TY - GEN

T1 - Hybrid Classical-Quantum Computing in Geophysical Inverse Problems:

T2 - The Case of Quantum Annealing for Residual Statics Estimation

AU - van der Linde, Stan

AU - Dukalski, Marcin

AU - Möller, Matthias

AU - Neumann, Niels

AU - Phillipson, Frank

AU - Rovetta, DIego

N1 - data source: no data used

PY - 2022

Y1 - 2022

N2 - Recent progress in geophysics can be attributed to developments in heterogeneous HPC architectures, with one of the next major leaps being forecasted to be due to quantum computers. It is, however, very difficult to find the right combination of hardware, algorithms and a use-case. This is especially true for applications which have to be simultaneously: relevant and operating at scales where problems become difficult to solve using classical means. Maximizing stack-power for improved near surface characterization and velocity model building, an NP-hard combinatorial optimization problem, appears to naturally fit a particular type of quantum computing known as quantum annealing. We present the quantum-native formulation of this problem. Furthermore, in order to improve the probability of success we embed it in a hybrid classical-quantum workflow. We present the results on controlled experiments run using a 5000-qubit machine and discuss the impact of different classical to quantum problem re-formulations.

AB - Recent progress in geophysics can be attributed to developments in heterogeneous HPC architectures, with one of the next major leaps being forecasted to be due to quantum computers. It is, however, very difficult to find the right combination of hardware, algorithms and a use-case. This is especially true for applications which have to be simultaneously: relevant and operating at scales where problems become difficult to solve using classical means. Maximizing stack-power for improved near surface characterization and velocity model building, an NP-hard combinatorial optimization problem, appears to naturally fit a particular type of quantum computing known as quantum annealing. We present the quantum-native formulation of this problem. Furthermore, in order to improve the probability of success we embed it in a hybrid classical-quantum workflow. We present the results on controlled experiments run using a 5000-qubit machine and discuss the impact of different classical to quantum problem re-formulations.

U2 - 10.3997/2214-4609.2022615002

DO - 10.3997/2214-4609.2022615002

M3 - Conference article in proceeding

VL - 2022

SP - 1

EP - 5

BT - Sixth EAGE High Performance Computing Workshop

PB - European Association of Geoscientists & Engineers

ER -