activity
20162026
most citedQuantum Optimization of Maximum Independent Set using Rydberg Atom Arrays

456 citations · 1.7k across the 24 of their papers we have counts for

collaborators

26 papers

quant-ph2026

CoDecoder: Make Quantum Decoders Up to 100x Faster and Even More Accurate

Yicheng Guang, Yuliang Xiong, Xun Gao +1

Fault-tolerant quantum computers need fast and accurate error decoding. We present CoDecoder, a small neural frontend that composes with an existing decoder to improve accuracy and…

quant-ph2023★ 20 cited

Native approach to controlled-Z gates in inductively coupled fluxonium qubits

Xizheng Ma, Gengyan Zhang, Feng Wu +27

The fluxonium qubits have emerged as a promising platform for gate-based quantum information processing. However, their extraordinary protection against charge fluctuations comes a…

quant-ph2022★ 78 cited

A polynomial-time classical algorithm for noisy random circuit sampling

Dorit Aharonov, Xun Gao, Zeph Landau +2

We give a polynomial time classical algorithm for sampling from the output distribution of a noisy random quantum circuit in the regime of anti-concentration to within inverse poly…

quant-ph2022★ 2 cited

Expressive Quantum Perceptrons for Quantum Neuromorphic Computing

Rodrigo Araiza Bravo, Khadijeh Najafi, Taylor L. Patti +2

Quantum neuromorphic computing (QNC) is a sub-field of quantum machine learning (QML) that capitalizes on inherent system dynamics. As a result, QNC can run on contemporary, noisy…

quant-ph2022★ 33 cited

Interpretable Quantum Advantage in Neural Sequence Learning

Eric R. Anschuetz, Hong-Ye Hu, Jin-Long Huang +1

Quantum neural networks have been widely studied in recent years, given their potential practical utility and recent results regarding their ability to efficiently express certain…

quant-ph2022★ 1 cited

Many-body localized hidden generative models

Weishun Zhong, Xun Gao, Susanne F. Yelin +1

Born machines are quantum-inspired generative models that leverage the probabilistic nature of quantum states. Here, we present a new architecture called many-body localized (MBL)…

quant-ph2022

Ultrafast adiabatic passages in ultrastrongly coupled light-matter systems

Xun Gao, Liwei Duan, Pinghua Tang +4

We have obtained the solutions of the multimode quantum Rabi model when all modes have identical frequencies , including dark states with at least $(K=1,2,3,\l…

quant-ph2022★ 456 cited

Quantum Optimization of Maximum Independent Set using Rydberg Atom Arrays

Sepehr Ebadi, Alexander Keesling, Madelyn Cain +21

Realizing quantum speedup for practically relevant, computationally hard problems is a central challenge in quantum information science. Using Rydberg atom arrays with up to 289 qu…

quant-ph2021★ 152 cited

Fluxonium: an alternative qubit platform for high-fidelity operations

Feng Bao, Hao Deng, Dawei Ding +25

Superconducting qubits provide a promising path toward building large-scale quantum computers. The simple and robust transmon qubit has been the leading platform, achieving multipl…

quant-ph2021★ 43 cited

Limitations of Linear Cross-Entropy as a Measure for Quantum Advantage

Xun Gao, Marcin Kalinowski, Chi-Ning Chou +3

Demonstrating quantum advantage requires experimental implementation of a computational task that is hard to achieve using state-of-the-art classical systems. One approach is to pe…

quant-ph2021★ 1 cited

Quantum reservoir computing using arrays of Rydberg atoms

Rodrigo Araiza Bravo, Khadijeh Najafi, Xun Gao +1

Quantum computing promises to provide machine learning with computational advantages. However, noisy intermediate-scale quantum (NISQ) devices pose engineering challenges to realiz…

quant-ph2021★ 84 cited

Enhancing Generative Models via Quantum Correlations

Xun Gao, Eric R. Anschuetz, Sheng-Tao Wang +2

Generative modeling using samples drawn from the probability distribution constitutes a powerful approach for unsupervised machine learning. Quantum mechanical systems can produce…

