Extracting Spectral Information from Noisy Quantum Data

点击翻译按钮获取中文摘要

Quantum computing describes an innovative approach to computing that utilizes the principles of quantum mechanics to solve problems in science and engineering. Existing implementations of quantum computers are highly susceptible to unwanted external disturbances, known as “decoherence”, which result in the loss of quantum information. This decoherence poses a significant constraint on the range of problems that can be simulated effectively on quantum computers. The limitation is especially severe in the simulation of properties of physically relevant and technologically significant quantum mechanical systems, such as molecules or solids. However, substantial knowledge exists regarding the mathematical and physical properties of these systems. This project aims to leverage this insight to improve the accuracy of quantum mechanical simulations on quantum computers. It will do so by designing precise and practical methodologies for reducing noise and improving accuracy, thereby promoting the progress of science.All quantum computers built so far suffer from noise and decoherence issues. When quantum computers are used to simulate the properties of molecules and solids in condensed matter and quantum chemistry, the main property of interest is the excitation information encoded in the spectra of response functions. This spectral information has mathematical properties that severely constrain the allowed response functions, and that can therefore be employed as a ‘noise filter’ for quantum computing data. This project will investigate ways to employ this mathematical information in practical algorithms to reduce noise of quantum data. Implementations and tests with synthetic data and with data from present-day quantum computers are proposed. In addition, an outreach collaboration with the University of Michigan’s Museum of Natural History will introduce the public at schools and libraries to quantum phenomena including quantum coherence.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.