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A new cluster analysis method, $K$-quantiles clustering, is introduced. $K$-quantiles clustering can be computed by a simple greedy algorithm in the style of the classical Lloyd's algorithm for $K$-means. It can be applied to large and…

Methodology · Statistics 2019-11-12 Christian Hennig , Cinzia Viroli , Laura Anderlucci

Bifurcation theory and continuation methods are well-established tools for the analysis of nonlinear mechanical systems subject to periodic forcing. We illustrate the added value and the complementary information provided by singularity…

Classical Physics · Physics 2017-03-08 G. I. Cirillo , G. Habib , G. Kerschen , R. Sepulchre

The randomized Kaczmarz (RK) method is an iterative method for approximating the least-squares solution of large linear systems of equations. The standard RK method uses sequential updates, making parallel computation difficult. Here, we…

Numerical Analysis · Mathematics 2020-02-12 Jacob D. Moorman , Thomas K. Tu , Denali Molitor , Deanna Needell

In this paper, some properties of resonances for multi-dimensional quantum walks are studied. Resonances for quantum walks are defined as eigenvalues of complex translated time evolution operators in the pseudo momentum space. For some…

Spectral Theory · Mathematics 2024-03-26 Kenta Higuchi , Hisashi Morioka

We obtain a class of parametric oscillation modes that we call K-modes with damping and absorption that are connected to the classical harmonic oscillator modes through the "supersymmetric" one-dimensional matrix procedure similar to…

Mathematical Physics · Physics 2009-11-10 H. C. Rosu , O. Cornejo-Perez , R. Lopez-Sandoval

We propose a variational scheme to represent composite quantum systems using multiple parameterized functions of varying accuracies on both classical and quantum hardware. The approach follows the variational principle over the entire…

Quantum Physics · Physics 2024-06-21 Stefano Barison , Filippo Vicentini , Giuseppe Carleo

J. Eells and L. Lemaire introduced k-harmonic maps, and Wang Shaobo showed the first variational formula. When, k=2, it is called biharmonic maps (2-harmonic maps). There have been extensive studies in the area. In this paper, We study…

Differential Geometry · Mathematics 2011-08-08 Shun Maeta

Scattering resonances play a crucial role in understanding wave behavior in various physical systems. While significant progress has been made in analyzing resonances in high-contrast and nonlinear media, a general characterization of…

Optics · Physics 2024-10-29 Taoufik Meklachi

We demonstrate the use of spatially encoded magnetic resonance to quantify ensemble dynamics of microscopic particles below the spatial resolution. By evaluating time series of k-space data-points, k-dependent motion patterns can be…

Instrumentation and Detectors · Physics 2018-05-16 Volker Herold , Thomas Kampf , Peter Michael Jakob

In this work, the possibility of clustering correlated random variables was examined, both because of their mutual similarity and because of their similarity to the principal components. The k-means algorithm and spectral algorithms were…

Machine Learning · Computer Science 2019-09-10 Zenon Gniazdowski , Dawid Kaliszewski

The importance of $S$-matrix unitarity in realistic meson spectroscopy is reviewed, both its historical development and more recent applications. First the effects of imposing $S$-matrix unitarity on meson resonances is demonstrated in both…

High Energy Physics - Phenomenology · Physics 2021-06-10 Eef van Beveren , George Rupp

In a standard cluster analysis, such as k-means, in addition to clusters locations and distances between them, it's important to know if they are connected or well separated from each other. The main focus of this paper is discovering the…

Machine Learning · Statistics 2017-05-22 Evgeny Bauman , Konstantin Bauman

This paper reviews Kunchenko's polynomials using as template matching method to recognize template in one-dimensional input signal. Kunchenko's polynomials method is compared with classical methods - cross-correlation and sum of squared…

Computer Vision and Pattern Recognition · Computer Science 2011-07-12 Oleg Chertov , Taras Slipets

Experimental observation of the decoherence of macroscopic objects is of fundamental importance to the study of quantum collapse models and the quantum to classical transition. Optomechanics is a promising field for the study of such models…

Quantum Physics · Physics 2018-06-20 Matthew J. Weaver , David Newsom , Fernando Luna , Wolfgang Löffler , Dirk Bouwmeester

This work focuses on the limitations about the insufficient fitting capability of current quantum machine learning methods, which results from the over-reliance on a single data embedding strategy. We propose a novel quantum machine…

Quantum Physics · Physics 2025-04-01 Siyu Han , Lihan Jia , Lanzhe Guo

Random unitaries are an important resource for quantum information processing. While their universal properties have been thoroughly analyzed, it is not known what happens to these properties when the unitaries are sampled on the…

Quantum Physics · Physics 2025-07-16 Kristian Wold , Pedro Ribeiro , Sergey Denisov

We verify a conjecture on the structure of higher-rank numerical ranges for a wide class of unitary and normal matrices. Using analytic and geometric techniques, we show precisely how the higher-rank numerical ranges for a generic unitary…

Quantum Physics · Physics 2008-06-11 Man-Duen Choi , John A. Holbrook , David W. Kribs , Karol Zyczkowski

We study a quantum-mechanical system of three particles in a one-dimensional box with two-particle harmonic interactions. The symmetry of the system is described by the point group $D_{3d}$. Group theory greatly facilitates the application…

Mathematical Physics · Physics 2015-04-09 Paolo Amore , Francisco M. Fernández

We show that the method of distributed noise-shaping beta-quantization offers superior performance for the problem of spectral super-resolution with quantization whenever there is redundancy in the number of measurements. More precisely, if…

Information Theory · Computer Science 2019-05-06 C. Sinan Güntürk , Weilin Li

A limitation of many clustering algorithms is the requirement to tune adjustable parameters for each application or even for each dataset. Some techniques require an \emph{a priori} estimate of the number of clusters while density-based…

Methodology · Statistics 2016-05-20 Jeremy F. Magland , Alex H. Barnett
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