Quantum computers are traditionally operated by programmers at the granularity of a gate-based instruction set. However, the actual device-level control of a quantum computer is performed via analog pulses. We introduce a compiler that exploits direct control at this microarchitectural level to achieve significant improvements for quantum programs. Unlike quantum optimal control, our approach is bootstrapped from existing gate calibrations and the resulting pulses are simple. Our techniques are applicable to any quantum computer and realizable on current devices. We validate our techniques with millions of experimental shots on IBM quantum computers, controlled via the OpenPulse control interface. For representative benchmarks, our pulse control techniques achieve both 1.6x lower error rates and 2x faster execution time, relative to standard gate-based compilation. These improvements are critical in the near-term era of quantum computing, which is bottlenecked by error rates and qubit lifetimes.
The effective use of current Noisy Intermediate-Scale Quantum (NISQ) devices is often limited by the noise which is caused by interaction with the environment and affects the fidelity of quantum gates. In transmon qubit systems, the quantum gate fidelity can be improved by applying control pulses that can minimize the effects of the environmental noise. In this work, we employ physics-guided quantum optimal control strategies to design optimal pulses driving quantum gates on superconducting qubit systems. We test our results by conducting experiments on the IBM Q hardware using their OpenPulse…
Optimized Compilation of Logical Clifford Circuits
Fraunhofer IIS, Fraunhofer Institute for Integrated Circuits IIS（弗劳恩霍夫集成电路研究所）；University of Würzburg（维尔茨堡大学）；Friedrich-Alexander-Universität Erlangen-Nürnberg（埃尔朗根-纽伦堡弗里德里希·阿历克西斯大学）
Quantum computing is on the cusp of reality with Noisy Intermediate-Scale Quantum (NISQ) machines currently under development and testing. Some of the most promising algorithms for these machines are variational algorithms that employ classical optimization coupled with quantum hardware to evaluate the quality of each candidate solution. Recent work used GRadient Descent Pulse Engineering (GRAPE) to translate quantum programs into highly optimized machine control pulses, resulting in a significant reduction in the execution time of programs. This is critical, as quantum machines can barely sup…
Recent developments in engineering and algorithms have made real-world applications in quantum computing possible in the near future. Existing quantum programming languages and compilers use a quantum assembly language composed of 1- and 2-qubit (quantum bit) gates. Quantum compiler frameworks translate this quantum assembly to electric signals (called control pulses) that implement the specified computation on specific physical devices. However, there is a mismatch between the operations defined by the 1- and 2-qubit logical ISA and their underlying physical implementation, so the current pra…
Optimized Compilation for Distributed Quantum Computing
Quantum Software Laboratory, Department of Engineering and Architecture, University of Parma（帕尔马大学工程与建筑学院量子软件实验室）；Department of Mathematical, Physical and Computer Sciences, University of Parma（帕尔马大学数学、物理和计算机科学系）；INFN–Sezione di Milano-Bicocca, gruppo collegato di Parma（米兰-比可卡INFN分部帕尔马协作组）
A Compilation Framework for Quantum Simulation of Non-unitary Dynamics
Institute of Software, Chinese Academy of Sciences（中国科学院软件研究所）；University of Chinese Academy of Sciences（中国科学院大学）；University of Technology Sydney（悉尼科技大学）
SAQC: A SAT-Aware Compilation Framework for QAOA-Based Quantum Optimization
DFKI, Bremen, Germany（德国弗劳恩霍夫协会第一智能系统研究所）；Institute of Computer Science, University of Bremen, Bremen, Germany（不来梅大学计算机科学研究所）；University of Bremen, Bremen, Germany（不来梅大学）
qgym: A Gym for Training and Benchmarking RL-Based Quantum Compilation
The Netherlands Organisation for Applied Scientific Research (TNO)（荷兰应用科学研究组织（TNO））；Bernoulli Institute（伯努利研究所）；Faculty of Science and Engineering（科学与工程学院）；University of Groningen（格罗宁根大学）；Quantum & Computer Engineering（量子与计算机工程系）；QuTech（QuTech（量子技术研究所））；Delft University of Technology（代尔夫特理工大学）
