Q#

Svore, Krysta M.; Geller, Alan; Troyer, Matthias; Azariah, John; Granade, Christopher; Heim, Bettina; Kliuchnikov, Vadym; Mykhailova, Mariia; Paz, Andres; Roetteler, Martin

doi:10.1145/3183895.3183901

Cited by 191 publications

(31 citation statements)

References 14 publications

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“…Given the rapid growth of QC infrastructure, programmers now have the chance to test a variety of quantum algorithms written in many languages [23]. To validate our overall approach, we crossvalidated our quantum programs and simulation results against equivalent programs written in other quantum programming languages, such as LIQUi|> [44], ProjectQ [12,47], and Q# [48].…”

Section: Simulation and Assertions Checking Methodologymentioning

confidence: 99%

“…In prior work, the Q# quantum programming language has support for assertion checks for integer values, and is able to check for such assertions in simulations of quantum programs [48]. To our knowledge, this paper is the first proposal for quantum assertions on superposition and (later in this paper) entangled quantum states.…”

Section: Classical and Superposition Precondition Assertions On Quantmentioning

confidence: 99%

“…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%

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Statistical assertions for validating patterns and finding bugs in quantum programs

Huang

Martonosi

2019

Proceedings of the 46th International Symposium on Computer Architecture

105

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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.

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Section: Simulation and Assertions Checking Methodologymentioning

confidence: 99%

Section: Classical and Superposition Precondition Assertions On Quantmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Statistical assertions for validating patterns and finding bugs in quantum programs

Huang

Martonosi

2019

Proceedings of the 46th International Symposium on Computer Architecture

105

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“…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

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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:

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“…In part due to the increasing viability of quantum computing and the scaling of NISQ [28] devices, there has been a recent explosion in quantum programming tools. Such tools range from software development kits (e.g., Qiskit [5], ProjectQ [32], Strawberry Fields [19], Pyquil [30]) to Embedded domain-specific languages (e.g., Quipper [11], Qwire [27], Q|SI [22]) and standalone languages and compilers (e.g., QCL [26], QML [2], ScaffCC [16], Q# [33]). Going beyond strict programming tools, software for the synthesis, optimization, and simulation of quantum circuits and programs (e.g., Revkit [31], TOpt [15], Feynman [3], PyZX [20], Quan-tum++ [9], QX [17]) are becoming more and more abundant.…”

Section: Introductionmentioning

confidence: 99%

Sized Types for Low-Level Quantum Metaprogramming

Amy

2019

Reversible Computation

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One of the most fundamental aspects of quantum circuit design is the concept of families of circuits parametrized by an instance size. As in classical programming, metaprogramming allows the programmer to write entire families of circuits simultaneously, an ability which is of particular importance in the context of quantum computing as algorithms frequently use arithmetic over non-standard word lengths. In this work, we introduce metaQASM, a typed extension of the openQASM language supporting the metaprogramming of circuit families. Our language and type system, built around a lightweight implementation of sized types, supports subtyping over register sizes and is moreover typesafe. In particular, we prove that our system is strongly normalizing, and as such any well-typed metaQASM program can be statically unrolled into a finite circuit.

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Q#

Cited by 191 publications

References 14 publications

Statistical assertions for validating patterns and finding bugs in quantum programs

Statistical assertions for validating patterns and finding bugs in quantum programs

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

Sized Types for Low-Level Quantum Metaprogramming

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