Variational Entanglement-Assisted Quantum Process Tomography with Arbitrary Ancillary Qubits

Quantum process tomography is a pivotal technique in fully characterizing quantum dynamics. However, exponential scaling of the Hilbert space with the increasing system size extremely restrains its experimental implementations. Here, we put forward a more efficient, flexible, and error-mitigated method: variational entanglement-assisted quantum process tomography with arbitrary ancillary qubits. Numerically, we simulate up to eight-qubit quantum processes and show that this tomography with m ancillary qubits (0 <= m <= n) alleviates the exponential costs on state preparation (from 4(n) to 2(n-m)), measurement settings (at least a 1 order of magnitude reduction), and data postprocessing (efficient and robust parameter optimization). Experimentally, we first demonstrate our method on a silicon photonic chip by rebuilding randomly generated one-qubit and two-qubit unitary quantum processes. Further using the error mitigation method, two-qubit quantum processes can be rebuilt with average gate fidelity enhanced from 92.38% to 95.56%. Our Letter provides an efficient and practical approach to process tomography on the noisy quantum computing platforms.

Automated summary

This research proposes a more efficient, flexible, and error-mitigated method for quantum process tomography. The method reduces the exponential costs associated with entanglement-assisted tomography and has been experimentally verified on a silicon photonic chip.