FET: Small: Efficient Inference Tools for Quantum Systems: Algorithms, Applications, and Analysis

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Quantum information science has entered an exciting new era. Researchers are now actively trying to build quantum computers that can achieve significant gains over classical computers. For example, Shor's quantum algorithm for factoring large integers can achieve an exponential speedup over the current best classical approaches. To realize this goal, however, researchers must design fault-tolerant protocols that deal with the fragile nature of quantum phenomena. In this broader context, this project will design efficient protocols to extract reliable information from noisy quantum devices. Another part of this project will use information-theoretic tools to study the information-processing power of quantum networks. The results are expected to have broad applications in quantum information science. The PIs will also mentor graduate students and provide undergraduate research opportunities in quantum technologies.The ability to distinguish quantum states is an important part of quantum communications and quantum information science. Even in relatively simple quantum systems, it can be difficult to design and implement good protocols for quantum state discrimination. One goal of this project is to answer the question: Are there efficient methods of quantum state discrimination that apply to large classes of practically relevant states? This is related to another part of the project, whose goal is to understand the strengths and limitations of quantum technology in the emerging era of noisy intermediate-scale quantum devices. This project will investigate the rate at which information and entanglement decay in noisy quantum networks. For instance, we will derive noise thresholds, below which information and entanglement can propagate through networks. Such results can be applied to fault-tolerant quantum computing and also to analyze information scrambling in chaotic quantum systems, such as black holes. Many research directions in this project are built upon mathematical tools for analyzing quantum systems, such as the strong data-processing inequality. The final part of this project will develop these tools and derive information-theoretic limits for quantum state discrimination and quantum networks.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.