NSF-BSF: Efficiently Modeling Continuous Quantum Measurements of High-Dimensional Multi-Qubit Systems

Chapman University, Orange CA

Investigators

Abstract

Modern computers developed rapidly, leading to a historically unprecedented wealth of technology. This technological revolution has improved standards of living globally and has become a cornerstone of the modern economy. Recently, the rapid growth of computational power has slowed, in part because the size of hardware components has shrunk to microscopic scales. At microscopic scales, hardware behaves according to the laws of quantum mechanics, which are quite different from the laws expected for traditional computers. These differences have impeded continued growth using established hardware techniques, but also allow for new possibilities. Efforts are ongoing to develop a paradigm of hardware that leverages the nuances of quantum mechanics to accelerate computation. This project contributes to these quantum computing efforts by addressing a pressing simulation problem for superconducting quantum circuits, which are a promising candidate for scalable quantum technology. The difficulty in accurately describing such a quantum circuit grows rapidly with the size of the system, making hardware design challenging. If successful, this work will provide numerical methods and open source software that dramatically simplify this modeling task for common scenarios, which should help accelerate the future development of superconducting quantum circuits. Large numbers of parameters are generally required to describe quantum circuits, making brute force simulation challenging. A particularly important example of this high dimensionality occurs during the standard measurement protocol for quantum circuits. In this protocol, traveling microwave fields couple with microwave resonators, which in turn couple with nonlinear oscillators that have several energy levels. As the traveling field is collected, the quantum system continuously evolves in accordance with the measured stochastic signal, producing complicated dynamics. This project will develop efficient methods for simulating these continuous quantum measurements using several design phases. After developing a full reference numerical model for the microwave amplification and readout circuitry on a multi-component chip, we will develop simplified semi-classical representations that compress the high dimensionality into a smaller number of parameters. These simplifications will extend known weak-field coherent steady-state approximations of the microwave dynamics to account for nonlinear effects. This project will explore the use of machine learning methods, particularly recurrent neural networks, to automatically learn how to compress the dynamics efficiently. In parallel, undergraduates will perform outreach to the local community through demonstrations, videos, and more to raise public literacy of quantum mechanics. This project will deliver open-source software, online interactive notes, and tutorials as part of its broad outreach effort. 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.