We present a detailed study of the coherence of a tunable capacitively-shunted flux qubit, designed for coherent quantum annealing applications. The measured relaxation at the qubitsymmetry point is mainly due to intrinsic flux noise in the main qubit loop for qubit frequencies below ∼3 GHz. At higher frequencies, thermal noise in the bias line makes a significant contribution to the relaxation, arising from the design choice to experimentally explore both fast annealing and high-frequency control. The measured dephasing rate is primarily due to intrinsic low-frequency flux noise in the two qubit loops, with additional contribution from the low-frequency noise of control electronics used for fast annealing. The flux-bias dependence of the dephasing time also reveals apparent noise correlation between the two qubit loops, possibly due to non-local sources of flux noise or junction critical-current noise. Our results are relevant for ongoing efforts toward building superconducting quantum annealers with increased coherence.
Flux tunability is an important engineering resource for superconducting circuits. Large-scale quantum computers based on flux-tunable superconducting circuits face the problem of fluxcrosstalk, which needs to be accurately calibrated to realize high-fidelity quantum operations. Typical calibration methods either assume that circuit elements can be effectively decoupled and simple models can be applied, or require a large amount of data. Such methods become ineffective as the system size increases and circuit interactions become stronger. Here we propose a new method for calibrating flux crosstalk, which is independent of the underlying circuit model. Using the fundamental property that superconducting circuits respond periodically to external fluxes, crosstalk calibration of N flux channels can be treated as N independent optimization problems, with the objective functions being the periodicity of a measured signal depending on the compensation parameters. We demonstrate this method on a small-scale quantum annealing circuit based on superconducting flux qubits, achieving comparable accuracy with previous methods. We also show that the objective function usually has a nearly convex landscape, allowing efficient optimization.
Magnetic flux tunability is an essential feature in most approaches to quantum computing based on superconducting qubits. Independent control of the fluxes in multiple loops is hamperedby crosstalk. Calibrating flux crosstalk becomes a challenging task when the circuit elements interact strongly. We present a novel approach to flux crosstalk calibration, which is circuit model independent and relies on an iterative process to gradually improve calibration accuracy. This method allows us to reduce errors due to the inductive coupling between loops. The calibration procedure is automated and implemented on devices consisting of tunable flux qubits and couplers with up to 27 control loops. We devise a method to characterize the calibration error, which is used to show that the errors of the measured crosstalk coefficients are all below 0.17%.
Dynamical decoupling (DD) is a widely-used quantum control technique that takes advantage of temporal symmetries in order to partially suppress quantum errors without the need resource-intensiveerror detection and correction protocols. This and other open-loop error mitigation techniques are critical for quantum information processing in the era of Noisy Intermediate-Scale Quantum technology. However, despite its utility, dynamical decoupling does not address errors which occur at unstructured times during a circuit, including certain commonly-encountered noise mechanisms such as cross-talk and imperfectly calibrated control pulses. Here, we introduce and demonstrate an alternative technique – `quantum measurement emulation‘ (QME) – that effectively emulates the measurement of stabilizer operators via stochastic gate application, leading to a first-order insensitivity to coherent errors. The QME protocol enables error suppression based on the stabilizer code formalism without the need for costly measurements and feedback, and it is particularly well-suited to discrete coherent errors that are challenging for DD to address.
A quantum algorithm consists of a sequence of operations and measurements applied to a quantum processor. To date, the instruction set which defines this sequence has been providedby a classical computer and passed via control hardware to the quantum processor. Here, we demonstrate the first experimental realization of a quantum instruction set, in which a fixed sequence of classically-defined gates perform an operation that is fully determined only by a quantum input to the fixed sequence. Specifically, we implement the density matrix exponentiation algorithm, which consumes N copies of the instruction state ρ to approximate the operation e−iρθ (θ an arbitrary angle). Our implementation relies on a 99.7\% fidelity controlled-phase gate between two superconducting transmon qubits. We achieve an average algorithmic fidelity ≈0.9, independent of the setting of ρ, to circuit depth nearly 90. This new paradigm for quantum instructions has applications to resource-efficient protocols for validating entanglement spectra, principal component analysis of large quantum states, and universal quantum emulation.