Autonomous Tuning for High-Fidelity Operation of Silicon Spin Qubits
Abstract
(1) Scientific objectives. The goal of this project, which fits most naturally in FastCARS (Research Area 1: Feedback for calibration, drift control, and stabilization and Research Area 2: Readout), is to develop software tools for automated tuning of high-fidelity readout and gates in silicon spin qubits. These efforts directly improve the scalability of the silicon spin qubit platform. (2) Methods to be employed. Our methodology will build on well-established tools for gate calibration such as randomized benchmarking, gate-set tomography, and cross-entropy benchmarking, while also pioneering new methods to estimate non-Markovian noise sources accurately. In addition, we will develop methods to implement optimal readout of spin qubits. Initial efforts in autonomous tuning will focus on optimizing readout systems, shifting to the gate and mid-circuit measurements in the second half of the project. We will collaborate with experimental groups to implement our new tomographic and autonomous tuning protocols as they become available. A further focus of this project is on the consideration of implementing developed software methods on specialized hardware, such as field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), or neuromorphic devices. The small physical size and the energy-efficient behavior of such hardware allow for an experimental integration close to the qubit system. (3) Significance of the proposed effort to the advancement of knowledge. The final outcomes of this project will be the development of software and systematic methods (detailed in publications) for autonomous tuning of high-fidelity readout and gate control for silicon spin qubits. In addition, we will develop new characterization methods that can efficiently treat fluctuating and non-Markovian noise sources relevant to silicon spin qubits. Integrating control tasks such as autonomous tuning, readout, and gate control in the experimental setup significantly reduces the amount of data transfer to external computers, as well as interactions with the environment. Such improvements are essential to guarantee a well-controlled, fast, and stable operation of silicon spin qubits. Such tools will be absolutely essential in scaling up silicon spin qubits to large intermediate-scale quantum processors, as well as future fault-tolerant quantum computers.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jul 27, 2023
- Source ID
- W911NF2310258
Entities
People
- Michael Gullans
Organizations
- Army Contracting Command
- National Security Agency
- University of Maryland