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1. QDB: From Quantum Algorithms Towards Correct Quantum Programs.

   Huang, Yipeng; Martonosi, Margaret (November 2018, PLATEAU, a workshop co-located with SPLASH)

   With the advent of small-scale prototype quantum computers, researchers can now code and run quantum algorithms that were previously proposed but not fully implemented. In support of this growing interest in quantum computing experimentation, programmers need new tools and techniques to write and debug QC code. In this work, we implement a range of QC algorithms and programs in order to discover what types of bugs occur and what defenses against those bugs are possible in QC programs. We conduct our study by running small-sized QC programs in QC simulators in order to replicate published results in QC implementations. Where possible, we cross-validate results from programs written in different QC languages for the same problems and inputs. Drawing on this experience, we provide a taxonomy for QC bugs, and we propose QC language features that would aid in writing correct code. 

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2. QDB: From Quantum Algorithms Towards Correct Quantum Programs

   https://doi.org/10.4230/OASIcs.PLATEAU.2018.4  

   Huang, Yipeng; Martonosi, Margaret. (October 2019, PLATEAU Workshop at ACM conference on Systems, Programming, Languages and Applications: Software for Humanity (SPLASH). 2018.)

   With the advent of small-scale prototype quantum computers, researchers can now code and run quantum algorithms that were previously proposed but not fully implemented. In support of this growing interest in quantum computing experimentation, programmers need new tools and techniques to write and debug QC code. In this work, we implement a range of QC algorithms and programs in order to discover what types of bugs occur and what defenses against those bugs are possible in QC programs. We conduct our study by running small-sized QC programs in QC simulators in order to replicate published results in QC implementations. Where possible, we cross-validate results from programs written in different QC languages for the same problems and inputs. Drawing on this experience, we provide a taxonomy for QC bugs, and we propose QC language features that would aid in writing correct code. 

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3. Statistical assertions for validating patterns and finding bugs in quantum programs

   https://doi.org/10.1145/3307650.3322213  

   Huang, Yipeng; Martonosi, Margaret (June 2019, Proceedings of the 46th International Symposium on Computer Architecture (ISCA ’19))

   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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4. CutQC: using small Quantum computers for large Quantum circuit evaluations

   https://doi.org/10.1145/3445814.3446758  

   Tang, Wei; Tomesh, Teague; Suchara, Martin; Larson, Jeffrey; Martonosi, Margaret (April 2021, Proceedings of the 26th ACM International Conference on Architectural Support for Programming Languages and Operating Systems)

   Quantum computing (QC) is a new paradigm offering the potential of exponential speedups over classical computing for certain computational problems. Each additional qubit doubles the size of the computational state space available to a QC algorithm. This exponential scaling underlies QC’s power, but today’s Noisy Intermediate-Scale Quantum (NISQ) devices face significant engineering challenges in scalability. The set of quantum circuits that can be reliably run on NISQ devices is limited by their noisy operations and low qubit counts. This paper introduces CutQC, a scalable hybrid computing approach that combines classical computers and quantum computers to enable evaluation of quantum circuits that cannot be run on classical or quantum computers alone. CutQC cuts large quantum circuits into smaller subcircuits, allowing them to be executed on smaller quantum devices. Classical postprocessing can then reconstruct the output of the original circuit. This approach offers significant runtime speedup compared with the only viable current alternative -- purely classical simulations -- and demonstrates evaluation of quantum circuits that are larger than the limit of QC or classical simulation. Furthermore, in real-system runs, CutQC achieves much higher quantum circuit evaluation fidelity using small prototype quantum computers than the state-of-the-art large NISQ devices achieve. Overall, this hybrid approach allows users to leverage classical and quantum computing resources to evaluate quantum programs far beyond the reach of either one alone. 

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5. Exploiting Quantum Assertions for Error Mitigation and Quantum Program Debugging

   https://doi.org/10.1109/ICCD56317.2022.00028  

   Li, Peiyi; Liu, Ji; Li, Yangjia; Zhou, Huiyang (October 2022, 2022 IEEE 40th International Conference on Computer Design (ICCD))

   An assertion is a predicate that should be evaluated true during program execution. In this paper, we present the development of quantum assertion schemes and show how they are used for hardware error mitigation and software debugging. Compared to assertions in classical programs, quantum assertions are challenging due to the no-cloning theorem and potentially destructive measurement. We discuss how these challenges can be circumvented such that certain properties of quantum states can be verified non-destructively during program execution. Furthermore, we show that besides detecting program bugs, dynamic assertion circuits can mitigate noise effects via post-selection of the assertion results. Our case studies demonstrate the use of quantum assertions in various quantum algorithms. 

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