The Phase-Contrast Imaging Instrument at the Matter in Extreme Conditions Endstation at LCLS

We describe the Phase-Contrast Imaging instrument at the Matter in Extreme Conditions (MEC) endstation of the Linac Coherent Light Source. The instrument can image phenomena with a spatial resolution of a few hundreds of nanometers and at the same time reveal the atomic structure through X-ray diffraction, with a temporal resolution better than 100 femtosecond. It was specifically designed for studies relevant to High-Energy-Density Science and can monitor, e.g., shock fronts, phase transitions, or void collapses. This versatile instrument was commissioned last year and is now available to the MEC user community

A quantum-classical co-processing protocol towards simulating nuclear reactions on contemporary quantum hardware

Quantum computers hold great promise for arriving at exact simulations of nuclear dynamical processes (e.g., scattering and reactions) that are paramount to the study of nuclear matter at the limit of stability and to explaining the formation of chemical elements in stars. However, quantum simulations of the unitary (real) time dynamics of fermionic many-body systems require a currently prohibitive number of reliable and long-lived qubits. We propose a co-processing algorithm for the simulation of real-time dynamics in which the time evolution of the spatial coordinates is carried out on a classical processor, while the evolution of the spin degrees of freedom is carried out on a quantum processor. This hybrid algorithm is demonstrated by a quantum simulation of the scattering of two neutrons performed at the Lawrence Berkeley National Laboratory's Advanced Quantum Testbed. We show that, after implementation of error mitigation strategies to improve the accuracy of the algorithm in addition to the use of either circuit compression techniques or tomography as methods to elucidate the onset of decoherence, this initial demonstration validates the principle of the proposed co-processing scheme. We anticipate that a generalization of this present scheme will open the way for (real-time) path integral simulations of nuclear scattering.Comment: 12 pages, 10 figure

Programmable Heisenberg Interactions Between Floquet Qubits

The trade-off between robustness and tunability is a central challenge in the pursuit of quantum simulation and fault-tolerant quantum computation. In particular, quantum architectures are often designed to achieve high coherence at the expense of tunability. Many current qubit designs have fixed energy levels and consequently limited types of controllable interactions. Here by adiabatically transforming fixed-frequency superconducting circuits into modifiable Floquet qubits, we demonstrate an XXZ Heisenberg interaction with fully adjustable anisotropy. This interaction model can act as the primitive for an expressive set of quantum operations, but is also the basis for quantum simulations of spin systems. To illustrate the robustness and versatility of our Floquet protocol, we tailor the Heisenberg Hamiltonian and implement two-qubit iSWAP, CZ and SWAP gates with good estimated fidelities. In addition, we implement a Heisenberg interaction between higher energy levels and employ it to construct a three-qubit CCZ gate, also with a competitive fidelity. Our protocol applies to multiple fixed-frequency high-coherence platforms, providing a collection of interactions for high-performance quantum information processing. It also establishes the potential of the Floquet framework as a tool for exploring quantum electrodynamics and optimal control

Random-access quantum memory using chirped pulse phase encoding

Quantum memories capable of faithfully storing and recalling quantum states on-demand are powerful ingredients in bulding quantum networks [arXiv:0806.4195] and quantum information processors [arXiv:1109.3743]. As in conventional computing, key attributes of such memories are high storage density and, crucially, random access, or the ability to read from or write to an arbitrarily chosen register. However, achieving such random access with quantum memories [arXiv:1904.09643] in a dense, hardware-efficient manner remains a challenge, for example requiring dedicated cavities per qubit [arXiv:1109.3743] or pulsed field gradients [arXiv:0908.0101]. Here we introduce a protocol using chirped pulses to encode qubits within an ensemble of quantum two-level systems, offering both random access and naturally supporting dynamical decoupling to enhance the memory lifetime. We demonstrate the protocol in the microwave regime using donor spins in silicon coupled to a superconducting cavity, storing up to four multi-photon microwave pulses and retrieving them on-demand up to 2~ms later. A further advantage is the natural suppression of superradiant echo emission, which we show is critical when approaching unit cooperativity. This approach offers the potential for microwave random access quantum memories with lifetimes exceeding seconds [arXiv:1301.6567, arXiv:2005.09275], while the chirped pulse phase encoding could also be applied in the optical regime to enhance quantum repeaters and networks

Randomized compiling for scalable quantum computing on a noisy superconducting quantum processor

