TE-PAI: exact time evolution by sampling random circuits

Journal article

Simulating time evolution under quantum Hamiltonians is one of the most natural applications of quantum computers. We introduce TE-PAI, which simulates time evolution exactly by sampling random quantum circuits for the purpose of estimating observable expectation values at the cost of an increased circuit repetition. The approach builds on the Probabilistic Angle Interpolation (PAI) technique and we prove that it simulates time evolution without discretisation or algorithmic error while achieving shallow circuit depths with optimal scaling that saturates the Lieb–Robinson bound. Another significant advantage of TE-PAI is that it only requires executing random circuits that consist of Pauli rotation gates of only two kinds of rotation angles ±Δ and π, along with measurements. While TE-PAI is highly beneficial for NISQ devices, we additionally develop an optimised early fault-tolerant implementation using catalyst circuits and repeat-until-success teleportation, concluding that the approach requires orders of magnitude fewer T-states than conventional techniques, such as Trotterization—we estimate 3×105 T states are sufficient for the fault-tolerant simulation of a 100-qubit Heisenberg spin Hamiltonian. Furthermore, TE-PAI allows for a highly configurable trade-off between circuit depth and measurement overhead by adjusting the rotation angle Δ arbitrarily. We expect that the approach will be a major enabler in the late NISQ and early fault-tolerant periods as it can compensate circuit-depth and qubit-number limitations through an increased circuit repetition.

Authors: Kiumi, C; Koczor, B

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: IOP Publishing
• Journal: Quantum Science and Technology
• Volume: 10
• Issue: 4
• Article number: 045071
• Publication date: 2025-10-22
• Acceptance date: 2025-10-09
• DOI: 10.1088/2058-9565/ae1160
• EISSN: 2058-9565
• Language: English
• Keywords: quantum simulation; quantum algorithm; early fault-tolerant quantum computer