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Current quantum computers have very different qubit implementations, instruction sets, qubit connectivity, and noise characteristics. Using real-system evaluations on seven quantum systems from three leading vendors, our work explores fundamental design questions concerning hardware choices, architecture, and compilation.

Two-qubit gate performance is vital for scaling up ion-trap quantum computing. Optimized quantum control is needed to achieve reductions in gate-time and gate error-rate. We describe two-qubit gates with addressed Raman beams within a linear trapped-ion chain by a quantum master equation (QME). The QME incorporates the single-ion two-photon effective Rabi frequency, Autler-Townes and vibrational Bloch-Siegert energy shifts, off-resonant transitions, Raman and Rayleigh scattering, laser-power fluctuations, motional heating, cross-Kerr phonon coupling, laser spillover, asymmetric addressing beams and an imperfect initial motional ground state, with no fitting parameters. Whereas state-of-the-art methods are oblivious to these effects in the gate design procedure. We employ global optimization to design pulse sequences for achieving a robust rapid two-qubit gate for seven trapped $^{171}$Yb$^{+}$ ions by optimizing over numerically integrated QME solutions. Here, robust means resilient against slow drift of motional frequencies, and rapid means gate execution where the effective Rabi frequency is comparable to the detuning of the laser from the ion's bare electronic transition. Our robust quantum control delivers rapid high-quality two-qubit gates in long ion chains, enabling scalable quantum computing with trapped ions., Comment: Seven pages, two figures

Combinatorial optimization problems on graphs have broad applications in science and engineering. The Quantum Approximate Optimization Algorithm (QAOA) is a method to solve these problems on a quantum computer by applying multiple rounds of variational circuits. However, there exist several challenges limiting the real-world applications of QAOA. In this paper, we demonstrate on a trapped-ion quantum computer that QAOA results improve with the number of rounds for multiple problems on several arbitrary graphs. We also demonstrate an advanced mixing Hamiltonian that allows sampling of all optimal solutions with predetermined weights. Our results are a step towards applying quantum algorithms to real-world problems., Comment: 8 pages, 5 figures

Tracking the dynamics of physical systems in real time is a prime application of digital quantum computers. Using a trapped-ion system with up to six qubits, we simulate the real-time dynamics of a lattice gauge theory in 1+1 dimensions, i.e., the lattice Schwinger model, and demonstrate non-perturbative effects such as pair creation for times much longer than previously accessible. We study the gate requirement of two formulations of the model using the Suzuki-Trotter product formula, as well as the trade-off between errors from the ordering of the Hamiltonian terms, the Trotter step size, and experimental imperfections. To mitigate experimental errors, a recent symmetry-protection protocol for suppressing coherent errors and a symmetry-inspired post-selection scheme are applied. This work demonstrates the integrated theoretical, algorithmic, and experimental approach that is essential for efficient simulation of lattice gauge theories and other complex physical systems.

Out-of-time-ordered correlators (OTOCs) are a key observable in a wide range of interconnected fields including many-body physics, quantum information science, and quantum gravity. Measuring OTOCs using near-term quantum simulators will extend our ability to explore fundamental aspects of these fields and the subtle connections between them. Here, we demonstrate an experimental method to measure OTOCs at finite temperatures and use the method to study their temperature dependence. These measurements are performed on a digital quantum computer running a simulation of the transverse field Ising model. Our flexible method, based on the creation of a thermofield double state, can be extended to other models and enables us to probe the OTOC's temperature-dependent decay rate. Measuring this decay rate opens up the possibility of testing the fundamental temperature-dependent bounds on quantum information scrambling., 6 pages, 3 figures