quant-ph2020★ 148 cited

Entanglement Devised Barren Plateau Mitigation

Taylor L. Patti, Khadijeh Najafi, Xun Gao +1

Hybrid quantum-classical variational algorithms are one of the most propitious implementations of quantum computing on near-term devices, offering classical machine learning suppor…

quant-ph2020★ 85 cited

Classical Simulation of Quantum Supremacy Circuits

Cupjin Huang, Fang Zhang, Michael Newman +10

It is believed that random quantum circuits are difficult to simulate classically. These have been used to demonstrate quantum supremacy: the execution of a computational task on a…

quant-ph2020

Spoofing Linear Cross-Entropy Benchmarking in Shallow Quantum Circuits

Boaz Barak, Chi-Ning Chou, Xun Gao

The linear cross-entropy benchmark (Linear XEB) has been used as a test for procedures simulating quantum circuits. Given a quantum circuit with inputs and outputs and purp…

quant-ph2020★ 8 cited

Alibaba Cloud Quantum Development Platform: Surface Code Simulations with Crosstalk

Cupjin Huang, Xiaotong Ni, Fang Zhang +11

We report, in a sequence of notes, our work on the Alibaba Cloud Quantum Development Platform (AC-QDP). AC-QDP provides a set of tools for aiding the development of both quantum co…

quant-ph2019★ 17 cited

Alibaba Cloud Quantum Development Platform: Applications to Quantum Algorithm Design

Cupjin Huang, Mario Szegedy, Fang Zhang +3

We report our work on the Alibaba Cloud Quantum Development Platform (AC-QDP). The capability of AC-QDP's computational engine was already reported in \cite{CZH+18, ZHN+19}.In this…

quant-ph2019★ 3 cited

Alibaba Cloud Quantum Development Platform: Large-Scale Classical Simulation of Quantum Circuits

Fang Zhang, Cupjin Huang, Michael Newman +10

We report, in a sequence of notes, our work on the Alibaba Cloud Quantum Development Platform(AC-QDP). AC-QDP provides a set of tools for aiding the development of both quantum com…

quant-ph2018★ 66 cited

Efficient Representation of Topologically Ordered States with Restricted Boltzmann Machines

Sirui Lu, Xun Gao, L. -M. Duan

Representation by neural networks, in particular by restricted Boltzmann machines (RBM), has provided a powerful computational tool to solve quantum many-body problems. An importan…

quant-ph2018★ 25 cited

Efficient classical simulation of noisy quantum computation

Xun Gao, Luming Duan

Understanding the boundary between classical simulatability and the power of quantum computation is a fascinating topic. Direct simulation of noisy quantum computation requires sol…

quant-ph2017★ 19 cited

An efficient quantum algorithm for generative machine learning

Xun Gao, Zhengyu Zhang, Luming Duan

A central task in the field of quantum computing is to find applications where quantum computer could provide exponential speedup over any classical computer. Machine learning repr…

quant-ph2017★ 8 cited

Can Chaotic Quantum Circuits Maintain Quantum Supremacy under Noise?

Man-Hong Yung, Xun Gao

Although the emergence of a fully-functional quantum computer may still be far away from today, in the near future, it is possible to have medium-size, special-purpose, quantum dev…

cond-mat.dis-nn2017★ 346 cited

Efficient Representation of Quantum Many-body States with Deep Neural Networks

Xun Gao, Lu-Ming Duan

The challenge of quantum many-body problems comes from the difficulty to represent large-scale quantum states, which in general requires an exponentially large number of parameters…

quant-ph2016

Experimental Study of Forrelation in Nuclear Spins

Hang Li, Xun Gao, Tao Xin +2

Correlation functions are often employed to quantify the relationships among interdependent variables or sets of data. Recently, a new class of correlation functions, called Forrel…