ProjectQ: an open source software framework for quantum computing

Steiger, Damian S.; Häner, Thomas; Troyer, Matthias

doi:10.22331/q-2018-01-31-49

Cited by 343 publications

(261 citation statements)

References 16 publications

(25 reference statements)

Supporting

Mentioning

258

Contrasting

Unclassified

Order By: Relevance

“…Several other compilation systems have been developed as Python modules targeting specific hardware. These include the Forest SDK/pyQuil [31] (for Rigetti backends), Qiskit [32] and ProjectQ [33] (for IBM backends), and Cirq [34] (for Google backends). Other projects have adopted a backend-agnostic approach.…”

Section: Related Workmentioning

confidence: 99%

“…The industry-standard OpenQASM [46] and the the functional language Quipper [27] are supported via direct source-file input. Python converters provide support for IBM's Qiskit [32], Google's Cirq [34] and Rigetti's pyQuil [31], as well as the independent open-source projects ProjectQ [33] and PyZX [47]. These Python libraries in turn support higher-level application programming frameworks such Figure 5: Code example showing front-end and back-end use.…”

Section: Front-ends and Back-endsmentioning

confidence: 99%

See 1 more Smart Citation

t|ket⟩: a retargetable compiler for NISQ devices

Sivarajah

Dilkes

Cowtan

et al. 2020

Quantum Sci. Technol.

300

238

View full text Add to dashboard Cite

We present t|ket , a quantum software development platform produced by Cambridge Quantum Computing Ltd. The heart of t|ket is a language-agnostic optimising compiler designed to generate code for a variety of NISQ devices, which has several features designed to minimise the influence of device error. The compiler has been extensively benchmarked and outperforms most competitors in terms of circuit optimisation and qubit routing. User Runtime GPU Classical HPC Logging Task Manager Scheduler Real-Time Controller Control Device Control Device Readout Device … Figure 2: Idealised system architecture for a NISQ Computerprogrammable devices which drive the evolution of the qubits and read out their states. An example of this kind of device is an arbitrary waveform generator, as found in many superconducting architectures. The microwave pulse sequences output by these devices are generated by simple low-level programs optimised for speed of execution. These devices, and the real-time controller which synchronises them, operate in a hard real-time environment where the computation takes place on the time-scale of the coherence time of the qubits. These components combine to execute a single instance of a quantum circuit, possibly with some classical control. By analogy with GPU computing, we refer to this layer as a kernel. One level higher, the scheduler is responsible for dispatching circuits to be run and packaging the results for the higher layers. It is also likely to be heavily involved in the device calibration process. (Calibration data are an important input to the compiler.) This layer and those below may be thought of as the low-level system software of the quantum computer, and must normally be physically close to the device. In the layer above we find service-oriented middleware, principally the task manager, which may distribute jobs to different quantum devices or simulators, GPUs, and perhaps conventional HPC resources, to perform the various subroutines of the quantum algorithm. This layer may also allocate access to the quantum system among multiple users. Finally, at the highest level is the user runtime, which defines the overall algorithm and integrates the results of the subcomputations to produce the final answer.

show abstract

Section: Related Workmentioning

confidence: 99%

Section: Front-ends and Back-endsmentioning

confidence: 99%

t|ket⟩: a retargetable compiler for NISQ devices

Sivarajah

Dilkes

Cowtan

et al. 2020

Quantum Sci. Technol.

300

238

View full text Add to dashboard Cite

show abstract

“…As previously noted, the {R x (θ ), R z (ϕ), CX} gate set alone is sufficient for universality, so in principle the H and SWAP gates could be removed from the compilation basis gate set. However, we include the generated pulses (using GRAPE as described below) for these gates in our compilation set, because quantum assembly languages typically include them in their basis set [19,22,33,46,47,50].…”

Section: Gate-based Compilationmentioning

confidence: 99%

Partial Compilation of Variational Algorithms for Noisy Intermediate-Scale Quantum Machines

Gokhale

Ding

Propson

et al. 2019

Proceedings of the 52nd Annual IEEE/ACM International Symposium on Microarchitecture

View full text Add to dashboard Cite

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 support the execution of short programs before failing.However, GRAPE suffers from high compilation latency, which is untenable in variational algorithms since compilation is interleaved with computation. We propose two strategies for partial compilation, exploiting the structure of variational circuits to pre-compile optimal pulses for specific blocks of gates. Our results indicate significant pulse speedups ranging from 1.5x-3x in typical benchmarks, with only a small fraction of the compilation latency of GRAPE. CCS CONCEPTS• Computer systems organization → Quantum computing. KEYWORDS quantum computing, optimal control, variational algorithms ACM Reference Format:

show abstract

“…While the problem of debugging and validating quantum programs has been extensively identified as a major barrier to useful quantum computation [4,9,13,34,39,44,49], little has been said about what actually constitutes a quantum program bug. Similarly limited detail has been shared about the inside story of translating QC algorithms in to working QC programs, even though the field is now making rapid progress in writing open source QC program benchmarks across several quantum programming languages [9,17,23,27,47,48].…”

Section: Introductionmentioning

confidence: 99%

Statistical assertions for validating patterns and finding bugs in quantum programs

Huang

Martonosi

2019

Proceedings of the 46th International Symposium on Computer Architecture

105

View full text Add to dashboard Cite

In support of the growing interest in quantum computing experimentation, programmers need new tools to write quantum algorithms as program code. Compared to debugging classical programs, debugging quantum programs is difficult because programmers have limited ability to probe the internal states of quantum programs; those states are difficult to interpret even when observations exist; and programmers do not yet have guidelines for what to check for when building quantum programs. In this work, we present quantum program assertions based on statistical tests on classical observations. These allow programmers to decide if a quantum program state matches its expected value in one of classical, superposition, or entangled types of states. We extend an existing quantum programming language with the ability to specify quantum assertions, which our tool then checks in a quantum program simulator. We use these assertions to debug three benchmark quantum programs in factoring, search, and chemistry. We share what types of bugs are possible, and lay out a strategy for using quantum programming patterns to place assertions and prevent bugs.

show abstract

ProjectQ: an open source software framework for quantum computing

Cited by 343 publications

References 16 publications

t|ket⟩: a retargetable compiler for NISQ devices

t|ket⟩: a retargetable compiler for NISQ devices

Partial Compilation of Variational Algorithms for Noisy Intermediate-Scale Quantum Machines

Statistical assertions for validating patterns and finding bugs in quantum programs

Contact Info

Product

Resources

About