# Regensburg 2022 – wissenschaftliches Programm

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# QI: Fachverband Quanteninformation

## QI 12: Quantum Computing and Algorithms

### QI 12.5: Vortrag

### Donnerstag, 8. September 2022, 16:00–16:15, H8

Estimating molecular forces and other energy gradients efficiently on a quantum computer — •Michael Streif^{2}, Thomas O’Brien^{1}, Nicholas C. Rubin^{1}, Raffaele Santagati^{2}, Yuan Su^{1}, William J. Huggins^{1}, Joshua J. Goings^{1}, Nikolaj Moll^{2}, Elica Kyoseva^{2}, Matthias Degroote^{2}, Christofer S. Tautermann^{3}, Joonho Lee^{1,4}, Dominic W. Berry^{5}, Nathan Wiebe^{6,7}, and Ryan Babbush^{1} — ^{1}Google Research, USA — ^{2}Quantum Lab, Boehringer Ingelheim, Germany — ^{3}Boehringer Ingelheim Pharma GmbH & Co KG, Germany — ^{4}Department of Chemistry, Columbia University, USA — ^{5}Department of Physics and Astronomy, Macquarie University, Australia — ^{6}Department of Computer Science, University of Toronto, Canada — ^{7}Pacific Northwest National Laboratory, USA

The calculation of energy derivatives underpins many fundamental properties for molecular systems, such as dipole moments or molecular forces. Nevertheless, most methods for quantum chemistry on quantum computers have focused on electronic structure calculations, even though energy derivatives are fundamental for many practical applications. Here, I will introduce quantum algorithms for the calculation of energy derivatives on noisy intermediate scale (NISQ) and fault tolerant (FTQC) quantum computers, with substantially reduced cost compared to previous methods. Our results suggest that the calculation of molecular forces has a similar cost to estimating energies. However, since molecular dynamics (MD) simulations typically require millions of force calculations, current known methods for MD on quantum computers are impractical and new approaches need to be found.