CAREER: The Research of Noise-Aware Scheduling for Noisy Intermediate-Scale Quantum Systems

点击翻译按钮获取中文摘要

In the Noisy Intermediate-Scale Quantum (NISQ) era, it is crucial to improve the fidelity of quantum computing, enabling the correctness of quantum algorithms. Designers of quantum algorithms need to clearly understand the hidden noise of different quantum computers and the noise inside different compiled circuits on the same quantum computer for a specific quantum algorithm. However, this is not a trivial task. The community lacks a systematic solution to overcome the impact of noise on the execution of the jobs. Existing error mitigation methods suffer from unaffordable overhead or unpredictable performance. The proposed approach addresses the major challenges that come from the complex and dynamically evolving quality of quantum computers and significant variations of the compiled circuits. The project's impacts include designing a novel noise-aware scheduling system for quantum cloud systems and a simulation framework for testing scheduling algorithms for quantum cloud systems. The proposed research will enhance the utilization and efficiency of the NISQ-era quantum cloud system. The proposed cloud system simulation toolkit bridges the gap of the lack of an experimental platform for quantum cloud system research by enabling a simulation platform for new resource management and scheduling approaches. In addition, the curriculum development and the student training program support the development of a diverse and competitive workforce of quantum information and science. New courses and new curriculum concentrations in quantum computing will be developed. Graduate and undergraduate students, especially from underrepresented groups, will be trained in multiple disciplines that will enable them to have successful careers in quantum information and science.This project builds upon existing knowledge to create a new insightful approach that enables the efficient usage of noisy quantum computers. This project presents the novelty of the research, practical value, and domain impacts. The research team will design, develop, and apply new methods to 1) profile and model hardware fidelity's temporal and spatial pattern, study the spatial and temporal noise model based on the temporal pattern, and further build the fidelity forecast mode; 2) build a novel noise-aware scheduling system, which proposes the optimal scheduling approach for backend allocation and qubit allocation based on the circuit noise tolerance factor and the prediction of the hardware fidelity; 3) build quantum cloud simulation toolkit to allow the quantum system engineers and researchers to test and evaluate the new resource management and scheduling strategies; 4) build a new training program “Quantum Computing for All”, by compiling the research outcomes to foster the workforce of quantum information and science.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.