Bulletin of the American Physical Society
APS March Meeting 2023
Volume 68, Number 3
Las Vegas, Nevada (March 5-10)
Virtual (March 20-22); Time Zone: Pacific Time
Session F70: Quantum Circuit Expression and Simulation |
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Sponsoring Units: DQI Chair: Zoltan Zimboras, Wigner Research Center for Physics Room: Room 409 |
Tuesday, March 7, 2023 8:00AM - 8:12AM |
F70.00001: Highly optimized quantum circuits synthesized via data-flow engines Zoltan Zimboras, Peter Rakyta, Gregory Morse, Oskar Mencer The formulation of quantum programs in terms of the fewest number of gate operations is crucial to retrieve meaningful results from the noisy quantum processors accessible these days. In this work we demonstrate a use case for Field Programmable Gate Array (FPGA) based data-flow engines (DFEs) to scale up optimization based quantum compilers to synthesize circuits up to 10-qubit unitaries. The developed DFE quantum computer simulator was designed to simulate arbitrary quantum circuit consisting of single qubit rotations and controlled two-qubit gates on FPGA chips. In our benchmark with the QISKIT package, the depth of the circuits produced by the SQUANDER package (with the DFE accelerator support) were less by $97\%$ on average, while the fidelity of the circuits was still close to unity by an error of 10^{-4}. |
Tuesday, March 7, 2023 8:12AM - 8:24AM |
F70.00002: Accelerating quantum algorithms with resource states William J Huggins We often analyze the computational complexity of a quantum algorithm in terms of the total amount of time and space required. In some cases, however, it is natural to allow a quantum algorithm access to a pre-prepared pool of resource states. In this talk, I consider an alternative cost model that neglects the cost of preparing (but not storing) such a pool of resource states. I argue that this cost model might be appropriate for thinking about real-world quantum advantage for certain algorithms. I also show that a quadratic improvement in the space-time volume for certain families of circuits can be obtained under this cost model. |
Tuesday, March 7, 2023 8:24AM - 8:36AM |
F70.00003: Improving Performance and Debuggability of Variational Quantum Algorithms using Compressed Sensing Kun Liu, Tianyi Hao, Swamit Tannu Variational quantum algorithms (VQAs) have the potential to solve practical problems using contemporary Noisy Intermediate Scale Quantum (NISQ) computers in the near term. VQAs find near-optimal solutions in the presence of qubit errors by classically optimizing a loss function computed by parameterized quantum circuits. However, developing and testing VQAs is challenging due to the limited availability of quantum hardware, their high error rates, and the significant overhead of classical simulations. Furthermore, VQA researchers must pick the right initialization for circuit parameters, utilize suitable classical optimizer configurations, and deploy appropriate error mitigation methods. Unfortunately, these tasks are done in an ad-hoc manner today, as there are no software tools to configure and tune the VQA hyperparameters. |
Tuesday, March 7, 2023 8:36AM - 8:48AM |
F70.00004: Approximate classical simulation of noisy quantum circuits Danylo Lykov, Yuri Alexeev, William Berquist, Minzhao Liu In this presentation, we will demonstrate our approaches to approximately simulate noisy quantum systems on classical hardware. The commonly used density matrix approach scales as 4^N which provides a challenge. We propose various approaches to reduce the simulation complexity at a cost of introducing numerical error in the final simulation result. We demonstrate large scale HPC simulations and compare the performance for various types of quantum circuits. Our approach allows to simulate hundreds of qubits with very small error in the final result. Finally, we will discuss limitations and possible improvements of these methods. |
Tuesday, March 7, 2023 8:48AM - 9:00AM |
F70.00005: Quantum Circuit Un-optimization as a Benchmark Task for Quantum Compilers Yusei Mori, Hideaki Hakoshima, Kyohei Sudo, Toshio Mori, Kosuke Mitarai, Keisuke Fujii Compilation of large complex quantum circuits into simpler ones is an essential task to fully exploit the power of quantum computers. In this work, we consider an opposite task: "quantum circuit un-optimization (QCU)", which makes a circuit more redundant while preserving its functionality. With QCU, we can systematically generate many kinds of benchmark datasets for optimization. These un-optimized circuits can be useful for evaluating the performance of quantum compilers. We try a method of QCU, where we insert redundant identity gates each consisting of a unitary and its adjoint and swap them around the circuit. We examine how many depths the optimization module such as Qiskit and TKET can reduce from the un-optimized quantum circuits. We expect that QCU enables us to compare the performance of different quantum compilers and to improve them. Also, we can use QCU for defining a machine learning task whose aim is to classify quantum states generated by two classes of circuits, each of which is derived by applying QCU procedures to two distinct original circuits. This task is easy with quantum computers since we can just run the circuits and compute the inner products of the states, but it is not so easy on classical computers. |
Tuesday, March 7, 2023 9:00AM - 9:12AM |
F70.00006: Evermore optimized simulations of fermionic systems on a quantum computer Qingfeng Wang, Ze-Pei Cian, Ming Li, Igor Markov, Yunseong Nam In this work, we present an advanced compilation and optimization technique to reduce the number of two-qubit entangling gates used for the simulation of fermonic interactions on a quantum computer. Our optimization method greatly simplifies the procedure used in the state-of-the-art method, by mapping the quantum circuit optimization problem to well-studied optimization problems, such as graph vertex coloring problem and traveling salesman problem. This enables us to exploit the well-studied classical optimization algorithms and commercial solvers. We present the optimization results for the simulation of several small molecules and show that the number of quantum gates used can be saved up to 24\% over the state of the art. Our advanced compilation and optimization technique can straightforwardly be generalized to wider classes of near-term simulations of the ground state of a fermionic system or real-time simulations probing dynamical properties of a fermionic system. |
