1:00 - 2:00 PM
High-fidelity and robust quantum control and quantum machine learning
Hsi-Sheng Goan
National Taiwan University
Abstract: To realize practical quantum computation, the ability to precisely control qubit systems is a prerequisite. To increase the reliable circuit depth on noisy intermediate-scale quantum (NISQ) computing devices, or achieve the ultimate goal of error-corrected fault-tolerant quantum computation, constructing high-fidelity and robust quantum gates to meet the stringent computing requirements (beyond the fault-tolerant error threshold) is an important and timely issue. Besides, as the size of the quantum processors scales up, the cross-talk effects from the neighboring qubits will get worse, and the gate robustness against the noises, the uncertainties of system parameters, and the imprecise pulse calibrations will become more important. The simple or intuitive control pulses implemented in experiments, which often do not take these factors into accounts, could not achieve very accurate gates. On the other hand, optimal control methods have the potential ability to construct high-fidelity and robust quantum gates tackling these multiple issues simultaneously. We apply the robust control method [1,2] to construct smooth optimal control pulses to enhance the gate fidelity and enlarge the robust window against noises and system parameter uncertainties for superconducting transmon qubits [3].
If the time allows, we will also briefly discuss the concept of quantum machine learning, and introduce the quantum-train framework, a novel approach that integrates quantum computing with classical machine learning algorithms for quantum-circuit-based parameter-efficient learning [4].
2:00 - 3:00 PM
Measurement-induced entanglement and control transitions using feedback
Justin Wilson
Department of physics, Louisiana State University
Abstract: In recent years, substantial progress has been achieved in understanding entanglement transitions in monitored quantum systems. In this talk, I will summarize some key facts we've learned and how they can be used in quantum control protocols. Drawing parallels with classically chaotic systems, we identify features that link and delink measurement and control transitions. In particular, by strategically engineering around an (approximate) unstable fixed point, control can be achieved at or above the measurement-induced phase transition. When these points coincide, the critical properties of control dominate other critical properties, becoming observable in linear operators in the density matrix. Conversely, when these transitions diverge, the entanglement transition can achieve different critical properties. We substantiate these findings through several versions of a quantum analog of the Bernoulli map: A purely quantum version, a stabilizer state version, and a limit that can be simulated classically as a (correlated) percolation problem. Finally, we point to some critical unanswered questions in the field.