Here, we introduce an iterative quantum heuristic optimization algorithm to solve combinatorial optimization problems. The quantum algorithm reduces to a classical greedy algorithm in the presence of strong noise. We implement the quantum algorithm on a programmable superconducting quantum system using up to 72 qubits for solving paradigmatic Sherrington-Kirkpatrick Ising spin glass problems. We find the quantum algorithm systematically outperforms its classical greedy counterpart, signaling a quantum enhancement.
Coherent control of a superconducting qubit using light
Here, we demonstrate coherent optical control of a superconducting qubit. We achieve this by developing a microwave-optical quantum transducer that operates with up to 1.18% conversion efficiency (1.16% cooperativity) and demonstrate optically-driven Rabi oscillations (2.27 MHz) in a superconducting qubit without impacting qubit coherence times (800 ns). Finally, we discuss outlooks towards using the transducer to network quantum processor nodes.
High-fidelity optical readout of a superconducting qubit using a scalable piezo-optomechanical transducer
Superconducting quantum processors have made significant progress in size and computing potential. As a result, the practical cryogenic limitations of operating large numbers of superconducting qubits are becoming a bottleneck for further scaling. Due to the low thermal conductivity and the dense optical multiplexing capacity of telecommunications fiber, converting qubit signal processing to the optical domain using microwave-to-optics transduction would significantly relax the strain on cryogenic space and thermal budgets. Here, we demonstrate high-fidelity multi-shot optical readout through an optical fiber of a superconducting transmon qubit connected via a coaxial cable to a fully integrated piezo-optomechanical transducer.
Evaluating quantum generative models via imbalanced data classification benchmarks
A limited set of tools exist for assessing whether the behavior of quantum machine learning models diverges from conventional models, outside of abstract or theoretical settings. We present a systematic application of explainable artificial intelligence techniques to analyze synthetic data generated from a hybrid quantum-classical neural network adapted from twenty different real-world data sets, including solar flares, cardiac arrhythmia, and speech data.
Modular superconducting qubit architecture with a multi-chip tunable coupler
We use a floating tunable coupler to mediate interactions between qubits on separate chips to build a modular architecture. We demonstrate three different designs of multi-chip tunable couplers using vacuum gap capacitors or superconducting indium bump bonds to connect the coupler to a microwave line on a common substrate and then connect to the qubit on the next chip.
Design and execution of quantum circuits using tens of superconducting qubits and thousands of gates for dense Ising optimization problems
We develop a hardware-efficient ansatz for variational optimization, derived from existing ansatze in the literature, that parametrizes subsets of all interactions in the Cost Hamiltonian in each layer. We treat gate orderings as a variational parameter and observe that doing so can provide significant performance boosts in experiments. We carried out experimental runs of a compilation-optimized implementation of fully-connected Sherrington-Kirkpatrick Hamiltonians on a 50-qubit linear-chain subsystem of Rigetti Aspen-M-3 transmon processor.
Systematic improvements in transmon qubit coherence enabled by niobium surface encapsulation
We present a novel transmon qubit fabrication technique that yields systematic improvements in T1 coherence times. We fabricate devices using an encapsulation strategy that involves passivating the surface of niobium and thereby preventing the formation of its lossy surface oxide.
Development and demonstration of an efficient readout error mitigation technique for use in NISQ algorithms
We consider the approximate state estimation of readout-mitigated expectation values, and how to best implement that procedure on the Rigetti quantum computing hardware. We discuss the theoretical aspects involved, providing an explicit computation of the effect of readout error on the estimated expectation values and how to mitigate that effect.
Navigating the noise-depth tradeoff in adiabatic quantum circuits
What is the optimal circuit depth that provides the best solution? Here, we address this question by investigating an adiabatic circuit that interpolates between the paramagnetic and ferromagnetic ground states of the one-dimensional quantum Ising model.
Direct pulse-level compilation of arbitrary quantum logic gates on superconducting qutrits
In this work, we demonstrate that any arbitrary qutrit gate can be realized with high fidelity. We generated and tested pulses for a large set of randomly selected arbitrary unitaries on two separate qutrit compatible processors, LLNL Quantum Device and Integration Testbed (QuDIT) standard QPU and Rigetti Aspen-11, achieving an average fidelity around 99 %.
Simulating the interplay of particle conservation and long-range coherence
We introduce two complementary probes of global and relative phase coherence, study how they are affected by measurements of the particle number, and implement them on a superconducting quantum computer by Rigetti.