A Practical Quantum Instruction Set Architecture

By Robert S. Smith, Michael J. Curtis, William J. Zeng. arXiv.org, 2016

380 citations recorded by the source corpus.

We introduce an abstract machine architecture for classical/quantum computations---including compilation---along with a quantum instruction language called Quil for explicitly writing these computations. With this formalism, we discuss concrete implementations of the machine and non-trivial algorithms targeting them. The introduction of this machine dovetails with ongoing development of quantum computing technology, and makes possible portable descriptions of recent classical/quantum algorithms.

View Paper: https://www.semanticscholar.org/paper/a160322cea30e47b9ac95f36e13c9d180e94be84

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Citations in the corpus

Open Quantum Assembly Language (2017, methodology): “jects, several of which include software that has been made readily available: Liquid [5,6], Scaold [7,8], Quipper [9{11], ProjectQ [12,13], QCL [14,15], Quiddpro [16,17], Chisel-q [18,19], and Quil [20,21]. Our goal in this document is to describe an interface language for the Quantum Experience th”
Potential of quantum computing for drug discovery (2018, background): “As quantum libraries for controlling quantum computers start to emerge [191–193], more developments are required to cover the wide range of calculations common in computational chemistry, such as molecular geometry optimization, calculation of molecular properties, molecular spectra, and tools for…”
Unsupervised Machine Learning on a Hybrid Quantum Computer (2017, methodology): “We implement said algorithm on a 19-qubit computer using a ﬂexible quantum programming platform [16, 17].”
Transfer learning in hybrid classical-quantum neural networks (2019, background): “The authors would like to thank Rigetti for access to their resources, Forest [45], QCS and Aspen4-4Q-A backend.”
Cloud Quantum Computing of an Atomic Nucleus. (2018, methodology): “Furthermore, the relevant software (e.g. PyQuil [16], XACC [17], OpenQASM [18], and OpenFermion [19]) to run on quantum computers and simulators is publicly available.”
Digital zero noise extrapolation for quantum error mitigation (2020, background): “Their advantage is that they can be used with the gate model access that is common to most quantum assembly languages [17]–[19].”
OpenFermion: the electronic structure package for quantum computers (2017, background): “Using the Jordan–Wigner transform functionality of OpenFermion, the Hubbard Hamiltonian can be transformed to a sum of QubitOperators which are then transformed to pyQuil PauliSum objects using routines in the Forest–OpenFermion plugin imported earlier.”
Quantum-assisted quantum compiling (2018, methodology): “Using Rigetti’s quantum virtual machine [25], we compile the controlled-Hadamard (CH) gate, the CZ gate, the SWAP gate, and the two-qubit Fourier transform QFT 2 by adopting the continuous optimization procedure in Algorithm 1.”
Q#: Enabling Scalable Quantum Computing and Development with a High-level DSL (2018, background): “Languages such as Quipper [6], ScaffCC/Scaffold [7, 8], LIQUi|⟩[22], QWire [15], Quil [19], and ProjectQ [20] enable programming of quantum computations and are intended as circuit definition languages.”
Qubit allocation (2018, unknown): “Programming languages that let developers interact with quantum machines came later [1, 15, 36, 39].”
Noise-Adaptive Compiler Mappings for Noisy Intermediate-Scale Quantum Computers (2019, background): “PyQuil, developed at Rigetti [37, 38] is another such Python framework.”
OpenQASM 3: A Broader and Deeper Quantum Assembly Language (2021, methodology): “Unlike other approaches to interfacing with classical computing, OpenQASM does not have an explicit synchronization primitive such as the WAIT instruction in QUIL [3, 73].”
Qulacs: a fast and versatile quantum circuit simulator for research purpose (2020, background): “[12] Robert S.”
Software Mitigation of Crosstalk on Noisy Intermediate-Scale Quantum Computers (2020, methodology): “ragile — the quality of quantum information loses “coherence” exponentially with increasing compute time. Because of this exponentialdecay,currenthardwareandcompilerssuchIBM Qiskit [1], Rigetti Quilc [57], and TriQ [44] schedule maximum instructions in parallel. An ideal schedule balances the need f”
PennyLane: Automatic differentiation of hybrid quantum-classical computations (2018, unknown): “As of version 0.8, PennyLane has plugins available for Strawberry Fields [ 25, 51 ] , Rigetti Forest [ 52, 53 ] , Qiskit [ 43, 44 ] , Cirq [ 54 ] , ProjectQ [ 22, 55 ] .”