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Quantum Speedups for Log-Concave Sampling from Local Structure
Chenghua Liu, Qisheng Wang, Zhengfeng Ji
For a convex function , the problem of sampling from a distribution proportional to is called log-concave sampling. In many practi…
Quantum Communication Lower Bounds for Search Problems via Matrix Discrepancy
Minbo Gao, Chenghua Liu, Guangxu Yang +1
We study one-way quantum communication lower bounds for search problems. Unlike decision problems, search problems can have many valid outputs, which pose a fundamental barrier to…
Lévy-Khintchine Structure Enables Fast-Forwardable Lindbladian Simulation
Minbo Gao, Zhengfeng Ji, Chenghua Liu
Simulation of open quantum systems is an area of active research in quantum algorithms. In this work, we revisit the connection between Markovian open-system dynamics and averages…
Accelerating Regression Tasks with Quantum Algorithms
Chenghua Liu, Zhengfeng Ji
Regression is a cornerstone of statistics and machine learning, with applications spanning science, engineering, and economics. While quantum algorithms for regression have attract…
Quantum Speedup for Hypergraph Sparsification
Chenghua Liu, Minbo Gao, Zhengfeng Ji +1
Graph sparsification serves as a foundation for many algorithms, such as approximation algorithms for graph cuts and Laplacian system solvers. As its natural generalization, hyperg…
Quantum Speedup for Sampling Random Spanning Trees
Simon Apers, Minbo Gao, Zhengfeng Ji +1
We present a quantum algorithm for sampling random spanning trees from a weighted graph in time, where and denote the number of vertices and edge…