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Many materials properties depend on higher-order derivatives of the potential energy surface, yet machine learned interatomic potentials (MLIPs) trained with a standard loss on energy, force, and stress errors can exhibit error in…

Materials Science · Physics 2026-01-30 Teddy Koker , Abhijeet Gangan , Mit Kotak , Jaime Marian , Tess Smidt

The performance and scalability of superconducting quantum circuits are fundamentally constrained by non-equilibrium quasiparticles, which induce microwave losses that limit resonator quality factors and qubit coherence times. Understanding…

We build a comprehensive methodology for the fast computation of entropy across both solid and liquid phases. The proposed method utilizes a single trajectory of molecular dynamics (MD) to facilitate the calculation of entropy, which is…

Computational Physics · Physics 2024-04-05 Qi-Jun Hong , Zi-Kui Liu

In this work, we present a first-principles density functional theory (DFT) computational investigation of the luminescence and absorption lineshapes associated with the neutral carbon-oxygen interstitial pair (CiOi) defect in silicon. We…

The phonon thermal conductivity in diamond nanowires (DNW) is studied by molecular dynamics simulation. It is found that the thermal conductivity in narrower DNW is lower and does not show obvious temperature dependence; a very small value…

Materials Science · Physics 2011-08-31 Jin-Wu Jiang , Bing-Shen Wang , Jian-Sheng Wang

We present a numerical code to simulate maps of Galactic emission in intensity and polarization at microwave frequencies, aiding in the design of Cosmic Microwave Background experiments. This Python code builds on existing efforts to…

Cosmology and Nongalactic Astrophysics · Physics 2017-06-21 Ben Thorne , Jo Dunkley , David Alonso , Sigurd Naess

Machine-learning interatomic potentials are widely used as computationally efficient surrogates for density functional theory in atomistic simulations, enabling large-scale, long-time modeling of materials systems. We investigate how…

Materials Science · Physics 2026-04-13 Jonas Grandel , Philipp Benner , Janine George

Machine learning approaches have recently emerged as powerful tools to probe structure-property relationships in crystals and molecules. Specifically, Machine learning interatomic potentials (MLIP) can accurately reproduce first-principles…

Materials Science · Physics 2024-03-01 Sasaank Bandi , Chao Jiang , Chris A. Marianetti

The anharmonicity resulted from the intrinsic phonon interaction is neglected by quasiharmonic approximation. Although the intensive researches about anharmonicity have been done, up to now the free energy contributed by the anharmonicity…

Statistical Mechanics · Physics 2007-05-23 Zhongqing Wu , Renata M. Wentzcovitch

Raman spectra from silicon nanostructures, recorded using excitation laser power density of 1.0 kW/cm^2, is employed here to reveal the dominance of thermal effects at temperatures higher than the room temperature. Room temperature Raman…

Mesoscale and Nanoscale Physics · Physics 2012-01-25 Rajesh Kumar , Vivek Kumar , A. K. Shukla

The underlying dielectric properties of materials, intertwined with intriguing phenomena such as topological polariton modes and anisotropic thermal conductivities, stem from the anisotropy in atomic vibrations. Conventionally, X-ray…

At room temperature, low frequency vibrations at far-infrared frequencies are thermally excited ($k_B T > h \nu$) and not restricted to harmonic fluctuations around a single potential energy minimum. For folded proteins, these intrinsically…

Statistical Mechanics · Physics 2026-05-08 Michael A. Sauer , Souvik Mondal , Madeline Cano , Matthias Heyden

Parameter-free calculations of lattice dynamics from first principles have achieved significant progress in the past decades, with a wealth of applications in thermodynamics, phase transitions, and transport properties of materials. Current…

Materials Science · Physics 2025-08-05 Changpeng Lin , Jian Han , Ben Xu , Nicola Marzari

Fault-tolerant quantum computation demands extremely low logical error rates, yet superconducting qubit arrays are subject to radiation-induced correlated noise arising from cosmic-ray muon-generated quasiparticles. The quasiparticle…

In this work, we present a software package in Python for high-throughput first-principles calculations of thermodynamic properties at finite temperatures, which we refer to as DFTTK (Density Functional Theory Tool Kit). DFTTK is based on…

We present a new approach for the two-temperature molecular dynamics (MD) model for coupled simulations of electronic and phonon heat conduction in nanoscale systems. The proposed method uses a master equation to perform heat conduction of…

Computational Physics · Physics 2019-09-04 Mohammad W. Ullah , Mauricio Ponga

This paper presents a computational methodology for analyzing intonation and deriving tuning systems in microtonal oral traditions, utilizing pitch histograms, Dynamic Time Warping (DTW), and optimization techniques, with a case study on a…

Sound · Computer Science 2025-08-29 Sepideh Shafiei , Shapour Hakam

Molecular motion at metallic surfaces is affected by nonadiabatic effects and electron-phonon coupling. The ensuing energy dissipation and dynamical steering effects are not captured by classical molecular dynamics simulations, but can be…

Materials Science · Physics 2021-12-02 Connor L. Box , Wojciech G. Stark , Reinhard J. Maurer

Using molecular dynamics (MD) with classical interaction potentials we present calculations of thermal conductivity and heat transport in crystals and glasses. Inducing shock waves and heat pulses into the systems we study the spreading of…

Materials Science · Physics 2009-10-31 C. Oligschleger , J. C. Sch"on

We present a first-principles framework for the calculation of phonons in nanostructures with cyclic and/or helical symmetry. In particular, we derive a cyclic- and helical-symmetry-adapted representation of the dynamical matrix at…

Materials Science · Physics 2026-03-27 Abhiraj Sharma , Phanish Suryanarayana
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