#COVIDisAirborne: AI-Enabled Multiscale Computational Microscopy of Delta SARS-CoV-2 in a Respiratory Aerosol

Abstract

Abigail Dommer ^1† , Lorenzo Casalino ^1† , Fiona Kearns ^1† , Mia Rosenfeld ¹ , Nicholas Wauer ¹ , Surl-Hee Ahn ¹ , John Russo, ² Sofia Oliveira ³ , Clare Morris ¹ , AnthonyBogetti ⁴ , AndaTrifan ^5,6 , Alexander Brace ^5,7 , TerraSztain ^1,8 , Austin Clyde ^5,7 , Heng Ma ⁵ , Chakra Chennubhotla ⁴ , Hyungro Lee ⁹ , Matteo Turilli ⁹ , Syma Khalid ¹⁰ , Teresa Tamayo-Mendoza ¹¹ , Matthew Welborn ¹¹ , Anders Christensen ¹¹ , Daniel G. A. Smith ¹¹ , Zhuoran Qiao ¹² , Sai Krishna Sirumalla ¹¹ , Michael O'Connor ¹¹ , Frederick Manby ¹¹ , Anima Anandkumar ^12,13 , David Hardy ⁶ , James Phillips ⁶ , Abraham Stern ¹³ , Josh Romero ¹³ , David Clark ¹³ , Mitchell Dorrell ¹⁴ , Tom Maiden ¹⁴ , Lei Huang ¹⁵ , John McCalpin ¹⁵ , Christo- pherWoods ³ , Alan Gray ¹³ , MattWilliams ³ , Bryan Barker ¹⁶ , HarindaRajapaksha ¹⁶ , Richard Pitts ¹⁶ , Tom Gibbs ¹³ , John Stone ⁶ , Daniel Zuckerman ² *, Adrian Mulholland ³ *, Thomas MillerIII ^11,12 *, ShantenuJha ⁹ *, Arvind Ramanathan ⁵ *, Lillian Chong ⁴ *, Rommie Amaro ¹ *. 2021. #COVIDisAirborne: AI-Enabled Multiscale Computational Microscopy ofDeltaSARS-CoV-2 in a Respiratory Aerosol. In <i>Supercomputing '21: International Conference for High Perfor-mance Computing, Networking, Storage, and Analysis</i> . ACM, New York, NY, USA, 14 pages. https://doi.org/finalDOI.