Bulletin of the American Physical Society
APS March Meeting 2020
Volume 65, Number 1
Monday–Friday, March 2–6, 2020; Denver, Colorado
Session B08: Programming and Compiling: the QC Stack session 
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Sponsoring Units: DQI Chair: Ali Javadi, IBM Room: 104 
Monday, March 2, 2020 11:15AM  11:27AM 
B08.00001: Extending Modern C++ for Heterogeneous QuantumClassical Computing Alexander McCaskey, Eugen Dumitrescu, Pavel Lougovski, Sarah Powers, Shirley Moore, Tiffany Mintz

Monday, March 2, 2020 11:27AM  11:39AM 
B08.00002: OpenPulse: Software for Experimental Physicists in Quantum Computing Lauren Capelluto, Thomas Alexander The quantum computing industry provides public access to superconducting qubit systems through opensource quantum computing frameworks such as Qiskit. Compilation techniques play a critical role in leveraging these small scale, noisy devices by driving down error rates in program execution. The compiler backend decomposes quantum operations into microwave pulses which aim to realize the desired quantum operations with the highest fidelity possible. We introduce OpenPulse, a pulselevel programming component of Qiskit, that hands over analog control of quantum computing systems to the user. Using OpenPulse, the user can specify the exact time dynamics of a program by scheduling arbitrary waveforms on control system resources, and can recover the time dynamics of the measured output. This is sufficient to allow the user to freely characterize, verify and validate the quantum system, and to explore gate optimization and error mitigation techniques to enhance system performance. OpenPulse enables the community to collectively push the field onwards towards practical computation. 
Monday, March 2, 2020 11:39AM  11:51AM 
B08.00003: qupulse: A quantum computing pulse parametrization and sequencing framework Pascal Cerfontaine, Simon Humpohl, Lukas Prediger, Patrick Bethke, Eugen Kammerloher, Lars Schreiber, Stefanie Meyer, Bernhard Rumpe, Hendrik Bluhm We present an open source python package for the operation of advanced qubit control experiments, which emerged from our experimental work on spin qubits. It allows for hierarchical definition of control pulses and pulse sequences with an arbitrary nesting depth in a hardwareindependent way. 
Monday, March 2, 2020 11:51AM  12:03PM 
B08.00004: Compiled Quantum Optimization Algorithms in NISQ Processors Davide Venturelli, Minh Do, Bryan O'Gorman, Zhihui Wang, Eleanor Rieffel, Jeremy Frank, Ryan M LaRose, Vanesa Gomez Gonzalez We discuss resource estimation and synthesis optimization results related to compilation of a variety of structured variational algorithms. Specifically, we look at software tools and methods for finding a swap network that allows the efficient execution of algorithms on different superconducting chips (Rigetti’s Aspen Chip, Google’s Sycamore, IBM’s Tokyo). Efficiency is measured in terms of the total temporal makespan of execution of the compiled quantum circuit. Examples include algorithms for scheduling and asset allocation with both soft and hard constraints. We address two different regimes: where nearoptimal compilations can be found, and where only heuristics (e.g., temporal planning methods) are available. 
Monday, March 2, 2020 12:03PM  12:15PM 
B08.00005: Optimizing compiler for Fermion simulation circuits Qingfeng Wang, Yunseong Nam, Christopher Roy Monroe JordanWigner and BravyiKitaev transformations are the two widely known examples of the Fermion $\rightarrow$ qubit operator mappings. There exist however at least $O(2^{n^2})$ possible such mappings. Thus, an appropriate choice of the mapping can result in the reduction of quantum resource cost in practice, such as twoqubit gate counts in Fermionsimulation circuits. In this talk, I will present a methodology that may be used to optimize these simulation circuits, leveraging the vastly large space from which a suitable mapping may be drawn. A series of heuristics will be explored to arrive at the postoptimization quantum circuits. 
Monday, March 2, 2020 12:15PM  12:27PM 
B08.00006: Heuristics for Quantum Compiling with a Continuous Gate Set Marc Davis, Costin Iancu

Monday, March 2, 2020 12:27PM  12:39PM 
B08.00007: Introducing Control Flow in Qubit Allocation for Quantum Turing Machines Michael Cubeddu, Will T Finigan, Prineha Narang, Vitali Vinokour To make NISQ devices practical for quantum software engineers, novel programming tools with maximal flexibility have to be developed. Several proposed algorithms and errorcorrecting codes for near term devices require the ability to execute classical control statements based on quantum measurements. However, the unpredictable nature of control flow on a quantum device complicates the compilation process in the presence of variable noise. The functionality of control flow allows for expanded algorithmic power of the programming language in the form of conditional statements and loops, which a linearlyexecuted program is incapable of computing. In this work, we introduce a framework to reconcile the nondeterministic properties of quantum control flow when allocating virtual qubits from a given quantum circuit to physical qubits on a specific NISQ device in the preprocessing and compiling stage. We consider the respective connectivity and fidelity constraints, with the goal of reducing the expected error rate of the computation. Our protocols will allow for quantum developers and NISQ devices together to more efficiently exploit the compelling algorithmic power that the quantum Turing machine model provides. 
