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Adiabatic quantum computing (AQC) is a promising approach for discrete and often NP-hard optimization problems. Current AQCs allow to implement problems of research interest, which has sparked the development of quantum representations for…

Machine Learning · Computer Science 2024-05-02 Jan-Nico Zaech , Martin Danelljan , Tolga Birdal , Luc Van Gool

We consider a two-level system coupled to an environment that evolves non-adiabatically. We present a non-perturbative method for determining the persistence amplitude whose phase contains all the corrections to Berry's phase produced by…

Quantum Physics · Physics 2007-05-23 Frank Gaitan

We investigate the convergence of coupled-cluster correlation energies and related quantities with respect to the employed basis set size for the uniform electron gas to gain a better understanding of the basis set incompleteness error. To…

Materials Science · Physics 2024-02-27 Nikolaos Masios , Felix Hummel , Andreas Grüneis , Andreas Irmler

In this project we are interested in performing clustering of observations such that the cluster membership is influenced by a set of predictors. To that end, we employ the Bayesian nonparameteric Common Atoms Model, which is a nested…

Methodology · Statistics 2025-12-11 Md Yasin Ali Parh , Jeremy T. Gaskins

Dynamical decoupling is a key method to mitigate errors in a quantum mechanical system, and we studied it in a series of papers dealing in particular with the problems arising from unbounded Hamiltonians. The standard bangbang model of…

Mathematical Physics · Physics 2022-11-15 Daniel Burgarth , Paolo Facchi , Robin Hillier

We consider a dynamical system subjected to weak but adiabatically slow fluctuations of external origin. Based on the ``adiabatic following'' approximation we carry out an expansion in \alpha/|\mu|, where \alpha is the strength of…

Statistical Mechanics · Physics 2009-10-31 S. K. Banik , D. S. Ray

Designing stable cluster synchronization patterns is a fundamental challenge in nonlinear dynamics of networks with great relevance to understanding neuronal and brain dynamics. So far, cluster synchronization has been studied exclusively…

Adaptation and Self-Organizing Systems · Physics 2026-02-03 Ahmed A. A. Zaid , Ginestra Bianconi

We present an efficient implementation of analytical non-adiabatic derivative coupling elements for the coupled cluster singles and doubles model. The derivative coupling elements are evaluated in a biorthonormal formulation in which the…

Chemical Physics · Physics 2023-05-10 Eirik F. Kjønstad , Henrik Koch

In this paper, we introduce Adaptive Cluster Lasso(ACL) method for variable selection in high dimensional sparse regression models with strongly correlated variables. To handle correlated variables, the concept of clustering or grouping…

Machine Learning · Statistics 2016-03-14 Niharika Gauraha , Swapan K. Parui

We show that short-range correlations have a dramatic impact on the steady-state phase diagram of quantum driven-dissipative systems. This effect, never observed in equilibrium, follows from the fact that ordering in the steady state is of…

Statistical Mechanics · Physics 2016-07-29 Jiasen Jin , Alberto Biella , Oscar Viyuela , Leonardo Mazza , Jonathan Keeling , Rosario Fazio , Davide Rossini

The well known concept, to reduce the spatio-temporal dynamics beyond instabilities of trivial states to amplitude modulated patterns, is reviewed from the point of view of a formal perturbation expansion for general dissipative partial…

We present an effective linear response approach to pump-probe femtosecond coherence spectroscopy in the well separated pulse limit. The treatment presented here is based on a displaced and squeezed state representation for the…

Chemical Physics · Physics 2009-11-06 Anand T. N. Kumar , Florin Rosca , Allan Widom , Paul M. Champion

We investigate the possibility of obtaining chimera state solutions of the non-local Complex Ginzburg-Landau Equation (NLCGLE) in the strong coupling limit when it is important to retain amplitude variations. Our numerical studies reveal…

Pattern Formation and Solitons · Physics 2015-06-15 Gautam C Sethia , Abhijit Sen , George L. Johnston

We reveal limitations of several standard coupled-cluster (CC) methods with perturbation-theorybased noniterative or approximate iterative treatments of triple excitations when applied to thedetermination of highly accurate potential energy…

Chemical Physics · Physics 2021-10-04 Jan Schnabel , Lan Cheng , Andreas Köhn

The clustering coefficient quantifies the abundance of connected triangles in a network and is a major descriptive statistics of networks. For example, it finds an application in the assessment of small-worldness of brain networks, which is…

Physics and Society · Physics 2018-06-28 Naoki Masuda , Michiko Sakaki , Takahiro Ezaki , Takamitsu Watanabe

Discovering and clustering subspaces in high-dimensional data is a fundamental problem of machine learning with a wide range of applications in data mining, computer vision, and pattern recognition. Earlier methods divided the problem into…

Machine Learning · Statistics 2018-08-30 Maryam Jaberi , Marianna Pensky , Hassan Foroosh

We consider nonlinear recurrences generated from the iteration of maps that arise from cluster algebras. More precisely, starting from a skew-symmetric integer matrix, or its corresponding quiver, one can define a set of mutation…

Exactly Solvable and Integrable Systems · Physics 2011-09-23 Allan P. Fordy , Andrew Hone

An externally corrected coupled cluster (CC) method, where an adaptive configuration interaction (ACI) wave function provides the external cluster amplitudes, named ACI-CC, is presented. By exploiting the connection between configuration…

Chemical Physics · Physics 2023-09-27 Gustavo J. R. Aroeira , Madeline M. Davis , Justin M. Turney , Henry F. Schaefer

The quantization of the electronic two site system interacting with a vibration is considered by using as the integrable reference system the decoupled oscillators resulting from the adiabatic approximation. A specific Bloch projection…

chao-dyn · Physics 2009-10-28 Holger Schanz , Bernd Esser

In this work, we introduce a novel methodology for divisive hierarchical clustering. Our divisive (``top-down'') approach is motivated by the fact that agglomerative hierarchical clustering (``bottom-up''), which is commonly used for…

Methodology · Statistics 2025-10-07 Jan O. Bauer
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