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In this brief paper, we go through the theoretical steps of the spectral clustering on quantum computers by employing the phase estimation and the amplitude amplification algorithms. We discuss circuit designs for each step and show how to…

Quantum Physics · Physics 2017-07-24 Ammar Daskin

Monte Carlo methods play an important role in scientific computation, especially when problems have a vast phase space. In this lecture an introduction to the Monte Carlo method is given. Concepts such as Markov chains, detailed balance,…

Statistical Mechanics · Physics 2011-05-05 Helmut G. Katzgraber

In sensor networks, it is not always practical to set up a fusion center. Therefore, there is need for fully decentralized clustering algorithms. Decentralized clustering algorithms should minimize the amount of data exchanged between…

Machine Learning · Statistics 2018-07-13 Elsa Dupraz , Dominique Pastor , François-Xavier Socheleau

We introduce a hybrid quantum-classical variational algorithm to simulate ground-state phase diagrams of frustrated quantum spin models in the thermodynamic limit. The method is based on a cluster-Gutzwiller ansatz where the wave function…

Quantum Physics · Physics 2022-12-14 Daniel Huerga

Transformers have been proven a successful model for a variety of tasks in sequence modeling. However, computing the attention matrix, which is their key component, has quadratic complexity with respect to the sequence length, thus making…

Machine Learning · Computer Science 2020-10-01 Apoorv Vyas , Angelos Katharopoulos , François Fleuret

We study the problem of clustering $T$ trajectories of length $H$, each generated by one of K unknown ergodic Markov chains over a finite state space of size $S$. We derive an instance-dependent, high-probability lower bound on the…

Machine Learning · Statistics 2026-03-18 Junghyun Lee , Yassir Jedra , Alexandre Proutière , Se-Young Yun

In this contribution, the clustering procedure based on K-Means algorithm is studied as an inverse problem, which is a special case of the illposed problems. The attempts to improve the quality of the clustering inverse problem drive to…

Numerical Analysis · Mathematics 2022-11-16 Alberto Arturo Vergani

We present an optimized version of a cluster labeling algorithm previously introduced by the authors. This algorithm is well suited for large-scale Monte Carlo simulations of spin models using cluster dynamics on parallel computers with…

High Energy Physics - Lattice · Physics 2015-06-25 M. Flanigan , P. Tamayo

We propose a high-order stochastic-statistical moment closure model for efficient ensemble prediction of leading-order statistical moments and probability density functions in multiscale complex turbulent systems. The statistical moment…

Numerical Analysis · Mathematics 2023-06-21 Di Qi , Jian-Guo Liu

We investigate the critical behavior of the two-dimensional spin-$1$ Baxter-Wu model in the presence of a crystal-field coupling $\Delta$ with the goal of determining the universality class of transitions along the second-order part of the…

Statistical Mechanics · Physics 2023-08-28 A. R. S. Macedo , A. Vasilopoulos , M. Akritidis , J. A. Plascak , N. G. Fytas , M. Weigel

Clustering analysis by nonnegative low-rank approximations has achieved remarkable progress in the past decade. However, most approximation approaches in this direction are still restricted to matrix factorization. We propose a new low-rank…

Machine Learning · Computer Science 2012-06-22 Zhirong Yang , Erkki Oja

This paper proposes a model reduction approach for simplifying the interconnection topology of Lur'e network systems. A class of reduced-order models are generated by the projection framework based on graph clustering, which not only…

Systems and Control · Electrical Eng. & Systems 2024-07-03 Yangming Dou , Xiaodong Cheng , Jacquelien M. A. Scherpen

Clustering is one of the widely used techniques to find out patterns from a dataset that can be applied in different applications or analyses. K-means, the most popular and simple clustering algorithm, might get trapped into local minima if…

Machine Learning · Computer Science 2022-10-19 Zillur Rahman , Md. Sabir Hossain , Mohammad Hasan , Ahmed Imteaj

Cluster variation method (CVM) and path probability method (PPM) have generally been employed to study replacive phase transitions in alloy systems. Recently, displacive phase transitions have been explored within the realm of replacive…

Materials Science · Physics 2019-07-24 Ryo Yamada , Tetsuo Mohri

An efficiency of the Tucker decomposition of amplitude tensors within the single-reference relativistic coupled cluster method with single and double excitations (RCCSD) was studied in a series of benchmark calculations for (AuCl)$_n$…

Computational Physics · Physics 2025-07-29 Alexander V. Oleynichenko , Artem S. Rumiantsev , Andrei Zaitsevskii , Ephraim Eliav

In recent years, a better understanding of the Monte Carlo method has provided us with many new techniques in different areas of statistical physics. Of particular interest are so called cluster methods, which exploit the considerable…

Statistical Mechanics · Physics 2007-05-23 Werner Krauth

A Monte Carlo algorithm is proposed to simulate ferromagnetic q-state Potts model for any real q>0. A single update is a random sequence of disordering and deterministic moves, one for each link of the lattice. A disordering move attributes…

Statistical Mechanics · Physics 2008-12-18 Ferdinando Gliozzi

The effects of bond randomness on the phase diagram and critical behavior of the square lattice ferromagnetic Blume-Capel model are discussed. The system is studied in both the pure and disordered versions by the same efficient two-stage…

Statistical Mechanics · Physics 2015-05-14 A. Malakis , A. Nihat Berker , I. A. Hadjiagapiou , N. G. Fytas , T. Papakonstantinou

We present the loop algorithm, a new type of cluster algorithm that we recently introduced for the F model. Using the framework of Kandel and Domany, we show how to GENERALIZE the algorithm to the arrow flip symmetric 6 vertex model. We…

High Energy Physics - Lattice · Physics 2007-05-23 H. G. Evertz , M. Marcu

The frustrated Ising model in two dimensions is revisited. The frustration is quantified in terms of the number of non-trivial plaquettes which is invariant under the Nishimori gauge symmetry. The exact ground state energy is calculated…

High Energy Physics - Lattice · Physics 2007-05-23 K. Langfeld , M. Quandt , W. Lutz , H. Reinhardt