Monday, March 2, 2020 12:39PM  12:51PM 
B08.00008: NoiseAware Qubit Allocation Techniques for NISQ Devices Michael Cubeddu, Will Finigan, Vitali Vinokour, Prineha Narang With a growing diversity in devices, control systems, topologies, programming languages, and applications, computation in the NISQ era needs to be navigated through adaptable cloudbased software. In order to provide the highest fidelity results to users, it is essential that this software employs hardwareaware optimizations at all levels of the stack, both in the preprocessing and postprocessing stages. We present our work in preprocessing error mitigation through variationaware qubit allocation techniques for gatebased quantum computers, with a focus on superconducting platforms. We formulate a description of the “allocation problem” and propose several solutions: a deterministic algorithm for finding the optimal solution as well as a more scalable and flexible randomized heuristic approach. We will present and validate the implications of these different techniques on various NISQ devices. 
Monday, March 2, 2020 12:51PM  1:03PM 
B08.00009: Benchmarking NISQ Devices Using qFlex Salvatore Mandra, Benjamin Villalonga, Dmitry Liakh, Sergio Boixo Quantum supremacy is the task to perform a quantum calculation on a NoisyIntermediate Scale Quantum (NISQ) device that cannot be performed on the latest and most powerful supercomputer by using the best known classical simulator. To this end, the Google team has designed a series of benchmarks, based on the sampling of Random Quantum Circuits (RQCs), to challenge classical supercomputers. In a programminglike language, the RQC sampling corresponds to the first “Hello, World!” program in the quantum computing era. In my talk I will present qFlex, a fast and flexible software to simulate large RQCs to both verify and benchmark NISQ devices. qFlex is a NASAGoogleORNL collaboration and it's now publicity available at https://github.com/ngnrsaa/qFlex. As part of my talk, I will show some live demos and present our latest results on benchmarking available NISQ devices. 
Monday, March 2, 2020 1:03PM  1:15PM 
B08.00010: Characterization of Statedependent Noise in NISQ Processors Ronald J Sadlier, Travis Humble Characterization of the quantum operations in current NISQ devices reveal noise spectra that are highly dependent on the underlying quantum state. These results indicate that a statedependent noise model is needed to accurately control the behavior of quantum computing programs on today’s noisy hardware. We develop a method for characterizing statedependent errors based on classical truth tables for the gate operations, and we use these results to compute the amplitudes of the corresponding channel operators. Using this method, we characterize a 20qubit fixedfrequency superconducting transmon processor to develop a noise model for this device. We then use this noise model to estimate the fidelity of quantum circuits executed on the hardware and compare these results with tomographic fidelities. 
Monday, March 2, 2020 1:15PM  1:27PM 
B08.00011: Strategies for reducing the number of controlled gates on noisy intermediate scale quantum circuits Kosuke Mitarai, Keisuke Fujii We show that certain kind of controlled gates can be decomposed into a sequence of singlequbit operations when expectation values of some operators are needed. It is performed by decomposing the corresponding quantum channels into linear combination of singlequbit channels. Firstly, we discuss the usefulness of the presented method in variational algorithms which runs on quantum computer by showing that it can extract information about the derivatives of the parametrized state without adding ancilla qubit. It can also be applied for measuring the time correlation of observables in quantum simulations. Finally, we show that the method can decompose a large, in the number of qubits, quatnum circuit into smaller ones. Although the runtime of this method scales exponentially in the number of decompositions performed, it reduces the requirement on the hardware by reducing the number of gates and qubits in the tradeoff of increased runtime. 
Monday, March 2, 2020 1:27PM  1:39PM 
B08.00012: qubitADAPTVQE: An adaptive algorithm for constructing hardwareefficient ansätze on a quantum processor Ho Lun Tang, Harper Grimsley, Nicholas J. Mayhall, Edwin Barnes, Sophia E. Economou The variational quantum eigensolver, being a promising algorithm on nearterm quantum devices, is extensively used for finding the ground state energy of molecular Hamiltonians. The classical and quantum resources needed by this algorithm, the number of variational parameters in the wavefunction ansatz and the depths of the state preparation circuits, critically depend on the choice of ansatz. Recently, an algorithm termed ADAPTVQE was introduced to build systemadapted ansätze with substantially fewer variational parameters compared to other approaches. However, deep state preparation circuits remain a challenge. Here, we present a hardwareefficient variant of this algorithm called qubitADAPT. By numerical simulations, we show that with a welldesigned operator pool, qubitADAPT can reduce the circuit depth by one order of magnitude while maintaining the same accuracy as the original ADAPTVQE. This result highlights the promise of adaptive ansätze algorithms on nearterm quantum devices. 
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