Bulletin of the American Physical Society
APS March Meeting 2018
Monday–Friday, March 5–9, 2018; Los Angeles, California
Session C39: Scaling up Quantum ComputersFocus

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Sponsoring Units: DQI Chair: Peter Groszkowski, Northwestern University Room: LACC 501B 
Monday, March 5, 2018 2:30PM  3:06PM 
C39.00001: Optimization and Planning Approaches for Lowlevel Hardware Compilation of Quantum Circuits Invited Speaker: Davide Venturelli , Minh Do , Kyle Booth , Eleanor Rieffel , Jeremy Frank , Christopher Beck As prototypes of quantum processing units (QPU) mature, it becomes increasingly pressing to design approaches to maximize the performance of noisy devices running implementations of algorithms that can be benchmarked in the nearterm. Minimizing the runtime of quantum circuits is particularly critical in early QPUs subject by decoherence which do not have resources for error correction. We show that the circuit compilation problem naturally maps to a planning problem similar to that encountered in automating operations of multiple agents that cooperatively need to achieve a goal. We demonstrate that stateofthe art Planning and Constraint Programming can effectively address the quantum circuit compilation problem. We applied our general compilation methods to the problem of compiling circuits related to the Quantum Alternating Operator Ansatz (QAOA), a prominent example of a quantum metaheuristics, for simply structured optimization problems, such as MaxCut. Formulations of practical discrete optimization problems within QAOA framework results in circuits that are logically composed of a large number of commuting multiqubit gates whose execution could be scheduled in a combinatorial number of ways. The architectural constraints of realworld QPUs, with available elementary gates manufactured in a planar nearest neighbor irregular graph layout and with each qubit individually calibrated to operate with different duration and fidelity. We exhibit efficient lowlevel compilation of QAOA circuits in this inhomogeneous, underconstrained setting, exemplified by the Rigetti, Google and IBM chips. We also discuss the general problem of quantum circuit compilation, taking into account additional constraints such as cross talk and additional algorithmic primitives such as measurement, in addition to optimizing the insertion of swap operations and accounting for different durations of synthesized logical gates. 
Monday, March 5, 2018 3:06PM  3:18PM 
C39.00002: Quantum Computer Programming, Compilation, and Execution with XACC Alexander McCaskey , Eugen Dumitrescu , Dmitry Liakh , Travis Humble We demonstrate how nearterm quantum processing units (QPUs) can be integrated into highperformance computing using applications for quantum chemistry, machine learning, and combinatorial optimization. The eXtremescale ACCelerator programming model (XACC) is an opensource framework that supports quantum acceleration of scientific workflows across many different vendor QPUs. We develop the XACC programming model as a coprocessor model akin to the design of OpenCL or CUDA for GPUs, in which the framework offloads computational work by defining quantum kernels for execution on an attached QPU accelerator. We demonstrate an extensible quantum compilation mechanism with general quantum circuit optimization and transformation capabilities. We show how this approach is agnostic to quantum programming language and QPU hardware, and we demonstrate how XACC enables hybrid computing programs to be ported to multiple processors for benchmarking, verification and validation. Finally, we measure the utility of this programming model by demonstrating a distributedmemory implementation of the variational quantum eigensolver. 
Monday, March 5, 2018 3:18PM  3:30PM 
C39.00003: Automating Quantum Algorithms Design Lukasz Cincio , Yigit Subasi , Francesco Caravelli , Andrew Sornborger , Patrick Coles Taking advantage of exponential speedups offered by quantum computers 
Monday, March 5, 2018 3:30PM  4:06PM 
C39.00004: Closing the Gap Between Quantum Algorithms and Hardware
through SoftwareEnabled Vertical Integration and CoDesign Invited Speaker: Frederic Chong

Monday, March 5, 2018 4:06PM  4:18PM 
C39.00005: Automatic tuning and drift control for quantum information processing Kevin Young , Robin BlumeKohout Quantum information processors are terrifically complicated systems. A quantum processor's controllable behavior depends quite sensitively on a large number of externally controllable parameters, and the processor will only function as intended if these parameters are (1) carefully calibrated, and (2) stabilized to avoid drift over time. As these processors' precision and size (number of qubits) grow, calibration and drift control will need to be optimized and automated. In this talk, we introduce fast, parallelizable feedback protocols for tuning up quantum processors and controlling their drift. These protocols rely only on resources that are already present in all modern quantum processors: the ability to perform quantum circuits, make measurements. They are suitable for both offline tuning and online drift control. 
Monday, March 5, 2018 4:18PM  4:30PM 
C39.00006: Quantum error correction in crossbar architectures Jonas Helsen , Mark Steudtner , Menno Veldhorst , Stephanie Wehner A central challenge for the scaling of quantum computing systems is the need to control all qubits in the system without a large overhead. A solution for this problem in classical computing comes in the form of so called crossbar architectures. Recently we made a proposal for a large scale quantum processor to be implemented in silicon quantum dots. This system features a crossbar control architecture which limits parallel single qubit control, but allows the scheme to overcome control scaling issues that form a major hurdle to large scale quantum computing systems. In this work, we develop a language that makes it possible to easily map quantum circuits to crossbar systems, taking into account their architecture and control limitations. Using this language we show how to map well known quantum error correction codes such as the planar surface and color codes in this limited control setting with only a small overhead in time. We analyze the logical error behavior of this surface code mapping for estimated experimental parameters of the crossbar system in and conclude that logical error suppression to a level useful for real quantum computation is feasible. 
