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Springer eBooks

Development Libraries for Quantum Computer Programming

Jack D. Hidary

Published Jan 1, 2019• 0 citations
Publisher
DOI
10.1007/978-3-030-23922-0_6

Related papers

Development Libraries for Quantum Computer Programming

Jack D. Hidary

Springer eBooks•Jan 1, 2021•2 citations

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A C++ library, named ZKCM, has been developed for the purpose of multiprecision matrix calculations, which is based on the GNU MP and MPFR libraries. It is especially convenient for writing programs involving tensor-product operations, tracing-out operations, and singular-value decompositions. Its extension library, ZKCM_QC, for simulating quantum computing has been developed using the time-dependent matrix-product-state simulation method. This report gives a brief introduction to the libraries with sample programs.

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High-level programming models like Q# significantly simplify the complexity of programming for quantum computing. These models are supported by a set of foundation libraries for code development. However, errors can occur in the library implementation, and one common root cause is the lack of or incomplete checks on properties like values, length, and quantum states of inputs passed to user-facing subroutines. This paper presents Upbeat, a fuzzing tool to generate random test cases for bugs related to input checking in Q# libraries. Upbeat develops an automated process to extract constraints from the API documentation and the developer implemented input-checking statements. It leverages open-source Q# code samples to synthesize test programs. It frames the test case generation as a constraint satisfaction problem for classical computing and a quantum state model for quantum computing to produce carefully generated subroutine inputs to test if the input-checking mechanism is appropriately implemented. Under 100 hours of automated test runs, Upbeat has successfully identified 16 bugs in API implementations and 4 documentation errors. Of these, 14 have been confirmed, and 12 have been fixed by the library developers.

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To help the understanding and development of quantum algorithms there is an effort focused on the investigation of new semantic models and programming languages for quantum computing. Researchers in computer science have the challenge of deve loping programming languages to support the creation, analysis, modeling and simulation of high level quantum algorithms. Based on previous works that use monads inside the programming language Haskell to elegantly explain the odd characteristics of quantum computation (like superposition and entanglement), in this work we present a monadic Java library for quantum programming. We use the extension of the programming language Java called BGGA Closure, that allow the manipulation of anonymous functions (closures) inside Java. We exemplify the use of the library with an implementation of the Toffoli quantum circuit.

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Quantum programming languages

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Frontiers of Computer Science in China•Jun 1, 2008•3 citations
A C++ library, named ZKCM, has been developed for the purpose of multiprecision matrix calculations, which is based on the GNU MP and MPFR libraries. It is especially convenient for writing programs involving tensor-product operations, tracing-out operations, and singular-value decompositions. Its extension library, ZKCM_QC, for simulating quantum computing has been developed using the time-dependent matrix-product-state simulation method. This report gives a brief introduction to the libraries with sample programs.
High-level programming models like Q# significantly simplify the complexity of programming for quantum computing. These models are supported by a set of foundation libraries for code development. However, errors can occur in the library implementation, and one common root cause is the lack of or incomplete checks on properties like values, length, and quantum states of inputs passed to user-facing subroutines. This paper presents Upbeat, a fuzzing tool to generate random test cases for bugs related to input checking in Q# libraries. Upbeat develops an automated process to extract constraints from the API documentation and the developer implemented input-checking statements. It leverages open-source Q# code samples to synthesize test programs. It frames the test case generation as a constraint satisfaction problem for classical computing and a quantum state model for quantum computing to produce carefully generated subroutine inputs to test if the input-checking mechanism is appropriately implemented. Under 100 hours of automated test runs, Upbeat has successfully identified 16 bugs in API implementations and 4 documentation errors. Of these, 14 have been confirmed, and 12 have been fixed by the library developers.
To help the understanding and development of quantum algorithms there is an effort focused on the investigation of new semantic models and programming languages for quantum computing. Researchers in computer science have the challenge of deve loping programming languages to support the creation, analysis, modeling and simulation of high level quantum algorithms. Based on previous works that use monads inside the programming language Haskell to elegantly explain the odd characteristics of quantum computation (like superposition and entanglement), in this work we present a monadic Java library for quantum programming. We use the extension of the programming language Java called BGGA Closure, that allow the manipulation of anonymous functions (closures) inside Java. We exemplify the use of the library with an implementation of the Toffoli quantum circuit.