A. Cangi

发表

Effective electronic forces and potentials ab initio path integral Monte Carlo simulations

J. Vorberger, Z. Moldabekov, T. Dornheim, 2022, 2204.14260.

A Machine-Learning Surrogate Model for ab initio Electronic Correlations at Extreme Conditions

Z. Moldabekov, T. Dornheim, A. Cangi, 2021, 2104.02941.

Effective electronic forces and potentials from ab initio path integral Monte Carlo simulations

J. Vorberger, Z. Moldabekov, T. Dornheim, 2022, 2204.14260.

Reduced Density Matrix Functional Theory at Finite Temperature: Theoretical Foundations

E. Gross, A. Cangi, T. Baldsiefen, 2012, 1208.4703.

Exchange-correlation approximations for reduced-density-matrix-functional theory at finite temperature: Capturing magnetic phase transitions in the homogeneous electron gas

E. Gross, A. Cangi, F. Eich, 2017 .

A Scalable 5, 6-Qubit Grover's Quantum Search Algorithm

Dinesh Reddy Vemula, A. Cangi, Debanjan Konar, 2022, ArXiv.

An \textit{ab initio} study of shock-compressed copper

Albuquerque, H Germany, Helmholtz-Zentrum Dresden-Rossendorf, 2022, 2205.06638.

Accelerating Equilibration in First-Principles Molecular Dynamics with Orbital-Free Density Functional Theory

Xuecheng Shao, M. Pavanello, Z. Moldabekov, 2022, 2206.03754.

AtoMEC: an open-source average-atom Python code

A. Cangi, Timothy J Callow, D. Kotik, 2022, 2206.01074.

Dissociating the phononic, magnetic and electronic contributions to thermal conductivity: a computational study in alpha-iron

M. A. Wood, A. Cangi, K. Ramakrishna, 2022, Journal of Materials Science.

Ab initio study of shock-compressed copper

A. Baczewski, R. Redmer, B. Witte, 2022, Physical Review B.

Accelerating Finite-temperature Kohn-Sham Density Functional Theory with Deep Neural Networks

A. Thompson, S. Rajamanickam, N. Modine, 2020, Physical Review B.

Accelerating equilibration in first-principles molecular dynamics with orbital-free density functional theory

Xuecheng Shao, M. Pavanello, Z. Moldabekov, 2022, Physical Review Research.

Physics-Informed Neural Networks as Solvers for the Time-Dependent Schr\"odinger Equation

Nico Hoffmann, A. Cangi, Karan Shah, 2022, 2210.12522.

Predicting electronic structures at any length scale with machine learning

A. Thompson, S. Rajamanickam, N. Modine, 2022, 2210.11343.

Predicting electronic structures at any length scale with machine learning

A. Thompson, S. Rajamanickam, N. Modine, 2022, npj Computational Materials.

Electrical and Thermal Conductivity of High-Pressure Solid Iron

A. Baczewski, J. Vorberger, A. Cangi, 2022, 2210.10132.

atoMEC: An open-source average-atom Python code

A. Cangi, Timothy J Callow, D. Kotik, 2022, SciPy.

Improved calculations of mean ionization states with an average-atom model

A. Cangi, Timothy J Callow, E. Kraisler, 2022, 2203.05863.

First-principles derivation and properties of density-functional average-atom models

S. Hansen, A. Cangi, Timothy J Callow, 2021, Physical Review Research.

Electronic density response of warm dense matter

T. Preston, F. Graziani, T. Döppner, 2022, Physics of Plasmas.

Predicting the Electronic Structure of Matter on Ultra-Large Scales.

A. Thompson, S. Rajamanickam, N. Modine, 2022 .

Data-driven magneto-elastic predictions with scalable classical spin-lattice dynamics

M. Desjarlais, A. Thompson, M. Marinica, 2021, npj Computational Materials.

Electrical Conductivity of Iron in Earth's Core from Microscopic Ohm's Law

A. Baczewski, J. Vorberger, A. Cangi, 2022, 2203.06025.

First-principles modeling of plasmons in aluminum under ambient and extreme conditions

A. Baczewski, J. Vorberger, T. Dornheim, 2020, 2009.12163.

Data-driven magneto-elastic predictions with scalable classical spin-lattice dynamics

M. Desjarlais, A. Thompson, M. Marinica, 2021, npj Computational Materials.

Higher harmonics in complex plasmas with alternating screening

S. Sundar, Z. Moldabekov, A. Cangi, 2021, Physical Review Research.

Effective electronic forces and potentials from ab initio path integral Monte Carlo simulations.

J. Vorberger, Z. Moldabekov, T. Dornheim, 2022, The Journal of chemical physics.

Improving dynamic collision frequencies: Impacts on dynamic structure factors and stopping powers in warm dense matter

Astronomy, Control, H Germany, 2023, Physics of Plasmas.

Effective Static Approximation: A Fast and Reliable Tool for Warm-Dense Matter Theory.

J. Vorberger, T. Dornheim, M. Böhme, 2020, Physical review letters.

Improved calculations of mean ionization states with an average-atom model

A. Cangi, Timothy J Callow, E. Kraisler, 2022, Physical Review Research.

Temperature analysis of X-ray Thomson scattering data

T. Preston, J. Vorberger, D. Chapman, 2022, 2212.10510.

Dataset and scripts for A Deep Dive into Machine Learning Density Functional Theory for Materials Science and Chemistry

M. Bussmann, A. Cangi, L. Fiedler, 2021, 2110.00997.

Deep dive into machine learning density functional theory for materials science and chemistry

M. Bussmann, M. Bussmann, A. Cangi, 2022, Physical Review Materials.

Corrections to Thomas-Fermi densities at turning points and beyond.

