Parallelization techniques for quantum simulation of fermionic systems
1Department of Physics, University of Maryland, College Park, Maryland 20742, USA
2Joint Center for Quantum Information and Computer Science, NIST/University of Maryland, College Park, Maryland 20742, USA
3Joint Quantum Institute, NIST/University of Maryland, College Park, Maryland 20742, USA
4Maryland Center for Fundamental Physics, University of Maryland, College Park, Maryland 20742, USA
5Institute for Robust Quantum Simulation, University of Maryland, College Park, Maryland 20742, USA
Published: | 2023-04-13, volume 7, page 975 |
Eprint: | arXiv:2207.12470v3 |
Doi: | https://doi.org/10.22331/q-2023-04-13-975 |
Citation: | Quantum 7, 975 (2023). |
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Abstract
Mapping fermionic operators to qubit operators is an essential step for simulating fermionic systems on a quantum computer. We investigate how the choice of such a mapping interacts with the underlying qubit connectivity of the quantum processor to enable (or impede) parallelization of the resulting Hamiltonian-simulation algorithm. It is shown that this problem can be mapped to a path coloring problem on a graph constructed from the particular choice of encoding fermions onto qubits and the fermionic interactions onto paths. The basic version of this problem is called the weak coloring problem. Taking into account the fine-grained details of the mapping yields what is called the strong coloring problem, which leads to improved parallelization performance. A variety of illustrative analytical and numerical examples are presented to demonstrate the amount of improvement for both weak and strong coloring-based parallelizations. Our results are particularly important for implementation on near-term quantum processors where minimizing circuit depth is necessary for algorithmic feasibility.

Featured image: A representative graph coloring corresponding to a particular parallelization scheme for simulating a fermionic system on a quantum computer. See Fig. 1 of text for details.
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