54 citations · 320 across the 29 of their papers we have counts for
29 papers
Physics-informed quantum algorithms for glueball-like excitations in a lattice gauge theory
Dan-Bo Zhang
Glueball spectroscopy and real-time production with quantum computing require three distinct ingredients: a correlated gauge vacuum, a controlled construction of pure-gauge excitat…
Interference Engineering for Quantum Imaginary-Time Evolution through Multiple Energy Shifts
Hong-Jian Tang, Dan-Bo Zhang
Energy shifting is usually trivial in imaginary-time evolution because it changes only the normalization of the evolved state. On a quantum computer, however, imaginary-time evolut…
Full-counting statistics of particle distribution on a digital quantum computer
Yun-Zhuo Fan, Dan-Bo Zhang
Full-counting statistics (FCS) provides a powerful framework to access the statistical information of a system from the characteristic function. However, applications of FCS for ge…
Variational quantum algorithms for scanning the complex spectrum of non-Hermitian systems
Xu-Dan Xie, Zheng-Yuan Xue, Dan-Bo Zhang
Solving non-Hermitian quantum many-body systems on a quantum computer by minimizing the variational energy is challenging as the energy can be complex. Here, based on energy varian…
Dissipative Quantum Gibbs Sampling
Daniel Zhang, Jan Lukas Bosse, Toby Cubitt
Systems in thermal equilibrium at non-zero temperature are described by their Gibbs state. For classical many-body systems, the Metropolis-Hastings algorithm gives a Markov process…
Quantum algorithm for evaluating operator size with Bell measurements
Xi-Dan Hu, Tong Luo, Dan-Bo Zhang
Operator size growth describes the scrambling of operators in quantum dynamics and stands out as an essential physical concept for characterizing quantum chaos. Important as it is,…
Exploring Light-Cone Distribution Amplitudes from Quantum Computing
Tianyin Li, Xingyu Guo, Wai Kin Lai +5
Light-cone distribution amplitudes (LCDAs) are essential nonperturbative quantities for theoretical predictions of exclusive high-energy processes in quantum chromodynamics (QCD).…
Variational thermal quantum simulation of the lattice Schwinger model
Xu-Dan Xie, Xingyu Guo, Hongxi Xing +3
Confinement of quarks due to the strong interaction and the deconfinement at high temperatures and high densities are a basic paradigm for understanding the nuclear matter. Their s…
Locating quantum critical points with shallow quantum circuits
Zhi-Quan Shi, Fang-Gang Duan, Dan-Bo Zhang
Quantum critical point is one key concept for studying many-body physics but its investigation may be resource-demanding even for a quantum computer due to the intrinsic complexity…
Quantum Gaussian filter for exploring ground-state properties
Min-Quan He, Dan-Bo Zhang, Z. D. Wang
Filter methods realize a projection from a superposed quantum state onto a target state, which can be efficient if two states have sufficient overlap. Here we propose a quantum Gau…
A loop Quantum Approximate Optimization Algorithm with Hamiltonian updating
Fang-Gang Duan, Dan-Bo Zhang
Designing noisy-resilience quantum algorithms is indispensable for practical applications on Noisy Intermediate-Scale Quantum~(NISQ) devices. Here we propose a quantum approximate…
Quantum kernels with squeezed-state encoding for machine learning
Long Hin Li, Dan-Bo Zhang, Z. D. Wang
Kernel methods are powerful for machine learning, as they can represent data in feature spaces that similarities between samples may be faithfully captured. Recently, it is realize…
Partonic collinear structure by quantum computing
Tianyin Li, Xingyu Guo, Wai Kin Lai +5
We present a systematic quantum algorithm, which integrates both the hadronic state preparation and the evaluation of real-time light-front correlators, to study parton distributio…
Selected topics of quantum computing for nuclear physics
Dan-Bo Zhang, Hongxi Xing, Hui Yan +2
Nuclear physics, whose underling theory is described by quantum gauge field coupled with matter, is fundamentally important and yet is formidably challenge for simulation with clas…
Inverse iteration quantum eigensolvers assisted with a continuous variable
Min-Quan He, Dan-Bo Zhang, Z. D. Wang
The capacity for solving eigenstates with a quantum computer is key for ultimately simulating physical systems. Here we propose inverse iteration quantum eigensolvers, which exploi…
Hybrid quantum-classical algorithms for solving quantum chemistry in Hamiltonian-wavefunction space
Zhan-Hao Yuan, Tao Yin, Dan-Bo Zhang
Variational quantum eigensolver~(VQE) typically optimizes variational parameters in a quantum circuit to prepare eigenstates for a quantum system. Its applications to many problems…
Variational quantum eigensolvers by variance minimization
Dan-Bo Zhang, Zhan-Hao Yuan, Tao Yin
Variational quantum eigensolver(VQE) typically minimizes energy with hybrid quantum-classical optimization, which aims to find the ground state. Here, we propose a VQE by minimizin…
Continuous-variable assisted thermal quantum simulation
Dan-Bo Zhang, Guo-Qing Zhang, Zheng-Yuan Xue +2
Simulation of a quantum many-body system at finite temperatures is crucially important but quite challenging. Here we present an experimentally feasible quantum algorithm assisted…
Collective optimization for variational quantum eigensolvers
Dan-Bo Zhang, Tao Yin
Variational quantum eigensolver (VQE) optimizes parameterized eigenstates of a Hamiltonian on a quantum processor by updating parameters with a classical computer. Such a hybrid qu…
Local and global patterns in quasiparticle interference: a reduced response function approach
Dan-Bo Zhang, Qiang Han, Z. D. Wang
A physical system exposes to us in a real space, while its description often refers to its reciprocal momentum space. A connection between them can be established by exploring patt…
Quantum-enhanced least-square support vector machine: simplified quantum algorithm and sparse solutions
Jie Lin, Dan-Bo Zhang, Shuo Zhang +3
Quantum algorithms can enhance machine learning in different aspects. Here, we study quantum-enhanced least-square support vector machine (LS-SVM). Firstly, a novel quantum algorit…
Protocol for implementing quantum nonparametric learning with trapped ions
Dan-Bo Zhang, Shi-Liang Zhu, Z. D. Wang
Nonparametric learning is able to make reliable predictions by extracting information from similarities between a new set of input data and all samples. Here we point out a quantum…
Nonlinear regression based on a hybrid quantum computer
Dan-Bo Zhang, Shi-Liang Zhu, Z. D. Wang
Incorporating nonlinearity into quantum machine learning is essential for learning a complicated input-output mapping. We here propose quantum algorithms for nonlinear regression,…
Realizing quantum linear regression with auxiliary qumodes
Dan-Bo Zhang, Zheng-Yuan Xue, Shi-Liang Zhu +1
In order to exploit quantum advantages, quantum algorithms are indispensable for operating machine learning with quantum computers. We here propose an intriguing hybrid approach of…