3 research outputs found
Benchmarking universal quantum gates via channel spectrum
Abstract Noise remains the major obstacle to scalable quantum computation. Quantum benchmarking provides key information on noise properties and is an important step for developing more advanced quantum processors. However, current benchmarking methods are either limited to a specific subset of quantum gates or cannot directly describe the performance of the individual target gate. To overcome these limitations, we propose channel spectrum benchmarking (CSB), a method to infer the noise properties of the target gate, including process fidelity, stochastic fidelity, and some unitary parameters, from the eigenvalues of its noisy channel. Our CSB method is insensitive to state-preparation and measurement errors, and importantly, can benchmark universal gates and is scalable to many-qubit systems. Unlike standard randomized schemes, CSB can provide direct noise information for both target native gates and circuit fragments, allowing benchmarking and calibration of global entangling gates and frequently used modules in quantum algorithms like Trotterized Hamiltonian evolution operator in quantum simulation
Fast Quantum Calibration using Bayesian Optimization with State Parameter Estimator for Non-Markovian Environment
As quantum systems expand in size and complexity, manual qubit
characterization and gate optimization will be a non-scalable and
time-consuming venture. Physical qubits have to be carefully calibrated because
quantum processors are very sensitive to the external environment, with control
hardware parameters slowly drifting during operation, affecting gate fidelity.
Currently, existing calibration techniques require complex and lengthy
measurements to independently control the different parameters of each gate and
are unscalable to large quantum systems. Therefore, fully automated protocols
with the desired functionalities are required to speed up the calibration
process. This paper aims to propose single-qubit calibration of superconducting
qubits under continuous weak measurements from a real physical experimental
settings point of view. We propose a real-time optimal estimator of qubit
states, which utilizes weak measurements and Bayesian optimization to find the
optimal control pulses for gate design. Our numerical results demonstrate a
significant reduction in the calibration process, obtaining a high gate
fidelity. Using the proposed estimator we estimated the qubit state with and
without measurement noise and the estimation error between the qubit state and
the estimator state is less than 0.02. With this setup, we drive an
approximated pi pulse with final fidelity of 0.9928. This shows that our
proposed strategy is robust against the presence of measurement and
environmental noise and can also be applicable for the calibration of many
other quantum computation technologies.Comment: 15 pages, 8 figures, 1 tabl