K. Burke, P. Elliott, R. Ribeiro, 2014, Physical review letters.

Leading corrections to local approximations

K. Burke, P. Elliott, A. Cangi, 2010, 1002.1351.

Electrical conductivity of iron in Earth's core from microscopic Ohm's law

A. Baczewski, J. Vorberger, A. Cangi, 2022, Physical Review B.

Non-empirical Mixing Coefficient for Hybrid XC Functionals from Analysis of the XC Kernel

J. Vorberger, Z. Moldabekov, T. Dornheim, 2022, The journal of physical chemistry letters.

Assessing the accuracy of hybrid exchange-correlation functionals for the density response of warm dense electrons.

J. Vorberger, Z. Moldabekov, T. Dornheim, 2022, The Journal of chemical physics.

Thermal excitation signals in the inhomogeneous warm dense electron gas

Z. Moldabekov, T. Dornheim, A. Cangi, 2022, Scientific reports.

Towards a quantum fluid theory of correlated many-fermion systems from first principles

F. Graziani, M. Bonitz, G. Gregori, 2021, SciPost Physics.

The relevance of electronic perturbations in the warm dense electron gas.

J. Vorberger, Z. Moldabekov, T. Dornheim, 2021, The Journal of chemical physics.

The Quantum Bohm Potential for Many-Fermion Systems

F. Graziani, M. Bonitz, G. Gregori, 2021 .

Benchmarking exchange-correlation functionals in the spin-polarized inhomogeneous electron gas under warm dense conditions

J. Vorberger, Z. Moldabekov, T. Dornheim, 2021, Physical Review B.

Electronic structure via potential functional approximations.

Kieron Burke, E K U Gross, Peter Elliott, 2011, Physical review letters.

Semiclassical origins of density functionals.

Kieron Burke, Peter Elliott, Attila Cangi, 2008, Physical review letters.

Corrections to Thomas-Fermi densities at turning points and beyond.

Kieron Burke, Peter Elliott, Attila Cangi, 2014, Physical review letters.

Thermal Signals from Collective Electronic Excitations in Inhomogeneous Warm Dense Matter

Z. Moldabekov, T. Dornheim, A. Cangi, 2021, 2105.09721.

Transferable interatomic potential for aluminum from ambient conditions to warm dense matter

Surinder Kumar, S. Nikolov, M. Wood, 2023, Physical Review Research.

Random Quantum Neural Networks (RQNN) for Noisy Image Recognition

A. Cangi, Debanjan Konar, Aditya Das Sarma, 2022, ArXiv.

A shallow hybrid classical-quantum spiking feedforward neural network for noise-robust image classification

V. Aggarwal, S. Bhattacharyya, A. Cangi, 2023, Appl. Soft Comput..

Almost exact exchange at almost no computational cost in electronic structure

K. Burke, E. Gross, P. Elliott, 2015 .

Potential functionals versus density functionals

K. Burke, E. Gross, A. Cangi, 2013, 1307.4235.

Ab initio insights on the ultrafast strong-field dynamics of anatase TiO$_2$

M. Posselt, A. Sharan, Assa Aravindh Sasikala Devi, 2023, 2306.17554.

Machine learning the electronic structure of matter across temperatures

N. Modine, A. Cangi, L. Fiedler, 2023, 2306.06032.

Imaginary-time correlation function thermometry: A new, high-accuracy and model-free temperature analysis technique for x-ray Thomson scattering data

T. Preston, T. Döppner, N. Schlünzen, 2023, Physics of Plasmas.

Physics-enhanced neural networks for equation-of-state calculations

A. Cangi, Timothy J Callow, E. Kraisler, 2023, 2305.06856.

Training-free hyperparameter optimization of neural networks for electronic structures in matter

S. Rajamanickam, Vladyslav Oles, A. Cangi, 2022, Mach. Learn. Sci. Technol..

LDOS/SNAP data for MALA: Aluminium at 298K and 933K

A. Thompson, S. Rajamanickam, N. Modine, 2021 .

Electronic Structure Machine Learning Surrogates without Training

S. Rajamanickam, Vladyslav Oles, A. Cangi, 2022 .

Finding Machine-Learning Surrogates for Electronic Structures without Training

S. Rajamanickam, Vladyslav Oles, A. Cangi, 2022 .

Improving Predictive Capability in REHEDS Simulations with Fast, Accurate, and Consistent Non-Equilibrium Material Properties

K. Cochrane, T. Nagayama, A. Baczewski, 2022 .

Accurate and efficient computation of mean ionization states with an average-atom Kubo–Greenwood approach

A. Cangi, Timothy J Callow, E. Kraisler, 2022 .

Impact of electronic correlations on high-pressure iron: insights from time-dependent density functional theory

A. Baczewski, J. Vorberger, A. Cangi, 2022, Electronic Structure.

Deep dive into machine learning density functional theory for materials science and chemistry

M. Bussmann, A. Cangi, L. Fiedler, 2021, Physical Review Materials.

Deep Spiking Quantum Neural Network for Noisy Image Classification

V. Aggarwal, A. Cangi, Debanjan Konar, 2023, 2023 International Joint Conference on Neural Networks (IJCNN).

Machine learning the electronic structure of matter across temperatures

N. Modine, A. Cangi, Kyle D. Miller, 2023, Physical Review B.

Electrical and Thermal Conductivity of High-Pressure Solid Iron

A. Baczewski, J. Vorberger, A. Cangi, 2022 .

Inverting the Kohn–Sham equations with physics-informed machine learning

A. Cangi, Karan Shah, Vincent Martinetto, 2023, Machine Learning: Science and Technology.