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A simple and efficient method to treat nuclear pairing correlations within a simple Hartree-Fock--plus-BCS description is proposed and discussed. It relies on the fact that the intensity of pairing correlations depends crucially on level…

Nuclear Theory · Physics 2024-09-18 Meng-Hock Koh , Philippe Quentin

We develop ab-initio coupled-cluster theory to describe resonant and weakly bound states along the neutron drip line. We compute the ground states of the helium chain 3-10He within coupled-cluster theory in singles and doubles (CCSD)…

Nuclear Theory · Physics 2008-11-26 G. Hagen , D. J. Dean , M. Hjorth-Jensen , T. Papenbrock

Quantum-chemical calculations aimed at deriving magnetic coupling constants in exchange-coupled spin clusters commonly utilize a broken-symmetry (BS) approach. This involves calculating several distinct collinear spin configurations,…

Strongly Correlated Electrons · Physics 2023-10-23 Shadan Ghassemi Tabrizi

Within the framework of imaginary-time evolution for matrix product states, we introduce a cluster version of the infinite time-evolving block decimation algorithm for simulating quantum many-body systems, addressing the computational…

Strongly Correlated Electrons · Physics 2025-09-01 Tao Yang , Rui Wang , Z. Y. Xie , Baigeng Wang

We present a clustering method and provide a theoretical analysis and an explanation to a phenomenon encountered in the applied statistical literature since the 1990's. This phenomenon is the natural adaptability of the order when using a…

Statistics Theory · Mathematics 2022-03-23 Thierry Dumont

We investigate a clustering problem with data from a mixture of Gaussians that share a common but unknown, and potentially ill-conditioned, covariance matrix. We start by considering Gaussian mixtures with two equally-sized components and…

Machine Learning · Statistics 2021-11-30 Damek Davis , Mateo Díaz , Kaizheng Wang

We tabulate angularly reduced fourth-order many-body corrections to matrix elements for univalent atoms, derived in [A. Derevianko and E.D. Emmons, Phys. Rev. A 65, 052115 (2002)]. In particular we focused on practically important diagrams…

Atomic Physics · Physics 2007-05-23 Andrei Derevianko

We continue the investigation of problems concerning correlation clustering or clustering with qualitative information, which is a clustering formulation that has been studied recently. The basic setup here is that we are given as input a…

Data Structures and Algorithms · Computer Science 2007-05-23 Ioannis Giotis , Venkatesan Guruswami

We introduce a range-separation approximation to coupled cluster doubles (CCD) theory that successfully overcomes limitations of regular CCD when applied to the uniform electron gas. We combine the short-range ladder channel with the…

Chemical Physics · Physics 2014-05-07 James J. Shepherd , Thomas M. Henderson , Gustavo E. Scuseria

Consistency is a key property of all statistical procedures analyzing randomly sampled data. Surprisingly, despite decades of work, little is known about consistency of most clustering algorithms. In this paper we investigate consistency of…

Statistics Theory · Mathematics 2008-12-18 Ulrike von Luxburg , Mikhail Belkin , Olivier Bousquet

It is shown how to adapt the non-perturbative coupled cluster method of many-body theory so that it may be successfully applied to Hamiltonian lattice $SU(N)$ gauge theories. The procedure involves first writing the wavefunctions for the…

High Energy Physics - Lattice · Physics 2009-10-22 C. H. Llewellyn Smith , N. J. Watson

The paper outlines an exact combinatorial approach to finite coagulating systems. In this approach, cluster sizes and time are discrete, and the binary aggregation alone governs the time evolution of the systems. By considering the growth…

Statistical Mechanics · Physics 2018-02-21 Agata Fronczak , Anna Chmiel , Piotr Fronczak

We consider the problem of inferring an unknown number of clusters in replicated multinomial data. Under a model based clustering point of view, this task can be treated by estimating finite mixtures of multinomial distributions with or…

Methodology · Statistics 2023-07-07 Panagiotis Papastamoulis

This paper presents Constrained Centroid Clustering (CCC), a method that extends classical centroid-based clustering by enforcing a constraint on the maximum distance between the cluster center and the farthest point in the cluster. Using a…

Machine Learning · Computer Science 2025-08-19 Sowmini Devi Veeramachaneni , Ramamurthy Garimella

Exact thermal studies of small (4-site, 5-site and 8-site) Hubbard clusters with local electron repulsion yield intriguing insight into phase separation, charge-spin separation, pseudogaps, condensation, in particular, pairing fluctuations…

Strongly Correlated Electrons · Physics 2015-06-25 G. W. Fernando , A. N. Kocharian , K. Palandage , Tun Wang , J. W. Davenport

We consider the problem of grouping items into clusters based on few random pairwise comparisons between the items. We introduce three closely related algorithms for this task: a belief propagation algorithm approximating the Bayes optimal…

Social and Information Networks · Computer Science 2016-08-26 Alaa Saade , Marc Lelarge , Florent Krzakala , Lenka Zdeborová

Partially recorded data are frequently encountered in many applications and usually clustered by first removing incomplete cases or features with missing values, or by imputing missing values, followed by application of a clustering…

Methodology · Statistics 2021-10-20 Emily M. Goren , Ranjan Maitra

In order to extract informations on pairing correlations in nuclei from experimental mass differences, the different contributions to odd-even mass differences are investigated within the Skyrme HFB method. In this first paper, the…

Nuclear Theory · Physics 2009-11-07 T. Duguet , P. Bonche , P. -H. Heenen , J. Meyer

Quality assessments of models in unsupervised learning and clustering verification in particular have been a long-standing problem in the machine learning research. The lack of robust and universally applicable cluster validity scores often…

Machine Learning · Statistics 2018-03-30 Luzie Helfmann , Johannes von Lindheim , Mattes Mollenhauer , Ralf Banisch

We propose a novel approach to the problem of multilevel clustering, which aims to simultaneously partition data in each group and discover grouping patterns among groups in a potentially large hierarchically structured corpus of data. Our…

Machine Learning · Statistics 2021-05-26 Viet Huynh , Nhat Ho , Nhan Dam , XuanLong Nguyen , Mikhail Yurochkin , Hung Bui , and Dinh Phung