Assertion-based optimization of Quantum programs

Häner, Thomas; Hoefler, Torsten; Troyer, Matthias

doi:10.1145/3428201

Cited by 11 publications

(10 citation statements)

References 31 publications

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“…Unlike Twist, this check is purely syntactic and cannot be refined by semantic knowledge about the program. Häner et al [2020] leverage entanglement annotations to optimize circuit gate count, but do not ensure that the annotations are sound. By contrast, we proved that pure-typed expressions are in fact pure.…”

Section: Related Workmentioning

confidence: 99%

Twist: sound reasoning for purity and entanglement in Quantum programs

Yuan

McNally

Carbin

2022

Proc. ACM Program. Lang.

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Quantum programming languages enable developers to implement algorithms for quantum computers that promise computational breakthroughs in classically intractable tasks. Programming quantum computers requires awareness of entanglement , the phenomenon in which measurement outcomes of qubits are correlated. Entanglement can determine the correctness of algorithms and suitability of programming patterns. In this work, we formalize purity as a central tool for automating reasoning about entanglement in quantum programs. A pure expression is one whose evaluation is unaffected by the measurement outcomes of qubits that it does not own, implying freedom from entanglement with any other expression in the computation. We present Twist, the first language that features a type system for sound reasoning about purity. The type system enables the developer to identify pure expressions using type annotations. Twist also features purity assertion operators that state the absence of entanglement in the output of quantum gates. To soundly check these assertions, Twist uses a combination of static analysis and runtime verification. We evaluate Twist’s type system and analyses on a benchmark suite of quantum programs in simulation, demonstrating that Twist can express quantum algorithms, catch programming errors in them, and support programs that existing languages disallow, while incurring runtime verification overhead of less than 3.5%.

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Section: Related Workmentioning

confidence: 99%

Twist: sound reasoning for purity and entanglement in Quantum programs

Yuan

McNally

Carbin

2022

Proc. ACM Program. Lang.

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“…Furthermore, optimization using phase polynomials has proven to be efective [2], especially when combined with other heuristics to tackle larger universal circuits [24]. Moreover, assertion-based optimization has been proposed to optimize quantum programs at higher levels of abstraction [13].…”

Section: Uantum Program Optimizationmentioning

confidence: 99%

“…Our IR may thus enable such quantum-classical optimizations. For example, assertion-based optimization may be extended to take branching and loop conditions into account [13].…”

Section: Uantum Program Optimizationmentioning

confidence: 99%

QIRO: A Static Single Assignment-based Quantum Program Representation for Optimization

Ittah

Häner

Kliuchnikov

et al. 2022

ACM Transactions on Quantum Computing

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We propose an IR for quantum computing that directly exposes quantum and classical data dependencies for the purpose of optimization. The Quantum Intermediate Representation for Optimization (QIRO) consists of two dialects, one input dialect and one that is specifically tailored to enable quantum-classical co-optimization. While the first employs a perhaps more intuitive memory-semantics (quantum operations act on qubits via side-effects), the latter uses value-semantics (operations consume and produce states) to integrate quantum dataflow in the IR’s Static Single Assignment (SSA) graph. Crucially, this allows for a host of optimizations that leverage dataflow analysis. We discuss how to map existing quantum programming languages to the input dialect and how to lower the resulting IR to the optimization dialect. We present a prototype implementation based on MLIR that includes several quantum-specific optimization passes. Our benchmarks show that significant improvements in resource requirements are possible even through static optimization. In contrast to circuit optimization at run time, this is achieved while incurring only a small constant overhead in compilation time, making this a compelling approach for quantum program optimization at application scale.

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“…Further quantum algorithms have been developed in recent years that achieve a polynomial speedup. However, as a single classical GPU chip can have a factor of 10 10 better performance in bit and floating-point operations than a single quantum chip, (Häner et al 2020;Troyer 2021) the latter will be more difficult to show a clear advantage over traditional computing.…”

Section: Introductionmentioning

confidence: 99%

Prospects of quantum computing for molecular sciences

et al. 2022

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Molecular science is governed by the dynamics of electrons and atomic nuclei, and by their interactions with electromagnetic fields. A faithful physicochemical understanding of these processes is crucial for the design and synthesis of chemicals and materials of value for our society and economy. Although some problems in this field can be adequately addressed by classical mechanics, many demand an explicit quantum mechanical description. Such quantum problems require a representation of wave functions that grows exponentially with system size and therefore should naturally benefit from quantum computation on a number of logical qubits that scales only linearly with system size. In this perspective, we elaborate on the potential benefits of quantum computing in the molecular sciences, i.e., in molecular physics, chemistry, biochemistry, and materials science.

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Assertion-based optimization of Quantum programs

Cited by 11 publications

References 31 publications

Twist: sound reasoning for purity and entanglement in Quantum programs

Twist: sound reasoning for purity and entanglement in Quantum programs

QIRO: A Static Single Assignment-based Quantum Program Representation for Optimization

Prospects of quantum computing for molecular sciences

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