15 citations · 31 across the 5 of their papers we have counts for
5 papers
HOSCF: Efficient decoupling algorithms for finding the best rank-one approximation of higher-order tensors
Chuanfu Xiao, Zeyu Li, Chao Yang
Best rank-one approximation is one of the most fundamental tasks in tensor computation. In order to fully exploit modern multi-core parallel computers, it is necessary to develop d…
Exponentially Complex Quantum Many-Body Simulation via Scalable Deep Learning Method
Xiao Liang, Mingfan Li, Qian Xiao +12
For decades, people are developing efficient numerical methods for solving the challenging quantum many-body problem, whose Hilbert space grows exponentially with the size of the p…
Explicit Quantum Circuits for Block Encodings of Certain Sparse Matrices
Daan Camps, Lin Lin, Roel Van Beeumen +1
Many standard linear algebra problems can be solved on a quantum computer by using recently developed quantum linear algebra algorithms that make use of block encodings and quantum…
A rank-adaptive higher-order orthogonal iteration algorithm for truncated Tucker decomposition
Chuanfu Xiao, Chao Yang
We propose a novel rank-adaptive higher-order orthogonal iteration (HOOI) algorithm to compute the truncated Tucker decomposition of higher-order tensors with a given error toleran…
Low Rank Approximation in Simulations of Quantum Algorithms
Linjian Ma, Chao Yang
Simulating quantum algorithms on classical computers is challenging when the system size, i.e., the number of qubits used in the quantum algorithm, is moderately large. However, so…