Parallel and Distributed Fermionic Simulation via Dynamic Encoding
Abstract
We demonstrate a simple and efficient method to parallelize and distribute Trotterized Hamiltonian simulation of fermionic systems across multiple QPUs. Using combinatorial covering designs to define a minimal set of fermion-qubit encodings, we demonstrate communication cost scaling as 𝒪(M q4 r) for a system of M fermionic modes and Trotter number r, improving on the static encoding bound for q QPUs, 𝒪(M4 q r). We compare this approach to dynamic encoding using a randomised method, Pauli-weight based optimisation and hypergraph partitioning. Applying these to the Hamiltonians of a range of molecular systems split across two QPUs, we find the combinatorial covering approach results in the lowest communication cost in all but the sparsest Hamiltonians.
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BibTeX
@misc{bastida2026parallel,
title = {{Parallel and Distributed Fermionic Simulation via Dynamic Encoding}},
author = {Michael Williams de la Bastida and Peter V. Coveney},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2609.31502},
eprint = {2609.31502},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.31502},
}
RIS
TY - UNPB
TI - Parallel and Distributed Fermionic Simulation via Dynamic Encoding
AU - Michael Williams de la Bastida
AU - Peter V. Coveney
PY - 2026
DA - 2026/10/08
PB - arXiv
DO - 10.48550/arxiv.2609.31502
UR - https://arxiv.org/abs/2609.31502
AB - We demonstrate a simple and efficient method to parallelize and distribute Trotterized Hamiltonian simulation of fermionic systems across multiple QPUs. Using combinatorial covering designs to define a minimal set of fermion-qubit encodings, we demonstrate communication cost scaling as 𝒪(M q^4 r) for a system of M fermionic modes and Trotter number r, improving on the static encoding bound for q QPUs, 𝒪(M^4 q r). We compare this approach to dynamic encoding using a randomised method, Pauli-weight based optimisation and hypergraph partitioning. Applying these to the Hamiltonians of a range of molecular systems split across two QPUs, we find the combinatorial covering approach results in the lowest communication cost in all but the sparsest Hamiltonians.
ER -