Fault-tolerant quantum error correction (QEC) is crucial for unlocking the true power of quantum computers. QEC codes use multiple physical qubits to encode a logical qubit, which is protected against errors at the physical qubit level. Here, we use a trapped-ion system to experimentally prepare $m$-qubit Greenberger-Horne-Zeilinger states and sample the measurement results to construct $m\ifmmode\times\else\texttimes\fi{}m$ logical states of the $[[{m}^{2},1,m]]$ Shor code, up to $m=7$. The synthetic logical fidelity shows how deeper encoding can compensate for additional gate errors in state preparation for larger logical states. However, the optimal code size depends on the physical error rate and we find that $m=5$ has the best performance in our system. We further realize the direct logical encoding of the $[[9,1,3]]$ Shor code on nine qubits in a 13-ion chain for comparison, with $98.8(1)\mathrm{%}$ and $98.5(1)\mathrm{%}$ fidelity for state ${|\ifmmode\pm\else\textpm\fi{}⟩}_{L}$, respectively.

A disordered quantum system of interacting particles exhibits localized behavior when the disorder is large compared to the interaction strength. Studying this phenomenon on a quantum computer with no, or limited, error correction is challenging because even weak coupling to a thermal environment destroys most signatures of localization. Fortunately, spectral functions of local operators are known to contain features that can survive the presence of noise. In these spectra, discrete peaks and a soft gap at low frequencies compared to the thermal phase indicate localization. Here, we present the computation of spectral functions on a trapped-ion quantum computer for a one-dimensional Heisenberg model with disorder. Further, we design an error-mitigation technique which is effective at removing the noise from the measurement allowing clear signatures of localization to emerge as the disorder increases. Thus, we show that spectral functions can serve as a robust and scalable diagnostic of many-body localization on current and future generations of quantum computers.

In order to scale up quantum processors and achieve a quantum advantage, it is crucial to economize on the power requirement of two-qubit gates, make them robust to drift in experimental parameters, and shorten the gate times. Applicable to all quantum computer architectures whose two-qubit gates rely on phase-space closure, we present here a new gate-optimizing principle according to which negligible amounts of gate fidelity are traded for substantial savings in power, which, in turn, can be traded for substantial increases in gate speed and/or qubit connectivity. As a concrete example, we illustrate the method by constructing optimal pulses for entangling gates on a pair of ions within a trapped-ion chain, one of the leading quantum computing architectures. Our method is direct, noniterative, and linear, and, in some parameter regimes, constructs gate-steering pulses requiring up to an order of magnitude less power than the standard method. Additionally, our method provides increased robustness to mode drift. We verify the new trade-off principle experimentally on our trapped-ion quantum computer.

We propose a set of Bell-type nonlocal games that can be used to prove an unconditional quantum advantage in an objective and hardware-agnostic manner. In these games, the circuit depth needed to prepare a cyclic cluster state and measure a subset of its Pauli stabilizers on a quantum computer is compared to that of classical Boolean circuits with the same, nearest-neighboring gate connectivity. Using a circuit-based trapped-ion quantum computer, we prepare and measure a six-qubit cyclic cluster state with an overall fidelity of 60.6% and 66.4%, before and after correcting for measurement-readout errors, respectively. Our experimental results indicate that while this fidelity readily passes conventional (or depth-0) Bell bounds for local hidden-variable models, it is on the cusp of demonstrating a higher probability of success than what is possible by depth-1 classical circuits. Our games offer a practical and scalable set of quantitative benchmarks for quantum computers in the pre-fault-tolerant regime as the number of qubits available increases., Comment: Published in Physical Review Research, 12 + 9 pages, 4 figures, 3 tables

The quantum walk formalism is a widely used and highly successful framework for modeling quantum systems, such as simulations of the Dirac equation, different dynamics in both the low and high energy regime, and for developing a wide range of quantum algorithms. Here we present the circuit-based implementation of a discrete-time quantum walk in position space on a five-qubit trapped-ion quantum processor. We encode the space of walker positions in particular multi-qubit states and program the system to operate with different quantum walk parameters, experimentally realizing a Dirac cellular automaton with tunable mass parameter. The quantum walk circuits and position state mapping scale favorably to a larger model and physical systems, allowing the implementation of any algorithm based on discrete-time quantum walks algorithm and the dynamics associated with the discretized version of the Dirac equation., 8 pages, 6 figures

