6 papers
Optimal local linear convergence of Nesterov's accelerated gradient method for functions under the Polyak--Åojasiewicz inequality
Zixu Feng, Hao Yuan
In this work, we establish that Nesterov's accelerated gradient method, applied to functions satisfying the Polyak--Åojasiewicz inequality around local minimizers, achieves…
Towards Exponential Quantum Improvements in Solving Cardinality-Constrained Binary Optimization
Haomu Yuan, Hanqing Wu, Kuan-Cheng Chen +2
Cardinality-constrained binary optimization is a fundamental computational primitive with broad applications in machine learning, finance, and scientific computing. In this work, w…
Classical Optimization Strategies for Variational Quantum Algorithms: A Systematic Study of Noise Effects and Parameter Efficiency
Tomáš BezdÄk, Haomu Yuan, VojtÄch Novák +2
This study systematically benchmarks classical optimization strategies for the Quantum Approximate Optimization Algorithm when applied to Generalized Mean-Variance Problems under n…
Experimental Demonstration of the PBR Test on a Superconducting Processor
Songqinghao Yang, Haomu Yuan, Crispin H. W. Barnes
We present an experimental implementation of the Pusey-Barrett-Rudolph (PBR) no-go theorem on IBM's 156-qubit Heron2 Marrakesh superconducting quantum processor. By preparing qubit…
Exponential Speed-ups for Structured Goemans-Williamson relaxations via Quantum Gibbs States and Pauli Sparsity
Haomu Yuan, Daniel Stilck França, Ilia Luchnikov +3
Quadratic Unconstrained Binary Optimization (QUBO) problems are prevalent in various applications and are known to be NP-hard. The seminal work of Goemans and Williamson introduced…
Iterative quantum optimisation with a warm-started quantum state
Haomu Yuan, Songqinghao Yang, Crispin H. W. Barnes
We provide a method to prepare a warm-started quantum state from measurements with an iterative framework to enhance the quantum approximate optimisation algorithm (QAOA). The nume…