Towards an Automated Framework for Realizing Quantum Computing Solutions

Abstract

Quantum computing is fast evolving as a technology due to recent advances in hardware, software, as well as the development of promising applications. To use this technology for solving specific problems, a suitable quantum algorithm has to be determined, the problem has to be encoded in a form suitable for the chosen algorithm, it has to be executed, and the result has to be decoded. To date, each of these tedious and error-prone steps is conducted in a mostly manual fashion. This creates a high entry barrier for using quantum computing -- especially for users with little to no expertise in that domain. In this work, we envision a framework that aims to lower this entry barrier by allowing users to employ quantum computing solutions in an automatic fashion. To this end, interfaces as similar as possible to classical solvers are provided, while the quantum steps of the workflow are shielded from the user as much as possible by a fully automated backend. To demonstrate the feasibility and usability of such a framework, we provide proof-of-concept implementations for two different classes of problems which are publicly available on GitHub (https://github.com/cda-tum/MQTProblemSolver) as part of the Munich Quantum Toolkit (MQT). By this, this work provides the foundation for a low-threshold approach realizing quantum computing solutions with no or only moderate expertise in this technology.

7 pages, 4 figures, minor changes, to be published at International Symposium on Multiple-Valued Logic (ISMVL), 2023

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Cited by in corpus (7)

• The MQT Handbook: A Summary of Design Automation Tools and Software for Quantum Computing
• Predicting Good Quantum Circuit Compilation Options
• MQT Predictor: Automatic Device Selection with Device-Specific Circuit Compilation for Quantum Computing
• Recommending Solution Paths for Solving Optimization Problems with Quantum Computing
• A Hybrid Classical Quantum Computing Approach to the Satellite Mission Planning Problem
• Reducing the Compilation Time of Quantum Circuits Using Pre-Compilation on the Gate Level
• A Predictive Approach for Selecting the Best Quantum Solver for an Optimization Problem