Molecular Dynamics Workflow Decomposition for Hybrid Classic/Quantum Systems

Since we are entering the Post-Moore Law era and consequently the limit of Von Neumann's architecture, the scientific community is looking for alternatives to satisfy the growing computing power demands of scientific applications. Quantum computing promises to achieve a computational advantage over the classic Von Neumann architecture. However, the limited capabilities of current noisy intermediate-scale quantum (NISQ) devices require quantum computers to interoperate with classic systems, forming the so-called hybrid quantum systems. Research on hybrid quantum systems led to the design of Variational Quantum Algorithms, currently the most promising way to move towards quantum advantage. However, execution time and accuracy of variational quantum algorithms are affected by different hyperparameters, including selected cost functions and parametrized quantum circuits. Consequently, providing developers with methods to select the right set of parameters is of paramount importance. In this work, we provide a formal method for the selection of hyperparameters in variational quantum algorithms, which will support quantum algorithms developers in the design of quantum applications, and evaluate it on a real-world scientific application, showing a reduction of error up to 31%.

Automated summary

With the end of Moore's Law and the limitations of Von Neumann's architecture, scientists are seeking alternatives to meet the increasing computing demands of scientific applications, and quantum computing appears to be the most promising. However, the current limitations of quantum devices require them to interoperate with classical systems, forming hybrid quantum systems. Variational Quantum Algorithms have emerged as the most promising approach to achieve quantum advantage, but their execution time and accuracy are influenced by various hyperparameters. Therefore, providing methods for developers to select the right set of parameters is crucial.