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Tensor networks provide succinct representations of quantum many-body states and are an important computational tool for strongly correlated quantum systems. Their expressive and computational power is characterized by an underlying…

The time evolution of a closed quantum system is connected to its Hamiltonian through Schroedinger's equation. The ability to estimate the Hamiltonian is critical to our understanding of quantum systems, and allows optimization of control.…

In this paper, we investigate whether Variational Principles can be associated with the Helmholtz equation subject to impedance (absorbing) boundary conditions. This model has been extensively studied in the literature from both…

Numerical Analysis · Mathematics 2025-11-18 G. Makrakis , C. Makridakis , D. Mitsoudis , M. Plexousakis , T. Pryer

Topological data analysis (TDA) approaches are becoming increasingly popular for studying the dependence patterns in multivariate time series data. In particular, various dependence patterns in brain networks may be linked to specific tasks…

Methodology · Statistics 2025-12-08 Anass El Yaagoubi Bourakna , Moo K. Chung , Hernando Ombao

We define a time-dependent extension of the quantum geometric tensor to describe the geometry of the time-parameter space for a quantum state, by considering small variations in both time and wave function parameters. Compared to the…

Quantum Physics · Physics 2025-02-05 Bogar Díaz , Diego Gonzalez , Marcos J. Hernández , J. David Vergara

The Kitaev honeycomb model is a paradigm of exactly-solvable models, showing non-trivial physical properties such as topological quantum order, abelian and non-abelian anyons, and chirality. Its solution is one of the most beautiful…

Strongly Correlated Electrons · Physics 2017-01-17 Philipp Schmoll , Roman Orus

The directional state transition tensor (DSTT) reduces the complexity of state transition tensor (STT) by aligning the STT terms in sensitive directions only, which provides comparable accuracy in orbital uncertainty propagation. The DSTT…

Instrumentation and Methods for Astrophysics · Physics 2024-12-11 Xingyu Zhou , Roberto Armellin , Dong Qiao , Xiangyu Li

This paper presents a computationally efficient robust model predictive control law for discrete linear time invariant systems subject to additive disturbances that may depend on the state and/or input norms. Despite the dependency being…

Optimization and Control · Mathematics 2019-08-12 Danylo Malyuta , Behcet Acikmese , Martin Cacan

The advantage of using a Discrete Variable Representation (DVR) is that the Hamiltonian of two interacting particles can be constructed in a very simple form. However the DVR Hamiltonian is approximate and, as a consequence, the results…

Atomic and Molecular Clusters · Physics 2016-09-08 M. Lombardi , P. Barletta , A. Kievsky

We study a class of time-dependent (TD) non-Hermitian Hamiltonians $H(t)$ that can be transformed into a time-independent pseudo-Hermitian Hamiltonian $\mathcal{H}_{0}^{PH}$ using a suitable TD unitary transformation $F(t)$. The latter can…

Quantum Physics · Physics 2025-10-06 F. Kecita , B. Khantoul , A. Bounames

Tree tensor network states (TTNS) decompose the system wavefunction to the product of low-rank tensors based on the tree topology, serving as the foundation of the multi-layer multi-configuration time-dependent Hartree (ML-MCTDH) method. In…

Quantum Physics · Physics 2024-08-29 Weitang Li , Jiajun Ren , Hengrui Yang , Haobin Wang , Zhigang Shuai

Tensor Networks (TN) offer a powerful framework to efficiently represent very high-dimensional objects. TN have recently shown their potential for machine learning applications and offer a unifying view of common tensor decomposition models…

Machine Learning · Computer Science 2021-06-24 Meraj Hashemizadeh , Michelle Liu , Jacob Miller , Guillaume Rabusseau

We describe a numerical many-body technique that is based on both tensor networks and quantum Monte Carlo. The variational ansatz is a tensor network that can harvest volume-law entanglement. It is constructed from a tensor train to which…

Strongly Correlated Electrons · Physics 2026-04-27 Miha Srdinsek , Gabriel Gouraud , Xavier Waintal

We consider the representation of operators in terms of tensor networks and their application to ground-state approximation and time evolution of systems with long-range interactions. We provide an explicit construction to represent an…

Quantum Physics · Physics 2010-07-20 F. Fröwis , V. Nebendahl , W. Dür

This paper presents a unifying theory of Linear second order systems that allows time-varying and time invariant systems to be treated in the same way for the first time. In the process, a transformation is given that diagonalizes an…

Systems and Control · Electrical Eng. & Systems 2026-04-24 Douglas R. Frey

Within the Projected Entangled Pair State (PEPS) tensor network formalism, a simple update (SU) method has been used to investigate the time evolution of a two-dimensional U(1) critical spin-1/2 spin liquid under Hamiltonian quench [Phys.…

Strongly Correlated Electrons · Physics 2023-10-11 Ravi Teja Ponnaganti , Matthieu Mambrini , Didier Poilblanc

We apply the multiconfigurational time-dependent Hartree method for indistinguishable particles (MCTDH-X) to systems of bosons or fermions in lattices described by Hubbard type Hamiltonians with long-range or short-range interparticle…

Quantum Gases · Physics 2016-07-27 Axel U. J. Lode , Christoph Bruder

An approximate method based on adiabatic time dependent density functional theory (TDDFT) is presented, that allows for the description of the electron dynamics in nanoscale junctions under arbitrary time dependent external potentials. In…

Mesoscale and Nanoscale Physics · Physics 2015-05-27 Y. Wang , C. -Y. Yam , G. H. Chen , Th. Frauenheim , T. A. Niehaus

In this work we show that the existence of a complete biorthonormal set of eigenvectors of the effective Hamiltonian governing the time evolution of neutral meson system is a necessary condition for diagonalizability of such a Hamiltonian.…

High Energy Physics - Phenomenology · Physics 2009-11-13 M. A. Gomshi Nobary , B. Mojaveri

Many real-world systems modeled using partial differential equations (PDEs) involve unknown parameters that must be estimated from limited, noisy system observations. While typically assumed to be constants, some of these unobserved…

Methodology · Statistics 2025-08-19 Andrea Arnold