Bulletin of the American Physical Society
APS March Meeting 2024
Monday–Friday, March 4–8, 2024; Minneapolis & Virtual
Session S49: Advances in Quantum Algorithms for Near-Term Applications
8:00 AM–10:36 AM,
Thursday, March 7, 2024
Room: 200G
Sponsoring
Unit:
DQI
Chair: Andy C. Y. Li, Fermilab
Abstract: S49.00010 : Challenges and opportunities for applying quantum computers to drug design
10:12 AM–10:24 AM
Presenter:
Raffaele Santagati
(Boehringer-Ingelheim Quantum Lab)
Authors:
Raffaele Santagati
(Boehringer-Ingelheim Quantum Lab)
Alán Aspuru-Guzik
(University of Toronto)
Ryan Babbush
(Google LLC)
Matthias Degroote
(Boehringer Ingelheim Pharm Inc)
Leticia Gonzalez
(University of Vienna)
Elica Kyoseva
(Boehringer-Ingelheim)
Nikolaj Moll
(Boehringer Ingelheim)
Markus Oppel
(University of Vienna)
Robert M Parrish
(QC WARE)
Nicholas C Rubin
(Google)
Michael Streif
(Boehringer Ingelheim)
Christofer Tautermann
(Boehringer Ingelheim)
Horst Weiss
(BASF)
Horst Weiss
(BASF)
Nathan Wiebe
(University of Toronto)
Clemens Utschig-Utschig
(Boehringer Ingelheim)
The current limitations of classical computing methods in accurately describing quantum systems hinder the application of quantum chemistry to drug design. More precise computations could replace many labor-intensive experiments, provided the computational cost is lower. Quantum computations could offer key insights into chemical systems, justifying high computational costs in an industrial setting. However, to significantly impact the pharmaceutical industry, quantum computers must address a broader set of problems, including those involving large protein structures. New methods that balance accuracy and time on quantum computers could be beneficial. Significant advancements in hardware and quantum algorithms have reduced computational costs over the years, sparking optimism for the future use of quantum computing in quantum chemistry. However, harnessing the full potential of quantum computing in the pharmaceutical industry requires further improvements in hardware and novel algorithms. We will discuss these challenges and explore several potential routes to achieve these goals.
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