The successful implementation of algorithms on quantum processors relies on the accurate control of quantum bits (qubits) to perform logic gate operations. In this era of noisy intermediate-scale quantum (NISQ) computing, systematic miscalibrations, drift, and crosstalk in the control of qubits can lead to a coherent form of error which has no classical analog. Coherent errors severely limit the performance of quantum algorithms in an unpredictable manner, and mitigating their impact is necessary for realizing reliable quantum computations. Moreover, the average error rates measured by randomized benchmarking and related protocols are not sensitive to the full impact of coherent errors, and therefore do not reliably predict the global performance of quantum algorithms, leaving us unprepared to validate the accuracy of future large-scale quantum computations. Randomized compiling is a protocol designed to overcome these performance limitations by converting coherent errors into stochastic noise, dramatically reducing unpredictable errors in quantum algorithms and enabling accurate predictions of algorithmic performance from error rates measured via cycle benchmarking. In this work, we demonstrate significant performance gains under randomized compiling for the four-qubit quantum Fourier transform algorithm and for random circuits of variable depth on a superconducting quantum processor. Additionally, we accurately predict algorithm performance using experimentally-measured error rates. Our results demonstrate that randomized compiling can be utilized to maximally-leverage and predict the capabilities of modern-day noisy quantum processors, paving the way forward for scalable quantum computing

Superstaq: Deep Optimization of Quantum Programs

We describe Superstaq, a quantum software platform that optimizes the execution of quantum programs by tailoring to underlying hardware primitives. For benchmarks such as the Bernstein-Vazirani algorithm and the Qubit Coupled Cluster chemistry method, we find that deep optimization can improve program execution performance by at least 10x compared to prevailing state-of-the-art compilers. To highlight the versatility of our approach, we present results from several hardware platforms: superconducting qubits (AQT @ LBNL, IBM Quantum, Rigetti), trapped ions (QSCOUT), and neutral atoms (Infleqtion). Across all platforms, we demonstrate new levels of performance and new capabilities that are enabled by deeper integration between quantum programs and the device physics of hardware.Comment: Appearing in IEEE QCE 2023 (Quantum Week) conferenc

Noise Tailoring for Enhancing the Capabilities of Quantum Computers

The successful implementation of algorithms on quantum processors relies on the accurate control of quantum bits (qubits) to perform logic gate operations. However, qubits in the noisy intermediate-scale quantum (NISQ) era are short-lived and susceptible to a variety of errors and noise due to imperfect control signals and incomplete isolation from the surrounding environment. For example, systematic miscalibrations, unwanted entanglement, and crosstalk in the control of qubits can lead to a coherent form of error which has no classical analog. Coherent errors can severely limit the performance of quantum algorithms in an unpredictable manner on timescales shorter than the coherence times of qubits. In recent years, there has been growing interest in using methods which randomize the physical implementation of quantum gates to mitigate the impact of coherent errors, effectively tailoring them into a form of stochastic noise. In this thesis, we study one such method --- randomized compiling --- and show how gate errors under randomized compiling are accurately described by a stochastic Pauli noise model without coherent errors. We demonstrate significant performance gains under randomized compiling for various different quantum algorithms, such as the quantum Fourier transform. We further show that randomized compiling can improve the predictability of quantum algorithms, and enables unique forms of error mitigation for enhancing the performance of quantum computations in the NISQ era. Finally, we show that randomized compiling can reduce worst-case error rates by orders of magnitude, enabling the accurate characterization of quantum gates for fault tolerance. Our results demonstrate that randomized compiling can be utilized to leverage and predict the capabilities of modern-day, noisy quantum processors, paving the way forward for scalable quantum computing and fault tolerant quantum error correction

Optimized SWAP networks with equivalent circuit averaging for QAOA

The SWAP network is a qubit routing sequence that can be used to efficiently execute the Quantum Approximate Optimization Algorithm (QAOA). Even with a minimally connected topology on an $n$-qubit processor, this routing sequence enables $\mathcal{O}({n}^{2})$ operations to execute in $\mathcal{O}(n)$ steps. In this work, we optimize the execution of SWAP networks for QAOA through two techniques. First, we take advantage of an overcomplete set of native hardware operations [including 150-ns controlled-$\frac{{\pi}}{2}$ phase gates with up to 99.67(1)% fidelity] to decompose the relevant quantum gates and SWAP networks in a manner which minimizes circuit depth and maximizes gate cancellation. Second, we introduce equivalent circuit averaging, which randomizes over degrees of freedom in the quantum circuit compilation to reduce the impact of systematic coherent errors. Our techniques are experimentally validated at the Advanced Quantum Testbed through the execution of QAOA circuits for finding the ground state of two- and four-node Sherrington-Kirkpatrick spin-glass models with various randomly sampled parameters. We observe a ${\sim}60$ average reduction in error (total variation distance) for QAOA of depth $p=1$ on four transmon qubits on a superconducting quantum processor