检索结果-内蒙古大学图书馆

End-to-end symmetry preserving inter-atomic potential energy model for finite and extended systems

学校读者我要写书评

暂无评论

arXiv 2018年

作者： Zhang, Linfeng Han, Jiequn Wang, Han Saidi, Wissam A. Car, Roberto Weinan, E. Program in Applied and Computational Mathematics Princeton University United States Institute of Applied Physics and Computational Mathematics China CAEP Software Center for High Performance Numerical Simulation China Department of Mechanical Engineering and Materials Science University of Pittsburgh United States Department of Chemistry and Department of Physics Princeton University United States Princeton Institute for the Science and Technology of Materials Princeton University United States Department of Mathematics Princeton University United States Beijing Institute of Big Data Research China

Machine learning models are changing the paradigm of molecular modeling, which is a fundamental tool for material science, chemistry, and computational biology. Of particular interest is the inter-atomic potential energy surface (PES). Here we develop Deep Potential - Smooth Edition (DeepPot-SE), an end-to-end machine learning-based PES model, which is able to efficiently represent the PES of a wide variety of systems with the accuracy of ab initio quantum mechanics models. By construction, DeepPot-SE is extensive and continuously differentiable, scales linearly with system size, and preserves all the natural symmetries of the system. Further, we show that DeepPot-SE describes finite and extended systems including organic molecules, metals, semiconductors, and insulators with high fidelity. Copyright © 2018, The Authors. All rights reserved.

关键词： Potential energy

Nonbacktracking bounds on the influence in independent cascade models 17

学校读者我要写书评

暂无评论

Nonbacktracking bounds on the influence in independent casca...

Proceedings of the 31st International Conference on Neural Information Processing Systems

作者： Emmanuel Abbe Sanjeev Kulkarni Eun Jee Lee Program in Applied and Computational Mathematics and The Department of Electrical Engineering Princeton University The Department of Electrical Engineering Princeton University Program in Applied and Computational Mathematics

ISBN: (纸本)9781510860964

This paper develops upper and lower bounds on the influence measure in a network, more precisely, the expected number of nodes that a seed set can influence in the independent cascade model. In particular, our bounds exploit nonbacktracking walks, Fortuin-Kasteleyn-Ginibre type inequalities, and are computed by message passing algorithms. Nonbacktracking walks have recently allowed for headways in community detection, and this paper shows that their use can also impact the influence computation. Further, we provide parameterized versions of the bounds that control the trade-off between the efficiency and the accuracy. Finally, the tightness of the bounds is illustrated with simulations on various network models.

关键词：

Author Correction: Hysteresis control of epithelial-mesenchymal transition dynamics conveys a distinct program with enhanced metastatic ability

学校读者我要写书评

暂无评论

Nature communications 2019年第1期10卷 527页

作者： Toni Celià-Terrassa Caleb Bastian Daniel D Liu Brian Ell Nicole M Aiello Yong Wei Jose Zamalloa Andres M Blanco Xiang Hang Dmitriy Kunisky Wenyang Li Elizabeth D Williams Herschel Rabitz Yibin Kang Department of Molecular Biology Princeton University Princeton NJ 08544 USA. Cancer Program IMIM (Hospital del Mar Medical Research Institute) 08003 Barcelona Spain. Program in Applied and Computational Mathematics Princeton University Princeton NJ 08544 USA. cbastian@princeton.edu. Lewis-Sigler Institute of Integrative Genomics Princeton University Princeton NJ 08544 USA. Department of Mathematics Princeton University Princeton NJ 08544 USA. School of Biomedical Sciences Translational Research Institute Queensland University of Technology (QUT) Brisbane QLD 4102 Australia. Program in Applied and Computational Mathematics Princeton University Princeton NJ 08544 USA. Department of Chemistry Princeton University Princeton NJ 08544 USA. Department of Molecular Biology Princeton University Princeton NJ 08544 USA. ykang@princeton.edu.

The original version of this Article contained an error in the spelling of the author Daniel D. Liu, which was incorrectly given as Daniel Liu. This has now been corrected in both the PDF and HTML versions of the Arti...

