activity
20182022
collaborators

6 papers

quant-ph2022

Experimental Quantum End-to-End Learning on a Superconducting Processor

Xiaoxuan Pan, Xi Cao, Weiting Wang +10

Machine learning can be substantially powered by a quantum computer owing to its huge Hilbert space and inherent quantum parallelism. In the pursuit of quantum advantages for machi…

quant-ph2020

Nearly quantum-limited Josephson-junction Frequency Comb synthesizer

Pinlei Lu, Saeed Khan, Tzu-Chiao Chien +5

While coherently-driven Kerr microcavities have rapidly matured as a platform for frequency comb formation, such microresonators generally possess weak Kerr coefficients; consequen…

quant-ph2020

End-to-End Quantum Machine Learning Implemented with Controlled Quantum Dynamics

Re-Bing Wu, Xi Cao, Pinchen Xie +1

Toward quantum machine learning deployed on imperfect near-term intermediate-scale quantum (NISQ) processors, the entire physical implementation of should include as less as possib…

quant-ph2019

Identification of Time-varying in situ Signals in Quantum Circuits

Xi Cao, Yu-xi Liu, Rebing Wu

The identification of time-varying \textit{in situ} signals is crucial for characterizing the dynamics of quantum processes occurring in highly isolated environments. Under certain…

quant-ph2019

Multiparametric Amplification and Qubit Measurement with a Kerr-free Josephson Ring Modulator

T. -C. Chien, O. Lanes, C. Liu +6

Josephson-junction based parametric amplifiers have become a ubiquitous component in superconducting quantum machines. Although parametric amplifiers regularly achieve near-quantum…

quant-ph2018

Learning to Calibrate Quantum Control Pulses by Iterative Deconvolution

Xi Cao, Bing Chu, Haijin Ding +3

In experimental control of quantum systems, the precision is often hindered by imperfect applied electronics that distort control pulses delivered to target quantum devices. To mit…