Efficient compilation of quantum algorithms is vital in the era of Noisy Intermediate-Scale Quantum (NISQ) devices. While multiple open-source quantum compilation and circuit optimization frameworks are available, e.g. IBM Qiskit, CQC Tket, Google Cirq, Rigetti Quilc, PyZX, their relative performance is not always clear to a quantum programmer. The growth of complexity and diversity of quantum circuit compilation algorithms creates a demand for a dedicated tool for cross-benchmarking and profiling of inner workflow of the quantum compilation stack. We present an open-source software package, A…
Università degli Studi di Padova（帕多瓦大学）；Istituto Nazionale di Fisica Nucleare, Sezione di Padova（意大利国家核物理研究所帕多瓦分部）；Padua Quantum Technologies Research Center（帕多瓦量子技术中心）
We study the problem of compilation of quantum algorithms into optimized physical-level circuits executable in a quantum information processing (QIP) experiment based on trapped atomic ions. We report a complete strategy: starting with an algorithm in the form of a quantum computer program, we compile it into a high-level logical circuit that goes through multiple stages of decomposition into progressively lower-level circuits until we reach the physical execution-level specification. We skip the fault-tolerance layer, as it is not within the scope of this work. The different stages are struct…
Compiling quantum circuits to realistic hardware architectures using temporal planners
NASA Ames Research Center, Quantum Artificial Intelligence Laboratory（美国国家航空航天局阿姆斯研究中心，量子人工智能实验室）；USRA Research Institute for Advanced Computer Science (RIACS)（美国宇航局高级计算机科学研究所（RIACS））；Stinger Ghaffarian Technologies (SGT Inc.)（Stinger Ghaffarian技术（SGT公司））；NASA Ames Research Center, Planning and Scheduling Group（美国国家航空航天局阿姆斯研究中心，计划与调度组）
Despite using a novel model of computation, quantum computers break down programs into elementary gates. Among such gates, entangling gates are the most expensive. In the context of fermionic simulations, we develop a suite of compilation and optimization techniques that massively reduce the entangling-gate counts. We exploit the well-studied non-quantum optimization algorithms to achieve up to 24\% savings over the state of the art for several small-molecule simulations, with no loss of accuracy or hidden costs. Our methodologies straightforwardly generalize to wider classes of near-term simu…
Compiler Optimization for Quantum Computing Using Reinforcement Learning
Technical University of Munich（慕尼黑工业大学）；Johannes Kepler University Linz（约翰内斯·开普勒大学林茨分校）；Software Competence Center Hagenberg GmbH (SCCH)（哈根伯格软件能力中心有限公司）
In order to support near-term applications of quantum computing, a new compute paradigm has emerged--the quantum-classical cloud--in which quantum computers (QPUs) work in tandem with classical computers (CPUs) via a shared cloud infrastructure. In this work, we enumerate the architectural requirements of a quantum-classical cloud platform, and present a framework for benchmarking its runtime performance. In addition, we walk through two platform-level enhancements, parametric compilation and active qubit reset, that specifically optimize a quantum-classical architecture to support variational…
Here we explore which heuristic quantum algorithms for combinatorial optimization might be most practical to try out on a small fault-tolerant quantum computer. We compile circuits for several variants of quantum accelerated simulated annealing including those using qubitization or Szegedy walks to quantize classical Markov chains and those simulating spectral gap amplified Hamiltonians encoding a Gibbs state. We also optimize fault-tolerant realizations of the adiabatic algorithm, quantum enhanced population transfer, the quantum approximate optimization algorithm, and other approaches. Many …
Quantum computing (QC) is at the cusp of a revolution. Machines with 100 quantum bits (qubits) are anticipated to be operational by 2020 [googlemachine,gambetta2015building], and several-hundred-qubit machines are around the corner. Machines of this scale have the capacity to demonstrate quantum supremacy, the tipping point where QC is faster than the fastest classical alternative for a particular problem. Because error correction techniques will be central to QC and will be the most expensive component of quantum computation, choosing the lowest-overhead error correction scheme is critical to…