关键词：

The Event Horizon Telescope Image of the Quasar NRAO 530

学校读者我要写书评

暂无评论

Astrophysical Journal 2023年第2期943卷 170-170页

作者： Jorstad, Svetlana Wielgus, Maciek Lico, Rocco Issaoun, Sara Broderick, Avery E. Pesce, Dominic W. Liu, Jun Zhao, Guang-Yao Krichbaum, Thomas P. Blackburn, Lindy Chan, Chi-Kwan Janssen, Michael Ramakrishnan, Venkatessh Akiyama, Kazunori Alberdi, Antxon Algaba, Juan Carlos Bouman, Katherine L. Cho, Ilje Fuentes, Antonio Gómez, José L. Gurwell, Mark Johnson, Michael D. Kim, Jae-Young Lu, Ru-Sen Martí-Vidal, Iván Moscibrodzka, Monika Pötzl, Felix M. Traianou, Efthalia van Bemmel, Ilse Alef, Walter Anantua, Richard Asada, Keiichi Azulay, Rebecca Bach, Uwe Baczko, Anne-Kathrin Ball, David Baloković, Mislav Barrett, John Bauböck, Michi Benson, Bradford A. Bintley, Dan Blundell, Raymond Bower, Geoffrey C. Boyce, Hope Bremer, Michael Brinkerink, Christiaan D. Brissenden, Roger Britzen, Silke Broguiere, Dominique Bronzwaer, Thomas Bustamante, Sandra Byun, Do-Young Carlstrom, John E. Ceccobello, Chiara Chael, Andrew Chatterjee, Koushik Chatterjee, Shami Chen, Ming-Tang Chen, Yongjun Cheng, Xiaopeng Christian, Pierre Conroy, Nicholas S. Conway, John E. Cordes, James M. Crawford, Thomas M. Crew, Geoffrey B. Cruz-Osorio, Alejandro Cui, Yuzhu Davelaar, Jordy De Laurentis, Mariafelicia Deane, Roger Dempsey, Jessica Desvignes, Gregory Dexter, Jason Dhruv, Vedant Doeleman, Sheperd S. Dougal, Sean Dzib, Sergio A. Eatough, Ralph P. Emami, Razieh Falcke, Heino Farah, Joseph Fish, Vincent L. Fomalont, Ed Ford, H. Alyson Fraga-Encinas, Raquel Freeman, William T. Friberg, Per Fromm, Christian M. Galison, Peter Gammie, Charles F. García, Roberto Gentaz, Olivier Georgiev, Boris Goddi, Ciriaco Gold, Roman Gómez-Ruiz, Arturo I. Gu, Minfeng Hada, Kazuhiro Haggard, Daryl Haworth, Kari Hecht, Michael H. Hesper, Ronald Heumann, Dirk Ho, Luis C. Ho, Paul Honma, Mareki Huang, Chih-Wei L. Huang, Lei Hughes, David H. Ikeda, Shiro Impellizzeri, C.M. Violette Inoue, Makoto James, David J. Jannuzi, Buell T. Jeter, Britton Jiang, Wu Jiménez-Rosales, Alejandra Joshi, Abhishek V. Jung, Taehyun Karami, Mansour Karuppusamy, Ramesh Kawashima, Tomohisa Keati Institute for Astrophysical Research Boston University 725 Commonwealth Avenue Boston 02215 MA United States Max-Planck-Institut für Radioastronomie Auf dem Hügel 69 Bonn D-53121 Germany Instituto de Astrofísica de Andalucía-CSIC Glorieta de la Astronomía s/n Granada E-18008 Spain INAF-Istituto di Radioastronomia Via P. Gobetti 101 Bologna I-40129 Italy Center for Astrophysics Harvard & Smithsonian 60 Garden Street Cambridge 02138 MA United States NASA Hubble Fellowship Program Perimeter Institute for Theoretical Physics 31 Caroline Street North Waterloo N2L 2Y5 ON Canada Department of Physics and Astronomy University of Waterloo 200 University Avenue West Waterloo N2L 3G1 ON Canada Waterloo Centre for Astrophysics University of Waterloo Waterloo N2L 3G1 ON Canada Harvard University 20 Garden Street Cambridge 02138 MA United States Steward Observatory Department of Astronomy University of Arizona 933 N. Cherry Avenue Tucson 85721 AZ United States Data Science Institute University of Arizona 1230 N. Cherry Avenue Tucson 85721 AZ United States Program in Applied Mathematics University of Arizona 617 N. Santa Rita Tucson 85721 AZ United States Astronomy Department Universidad de Concepción Casilla 160-C Concepción Chile Finnish Centre for Astronomy with ESO University of Turku FI-20014 Finland Aalto University Metsähovi Radio Observatory Metsähovintie 114 Kylmälä FI-02540 Finland Massachusetts Institute of Technology Haystack Observatory 99 Millstone Road Westford 01886 MA United States National Astronomical Observatory of Japan 2-21-1 Osawa Mitaka Tokyo 181-8588 Japan Department of Physics Faculty of Science Universiti Malaya Kuala Lumpur 50603 Malaysia California Institute of Technology 1200 East California Boulevard Pasadena 91125 CA United States Department of Astronomy and Atmospheric Sciences Kyungpook National University Daegu 702-701 South Korea Shanghai Astronomical Observatory Chinese Academy of Sciences 80

