53 citations · 328 across the 20 of their papers we have counts for
23 papers
Mid-circuit measurements and feedforward implement every unitary exactly in constant depth
Chenfeng Cao
Mid-circuit measurements with feedforward reduce the optimal worst-case quantum depth for exact -qubit unitary synthesis from to , using arbitrary one- and two-qubi…
Apparent Compression, Real Stability: The Intrinsic Dimension of Learning a Quantum Wavefunction
Lu Wei, Yufeng Wang, Chenfeng Cao +1
How many directions in weight space does training need? The intrinsic dimension answers this with the smallest number of random directions in which training still reaches a target…
AG-CoT: Verified Algorithmic Traces for LLM Program Synthesis on Clifford Circuits
Lu Wei, Yufeng Wang, Chenfeng Cao +2
Scientific code generation can produce executable programs that fail to compute the intended scientific object. We study this problem in language-model synthesis of Clifford circui…
Exploiting many-body localization for scalable variational quantum simulation
Chenfeng Cao, Yeqing Zhou, Swamit Tannu +2
Variational quantum algorithms (VQAs) represent a promising pathway toward achieving practical quantum advantage on near-term hardware. Despite this promise, for generic, expressiv…
Accelerated variational quantum eigensolver with joint Bell measurement
Chenfeng Cao, Hiroshi Yano, Yuya O. Nakagawa
The variational quantum eigensolver (VQE) stands as a prominent quantum-classical hybrid algorithm for near-term quantum computers to obtain the ground states of molecular Hamilton…
Solution of SAT Problems with the Adaptive-Bias Quantum Approximate Optimization Algorithm
Yunlong Yu, Chenfeng Cao, Xiang-Bin Wang +2
The quantum approximate optimization algorithm (QAOA) is a promising method for solving certain classical combinatorial optimization problems on near-term quantum devices. When emp…
Detecting Entanglement by Pure Bosonic Extension
Xuanran Zhu, Chao Zhang, Chenfeng Cao +3
In the realm of quantum information theory, the detection and quantification of quantum entanglement stand as paramount tasks. The relative entropy of entanglement (REE) serves as…
Maximum entropy methods for quantum state compatibility problems
Shi-Yao Hou, Zipeng Wu, Jinfeng Zeng +4
Inferring a quantum system from incomplete information is a common problem in many aspects of quantum information science and applications, where the principle of maximum entropy (…
Quantum variational learning for quantum error-correcting codes
Chenfeng Cao, Chao Zhang, Zipeng Wu +2
Quantum error correction is believed to be a necessity for large-scale fault-tolerant quantum computation. In the past two decades, various constructions of quantum error-correctin…
Mitigating algorithmic errors in quantum optimization through energy extrapolation
Chenfeng Cao, Yunlong Yu, Zipeng Wu +3
Quantum optimization algorithms offer a promising route to finding the ground states of target Hamiltonians on near-term quantum devices. None the less, it remains necessary to lim…
Learning quantum phases via single-qubit disentanglement
Zheng An, Chenfeng Cao, Cheng-Qian Xu +1
Identifying phases of matter presents considerable challenges, particularly within the domain of quantum theory, where the complexity of ground states appears to increase exponenti…
Quantum Approximate Optimization Algorithm with Adaptive Bias Fields
Yunlong Yu, Chenfeng Cao, Carter Dewey +3
The quantum approximate optimization algorithm (QAOA) transforms a simple many-qubit wavefunction into one which encodes a solution to a difficult classical optimization problem. I…
Quantum imaginary time evolution steered by reinforcement learning
Chenfeng Cao, Zheng An, Shi-Yao Hou +2
The quantum imaginary time evolution is a powerful algorithm for preparing the ground and thermal states on near-term quantum devices. However, algorithmic errors induced by Trotte…
All-optical neural network quantum state tomography
Ying Zuo, Chenfeng Cao, Ningping Cao +3
Quantum state tomography (QST) is a crucial ingredient for almost all aspects of experimental quantum information processing. As an analog of the "imaging" technique in the quantum…
SpinQ Gemini: a desktop quantum computer for education and research
Shi-Yao Hou, Guanru Feng, Zipeng Wu +13
SpinQ Gemini is a commercial desktop quantum computer designed and manufactured by SpinQ Technology. It is an integrated hardware-software system. The first generation product with…
Noise-Assisted Quantum Autoencoder
Chenfeng Cao, Xin Wang
Quantum autoencoder is an efficient variational quantum algorithm for quantum data compression. However, previous quantum autoencoders fail to compress and recover high-rank mixed…
Phase Analysis on the Error Scaling of Entangled Qubits in a 53-Qubit System
Wei-Jia Huang, Wei-Chen Chien, Chien-Hung Cho +6
We have studied carefully the behaviors of entangled qubits on the IBM Rochester with various connectivities and under a "noisy" environment. A phase trajectory analysis based on o…
Simulating noisy variational quantum eigensolver with local noise models
Jinfeng Zeng, Zipeng Wu, Chenfeng Cao +4
Variational quantum eigensolver (VQE) is promising to show quantum advantage on near-term noisy-intermediate-scale quantum (NISQ) computers. One central problem of VQE is the effec…
A variational quantum algorithm for Hamiltonian diagonalization
Jinfeng Zeng, Chenfeng Cao, Chao Zhang +2
Hamiltonian diagonalization is at the heart of understanding physical properties and practical applications of quantum systems. It is highly desired to design quantum algorithms th…
Speedup of the Quantum Adiabatic Algorithm using Delocalization Catalysis
Chenfeng Cao, Jian Xue, Nic Shannon +1
We propose a method to speed up the quantum adiabatic algorithm using catalysis by many-body delocalization. This is applied to random-field antiferromagnetic Ising spin models. Th…
Supervised learning in Hamiltonian reconstruction from local measurements on eigenstates
Chenfeng Cao, Shi-Yao Hou, Ningping Cao +1
Reconstructing a system Hamiltonian through measurements on its eigenstates is an important inverse problem in quantum physics. Recently, it was shown that generic many-body local…
Simulating Noisy Quantum Circuits with Matrix Product Density Operators
Song Cheng, Chenfeng Cao, Chao Zhang +4
Simulating quantum circuits with classical computers requires resources growing exponentially in terms of system size. Real quantum computer with noise, however, may be simulated p…
Upper bounds for relative entropy of entanglement based on active learning
Shi-Yao Hou, Chenfeng Cao, D. L. Zhou +1
Quantifying entanglement for multipartite quantum state is a crucial task in many aspects of quantum information theory. Among all the entanglement measures, relative entropy of en…