Bootstrapping quantum process tomography via a perturbative ansatz

Area of Science:

• Quantum Information Science
• Quantum Computing
• Quantum Control

Background:

• Quantum process tomography (QPT) is vital for verifying and debugging quantum processors.
• Standard QPT faces scalability issues with increasing qubit numbers.

Purpose of the Study:

• To develop an efficient quantum process tomography method for multi-qubit systems.
• To enable accurate characterization of quantum processes on larger quantum processors.

Main Methods:

• Introduced a physically motivated ansatz for unknown quantum processes.
• Bootstrapped multi-qubit process descriptions from pairwise two-qubit tomographic data.
• Inherited error resilience from the two-qubit tomography scheme.

Main Results:

• Achieved highly accurate characterizations of quantum processes via numerical simulations of noisy three-qubit gates.
• Successfully demonstrated the approach experimentally on a superconducting quantum processor.
• Reconstructed three-qubit gates using only two-qubit tomographic data.

Conclusions:

• The proposed efficient QPT method effectively characterizes multi-qubit quantum processes.
• This approach offers a scalable solution for quantum processor verification and debugging.
• Experimental validation confirms the practical applicability of the method.