Search Results for author: Roland Haas

Found 6 papers, 1 papers with code

APACE: AlphaFold2 and advanced computing as a service for accelerated discovery in biophysics

1 code implementation15 Aug 2023 Hyun Park, Parth Patel, Roland Haas, E. A. Huerta

The prediction of protein 3D structure from amino acid sequence is a computational grand challenge in biophysics, and plays a key role in robust protein structure prediction algorithms, from drug discovery to genome interpretation.

Drug Discovery Protein Structure Prediction

DataVault: A Data Storage Infrastructure for the Einstein Toolkit

no code implementations11 Dec 2020 Yufeng Luo, Roland Haas, Qian Zhang, Gabrielle Allen

Data sharing is essential in the numerical simulations research.

General Relativity and Quantum Cosmology Databases

Deep Learning for Multi-Messenger Astrophysics: A Gateway for Discovery in the Big Data Era

no code implementations1 Feb 2019 Gabrielle Allen, Igor Andreoni, Etienne Bachelet, G. Bruce Berriman, Federica B. Bianco, Rahul Biswas, Matias Carrasco Kind, Kyle Chard, Minsik Cho, Philip S. Cowperthwaite, Zachariah B. Etienne, Daniel George, Tom Gibbs, Matthew Graham, William Gropp, Anushri Gupta, Roland Haas, E. A. Huerta, Elise Jennings, Daniel S. Katz, Asad Khan, Volodymyr Kindratenko, William T. C. Kramer, Xin Liu, Ashish Mahabal, Kenton McHenry, J. M. Miller, M. S. Neubauer, Steve Oberlin, Alexander R. Olivas Jr, Shawn Rosofsky, Milton Ruiz, Aaron Saxton, Bernard Schutz, Alex Schwing, Ed Seidel, Stuart L. Shapiro, Hongyu Shen, Yue Shen, Brigitta M. Sipőcz, Lunan Sun, John Towns, Antonios Tsokaros, Wei Wei, Jack Wells, Timothy J. Williams, JinJun Xiong, Zhizhen Zhao

We discuss key aspects to realize this endeavor, namely (i) the design and exploitation of scalable and computationally efficient AI algorithms for Multi-Messenger Astrophysics; (ii) cyberinfrastructure requirements to numerically simulate astrophysical sources, and to process and interpret Multi-Messenger Astrophysics data; (iii) management of gravitational wave detections and triggers to enable electromagnetic and astro-particle follow-ups; (iv) a vision to harness future developments of machine and deep learning and cyberinfrastructure resources to cope with the scale of discovery in the Big Data Era; (v) and the need to build a community that brings domain experts together with data scientists on equal footing to maximize and accelerate discovery in the nascent field of Multi-Messenger Astrophysics.

Astronomy Management

Time domain calculation of the electromagnetic self-force on eccentric geodesics in Schwarzschild spacetime

no code implementations16 Dec 2011 Roland Haas

I also display the regularization parameters used in the mode-sum regularization scheme.

General Relativity and Quantum Cosmology

Mode-sum regularization of the scalar self-force: Formulation in terms of a tetrad decomposition of the singular field

no code implementations12 May 2006 Roland Haas, Eric Poisson

We examine the motion in Schwarzschild spacetime of a point particle endowed with a scalar charge.

General Relativity and Quantum Cosmology

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