456 citations · 1.9k across the 27 of their papers we have counts for
15 papers · 1 filter
Quantum Compiler Design for Fault-Tolerant Quantum Computing
Chenghong Zhu, Jiahan Chen, Keming He +9
Scalable quantum computation is expected to rely on fault-tolerant quantum computation (FTQC), in which quantum error correction (QEC) suppresses physical errors sufficiently to su…
Sampling isometric tensor network states with monitored quantum circuits
Yuqing Rong, Huan-Hai Zhou, Guo-Yi Zhu +1
Projected entangled pair states (PEPS) provide an efficient variational ansatz for two-dimensional quantum phases, but computing observables remains challenging because PEPS contra…
Decoupling 2D translation-invariant topological CSS codes
Yifei Wang, Zhongyi Ni, Mingxin He +2
Two-dimensional translation-invariant topological CSS codes on qubits are known to be locally equivalent, after coarse-graining, to stacks of toric codes. However, existing constru…
Realified tensor networks: quantum circuit simulation on real-valued matrix accelerators
Yusheng Zhao, Xiwei Pan, Enji Xiong +2
Tensor-network contraction simulates quantum circuits, but modern matrix accelerators (NPUs, TPUs) expose only real GEMM pipelines, so the complex networks of quantum simulation mu…
Measurement-Free Toric-Code Memory in Array Globally Controlled Rydberg Array
Han Wang, Yusheng Zhao, Xiuhao Deng +1
The central prerequisite of any fault-tolerant quantum architecture is a quantum memory: a block of encoded physical qubits whose logical state is actively preserved against noise…
Ergotropy of quantum many-body scars
Zhaohui Zhi, Qingyun Qian, Jin-Guo Liu +1
Quantum many-body scars break ergodicity and evade thermalization, resulting in sub-volume law entanglement entropy even with high energy density. While their quantum correlations…
Quantum speedup for combinatorial optimization with flat energy landscapes
Madelyn Cain, Sambuddha Chattopadhyay, Jin-Guo Liu +3
Designing quantum algorithms with a speedup over their classical analogs is a central challenge in quantum information science. Motivated by recent experimental observations of a s…
Quantum optimization with arbitrary connectivity using Rydberg atom arrays
Minh-Thi Nguyen, Jin-Guo Liu, Jonathan Wurtz +3
Programmable quantum systems based on Rydberg atom arrays have recently been used for hardware-efficient tests of quantum optimization algorithms [Ebadi et al., Science, 376, 1209…
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…
Probabilistic Nonunitary Gate in Imaginary Time Evolution
Tong Liu, Jin-Guo Liu, Heng Fan
Simulation of quantum matters is a significant application of quantum computers. In contrast to the unitary operation which can be realized naturally on a quantum computer, the imp…
Solving Quantum Statistical Mechanics with Variational Autoregressive Networks and Quantum Circuits
Jin-Guo Liu, Liang Mao, Pan Zhang +1
We extend the ability of unitary quantum circuits by interfacing it with classical autoregressive neural networks. The combined model parametrizes a variational density matrix as a…
Yao.jl: Extensible, Efficient Framework for Quantum Algorithm Design
Xiu-Zhe Luo, Jin-Guo Liu, Pan Zhang +1
We introduce Yao, an extensible, efficient open-source framework for quantum algorithm design. Yao features generic and differentiable programming of quantum circuits. It achieves…
Variational Quantum Eigensolver with Fewer Qubits
Jin-Guo Liu, Yi-Hong Zhang, Yuan Wan +1
We propose a qubit efficient scheme to study ground state properties of quantum many-body systems on near-term noisy intermediate scale quantum computers. One can obtain a tensor n…
Learning and Inference on Generative Adversarial Quantum Circuits
Jinfeng Zeng, Yufeng Wu, Jin-Guo Liu +2
Quantum mechanics is inherently probabilistic in light of Born's rule. Using quantum circuits as probabilistic generative models for classical data exploits their superior expressi…
Differentiable Learning of Quantum Circuit Born Machine
Jin-Guo Liu, Lei Wang
Quantum circuit Born machines are generative models which represent the probability distribution of classical dataset as quantum pure states. Computational complexity consideration…