activity
19982023
most citedAccelerating first-principles estimation of thermal conductivity by machine-learning interatomic potentials: A MTP/ShengBTE solution

224 citations · 654 across the 20 of their papers we have counts for

collaborators

22 papers

physics.comp-ph2023★ 3 cited

MLIP-3: Active learning on atomic environments with Moment Tensor Potentials

Evgeny Podryabinkin, Kamil Garifullin, Alexander Shapeev +1

Nowadays, academic research relies not only on sharing with the academic community the scientific results obtained by research groups while studying certain phenomena, but also on…

hep-ph2022★ 6 cited

The photon energy spectrum in at NLL

Bahman Dehnadi, Ivan Novikov, Frank J. Tackmann

We present predictions for the photon energy spectrum in inclusive decays mediated by the electromagnetic penguin operator to NLL. We use soft-collinear ef…

cond-mat.mtrl-sci2022★ 8 cited

AI-accelerated Materials Informatics Method for the Discovery of Ductile Alloys

Ivan Novikov, Olga Kovalyova, Alexander Shapeev +1

In computational materials science, a common means for predicting macroscopic (e.g., mechanical) properties of an alloy is to define a model using combinations of descriptors that…

hep-ph2022

xFitter: An Open Source QCD Analysis Framework. A resource and reference document for the Snowmass study

The xFitter Developers' Team, :, H. Abdolmaleki +21

We provide an overview of the xFitter open-source software package, review the general capabilities of the program, and highlight applications relevant to the Snowmass study. An up…

physics.chem-ph2022

Towards reliable calculations of thermal rate constants: ring polymer molecular dynamics for the OH + HBr Br + HO reaction

Ivan S. Novikov, Edgar M. Makarov, Alexander V. Shapeev +1

We combined Moment Tensor Potential (MTP) and Ring Polymer Molecular Dynamics (RPMD) for calculating the thermal rate constants of the OH + HBr system. We used the active learning…

physics.chem-ph2020

Assessing Parameters for Ring Polymer Molecular Dynamics Simulations at Low Temperatures: DH+H Chemical Reaction

Ivan S. Novikov, Yury V. Suleimanov, Alexander V. Shapeev

Ring polymer molecular dynamics (RPMD) is an accurate method for calculating thermal chemical reaction rates. It has recently been discovered that low-temperature calculations are…

physics.atom-ph2020★ 1 cited

Magnetic Moment Tensor Potentials for collinear spin-polarized materials reproduce different magnetic states of bcc Fe

Ivan Novikov, Blazej Grabowski, Fritz Kormann +1

We present the magnetic Moment Tensor Potentials (mMTPs), a class of machine-learning interatomic potentials, accurately reproducing both vibrational and magnetic degrees of freedo…

cond-mat.mtrl-sci2020★ 224 cited

Accelerating first-principles estimation of thermal conductivity by machine-learning interatomic potentials: A MTP/ShengBTE solution

Bohayra Mortazavi, Evgeny P. Podryabinkin, Ivan S. Nvikovb +3

Accurate evaluation of the thermal conductivity of a material can be a challenging task from both experimental and theoretical points of view. In particular for the nanostructured…

physics.comp-ph2020

The MLIP package: Moment Tensor Potentials with MPI and Active Learning

Ivan S. Novikov, Konstantin Gubaev, Evgeny V. Podryabinkin +1

The subject of this paper is the technology (the "how") of constructing machine-learning interatomic potentials, rather than science (the "what" and "why") of atomistic simulations…

cond-mat.mtrl-sci2020★ 156 cited

Exploring Phononic Properties of Two-Dimensional Materials using Machine Learning Interatomic Potentials