We report on the observations of the quasar NRAO 530 with the Event Horizon Telescope (EHT) on 2017 April 5−7, when NRAO 530 was used as a calibrator for the EHT observations of Sagittarius A*. At z = 0.902, this is the most distant object imaged by the EHT so far. We reconstruct the first images of the source at 230 GHz, at an unprecedented angular resolution of ∼20 μas, both in total intensity and in linear polarization (LP). We do not detect source variability, allowing us to represent the whole data set with static images. The images reveal a bright feature located on the southern end of the jet, which we associate with the core. The feature is linearly polarized, with a fractional polarization of ∼5%-8%, and it has a substructure consisting of two components. Their observed brightness temperature suggests that the energy density of the jet is dominated by the magnetic field. The jet extends over 60 μas along a position angle ∼ −28°. It includes two features with orthogonal directions of polarization (electric vector position angle), parallel and perpendicular to the jet axis, consistent with a helical structure of the magnetic field in the jet. The outermost feature has a particularly high degree of LP, suggestive of a nearly uniform magnetic field. Future EHT observations will probe the variability of the jet structure on microarcsecond scales, while simultaneous multiwavelength monitoring will provide insight into the high-energy emission origin. © 2023. The Author(s). Published by the American Astronomical Society.

关键词：

Reactive particle-tracking solutions to a benchmark problem on heavy metal cycling in lake sediments

学校读者我要写书评

暂无评论

arXiv 2019年

作者： Schmidt, Michael J. Pankavich, Stephen D. Navarre-Sitchler, Alexis Engdah, Nicholas B. Bolster, Diogo Benson, David A. Department of Civil and Environmental Engineering and Earth Sciences University of Notre Dame Notre DameIN46556 United States Department of Applied Mathematics and Statistics Colorado School of Mines GoldenCO80401 United States Hydrologic Science and Engineering Program Department of Geology and Geological Engineering Colorado School of Mines GoldenCO80401 United States Department of Civil and Environmental Engineering Washington State University PullmanWA99164 United States

Geochemical systems are known to exhibit highly variable spatiotemporal behavior. This may be observed both in non-smooth concentration curves in space for a single sampling time and also in variability between samples taken from the same location at different times. However, most models that are designed to simulate these systems provide only single-solution smooth curves and fail to capture the noise and variability seen in the data. We apply a recently developed reactive particle-tracking method to a system that displays highly-complex geochemical behavior. When the method is made to most closely resemble a corresponding Eulerian method, in its unperturbed form, we see near-exact match between solutions of the two models. More importantly, we consider two approaches for perturbing the model and find that the spatially-perturbed condition is able to capture a greater degree of the variability present in the data. This method of perturbation is a task to which particle methods are uniquely suited and Eulerian models are not well-suited. Additionally, because of the nature of the algorithm, noisy spatial gradients can be highly resolved by a large number of mobile particles, and this incurs negligible computational cost, as compared to expensive chemistry calculations. Copyright © 2019, The Authors. All rights reserved.

