Trotter Error Mitigation with Error Profiling Method

Trotter–Suzuki product formulas underpin digital quantum simulation, yet noncommuting terms introduce algorithmic bias. Higher-order and multi-product variants mitigate this bias only by increasing circuit depth. Building on the recently introduced error profiling paradigm, we conduct an experimental study on a NISQ processor for representative many-body Hamiltonians. At fixed depth, the procedure learns and compensates for Trotter bias from shallow calibration data with classical post-processing, yielding accuracy improvements across several observables within the tested regimes. These results provide hardware evidence that error profiling can relax the depth–accuracy trade-off in digital quantum simulation and serve as a practical complement to higher-order product formulas on current devices.