Architectures for Multinode Superconducting Quantum Computers

Many proposals to scale quantum technology rely on modular or distributed designs where individual quantum processors, called nodes, are linked together to form one large multinode quantum computer (MNQC). One scalable method to construct an MNQC is using superconducting quantum systems with optical interconnects. However, a limiting factor of these machines will be internode gates, which may be two to three orders of magnitude noisier and slower than local operations. Surmounting the limitations of internode gates will require a range of techniques, including improvements in entanglement generation, the use of entanglement distillation, and optimized software and compilers, and it remains unclear how improvements to these components interact to affect overall system performance, what performance from each is required, or even how to quantify the performance of each. In this paper, we employ a `co-design' inspired approach to quantify overall MNQC performance in terms of hardware models of internode links, entanglement distillation, and local architecture. In the case of superconducting MNQCs with microwave-to-optical links, we uncover a tradeoff between entanglement generation and distillation that threatens to degrade performance. We show how to navigate this tradeoff, lay out how compilers should optimize between local and internode gates, and discuss when noisy quantum links have an advantage over purely classical links. Using these results, we introduce a roadmap for the realization of early MNQCs which illustrates potential improvements to the hardware and software of MNQCs and outlines criteria for evaluating the landscape, from progress in entanglement generation and quantum memory to dedicated algorithms such as distributed quantum phase estimation. While we focus on superconducting devices with optical interconnects, our approach is general across MNQC implementations.Comment: 23 pages, white pape

Demonstration of quantum volume 64 on a superconducting quantum computing system

We improve the quality of quantum circuits on superconducting quantum computing systems, as measured by the quantum volume, with a combination of dynamical decoupling, compiler optimizations, shorter two-qubit gates, and excited state promoted readout. This result shows that the path to larger quantum volume systems requires the simultaneous increase of coherence, control gate fidelities, measurement fidelities, and smarter software which takes into account hardware details, thereby demonstrating the need to continue to co-design the software and hardware stack for the foreseeable future.Comment: Fixed typo in author list. Added references [38], [49] and [52

Pulsed field gradient magnetic resonance measurements of lithium-ion diffusion

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Nuclear Science and Engineering, 2014.Cataloged from PDF version of thesis.Includes bibliographical references (pages 102-119).The transport of lithium ions between the electrolyte-electrode interface and the electrode bulk is an essential and presently rate limiting process in the high-current operation of lithium-ion batteries. Despite their importance, few methods exist to experimentally investigate these macroscopic diffusion processes and, as a result, much remains unknown regarding their underlying mechanisms and the resulting macroscopic transport. Gradient nuclear magnetic resonance measurements are a mature and effective means of investigating macroscopic transport phenomena and posses several advantages over competing measures of transport in ionic solids. However, short coherence times, slow diffusion rates and a small gyromagnetic ratio have, to date, limited their usefulness for measurements of room-temperature transport in solid lithium-ion conductors. Recent developments in quantum control have demonstrated methods for extending the coherence times of dipolar-coupled nuclear spins by several orders of magnitude, into a regime enabling gradient measurements of slow lithium-ion diffusion. This thesis proposes and demonstrates, through the utilization of a dipolar refocusing sequence and a strong pulsed magnetic field gradient, a nuclear magnetic resonance method for the direct measurement of the lithium ion self-diffusion coefficient within room-temperature lithium-ion conductors. Magnetic resonance field gradient measurements derive ensemble transport statistics through observation of the residual phase mismatch following two position dependent phase rotations, implemented as DC pulses of a spatially varying gradient field, separated in time by a transport period. Generating sufficiently fine spatial encodings to be sensitive to slow diffusion has proven challenging in solids where strong relaxation due to the homonuclear dipole-dipole interaction drastically shortens coherence times and thus limits the duration of applied gradient pulses. This study utilizes a magic echo based refocusing sequence to nullify the dominant decoherence mechanism allowing effective gradient pulses on the order of one millisecond. Combined with a custom-built pulsed field gradient, spatial encodings on the order of 1 [mu]m are obtained. For a demonstrative sample, the lithium-ion conductor lithium sulfide is chosen both for its favorable NMR properties and for its role in the recent renewal of interest in nanostructured integration cathode materials. Initial sample characterization reveals two ⁷Li NMR lines distinguished by their static line widths and refocusing behavior. A modified version of the 1D EXSY selective inversion experiment is performed to characterize an exchange process between these two lines and extract their intrinsic spin-lattice relaxation rates. Two stimulated echo diffusion measurements are performed to identify the apparent diffusion coefficients of each line in the presence of exchange. The observed diffusion coefficient of the narrow line is determined to be 2.39 +/- 0.34 . 10-⁸ cm²/s. Diffusive attenuation is not observed for the broad line. These results are analyzed through a two bath exchange model parameterized by the results of the earlier exchange experiments. The influence of exchange on the observed diffusion coefficients is determined to be negligible as diffusion times are limited by the inverse of the exchange rates.by Kevin D. Krsulich.Ph. D

Optimal Partitioning of Quantum Circuits Using Gate Cuts and Wire Cuts

A limited number of qubits, high error rates, and limited qubit connectivity are major challenges for effective near-term quantum computations. Quantum circuit partitioning divides a quantum computation into classical postprocessing steps and a set of smaller scale quantum computations that individually require fewer qubits, lower qubit connectivity, and typically incur less error. However, as partitioning generally increases the duration of a quantum computation exponentially in the required partitioning effort, it is crucial to select optimal partitioning points, so-called cuts, and to use optimal cut realizations. In this work, we develop the first optimal partitioning method relying on quantum circuit knitting for optimal cut realizations and an optimal selection of wire cuts and gate cuts that trades off ancilla qubit insertions for a decrease in quantum computing time. Using this combination, the developed method demonstrates a reduction in quantum computing runtime by 41% on average compared to previous quantum circuit partitioning methods. Furthermore, the qubit requirement of the evaluated quantum circuits was reduced by 40% on average for a runtime budget of one hour and a sampling frequency of 1 kHz. These results highlight the optimality gap of previous quantum circuit partitioning methods and the possible extension in the computational reach of near-term quantum computers

Qiskit/qiskit: Qiskit 0.25.3

<h1>Changelog</h1> <h2>Fixed</h2> <ul> <li>Fix input normalisation of <code>transpile(initial_layout=...)</code> (backport #11031) (#11058)</li> <li>Fix calling backend.name() for backendV2 (#11065) (#11076) (#11092)</li> <li>Fix build filter coupling map with mix ideal/physical targets (#11009) (#11049)</li> <li>Emit a descriptive error when the QPY version is too new (#11094)</li> <li>BackendEstimator support BackendV2 without coupling_map (#10956) (#11006)</li> <li>Support dynamic circuit in BackendEstimator (#9700) (#10984)</li> <li>Avoid useless deepcopy of target with custom pulse gates in transpile (#10973) (#10978)</li> <li>Fix bug in qs_decomposition (#10850) (#10957)</li> </ul&gt