2014/07/03 by Andrey V. Rodionov, Andrzej Veitia, R. Barends +7 · 2 citations
Computer Science · Engineering · Physics and Astronomy · #Algorithm #Computer science #Materials science #Matrix (chemical analysis) #Physics #Quantum #Quantum Computing Algorithms and Architecture #Quantum Information and Cryptography #Quantum algorithm #Quantum computer #Quantum dynamics #Quantum gate #Quantum mechanics #Quantum process #Qubit #Sparse and Compressive Sensing Techniques #Statistical physics #Toffoli gate #Underdetermined system #quant-ph
paper · pdf · doi:10.1103/physrevb.90.144504
16 pages, 11 figures
arxiv created 2014/07/03 · openalex publication_date 2014/10/09 · arxiv updated 2015/06/22 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
We apply the method of compressed sensing (CS) quantum process tomography (QPT) to characterize quantum gates based on superconducting Xmon and phase qubits. Using experimental data for a two-qubit controlled-Z gate, we obtain an estimate for the process matrix \ensuremathχ with reasonably high fidelity compared to full QPT, but using a significantly reduced set of initial states and measurement configurations. We show that the CS method still works when the amount of used data is so small that the standard QPT would have an underdetermined system of equations. We also apply the CS method to the analysis of the three-qubit Toffoli gate with numerically added noise, and similarly show that the method works well for a substantially reduced set of data. For the CS calculations, we use two different bases in which the process matrix \ensuremathχ is approximately sparse, and show that the resulting estimates of the process matrices match each other with reasonably high fidelity. For both two-qubit and three-qubit gates, we characterize the quantum process by not only its process matrix and fidelity, but also by the corresponding standard deviation, defined via variation of the state fidelity for different initial states.