The fermionic SWAP network is a qubit routing sequence that can be used to efficiently execute the Quantum Approximate Optimization Algorithm (QAOA). Even with a minimally-connected topology on an n-qubit processor, this routing sequence enables O(n^2) operations to execute in O(n) steps. In this work, we optimize the execution of fermionic SWAP networks for QAOA through two techniques. First, we take advantage of an overcomplete set of native hardware operations [including 150 ns controlled-pi/2 phase gates with up to 99.67(1)% fidelity] in order to decompose the relevant quantum gates and SW…
Lazy-Move Compilation for Neutral-Atom Quantum Computers via a Buffer-Relay Fabric
Beijing Academy of Quantum Information Sciences（北京量子信息科学研究院）；Department of Computer Science and Engineering, The Chinese University of Hong Kong（香港中文大学计算机科学与工程系）；Open Quantum Intelligence (Shanghai) Co., Ltd.（上海开放量子智能有限公司）；State Key Laboratory of Quantum Information Technologies and Materials, The Chinese University of Hong Kong（香港中文大学量子信息技术与材料国家重点实验室）；CAS Cold Atom Technology (Wuhan) Co., Ltd.（中科院冷原子技术（武汉）有限公司）；Key Laboratory of Quantum Optics and Center of Cold Atom Physics, Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences（中国科学院上海光学精密机械研究所量子光学重点实验室和冷原子物理中心）；State Key Laboratory of Low Dimensional Quantum Physics, Department of Physics, Tsinghua University（清华大学物理系低维量子物理国家重点实验室）
Adversarial learning represents a powerful technique for generating data statistics. Its successful implementation in quantum computational platforms is not straightforward due to limitations in connectivity, quantum operation fidelity, and limited access to the quantum processor for statistically relevant results. Constraining the number of quantum operations and providing a design with a low compilation cost, we propose a quantum generative adversarial network design that uses real Hilbert spaces as the framework for the generative model and a novel strategy to encode classical information i…
Simulating the time evolution of a physical system at quantum mechanical levels of detail -- known as Hamiltonian Simulation (HS) -- is an important and interesting problem across physics and chemistry. For this task, algorithms that run on quantum computers are known to be exponentially faster than classical algorithms; in fact, this application motivated Feynman to propose the construction of quantum computers. Nonetheless, there are challenges in reaching this performance potential. Prior work has focused on compiling circuits (quantum programs) for HS with the goal of maximizing either acc…
Transpiler-Architecture Co-Design to Curb Clifford Costs in Fault-Tolerant Quantum Computing
The University of British Columbia（不列颠哥伦比亚大学）；Pacific Northwest National Laboratory（太平洋西北国家实验室）；University of California San Diego（加州大学圣地亚哥分校）；The University of Texas at Austin（德克萨斯大学奥斯汀分校）；University of Washington（华盛顿大学）
Existing quantum compilers focus on mapping a logical quantum circuit to a quantum device and its native quantum gates. Only simple circuit identities are used to optimize the quantum circuit during the compilation process. This approach misses more complex circuit identities, which could be used to optimize the quantum circuit further. We propose Quanto, the first quantum optimizer that automatically generates circuit identities. Quanto takes as input a gate set and generates provably correct circuit identities for the gate set. Quanto's automatic generation of circuit identities includes sin…
University of Maryland（马里兰大学）；Joint Quantum Institute（联合量子研究所）；Brookhaven National Laboratory（布鲁克海文国家实验室）
Recent advances in quantum computing have drawn considerable attention to building realistic application for and using quantum computers. However, designing a suitable quantum circuit architecture requires expert knowledge. For example, it is non-trivial to design a quantum gate sequence for generating a particular quantum state with as fewer gates as possible. We propose a quantum architecture search framework with the power of deep reinforcement learning (DRL) to address this challenge. In the proposed framework, the DRL agent can only access the Pauli-$X$, $Y$, $Z$ expectation values and a …
