Experimental Sample-Efficient Quantum State Tomography via Parallel Measurements

Area of Science:

• Quantum Information Science
• Quantum Computing
• Experimental Quantum Physics

Background:

• Quantum state tomography (QST) is crucial for characterizing quantum systems.
• Local QST (LQST) using reduced density matrices is impractical for large quantum systems due to high measurement costs.
• Existing methods struggle with scalability and noise resilience.

Purpose of the Study:

• To develop an efficient and scalable quantum state tomography method.
• To reduce the number of measurements required for QST.
• To enhance robustness against experimental noise.

Main Methods:

• Developed parallel quantum state tomography (PQST) inspired by quantum overlapping tomography.
• Implemented PQST on a treelike superconducting qubit chip.
• Prepared various quantum states including W states, ground states, and random states.
• Reconstructed density matrices using PQST, LQST, and full QST (FQST) for comparison.

Main Results:

• PQST significantly reduces measurement overhead compared to LQST and FQST.
• Achieved high fidelities (98.68% for 6-qubit, 95.07% for 9-qubit W states) with fewer measurements.
• Successfully reconstructed a 12-qubit W state density matrix with 89.23% similarity using only 243 parallel observables, versus over 5 million for FQST.
• Demonstrated PQST's robustness against shot noise.

Conclusions:

• PQST is a highly efficient and scalable method for quantum state tomography.
• PQST overcomes the limitations of LQST for large quantum systems.
• PQST is a valuable tool for quantum state reconstruction, characterization, benchmarking, and properties learning in future quantum technologies.