Quantum Simulation of the First-Quantized Pauli-Fierz Hamiltonian

Journal Article · 14 March 2024 · PRX Quantum

DOI: https://doi.org/10.1103/PRXQuantum.5.010345 · OSTI ID:2323947

Mukhopadhyay, Priyanka ; Stetina, Torin F.; Wiebe, Nathan

We provide an explicit recursive divide-and-conquer approach for simulating quantum dynamics and derive a discrete first-quantized nonrelativistic QED Hamiltonian based on the many-particle Pauli-Fierz Hamiltonian. We apply this recursive divide-and-conquer algorithm to this Hamiltonian and compare it to a concrete simulation algorithm that uses qubitization. Our divide-and-conquer algorithm, using lowest-order Trotterization, scales for fixed grid spacing as $\tilde{O}(\mathrm{\Lambda }{N}^2{\eta }^2{t}^2/ϵ)$ for grid size $N$ , $\eta$ particles, simulation time $t$ , field cutoff $\mathrm{\Lambda }$ , and error $ϵ$ . Our qubitization algorithm scales as $\tilde{O}\left(N\right(\eta +N\left)\right(\eta +{\mathrm{\Lambda }}^2)t\log (1/ϵ\left)\right)$ . This shows that even a naive partitioning and low-order splitting formula can yield, through our divide-and-conquer formalism, superior scaling to qubitization for large $\mathrm{\Lambda }$ . We compare the relative costs of these two algorithms on systems that are relevant for applications such as the spontaneous emission of photons and the photoionization of electrons. We observe that for different parameter regimes, one method can be favored over the other. Finally, we give new algorithmic and circuit-level techniques for gate optimization, including a new way of implementing a group of multicontrolled- $X$ gates that can be used for better analysis of circuit cost. Published by the American Physical Society 2024

• Sponsoring Organization: USDOE Office of Science (SC), Basic Energy Sciences (BES)
• OSTI ID: 2323947
• Journal Information: PRX Quantum, Journal Name: PRX Quantum Journal Issue: 1 Vol. 5; ISSN 2691-3399; ISSN PQRUAG
• Publisher: American Physical SocietyCopyright Statement
• Country of Publication: United States
• Language: English