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The product formula, commonly known as Trotter decomposition, is a central tool for digital quantum simulation, whose performance depends critically on how the Hamiltonian is partitioned into tractable blocks. Standard decompositions…

Quantum Physics · Physics 2026-05-18 Naoki Negishi , Bo Yang

The cluster-based Mean Field method (cMF) and it's second order perturbative correction[1], was introduced by Jim\'enez-Hoyos and Scuseria to reduce the cost of modeling strongly correlated systems by dividing an active space up into small…

Chemical Physics · Physics 2024-06-14 Arnab Bachhar , Nicholas J. Mayhall

Spinor structure and internal symmetries are considered within one theoretical framework based on the generalized spin and abstract Hilbert space. Complex momentum is understood as a generating kernel of the underlying spinor structure. It…

Mathematical Physics · Physics 2015-12-07 V. V. Varlamov

In this work, we report on a detailed simulation of the Bullet Cluster (1E0657-56) merger, including magnetohydrodynamics, plasma cooling, and adaptive mesh refinement. We constrain the simulation with data from gravitational lensing…

Cosmology and Nongalactic Astrophysics · Physics 2014-05-21 Craig Lage , Glennys Farrar

In this article we investigate a problem within Dempster-Shafer theory where 2**q - 1 pieces of evidence are clustered into q clusters by minimizing a metaconflict function, or equivalently, by minimizing the sum of weight of conflict over…

Artificial Intelligence · Computer Science 2007-05-23 Mats Bengtsson , Johan Schubert

A natural way to characterize the cluster structure of a dataset is by finding regions containing a high density of data. This can be done in a nonparametric way with a kernel density estimate, whose modes and hence clusters can be found…

Machine Learning · Computer Science 2015-03-03 Miguel Á. Carreira-Perpiñán

In this letter, we propose a novel tensor-based modulation scheme for massive unsourced random access. The proposed modulation can be deemed as a summation of third-order tensors, of which the factors are representatives of subspaces. A…

Signal Processing · Electrical Eng. & Systems 2021-12-07 Zhenting Luan , Yuchi Wu , Shansuo Liang , Liping Zhang , Wei Han , Bo Bai

We propose a sparse and low-rank tensor regression model to relate a univariate outcome to a feature tensor, in which each unit-rank tensor from the CP decomposition of the coefficient tensor is assumed to be sparse. This structure is both…

Machine Learning · Computer Science 2018-11-06 Lifang He , Kun Chen , Wanwan Xu , Jiayu Zhou , Fei Wang

Tensor networks and quantum computation are two of the most powerful tools for the simulation of quantum many-body systems. Rather than viewing them as competing approaches, here we consider how these two methods can work in tandem. We…

We study the shell and alpha cluster structures in the ground and excited states of 8Be in terms of the tensor-optimized shell model (TOSM). In TOSM, the tensor correlation is optimized in the full space of 2p2h configurations involving…

Nuclear Theory · Physics 2014-10-21 Takayuki Myo , Atsushi Umeya , Kaori Horii , Hiroshi Toki , Kiyomi Ikeda

The recent BICEP2 detection of degree scale CMB B-mode polarization, coupled with a deficit of observed power in large angle temperature anisotropy, suggest that the slow-roll parameter $\epsilon_H$, the fractional variation in the Hubble…

Cosmology and Nongalactic Astrophysics · Physics 2014-06-11 Wayne Hu

This paper presents a novel framework for tensor eigenvalue analysis in the context of multi-modal data fusion, leveraging topological invariants such as Betti numbers. Traditional approaches to tensor eigenvalue analysis often extend…

Machine Learning · Statistics 2025-05-29 Ronald Katende

We develop a systematic approach to deriving addition theorems for, and some other bilocal sums of, spin spherical harmonics. In this first part we establish some necessary technical results. We discuss the factorization of orbital and spin…

Mathematical Physics · Physics 2013-06-13 Antonio O. Bouzas

The integrated perturbation theory (iPT) is a set of methods in nonlinear perturbation theory for the structure formation in the Universe. In Papers I and II [arXiv:2210.10435, arXiv:2210.11085], the basic formalism and technical methods of…

Cosmology and Nongalactic Astrophysics · Physics 2024-09-23 Takahiko Matsubara

In this work we study the contribution of the isoscalar tensor coupling to the realization of pseudospin symmetry in nuclei. Using realistic values for the tensor coupling strength, we show that this coupling reduces noticeably the…

Nuclear Theory · Physics 2009-11-10 P. Alberto , R. Lisboa , M. Malheiro , A. S. de Castro

In the current era of vast data and transparent machine learning, it is essential for techniques to operate at a large scale while providing a clear mathematical comprehension of the internal workings of the method. Although there already…

Machine Learning · Statistics 2024-02-05 David Rügamer

Tensor factorization models are widely used in many applied fields such as chemometrics, psychometrics, computer vision or communication networks. Real life data collection is often subject to errors, resulting in missing data. Here we…

Signal Processing · Electrical Eng. & Systems 2022-03-23 Amaury Durand , François Roueff , Jean-Marc Jicquel , Nicolas Paul

A new method is introduced to study three-body clusters. Triangular configurations with ${\cal D}_{3h}$ point-group symmetry are analyzed. The spectrum, transition form factors and $B(E\lambda)$ values of $^{12}$C are investigated. It is…

Nuclear Theory · Physics 2009-11-07 R. Bijker , F. Iachello

Consensus clustering fuses diverse basic partitions (i.e., clustering results obtained from conventional clustering methods) into an integrated one, which has attracted increasing attention in both academic and industrial areas due to its…

Machine Learning · Computer Science 2019-06-04 Hongfu Liu , Zhiqiang Tao , Zhengming Ding

Monte Carlo sampling techniques have been proposed as a strategy to reduce the computational cost of contractions in tensor network approaches to solving many-body systems. Here we put forward a variational Monte Carlo approach for the…

Strongly Correlated Electrons · Physics 2012-05-01 Andrew J. Ferris , Guifre Vidal
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