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 Streif², Thomas O’Brien¹, Nicholas C. Rubin¹, Raffaele Santagati², Yuan Su¹, William J. Huggins¹, Joshua J. Goings¹, Nikolaj Moll², Elica Kyoseva², Matthias Degroote², Christofer S. Tautermann³, Joonho Lee^1,4, Dominic W. Berry⁵, Nathan Wiebe^6,7, and Ryan Babbush¹ — ¹Google Research, USA — ²Quantum Lab, Boehringer Ingelheim, Germany — ³Boehringer Ingelheim Pharma GmbH & Co KG, Germany — ⁴Department of Chemistry, Columbia University, USA — ⁵Department of Physics and Astronomy, Macquarie University, Australia — ⁶Department of Computer Science, University of Toronto, Canada — ⁷Pacific 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.