6 citations · 12 across the 10 of their papers we have counts for
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Toward Consistent High-fidelity Quantum Learning on Unstable Devices via Efficient In-situ Calibration
Zhirui Hu, Robert Wolle, Mingzhen Tian +3
In the near-term noisy intermediate-scale quantum (NISQ) era, high noise will significantly reduce the fidelity of quantum computing. Besides, the noise on quantum devices is not s…
Online Detection of Golden Circuit Cutting Points
Daniel T. Chen, Ethan H. Hansen, Xinpeng Li +7
Quantum circuit cutting has emerged as a promising method for simulating large quantum circuits using a collection of small quantum machines. Running low-qubit "circuit fragments"…
Carbon Emissions of Quantum Circuit Simulation: More than You Would Think
Jinyang Li, Qiang Guan, Dingwen Tao +1
The rapid advancement of quantum hardware brings a host of research opportunities and the potential for quantum advantages across numerous fields. In this landscape, quantum circui…
Battle Against Fluctuating Quantum Noise: Compression-Aided Framework to Enable Robust Quantum Neural Network
Zhirui Hu, Youzuo Lin, Qiang Guan +1
Recently, we have been witnessing the scale-up of superconducting quantum computers; however, the noise of quantum bits (qubits) is still an obstacle for real-world applications to…
Efficient Quantum Circuit Cutting by Neglecting Basis Elements
Daniel T. Chen, Ethan H. Hansen, Xinpeng Li +7
Quantum circuit cutting has been proposed to help execute large quantum circuits using only small and noisy machines. Intuitively, cutting a qubit wire can be thought of as classic…
Improving CNN-base Stock Trading By Considering Data Heterogeneity and Burst
Keer Yang, Guanqun Zhang, Chuan Bi +3
In recent years, there have been quite a few attempts to apply intelligent techniques to financial trading, i.e., constructing automatic and intelligent trading framework based on…