In recent years, Quantum Computing (QC) has progressed to the point where small working prototypes are available for use. Termed Noisy Intermediate-Scale Quantum (NISQ) computers, these prototypes are too small for large benchmarks or even for Quantum Error Correction, but they do have sufficient resources to run small benchmarks, particularly if compiled with optimizations to make use of scarce qubits and limited operation counts and coherence times. QC has not yet, however, settled on a particular preferred device implementation technology, and indeed different NISQ prototypes implement qubits with very different physical approaches and therefore widely-varying device and machine characteristics. Our work performs a full-stack, benchmark-driven hardware-software analysis of QC systems. We evaluate QC architectural possibilities, software-visible gates, and software optimizations to tackle fundamental design questions about gate set choices, communication topology, the factors affecting benchmark performance and compiler optimizations. In order to answer key cross-technology and cross-platform design questions, our work has built the first top-to-bottom toolflow to target different qubit device technologies, including superconducting and trapped ion qubits which are the current QC front-runners. We use our toolflow, TriQ, to conduct {\em real-system} measurements on 7 running QC prototypes from 3 different groups, IBM, Rigetti, and University of Maryland. From these real-system experiences at QC's hardware-software interface, we make observations about native and software-visible gates for different QC technologies, communication topologies, and the value of noise-aware compilation even on lower-noise platforms. This is the largest cross-platform real-system QC study performed thus far; its results have the potential to inform both QC device and compiler design going forward., Comment: Preprint of a publication in ISCA 2019

Significance Our experiment prepares two types of nontrivial quantum states on a trapped ion quantum computer: the thermofield double state of the transverse-field Ising model at arbitrary temperature and the quantum critical state of the zero-temperature model. We use techniques motivated by the quantum approximate optimization algorithm, and we implement a hybrid quantum–classical optimization loop to prepare the quantum critical state. Our results pave the way for exploring strongly correlated models at finite temperature and teleportation protocols inspired by black hole physics., Finite-temperature phases of many-body quantum systems are fundamental to phenomena ranging from condensed-matter physics to cosmology, yet they are generally difficult to simulate. Using an ion trap quantum computer and protocols motivated by the quantum approximate optimization algorithm (QAOA), we generate nontrivial thermal quantum states of the transverse-field Ising model (TFIM) by preparing thermofield double states at a variety of temperatures. We also prepare the critical state of the TFIM at zero temperature using quantum–classical hybrid optimization. The entanglement structure of thermofield double and critical states plays a key role in the study of black holes, and our work simulates such nontrivial structures on a quantum computer. Moreover, we find that the variational quantum circuits exhibit noise thresholds above which the lowest-depth QAOA circuits provide the best results.

We train generative modeling circuits on a quantum hybrid computer showing an optimization strategy and a resource trade-off., Generative modeling is a flavor of machine learning with applications ranging from computer vision to chemical design. It is expected to be one of the techniques most suited to take advantage of the additional resources provided by near-term quantum computers. Here, we implement a data-driven quantum circuit training algorithm on the canonical Bars-and-Stripes dataset using a quantum-classical hybrid machine. The training proceeds by running parameterized circuits on a trapped ion quantum computer and feeding the results to a classical optimizer. We apply two separate strategies, Particle Swarm and Bayesian optimization to this task. We show that the convergence of the quantum circuit to the target distribution depends critically on both the quantum hardware and classical optimization strategy. Our study represents the first successful training of a high-dimensional universal quantum circuit and highlights the promise and challenges associated with hybrid learning schemes.

Purpose. To optimize the conditions for determining Caco-2 permeation of HIV protease inhibitors and other lipophilic compounds, and to compare cyclic urea HIV protease inhibitors with marketed compounds.

