7 papers
Faster quantum linear system solver beyond the condition number
Alexander M. Dalzell, Jianqiang Li, Yuan Su
The spectral condition number is a widely adopted measure of worst-case cost for quantum linear system solvers. Yet it can significantly overestimate the actual runtime for a typic…
Exploiting Low-Rank Objective Structure in Discrete Quadratic Optimization
Ria Stevens, Fangshuo Liao, Barbara Su +3
We study the problem of maximizing a complex-valued quadratic form over the roots of unity. We show that when the objective matrix $\mathbf{Q}^\star \in \mathbb{C}^…
A New Quantum Linear System Algorithm Beyond the Condition Number and Its Application to Solving Multivariate Polynomial Systems
Jianqiang Li
Given a matrix of dimension and a vector , the quantum linear system (QLS) problem asks for the preparation of a quantum state proportio…
Layerwise Federated Learning for Heterogeneous Quantum Clients using Quorus
Jason Han, Nicholas S. DiBrita, Daniel Leeds +3
Quantum machine learning (QML) holds the promise to solve classically intractable problems, but, as critical data can be fragmented across private clients, there is a need for dist…
Multidimensional Electrical Networks and their Application to Exponential Speedups for Graph Problems
Jianqiang Li, Sebastian Zur
Recently, Apers and Piddock [TQC '23] strengthened the connection between quantum walks and electrical networks via Kirchhoff's Law and Ohm's Law. In this work, we develop a new mu…
Exponential Quantum Advantage for Pathfinding in Regular Sunflower Graphs
Jianqiang Li, Yu Tong
Finding problems that allow for superpolynomial quantum speedup is one of the most important tasks in quantum computation. A key challenge is identifying problem structures that ca…