关键词： Heavy metals

Stationary frequencies and mixing times for neutral drift processes with spatial structure

学校读者我要写书评

暂无评论

arXiv 2018年

作者： McAvoy, Alex Adlam, Ben Allen, Benjamin Nowak, Martin A. Program for Evolutionary Dynamics Harvard University CambridgeMA02138 School of Engineering and Applied Sciences Harvard University CambridgeMA02138 Department of Mathematics Emmanuel College BostonMA02115 Department of Mathematics Harvard University CambridgeMA02138 Department of Organismic and Evolutionary Biology Harvard University CambridgeMA02138

We study a general setting of neutral evolution in which the population is of finite, constant size and can have spatial structure. Mutation leads to different genetic types ("traits"), which can be discrete or continuous. Under minimal assumptions, we show that the marginal trait distributions of the evolutionary process, which specify the probability that any given individual has a certain trait, all converge to the stationary distribution of the mutation process. In particular, the stationary frequencies of traits in the population are independent of its size, spatial structure, and evolutionary update rule, and these frequencies can be calculated by evaluating a simple stochastic process describing a population of size one (i.e. the mutation process itself). We conclude by analyzing mixing times, which characterize rates of convergence of the mutation process along the lineages, in terms of demographic variables of the evolutionary process. Copyright © 2018, The Authors. All rights reserved.

关键词： Random processes

Randomized near neighbor graphs, giant components and applications in data science

学校读者我要写书评

暂无评论

arXiv 2017年

作者： Linderman, George C. Mishne, Gal Kluger, Yuval Steinerberger, Stefan Department of Pathology Program in Applied Mathematics Yale University

If we pick n random points uniformly in [0;1]dand connect each point to its k-nearest neighbors, then it is well known that there exists a giant connected component with high probability. We prove that in [0;1]dit suffices to connect every point to cd,1log log n points chosen randomly among its cd,2log n-nearest neighbors to ensure a giant component of size n-o(n) with high probability. This construction yields a much sparser random graph with ∼ n log log n instead of ∼ n log n edges that has comparable connectivity properties. This result has nontrivial implications for problems in data science where an affinity matrix is constructed: instead of picking the k-nearest neighbors, one can often pick′ k random points out of the k-nearest neighbors without sacrificing efficiency. This can massively simplify and accelerate computation, we illustrate this with several numerical examples. Copyright © 2017, The Authors. All rights reserved.