DMP 323 is the first clinical candidate from a novel series of HIV protease inhibitors having a cyclic urea structural backbone. In dogs dosed with glycol-based vehicles, DMP 323 was approximately 50% orally bioavailable after a 100 mg dose, but bioavailability was almost 10-fold lower when a 350 mg dose was administered. Since DMP 323 has very low water solubility, it was expected that this loss of bioavailability at a high dose was due to drug precipitation in the aqueous fluids of the gastrointestinal tract. Clinically, high doses were desired so as to maximize antiviral effects. Therefore, formulation strategies to improve bioavailability at high doses were examined. Bioavailability of 350 mg doses in dogs was not improved using formulations consisting of glycols with low concentrations of added surfactants, or with solid dispersions of DMP 323 in PEG or PEG/PVP matrices. An alternative approach was to use formulations comprised primarily of an amphiphilic material such as Gelucire 44/14 (a mixture of glycerides and PEG esters). Bioavailability was increased to 50% using a semi-solid Gelucire 44/14 formulation, compared with the 6% or lower value observed at this dose with glycol vehicles. Gelucire 44/14 increased DMP 323 aqueous solubility and dissolution rate, as did other amphiphilic materials with high HLB values. Oral bioavailability of DMP 323 is determined by the DMP 323 dose, the solubilization afforded by the vehicle when diluted into an aqueous environment, and the vehicle dose. Amphiphilic vehicles such as Gelucire 44/14 could be used to administer high doses of DMP 323 without compromising oral bioavailability. A limitation of this approach is the volume of vehicle required.

The purpose of this work was to evaluate compaction of the beads containing microcrystalline cellulose (MCC). Although MCC in its powder form is universally recognized as a very compressible material, studies in these laboratories demonstrated that MCC beads prepared by extrusion/spheronization were not. In fact, MCC beads are very hard and not easily deformable or broken. Therefore, the objectives of this work were to modify the bead composition by incorporating materials which might change the bead compactibility and to describe the effects. The dissolution properties of the compacted forms were also evaluated.To study the compaction behavior of the MCC beads it was necessary to modify the Athy-Heckel equation to describe compression and to combine that analysis with the Leuenberger equation to describe consolidation.

DPC 961 is a low-solubility, high-permeability, second-generation non-nucleoside reverse transcriptase inhibitor. The purpose of these studies was to evaluate the effects of drug substance and formulation variables on DPC 961 oral absorption, and to compare fed and fasted state oral absorption. To accomplish this, groups of four to six dogs were dosed with various formulations of DPC 961 under fasted or fed conditions, and DPC 961 pharmacokinetics were examined. Absolute oral bioavailability, based on i.v. AUC in the same dogs, was 24% after a suspension dose in fasted dogs and was 51% in fed dogs. Bioavailability with an unoptimized tablet formulation was 30% in fasted dogs and 86% in fed dogs. DPC 961 oral absorption was shown to be dependent on drug substance particle size in fasted dogs, after dosing with a tablet formulation where only the drug substance particle size was varied, but there was no difference in fed dogs. AUC and C(max) increased in proportion with increases in tablet strength from 100 to 400 mg, using tablets manufactured from a common granulation. Tablets made with 50 and 66% drug loadings showed similar relative oral bioavailabilities. Tablets prepared with two different polymorphic forms of DPC 961 were also compared, and these were found to be equivalent. These studies provided a useful component of the formulation development process, to help identify and control the variables affecting oral absorption of this potential new therapeutic agent.

The Hutchinson-Gilford syndrome, commonly referred to as progeria, is a rare childhood syndrome that results in premature ageing. We focus on two anaesthetics administered to a child with progeria and a review of the available literature.

Arthrogryposis multiplex congenita (AMC) is a spectrum syndrome of multiple persistent limb contractures often accompanied by associated anomalies, including cleft palate, genitourinary defects, gastroschisis, and cardiac defects. Pediatric patients with AMC frequently present for multiple surgeries requiring general endotracheal anesthesia. We describe our anesthetic experience with the laryngeal mask airway and endotracheal tube in two neonates with AMC and severe micrognathia. We discuss AMC and outline the problems encountered in difficult airway management.