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We propose the regularized compressed double factorization (RC-DF) method toclassically compute compressed representations of molecular Hamiltonians thatenable efficient simulation with noisy intermediate scale (NISQ) and errorcorrected quantum algorithms. We find that already for small systems with 12 to20 qubits, the resulting NISQ measurement scheme reduces the number ofmeasurement bases by roughly a factor of three and the shot count to reachchemical accuracy by a factor of three to six compared to truncated doublefactorization (DF) and we see order of magnitude improvements over Pauligrouping schemes. We demonstrate the scalability of our approach by performingRC-DF on the CpdI species of cytochrome P450 with 58 orbitals and find thatusing the resulting compressed Hamiltonian cuts the run time of qubitizationand truncated DF based error corrected algorithms almost in half and evenoutperforms the lambda parameters achievable with tensor hypercontraction (THC)while at the same time reducing the CCSD(T) energy error heuristic by an orderof magnitude.

Accelerating Quantum Computations of Chemistry Through Regularized Compressed Double Factorization