关键词： k-nearest neighbors

The Black Hole Explorer: Motivation and Vision

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Johnson, Michael D. Akiyama, Kazunori Baturin, Rebecca Bilyeu, Bryan Blackburn, Lindy Boroson, Don Cárdenas-Avendaño, Alejandro Chael, Andrew Chan, Chi-Kwan Chang, Dominic Cheimets, Peter Chou, Cathy Doeleman, Sheperd S. Farah, Joseph Galison, Peter Gamble, Ronald Gammie, Charles F. Gelles, Zachary Gómez, José L. Gralla, Samuel E. Grimes, Paul Gurvits, Leonid I. Hadar, Shahar Haworth, Kari Hada, Kazuhiro Hecht, Michael H. Honma, Mareki Houston, Janice Hudson, Ben Issaoun, Sara Jia, He Jorstad, Svetlana Kauffmann, Jens Kovalev, Yuri Y. Kurczynski, Peter Lafon, Robert Lupsasca, Alexandru Lehmensiek, Robert Ma, Chung-Pei Marrone, Daniel P. Marscher, Alan P. Melnick, Gary J. Narayan, Ramesh Niinuma, Kotaro Noble, Scott C. Palmer, Eric J. Palumbo, Daniel C.M. Paritsky, Lenny Peretz, Eliad Pesce, Dominic Plavin, Alexander Quataert, Eliot Rana, Hannah Ricarte, Angelo Roelofs, Freek Shtyrkova, Katia Sinclair, Laura C. Small, Jeffrey Kumara, Sridharan Tirupati Srinivasan, Ranjani Strominger, Andrew Tiede, Paul Tong, Edward Wang, Jade Weintroub, Jonathan Wielgus, Maciek Wong, George Zhang, Xinyue Alice Center for Astrophysics | Harvard & Smithsonian 60 Garden Street CambridgeMA02138 United States Black Hole Initiative Harvard University 20 Garden Street CambridgeMA02138 United States Haystack Observatory Massachusetts Institute of Technology WestfordMA01886 United States Mizusawa VLBI Observatory National Astronomical Observatory of Japan Iwate023-0861 Japan MIT Lincoln Laboratory LexingtonMA02421 United States Princeton Gravity Initiative Princeton University PrincetonNJ08544 United States Steward Observatory and Department of Astronomy University of Arizona 933 N. Cherry Ave. TucsonAZ85721 United States Data Science Institute University of Arizona 1230 N. Cherry Ave. TucsonAZ85721 United States Program in Applied Mathematics University of Arizona 617 N. Santa Rita TucsonAZ85721 United States Las Cumbres Observatory 6740 Cortona Drive GoletaCA93117-5575 United States Department of Physics University of California Santa BarbaraCA93106-9530 United States Department of History of Science Harvard University CambridgeMA02138 United States Department of Physics Harvard University CambridgeMA02138 United States NASA Goddard Space Flight Center GreenbeltMD20771 United States Departments of Astronomy and of Physics University of Illinois UrbanaIL61801 United States Instituto de Astrofísica de Andalucía CSIC Glorieta de la Astronomía s/n GranadaE-18008 Spain Department of Physics University of Arizona TucsonAZ85719 United States Joint Institute for VLBI ERIC Dwingeloo7991PD Netherlands Faculty of Aerospace Engineering Delft University of Technology Delft2629 HS Netherlands Department of Mathematics and Physics University of Haifa at Oranim Kiryat Tivon3600600 Israel Haifa Research Center for Theoretical Physics and Astrophysics University of Haifa Haifa3498838 Israel 2-21-1 Osawa Mitaka Tokyo181-8588 Japan Department of Astronomy Graduate School of Science The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-

We present the Black Hole Explorer (BHEX), a mission that will produce the sharpest images in the history of astronomy by extending submillimeter Very-Long-Baseline Interferometry (VLBI) to space. BHEX will discover and measure the bright and narrow "photon ring" that is predicted to exist in images of black holes, produced from light that has orbited the black hole before escaping. This discovery will expose universal features of a black hole's spacetime that are distinct from the complex astrophysics of the emitting plasma, allowing the first direct measurements of a supermassive black hole's spin. In addition to studying the properties of the nearby supermassive black holes M87*and Sgr A*, BHEX will measure the properties of dozens of additional supermassive black holes, providing crucial insights into the processes that drive their creation and growth. BHEX will also connect these supermassive black holes to their relativistic jets, elucidating the power source for the brightest and most efficient engines in the universe. BHEX will address fundamental open questions in the physics and astrophysics of black holes that cannot be answered without submillimeter space VLBI. The mission is enabled by recent technological breakthroughs, including the development of ultra-high-speed downlink using laser communications, and it leverages billions of dollars of existing ground infrastructure. We present the motivation for BHEX, its science goals and associated requirements, and the pathway to launch within the next decade. © 2024, CC BY.

关键词： Photons

Corrigendum to ``A mathematical model of tumor-immune interactions'' [Journal of Theoretical Biology 294 (2012) 56-73]

学校读者我要写书评

暂无评论

Journal of theoretical biology 2019年 464卷 180页

作者： Mark Robertson-Tessi Ardith El-Kareh Alain Goriely Program in Applied Mathematics University of Arizona Tucson AZ 85721 United States. Electronic address: mark.robertsontessi@***. ARL-Microcirculation Division University of Arizona Tucson AZ 85724 United States. Oxford Center for Collaborative Applied Mathematics Mathematical Institute Oxford OX2 6HA UK.