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 Quantum-Classical Computing Alexander McCaskey, Eugen Dumitrescu, Pavel Lougovski, Sarah Powers, Shirley Moore, Tiffany Mintz
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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 open-source 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 pulse-level 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 hardware-independent 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 near-optimal 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 Jordan-Wigner and Bravyi-Kitaev 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 two-qubit gate counts in Fermion-simulation 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 post-optimization 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
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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 error-correcting 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 linearly-executed program is incapable of computing. In this work, we introduce a framework to reconcile the non-deterministic properties of quantum control flow when allocating virtual qubits from a given quantum circuit to physical qubits on a specific NISQ device in the pre-processing 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: Noise-Aware 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 cloud-based software. In order to provide the highest fidelity results to users, it is essential that this software employs hardware-aware optimizations at all levels of the stack, both in the pre-processing and post-processing stages. We present our work in pre-processing error mitigation through variation-aware qubit allocation techniques for gate-based 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 Noisy-Intermediate 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 programming-like 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 NASA-Google-ORNL 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 State-dependent 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 state-dependent noise model is needed to accurately control the behavior of quantum computing programs on today’s noisy hardware. We develop a method for characterizing state-dependent 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 20-qubit fixed-frequency 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 single-qubit operations when expectation values of some operators are needed. It is performed by decomposing the corresponding quantum channels into linear combination of single-qubit 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 trade-off of increased runtime. |
Monday, March 2, 2020 1:27PM - 1:39PM |
B08.00012: qubit-ADAPT-VQE: An adaptive algorithm for constructing hardware-efficient 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 near-term 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 ADAPT-VQE was introduced to build system-adapted ansätze with substantially fewer variational parameters compared to other approaches. However, deep state preparation circuits remain a challenge. Here, we present a hardware-efficient variant of this algorithm called qubit-ADAPT. By numerical simulations, we show that with a well-designed operator pool, qubit-ADAPT can reduce the circuit depth by one order of magnitude while maintaining the same accuracy as the original ADAPT-VQE. This result highlights the promise of adaptive ansätze algorithms on near-term quantum devices. |
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