Monday, March 5, 2018 4:30PM  4:42PM 
C39.00007: Machine Learning of Noise in SingleQubit Hardware Travis Scholten , Robin BlumeKohout As quantum information processors (QIPs) grow from 2, to 5, to 16 or more qubits, characterizing their behavior rapidly becomes challenging. Techniques commonly used today, such as tomography and randomized benchmarking, are unlikely to scale easily to many qubits while providing useful debugging information. QIP development will require fast, scalable, and accurate techniques that extract useful information about noise affecting QIPs and the errors they are likely to suffer in use. Machine learning tools are a promising alternative to the brute force and/or adhoc statistical methods that underlie most existing techniques. Here, we demonstrate a machine learning classifier that distinguishes whether the noise on a singlequbit QIP is stochastic or coherent. The classifier uses data from certain structured circuits, specifically those used for gate set tomography, but does not rely on any of the standard statistical tools for analyzing such data, and can in principle be applied to arbitrary data that contains information about the property of interest. 
Monday, March 5, 2018 4:42PM  4:54PM 
C39.00008: Detecting and characterizing qubit crosstalk Kenneth Rudinger , Mohan Sarovar , Dylan Langharst , Timothy Proctor , Kevin Young , Erik Nieslen , Robin BlumeKohout Quantum information processors have grown rapidly in both size and fidelity. Currently available processors comprise 5, 8, or even 16 qubits, with 1 and 2qubit gate infidelities below 1%. One of the looming obstacles to successfully running small algorithms or quantum error correction is crosstalk: each qubit may be influenced by the state of its neighbors, or by the operations performed on those neighbors. Crosstalk could ruin any desired computation if not eliminated or mitigated. We have been developing and testing methods to detect, quantify, and characterize crosstalk so that it can be eliminated by device engineering, or mitigated through modeling and adaptation. In this talk we provide a comprehensive taxonomy of crosstalk, and present hardwareagnostic protocols to diagnose and characterize it. Finally, we demonstrate these techniques by applying them to experimental data from superconducting qubit systems, and show that we can characterize signatures of various distinct crosstalk processes. 
Monday, March 5, 2018 4:54PM  5:06PM 
C39.00009: Measuring and Suppressing Error Correlations in Quantum Circuits Claire Edmunds , Cornelius Hempel , Sandeep Mavadia , Harrison Ball , Robert Harris , Virginia Frey , Thomas Stace , Michael Biercuk Quantum error correction, fundamental to enabling largescale quantum computing, relies on stochastic errors throughout a quantum circuit. Correlated errors between sequential logic gates violate this requirement, but are a realistic element of laboratory environments. To facilitate QEC it is necessary to identify and suppress such errors at both the physical and virtual layers of the quantum processor architecture. 
Monday, March 5, 2018 5:06PM  5:18PM 
C39.00010: Measuring the Renyi entropy of a twosite FermiHubbard model on a trapped ion quantum computer Norbert Linke , Sonika Johri , K.A. Landsman , Caroline Figgatt , C. Monroe , Anne Matsuura The efficient simulation of correlated quantum systems is the most promising nearterm application of quantum computers. Here, we present the calculation of the second Renyi entropy of the ground state of the twosite FermiHubbard model on a 5 qubit programmable quantum computer based on trapped ions. Our work illustrates efficient mapping of the electronic system to the qubit Hilbert space, circuit compilation and implementation on a physical quantum computer, optimized use of finite quantum gate depth, extraction of a nonlinear characteristic of a quantum state using the controlledswap gate, and effective reduction of experimental errors by over 40% using a symmetrybased postselection scheme. Thus we demonstrate the first scalable measurement of entanglement on a digital quantum computer, which on larger systems will provide insights into manybody quantum systems that are impossible to simulate on classical computers. 
Monday, March 5, 2018 5:18PM  5:30PM 
C39.00011: Tensor network simulator of the surface code in the presence of noisy syndromes Hari Krovi , Diego Ristè , Borja Peropadre The performance of the surface code (SC) is usually estimated under Pauli errors, as they can be efficiently simulated using the stabilizer formalism. However, Pauli errors do not reflect the actual decoherence mechanisms that physical qubits undergo, which may negatively impact the predictions about the code performance in actual experiments. Here we present a tensor network simulator of the SC subject to arbitrary physical local noise [1], such as relaxation and dephasing, and always present ZZ interactions. Our simulation includes not only noisy data qubits, but also noisy syndrome qubits resulting in imperfect parity measurements. The simulator is exact for small surface code distances, and relies on approximate contraction techniques to extend the result to larger patches. We derive logical error rates on SC implemented in cirQED architectures. 
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