Bohayra Mortazavi, Ivan S. Novikov, Evgeny V. Podryabinkin +4

Phononic properties are commonly studied by calculating force constants using the density functional theory (DFT) simulations. Although DFT simulations offer accurate estimations o…

hep-ph2020★ 116 cited

Parton Distribution Functions of the Charged Pion Within The xFitter Framework

Ivan Novikov, Hamed Abdolmaleki, Daniel Britzger +9

We present the first open-source analysis of parton distribution functions (PDFs) of charged pions using xFitter, an open-source QCD fit framework to facilitate PDF extraction and…

physics.chem-ph2019★ 18 cited

Ring Polymer Molecular Dynamics and Active Learning of Moment Tensor Potential for Gas-Phase Barrierless Reactions: Application to S + H2

Ivan S. Novikov, Alexander V. Shapeev, Yury V. Suleimanov

Ring polymer molecular dynamics (RPMD) has proven to be an accurate approach for calculating thermal rate coefficients of various chemical reactions. For wider application of this…

hep-ph2019

Recent QCD results from the xFitter project: Probing the strange content of the proton with charm production in charged current at LHeC

xFitter Developers Team, Hamed Abdolmaleki, Valerio Bertone +11

We investigate charm production in charged-current deep-inelastic scattering (DIS) using the xFitter program. xFitter is an open-source software framework for the determination of…

hep-ph2019★ 5 cited

Forward-Backward Drell-Yan Asymmetry and PDF Determination

H Abdolmaleki, E Accomando, V Bertone +9

We investigate the impact of high-statistics Drell-Yan (DY) measurements at the LHC on the study of non-perturbative QCD effects from parton distribution functions (PDF). We presen…

hep-ph2019★ 21 cited

PDF Profiling Using the Forward-Backward Asymmetry in Neutral Current Drell-Yan Production

Elena Accomando, Juri Fiaschi, Francesco Hautmann +11

Non-perturbative QCD effects from Parton Distribution Functions (PDFs) may be constrained by using high-statistics Large Hadron Collider (LHC) data. Drell-Yan (DY) measurements in…

hep-ph2019

Probing the strange content of the proton with charm production in charged current at LHeC

xFitter Developers' team, :, Hamed Abdolmaleki +12

We study charm production in charged-current deep-inelastic scattering (DIS) using the xFitter framework. Recent results from the LHC have focused renewed attention on the determin…

physics.comp-ph2018

Improving accuracy of interatomic potentials: more physics or more data? A case study of silica

Ivan S. Novikov, Alexander V. Shapeev

In this paper we test two strategies to improving the accuracy of machine-learning potentials, namely adding more fitting parameters thus making use of large volumes of available q…

physics.chem-ph2018★ 47 cited

Automated Calculation of Thermal Rate Coefficients using Ring Polymer Molecular Dynamics and Machine-Learning Interatomic Potentials with Active Learning

Ivan S. Novikov, Yury V. Suleimanov, Alexander V. Shapeev

We propose a methodology for fully automated calculation of thermal rate coefficients of gas phase chemical reactions, which is based on combining the ring polymer molecular dynami…

nucl-th2013

Complete Glauber calculations of reaction and interaction cross sections in light ion collisions

I. S. Novikov, Yu. Shabelski

We calculate the differences between reaction and interaction cross sections in the collisions of relativistic light ions with in the framework of Glauber theory. Alt…

nucl-th2011★ 33 cited

Nuclear Radii of Unstable Nuclei

G. D. Alkhazov, I. S. Novikov, Yu. Shabelski

In the presented review we discuss the problem of extraction the parameters of nuclear matter and charge distribution in stable and unstable isotopes. A substantial amount of infor…

nucl-th2009★ 10 cited

Nuclear Radii Calculations in Various Theoretical Approaches for Nucleus-Nucleus Interactions

C. Merino, I. S. Novikov, Yu. M. Shabelski

The information about sizes and nuclear density distributions in unstable (radioactive) nuclei is usually extracted from the data on interaction of radioactive nuclear beams with a…

nucl-th1998★ 6 cited

P- and T-violation Tests with Polarized Resonance Neutrons

V. Bunakov, Y. Novikov

The enhancements of CP-violating effects in resonance neutron transmissionthrough polarized targets are studied for 2 possible versions of experiment. The importance is stressed of…