Automatic Generation and Verification of Quantum Hardware Characteristics and Constraints

Jincheng Zhang

This paper presents a novel hardware compiler designed to accelerate quantum information encoding leveraging the principles of quantum entanglement. The compiler's core functionality centers on automatically optimizing quantum algorithms for specific quantum hardware architectures, focusing on maximizing the efficiency of entanglement-based information encoding. The system employs a simulation approach based on entangled state circuits, integrating hardware-specific characteristics such as decoherence and connectivity during the compilation process. This allows for the generation of optimized quantum algorithms tailored to the unique constraints and capabilities of the target quantum device. The research addresses a critical gap in current quantum compilation techniques, which predominantly concentrate on general quantum algorithms without considering the nuanced impact of hardware limitations on entanglement-based encoding. This work outlines the architecture, key components, and optimization strategies of the compiler, highlighting its potential to significantly enhance the performance of quantum information processing.

Prabhat Mishra

Dimitrios Thanos, Alejandro Villoria, Sebastiaan Brand +4 more

Shangzhou Xia, Haitao Fu, Jianjun Zhao

With the growing interest in quantum programs, ensuring their correctness is a fundamental challenge. Although constraint-solving techniques can overcome some limitations of traditional testing and verification, they have not yet been sufficiently explored in the context of quantum programs. To address this gap, we present QSolver, the first quantum constraint solver. QSolver provides a structured framework for handling five types of quantum constraints and incorporates an automated assertion generation module to verify quantum states. QSolver transforms quantum programs and multi-moment constraints into symbolic representations, and utilizes an SMT solver to obtain quantum states that satisfy these constraints. To validate the correctness of the generated input states, QSolver automatically generates assertion programs corresponding to each constraint. Experimental results show that QSolver efficiently processes commonly used quantum gates and demonstrates good scalability across quantum programs of different sizes.

Robert Wille, L. Schmid, Yannick Stade +4 more

Quantum computing is a promising technology that requires a sophisticated software stack to connect end users to the wide range of possible quantum backends. However, current software tools are usually hard-coded for single platforms and lack a dynamic interface that can automatically retrieve and adapt to changing physical characteristics and constraints of different platforms. With new hardware platforms frequently introduced and their performance changing on a daily basis, this constitutes a serious limitation. In this paper, we show-case a concept and a prototypical realization of an interface, called the Quantum Device Management Interface (QDMI), that addresses this problem by explicitly connecting the software and hardware developers, mediating between their competing interests. QDMI allows hardware platforms to provide their physical characteristics in a standardized way, and software tools to query that data to guide the compilation process accordingly. This enables software tools to automatically adapt to different platforms and to optimize the compilation process for the specific hardware constraints. QDMI is a central part of the Munich Quantum Software Stack (MQSS)-a sophisticated software stack to connect end users to the wide range of possible quantum backends. QDMI is publicly available as open source at https://github.com/Munich-Quantum-Software-Stack/QDMI.

Mingsheng Ying, Nengkun Yu, Yuan Feng +1 more