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The preparation of quantum Gibbs states at finite temperatures is a cornerstone of quantum computation, enabling applications in quantum simulation of many-body systems, machine learning via quantum Boltzmann machines, and optimization…

Quantum Physics · Physics 2026-04-17 Rui-Hao Li , Semeon Valgushev , Khadijeh Najafi

The calculation of free energies from first principles in materials is a formidable task which enables the prediction of phase stability with high accuracy; these calculations are complicated in magnetic materials by the interplay of…

Materials Science · Physics 2023-01-18 Davide Gambino , Johan Klarbring , Björn Alling

Choice of appropriate force field is one of the main concerns of any atomistic simulation that needs to be seriously considered in order to yield reliable results. Since, investigations on mechanical behavior of materials at micro/nanoscale…

Computational Physics · Physics 2016-07-12 Seyed Moein Rassoulinejad-Mousavi , Yijin Mao , Yuwen Zhang

We solve the Schr\"odinger equation with a position-dependent mass (PDM) charged particle interacted via the superposition of the Morse and Coulomb potentials and exposed to external magnetic and Aharonov-Bohm (AB) flux fields. The…

Quantum Physics · Physics 2017-05-10 Mahdi Eshghi , Hussein Mehraban , Sameer M. Ikhdair

There exists a geometric phase for a quantum state during the adiabatic evolution of the system. If the adiabatic procedure happens between the system and the environment interacting with it similar to Born-Oppenheimer (BO) approximation,…

Quantum Physics · Physics 2026-04-30 Zheng-Chuan Wang

We develop the variational-cluster-approximation method based on the thermal-pure-quantum-state approach and apply the method to the calculations of the thermodynamic properties of the Hubbard model, thereby obtaining the temperature…

Strongly Correlated Electrons · Physics 2020-02-19 Hisao Nishida , Ryo Fujiuchi , Koudai Sugimoto , Yukinori Ohta

We study the mixing time of a recently proposed efficiently implementable Lindbladian designed to prepare the Gibbs states in the setting of weakly interacting fermionic systems. We show that at any temperature, the Lindbladian spectral gap…

Quantum Physics · Physics 2025-01-22 Yu Tong , Yongtao Zhan

A multilevel approach to sample the potential energy surface in a path integral formalism is proposed. The purpose is to reduce the required number of ab initio evaluations of energy and forces in ab initio path integral molecular dynamics…

Computational Physics · Physics 2014-12-22 Hua Y. Geng

Finite-temperature calculations are relevant for rationalizing material properties yet they are computationally expensive because large system sizes or long simulation times are typically required. Circumventing the need for performing many…

We describe and test an implicit solvent all-atom potential for simulations of protein folding and aggregation. The potential is developed through studies of structural and thermodynamic properties of 17 peptides with diverse secondary…

Biomolecules · Quantitative Biology 2009-04-09 Anders Irbäck , Simon Mitternacht , Sandipan Mohanty

We consider a random Hamiltonian $H:\Sigma\to\mathbb R$ defined on a compact space $\Sigma$ that admits a transitive action by a compact group $\mathcal G$. When the law of $H$ is $\mathcal G$-invariant, we show its expected free energy…

Probability · Mathematics 2023-04-26 Mark Sellke

Predictions of relative stabilities of (competing) molecular crystals are of great technological relevance, most notably for the pharmaceutical industry. However, they present a long-standing challenge for modeling, as often minuscule free…

Materials Science · Physics 2022-05-25 Venkat Kapil , Edgar A Engel

We propose a way of obtaining effective low energy Hubbard-like model Hamiltonians from ab initio Quantum Monte Carlo calculations for molecular and extended systems. The Hamiltonian parameters are fit to best match the ab initio two-body…

Strongly Correlated Electrons · Physics 2015-08-06 Hitesh J. Changlani , Huihuo Zheng , Lucas K. Wagner

Systems with many interacting stochastic constituents are fully characterized by their free energy. Computing this quantity is therefore the objective of various approaches, notably perturbative expansions, which are applied in problems…

Statistical Mechanics · Physics 2026-04-08 Tobias Kühn

Simulation of warm dense matter requires computational methods that capture both quantum and classical behavior efficiently under high-temperature, high-density conditions. Currently, density functional theory molecular dynamics is used to…

Chemical Physics · Physics 2015-10-21 Attila Cangi , Aurora Pribram-Jones

We present a lattice Boltzmann algorithm based on an underlying free energy that allows the simulation of the dynamics of a multicomponent system with an arbitrary number of components. The thermodynamic properties, such as the chemical…

Soft Condensed Matter · Physics 2009-11-13 Qun Li , A. J. Wagner

We recently introduced a novel replica-exchange scheme in which an individual replica can sample from states encountered by other replicas at any previous time by way of a global configuration database, enabling the fast propagation of…

Computational Physics · Physics 2015-12-15 Thomas Vogel , Danny Perez

We propose a method to incorporate the coupling between shape and pairing collective degrees of freedom in the framework of the interacting boson model (IBM), based on the nuclear density functional theory. To account for pairing…

Nuclear Theory · Physics 2020-11-18 K. Nomura , D. Vretenar , Z. P. Li , J. Xiang

We use the two dimensional extended Hubbard Hamiltonian with the position of the attractive potential as a variable parameter with a BCS type approach to study the interplay between the superconductor transition temperature $T_c$ and hole…

Superconductivity · Physics 2007-05-23 E. V. L. de Mello

While traditional trial-and-error methods for designing amorphous alloys are costly and inefficient, machine learning approaches based solely on composition lack critical atomic structural information. Machine learning interatomic…

Materials Science · Physics 2025-08-19 Xuhe Gong , Hengbo Zhao , Xiao Fu , Jingchen Lian , Qifan Yang , Ran Li , Ruijuan Xiao , Tao Zhang , Hong Li
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