Results 51 to 60 of about 2,318,291 (294)

Quantum simulation of quantum field theories as quantum chemistry

Journal of High Energy Physics, 2020
Conformal truncation is a powerful numerical method for solving generic strongly-coupled quantum field theories based on purely field-theoretic technics without introducing lattice regularization.
Junyu Liu, Yuan Xin
doaj   +1 more source

Quantum Chemistry Common Driver and Databases (QCDB) and Quantum Chemistry Engine (QCEngine): Automation and interoperability among computational chemistry programs.

Journal of Chemical Physics, 2021
Community efforts in the computational molecular sciences (CMS) are evolving toward modular, open, and interoperable interfaces that work with existing community codes to provide more functionality and composability than could be achieved with a single ...
Daniel G. A. Smith, Annabelle T. Lolinco, Zachary L. Glick, Jiyoung Lee, Asem Alenaizan, Taylor A. Barnes, C. Borca, Roberto Di Remigio, David L. Dotson, S. Ehlert, Alexander G. Heide, Michael F. Herbst, J. Hermann, Colton B Hicks, Joshua T. Horton, Adrian G. Hurtado, P. Kraus, H. Kruse, Sebastian J. R. Lee, J. Misiewicz, Levi N. Naden, F. Ramezanghorbani, Maximilian Scheurer, Jeffrey B. Schriber, Andrew C. Simmonett, J. Steinmetzer, J Wagner, Logan T. Ward, Matthew Welborn, Doaa Altarawy, J. Anwar, J. Chodera, A. Dreuw, Heather J. Kulik, F. Liu, T. Martínez, D. Matthews, H. Schaefer, J. Šponer, J. Turney, Lee‐Ping Wang, N. D. De Silva, R. King, J. Stanton, M. Gordon, T. Windus, C. Sherrill, L. Burns   +47 more
semanticscholar   +1 more source

Psi4 1.4: Open-source software for high-throughput quantum chemistry.

Journal of Chemical Physics, 2020
PSI4 is a free and open-source ab initio electronic structure program providing implementations of Hartree-Fock, density functional theory, many-body perturbation theory, configuration interaction, density cumulant theory, symmetry-adapted perturbation ...
Daniel G. A. Smith, L. Burns, Andrew C. Simmonett, R. Parrish, M. Schieber, Raimondas Galvelis, P. Kraus, H. Kruse, Roberto Di Remigio, Asem Alenaizan, Andrew James, S. Lehtola, J. Misiewicz, Maximilian Scheurer, R. Shaw, Jeffrey B. Schriber, Yi Xie, Zachary L. Glick, Dominic A Sirianni, J. O'Brien, Jonathan M. Waldrop, Ashutosh Kumar, E. Hohenstein, Benjamin P. Pritchard, B. Brooks, H. Schaefer, A. Sokolov, K. Patkowski, Eugene DePrince, U. Bozkaya, R. King, Francesco A. Evangelista, J. Turney, T. Daniel Crawford, David Sherrill   +34 more
semanticscholar   +1 more source

The Limits of Classical Extensional Mereology for the Formalization of Whole–Parts Relations in Quantum Chemical Systems

Philosophies, 2020
This paper examines whether classical extensional mereology is adequate for formalizing the whole–parts relation in quantum chemical systems. Although other philosophers have argued that classical extensional and summative mereology does not adequately ...
Marina Paola Banchetti-Robino
doaj   +1 more source

Colorectal cancer‐derived FGF19 is a metabolically active serum biomarker that exerts enteroendocrine effects on mouse liver

Molecular Oncology, EarlyView.
Meta‐transcriptome analysis identified FGF19 as a peptide enteroendocrine hormone associated with colorectal cancer prognosis. In vivo xenograft models showed release of FGF19 into the blood at levels that correlated with tumor volumes. Tumoral‐FGF19 altered murine liver metabolism through FGFR4, thereby reducing bile acid synthesis and increasing ...
Jordan M. Beardsley, Michael W. Rohr, Joseph A. Goode, Sai Preethi Nakkina, Jignesh G. Parikh, Deborah A. Altomare   +5 more
wiley   +1 more source

Advances in molecular quantum chemistry contained in the Q-Chem 4 program package

