Entanglement across separate silicon dies in a modular superconducting qubit device
We demonstrate a modular solid state architecture with deterministic inter-module coupling between four physically separate, interchangeable superconducting qubit integrated circuits.
A multilevel approach for solving large-scale QUBO problems with noisy hybrid quantum approximate optimization
Quantum approximate optimization is one of the promising candidates for useful quantum computation, particularly in the context of finding approximate solutions to Quadratic Unconstrained Binary Optimization (QUBO) problems. However, the existing QPUs are relatively small, and canonical mappings of QUBO via the Ising model require one qubit per variable, rendering direct large-scale optimization infeasible. In classical optimization, a general strategy for addressing many large-scale problems is via multilevel/multigrid methods, where the large target problem is iteratively coarsened, and the global solution is constructed from multiple small-scale optimization runs. In this work, we experimentally test how existing QPUs perform as a sub-solver within such a multilevel strategy.
Alternating bias assisted annealing of amorphous oxide tunnel junctions
We demonstrate a transformational technique for controllably tuning the electrical properties of fabricated thermally oxidized amorphous aluminum-oxide tunnel junctions. Using conventional test equipment to apply an alternating bias to a heated tunnel barrier, giant increases in the room temperature resistance, greater than 70%, can be achieved.
Error budget of parametric resonance entangling gate with a tunable coupler
We analyze the experimental error budget of parametric resonance gates in a tunable coupler architecture. We identify and characterize various sources of errors, including incoherent, leakage, amplitude, and phase errors. By varying the two-qubit gate time, we explore the dynamics of these errors and their impact on the gate fidelity.
Quantum optimization solvers typically rely on one-variable-to-one-qubit mapping. However, the low qubit count on current quantum computers is a major obstacle in competing against classical methods. Here, we develop a qubit-efficient algorithm that overcomes this limitation by mapping a candidate bit string solution to an entangled wave function of fewer qubits. We propose a variational quantum circuit generalizing the quantum approximate optimization ansatz (QAOA).
Precision frequency tuning of tunable transmon qubits using alternating-bias assisted annealing
Superconducting quantum processors are one of the leading platforms for realizing scalable fault-tolerant quantum computation (FTQC). The recent demonstration of post-fabrication tuning of Josephson junctions using alternating-bias assisted annealing (ABAA) technique and a reduction in junction loss after ABAA illuminates a promising path towards precision tuning of qubit frequency while maintaining high coherence. Here, we demonstrate precision tuning of the maximum |0⟩→|1⟩ transition frequency of tunable transmon qubits by performing ABAA at room temperature using commercially available test equipment.
Exploring the relationship between deposition method, microstructure, and performance of Nb/Si-based superconducting coplanar waveguide resonators
In this study, we performed a comprehensive investigation on the microstructure, superconductivity, and resonator quality factor of Nb films deposited by high-power impulse magnetron sputtering (HiPIMS) and direct current (DC) magnetron sputtering.
Fault-tolerant resource estimation using graph-state compilation on a modular superconducting architecture
Here, we present a resource estimation framework and software tool that estimates the physical resources required to execute specific quantum algorithms, compiled into their graph-state form, and laid out onto a modular superconducting hardware architecture. This tool can predict the size, power consumption, and execution time of these algorithms at as they approach utility-scale according to explicit assumptions about the system's physical layout, thermal load, and modular connectivity. We use this tool to study the total resources on a proposed modular architecture and the impact of tradeoffs between and inter-module connectivity, latency and resource requirements.
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.
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.
Quantum optimization for the maximum cut problem on a superconducting quantum computer
Using a superconducting quantum computer, we experimentally investigate the performance of a hybrid quantum-classical algorithm inspired by semidefinite programming approaches for solving the maximum cut problem on 3-regular graphs up to several thousand variables. We leverage the structure of the input problems to address sizes beyond what current quantum machines can naively handle.
We demonstrate the benefits of using a quantum algorithm rather than its classical counterpart on one of the most fundamental problems of quantitative finance– classification of probability distributions. This problem has many direct applications to practical financial use cases including time series analysis, detection of structural breaks, and monitoring of alpha decay. We present an efficient quantum two-sample test analogous to the classical maximum mean discrepancy test. Experimental results are obtained on Rigetti’s Ankaa-2 quantum computer, applied to a specific instance of the probability distribution classification problem.
Formation and microwave losses of hydrides in superconducting niobium thin films resulting from fluoride chemical processing
This work provides insight into the formation of Nb hydrides and their role in microwave loss, thus guiding ongoing efforts to maximize coherence time in superconducting quantum devices.