Tuesday, March 7, 2023 9:12AM - 9:24AM |
F70.00007: Crossing the QASM: gate level compilation for practical quantum control Yonatan Cohen, Dor Israeli, Yonatan Rosmarin With the quantum computing ecosystem growing substantially in qubit technologies, cloud-accessible solutions and programming languages, it becomes increasingly important to rely on and develop high level interface standards like OpenQASM3. Towards standardization of programming languages to describe quantum circuit models we must indeed be able to link applications to pulse-level languages, which are highly dependent on the underlying physical system. Here, we showcase an effective and convenient software interface for controlling the physical layer, connecting the OpenQASM3 standard to QUA, the pulse-level language of the Quantum Orchestration Platform. Once configured, our compiler provides the ability to write an algorithm on a gate-level abstraction, and run it on different real devices and qubits. We highlight the currently supported features and their usage, from control flow to parametric executions, cross embedding of OpenQASM3 and QUA, channel scheduling, semantic optimization and automatic qubit allocation. This compiler is critical in enabling the rich quantum ecosystem and its promises for society. |
Tuesday, March 7, 2023 9:24AM - 9:36AM |
F70.00008: A language-oriented approach to exchange-only silicon dot qubit software Robert S Smith A standard approach to achieving a hardware agnostic programming interface for quantum computational experiments is to develop a hardware abstraction layer in the form of high-level classes and methods in a given programming language, such as Python. To allow for rapidly developing these experimental goals, we instead opted for a language-oriented approach to both hardware and abstraction. In our quantum computing software stack called Quiver, we have progressed on developing a series of new programming languages—called Coalton, Quil-E, PulseScript, and PulseIR—to provide more direct ways of writing flexible, expressive, and optimized experimental code for silicon dot qubit experiments. |
Tuesday, March 7, 2023 9:36AM - 9:48AM |
F70.00009: A software framework for scalable quantum computing Kent R Shirer, Clemens Müller, Andreas Messner, Edward Kluender, Zhixin Wang, Tino Wagner, Donjan Rodic, Markus Emmenegger, Konstantin Korotkov, Jan Lienemann, Chi-Huan Nguyen, Pol Welter Quantum computing architectures have expanded to systems that support many qubits. With an increase in qubit number, both qubit control hardware and software must support quantum engineers and scientists in breaking down experimental complexity. Here, we show the advantage provided by our open-source software framework capable of programming many instruments together as a single machine, allowing users to program experiments at a high level, from which optimized code is generated for the control hardware. The optimization of instrument settings, waveform generation and upload, and pulse synchronization and scheduling are automated, enabling fast qubit characterization and tune-up. The software framework supports real-time calibration sequences which are interleaved with optimization steps, e.g., using intermediate measurement results to optimally calibrate a gate pulse, and it provides browser-based tools for visualization of experimental sequences and pulses before execution. We show how the software is used to implement quantum error correction using surface code. This software, in combination with high-performance control electronics, is capable of performing state-of-the-art experiments on the latest qubit processors. |
Tuesday, March 7, 2023 9:48AM - 10:00AM |
F70.00010: Efficient compiling of quantum programs using experimentally demonstrated global gates Yunseong Nam While most quantum programs are compiled using single- and two-qubit gates, some quantum computers support parallel, global gates. Indeed, it has been experimentally demonstrated that such global instructions can be implemented with little additional complication over that required to implement a single two-qubit gate. In this talk, I will briefly discuss how one can implement such a global native gate at a high level. I will then use it to enable efficient quantum program compilation, for a large class of oft-used unitary operators. Included are (i) n-qubit Clifford operations and (ii) multiply-controlled gates, implemented using a constant or effectively-constant number of global gates. An overview of previous results will be provided to highlight the striking advantage afforded by the compilation techniques. |
Tuesday, March 7, 2023 10:00AM - 10:12AM |
F70.00011: Resource requirements for observable estimation, enabled by QuPython Antonio E Russo, Nathan Arnold, Stefan Seritan, Shivesh Pathak, Andrew D Baczewski I will present an analysis of the resources required to estimate observables in the quantum simulation of a first principles model for a condensed phase system. The complexity of the associated algorithms is severe enough that this is greatly facilitated by a high-level quantum programming language QuPython. This tool allows us to graduate from asymptotic estimates of T-gates and qubit counts to numerically quantitative ones. In addition to informing requirements for application-scale quantum computation like observable estimation, this also showcases several high-level features, and an extensible framework, built on top of the popular Python programming language. |
Tuesday, March 7, 2023 10:12AM - 10:24AM |
F70.00012: Very large scale quantum circuit optimisation using alternative circuit representations Ioana Moflic, Vikas Garg, Alexandru Paler Quantum computations are often described by diagrams, such as quantum circuits, tensor networks or ZX-diagrams. Optimizing quantum circuits implies implementing methods for manipulating the diagrams according to well-defined sets of rules. Quantum circuit optimization using the diagrammatic representation is a highly complex, combinatorial problem even for heuristic methods and it does not easily scale to large-scale circuits. |
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