Speaker
Description
We present a cohesive framework for simulating seismic wave propagation utilizing quantum computing paradigms and their classical tensor network equivalents.
We detail a quantum circuit-based formulation for the explicit finite-difference time-domain (FDTD) solution of the two-dimensional acoustic wave equation and
map this quantum architecture onto a tensor train representation, namely for Matrix Product State (MPS).
The MPS solver enables deterministic simulation of large-scale wavefield dynamics on classical high-performance computing systems.
By circumventing the quantum Fourier transform (QFT) overhead through direct spatial basis encoding and arithmetic shift circuits, we establish a robust algorithm.
Recognizing current near-term hardware limitations for deep Linear Combination of Unitaries (LCU) sequences, we formally map this quantum architecture onto a Tensor Train (Matrix Product State) representation, enabling deterministic emulation of large-scale wavefield dynamics on classical high-performance computing systems.