Molecular Physics, 2014
A summary of the technical advances that are incorporated in the fourth major release of the Q-Chem quantum chemistry program is provided, covering approximately the last seven years.
Y. Shao, Zhengting Gan, E. Epifanovsky, A. Gilbert, M. Wormit, Joerg Kussmann, A. Lange, Andrew Behn, Jia Deng, Xintian Feng, Debashree Ghosh, Matthew B Goldey, P. Horn, Leif D Jacobson, I. Kaliman, Rustam Z. Khaliullin, T. Kus, A. Landau, Jie Liu, E. Proynov, Young Min Rhee, R. M. Richard, M. A. Rohrdanz, R. P. Steele, E. Sundstrom, H. Woodcock, P. Zimmerman, D. Zuev, Benjamin J. Albrecht, Ethan C Alguire, Brian Austin, G. Beran, Yves A. Bernard, E. Berquist, Kai Brandhorst, K. Bravaya, Shawn T. Brown, D. Casanova, Chun-Min Chang, Yunqing Chen, S. Chien, K. D. Closser, D. Crittenden, M. Diedenhofen, R. Distasio, Hainam Do, A. Dutoi, R. Edgar, S. Fatehi, L. Fusti-Molnar, A. Ghysels, A. Golubeva-Zadorozhnaya, J. Gomes, M. W. Hanson-Heine, P. Harbach, A. Hauser, E. Hohenstein, Z. C. Holden, Thomas-C. Jagau, Hyunjun Ji, B. Kaduk, K. Khistyaev, Jaehoon Kim, Jihan Kim, R. King, P. Klunzinger, D. Kosenkov, T. Kowalczyk, C. M. Krauter, K. Lao, Adèle D. Laurent, K. Lawler, S. Levchenko, C. Lin, Fenglai Liu, Ester Livshits, R. Lochan, A. Luenser, P. Manohar, S. Manzer, Shan-Ping Mao, N. Mardirossian, A. Marenich, S. Maurer, N. Mayhall, Eric Neuscamman, C. Oana, R. Olivares-Amaya, D. O’Neill, John A. Parkhill, T. M. Perrine, R. Peverati, A. Prociuk, D. Rehn, E. Rosta, N. J. Russ, S. Sharada, Sandeep Sharma, David W. Small, A. Sodt, T. Stein, D. Stück, Yu-Chuan Su, A. Thom, T. Tsuchimochi, V. Vanovschi, Leslie Vogt, Oleg A. Vydrov, Tao Wang, M. Watson, J. Wenzel, Alec F. White, C. F. Williams, J. Yang, Sina Yeganeh, Shane R. Yost, Zhi-Qiang You, Igor Ying Zhang, Xing Zhang, Yan Zhao, B. Brooks, G. Chan, D. Chipman, C. Cramer, W. Goddard, M. Gordon, W. Hehre, A. Klamt, H. Schaefer, Michael W. Schmidt, C. Sherrill, D. Truhlar, A. Warshel, Xin Xu, Alán Aspuru-Guzik, R. Baer, A. Bell, N. Besley, Jeng-Da Chai, A. Dreuw, B. Dunietz, T. Furlani, S. Gwaltney, Chao‐Ping Hsu, Yousung Jung, Jing Kong, D. Lambrecht, W. Liang, C. Ochsenfeld, V. Rassolov, L. Slipchenko, Joseph E. Subotnik, T. Van Voorhis, J. Herbert, A. Krylov, P. Gill, M. Head‐Gordon   +156 more
semanticscholar   +1 more source

Unifying machine learning and quantum chemistry with a deep neural network for molecular wavefunctions [PDF]

Nature Communications, 2019
Machine learning advances chemistry and materials science by enabling large-scale exploration of chemical space based on quantum chemical calculations. While these models supply fast and accurate predictions of atomistic chemical properties, they do not ...
Kristof T. Schütt, M. Gastegger, A. Tkatchenko, K. Müller, R. Maurer   +4 more
semanticscholar   +1 more source

Band Representations and Topological Quantum Chemistry [PDF]

Annual Review of Condensed Matter Physics, 2020
In this article, we provide a pedagogical review of the theory of topological quantum chemistry and topological crystalline insulators. We begin with an overview of the properties of crystal symmetry groups in position and momentum space.
Jennifer Cano, B. Bradlyn
semanticscholar   +1 more source

Polarization‐resolved femtosecond Vis/IR spectroscopy tailored for resolving weak signals in biological samples using minimal sample volume

FEBS Open Bio, EarlyView.
Unique biological samples, such as site‐specific mutant proteins, are available only in limited quantities. Here, we present a polarization‐resolved transient infrared spectroscopy setup with referencing to improve signal‐to‐noise tailored towards tracing small signals. We provide an overview of characterizing the excitation conditions for polarization‐
Clark Zahn, Karsten Heyne
wiley   +1 more source

A light‐triggered Time‐Resolved X‐ray Solution Scattering (TR‐XSS) workflow with application to protein conformational dynamics

FEBS Open Bio, EarlyView.
Time‐resolved X‐ray solution scattering captures how proteins change shape in real time under near‐native conditions. This article presents a practical workflow for light‐triggered TR‐XSS experiments, from data collection to structural refinement. Using a calcium‐transporting membrane protein as an example, the approach can be broadly applied to study ...
Fatemeh Sabzian‐Molaei, Fredrik Orädd, Konstantinos Magkakis, Magnus Andersson   +3 more
wiley   +1 more source