynamical system. At the limit of large trajectories, we obtain a distribution of…

Chaotic Dynamics · Physics 2022-08-31 Theophile Caby

Electromagnetic waves propagating, at finite speeds, in conventional wave-guiding structures are reflected by discontinuities and decay in lossy regions. In this Letter, we drastically modify this typical guided-wave behavior by combining…

Optics · Physics 2018-09-12 S. Ali Hassani Gangaraj , Francesco Monticone

We study the local geometry of empirical risks in high dimensions via the spectral theory of their Hessian and information matrices. We focus on settings where the data, $(Y_\ell)_{\ell =1}^n \in \mathbb{R}^d$, are i.i.d. draws of a…

Statistics Theory · Mathematics 2026-01-23 Gerard Ben Arous , Reza Gheissari , Jiaoyang Huang , Aukosh Jagannath

High dimensional random dynamical systems are ubiquitous, including -- but not limited to -- cyber-physical systems, daily return on different stocks of S&P 1500 and velocity profile of interacting particle systems around McKeanVlasov…

Statistics Theory · Mathematics 2023-10-17 Muhammad Abdullah Naeem , Amir Khazraei , Miroslav Pajic

The central goal of this thesis is to develop methods to experimentally study topological phases. We do so by applying the powerful toolbox of quantum simulation techniques with cold atoms in optical lattices. To this day, a complete…

Quantum Gases · Physics 2017-09-26 Samuel Mugel

We formulate a continuous version of the well known discrete hardcore (or independent set) model on a locally finite graph, parameterized by the so-called activity parameter $\lambda > 0$. In this version, the state or "spin value" $x_u$ of…

Probability · Mathematics 2017-08-16 David Gamarnik , Kavita Ramanan

The Gumbel trick is a method to sample from a discrete probability distribution, or to estimate its normalizing partition function. The method relies on repeatedly applying a random perturbation to the distribution in a particular way, each…

Machine Learning · Statistics 2017-06-14 Matej Balog , Nilesh Tripuraneni , Zoubin Ghahramani , Adrian Weller

We investigate how the topology of attributed graphs influences the distribution of node attributes. This work offers a novel perspective by treating topology and attributes as structurally distinct but interacting components. We introduce…

Machine Learning · Computer Science 2026-02-03 Amirreza Shiralinasab Langari , Leila Yeganeh , Kim Khoa Nguyen
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