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EPW is an open-source software for $\textit{ab initio}$ calculations of electron-phonon interactions and related materials properties. The code combines density functional perturbation theory and maximally-localized Wannier functions to…

We present a computational protocol, based on density matrix perturbation theory, to obtain non-adiabatic, frequency-dependent electron-phonon self-energies for molecules and solids. Our approach enables the evaluation of electron-phonon…

Materials Science · Physics 2023-05-09 Han Yang , Marco Govoni , Arpan Kundu , Giulia Galli

The electron-phonon coupling (EPC) is a ubiquitous interaction in condensed systems and plays a vital role in shaping the electronic properties of materials. Yet, achieving coherent manipulation of electron-phonon coupling has posed a…

Materials Science · Physics 2024-05-13 Jicai Zhang , Tien-Dat Tran , Ziwen Wang , Wenhao Yu , Chong Zhang , Marcus Lo , Wenqi Xu , Tran Trung Luu

The combinations of machine learning with ab initio methods have attracted much attention for their potential to resolve the accuracy-efficiency dilemma and facilitate calculations for large-scale systems. Recently, equivariant message…

Computational Physics · Physics 2025-09-08 Zhixin Liang , Yunlong Wang , Chi Ding , Junjie Wang , Hui-Tian Wang , Dingyu Xing , Jian Sun

Electron-phonon coupling (EPC) governs lattice dynamics, charge transport, and collective electronic phases in quantum materials. In several families of unconventional superconductors, including transition-metal dichalcogenides and kagome…

A method to evaluate the particle-phonon coupling (PC) corrections to the single-particle energies in semi-magic nuclei, based on a direct solving the Dyson equation with PC corrected mass operator, is used for finding the odd-even mass…

Nuclear Theory · Physics 2017-12-12 E. E. Saperstein , M. Baldo , S. S. Pankratov , S. V. Tolokonnikov

In this report, we present a deep learning framework termed the Electron Correlation Potential Neural Network (eCPNN) that can learn succinct and compact potential functions. These functions can effectively describe the complex…

Quantum Physics · Physics 2021-12-01 Hector H. Corzo , Arijit Sehanobish , Onur Kara

Electron-phonon interactions are of great importance to a variety of physical phenomena, and their accurate description is an important goal for first-principles calculations. Isolated examples of materials and molecular systems have…

Materials Science · Physics 2024-03-14 Antonios M. Alvertis , David B. Williams-Young , Fabien Bruneval , Jeffrey B. Neaton

We show an efficient way to compute the electron-phonon coupling constant, $\lambda$, and the superconducting transition temperature, Tc from first-principles calculations. This approach gives rapid convergence of Tc with respect to the…

Superconductivity · Physics 2017-10-11 Takashi Koretsune , Ryotaro Arita

We describe a coupled cluster framework for coupled systems of electrons and phonons. Neutral and charged excitations are accessed via the equation-of-motion version of the theory. Benchmarks on the Hubbard-Holstein model allow us to assess…

Materials Science · Physics 2021-02-03 Alec F. White , Yang Gao , Austin J. Minnich , Garnet Kin-Lic Chan

Using a computationally inexpensive frozen phonon approach we have developed a technique which can be used to screen large unit cell materials and systems for enhanced superconducting critical temperatures. The method requires only density…

Superconductivity · Physics 2024-05-07 Oliver A. Dicks , Kateryna Foyevtsova , Ilya Elfimov , Rohit Prasankumar , George Sawatzky

We investigate the ${\rm H_3S}$ phase of sulphur hydride under high pressure $\simeq$ 200 GPa by means of {\it ab-initio} calculations within the framework of the density-functional theory (DFT) with the PBE0 hybrid exchange-correlation…

Superconductivity · Physics 2015-11-30 Matej Komelj , Henry Krakauer

Despite the successes of machine learning methods in physical sciences, prediction of the Hamiltonian, and thus electronic properties, is still unsatisfactory. Here, based on graph neural network architecture, we present an extendable…

Materials Science · Physics 2023-01-12 Mao Su , Ji-Hui Yang , Hong-Jun Xiang , Xin-Gao Gong

Following the work in graphene, we report a first-principles study of electron-phonon coupling (EPC) in low-buckled (LB) monolayer silicene and germanene. Despite of the similar honeycomb atomic arrangement and linear band dispersion, the…

Mesoscale and Nanoscale Physics · Physics 2015-06-16 Jia-An Yan , Ryan Stein , David M. Schaefer , Xiao-Qian Wang , M. Y. Chou

EPW (Electron-Phonon coupling using Wannier functions) is a program written in FORTRAN90 for calculating the electron-phonon coupling in periodic systems using density-functional perturbation theory and maximally-localized Wannier…

Other Condensed Matter · Physics 2015-05-19 Jesse Noffsinger , Feliciano Giustino , Brad D. Malone , Cheol-Hwan Park , Steven G. Louie , Marvin L. Cohen

The account of electron correlation and its efficient separation into dynamic and nondynamic parts plays a key role in the development of computational methods. In this paper we suggest a physically-sound matrix formulation to split…

Chemical Physics · Physics 2016-08-16 Eloy Ramos-Cordoba , Pedro Salvador , Eduard Matito

We formulate an ab initio downfolding scheme for electron-phonon coupled systems. In this scheme, we calculate partially renormalized phonon frequencies and electron-phonon coupling, which include the screening effects of high-energy…

Strongly Correlated Electrons · Physics 2015-12-10 Yusuke Nomura , Ryotaro Arita

We have developed a first-principles method to calculate the electron-phonon coupling for specific modes and q-points in the Brillouin Zone for crystalline organic semiconductors. Using the obtained coupling strengths, we propose an…

We present a workflow of practical calculations of electron-phonon (e-ph) coupling with many-electron correlation effects included using the GW perturbation theory (GWPT). This workflow combines BerkeleyGW, ABINIT, and EPW software packages…

Materials Science · Physics 2024-09-20 Zhenglu Li , Gabriel Antonius , Yang-Hao Chan , Steven G. Louie

We present a workflow that iteratively combines \textit{ab-initio} calculations with a machine-learning (ML) guided search for superconducting compounds with both dynamical stability and instability from imaginary phonon modes, the latter…

Superconductivity · Physics 2026-03-09 Niraj K. Nepal , Lin-Lin Wang