3 papers
quant-ph2026
Benchmarking loss functions for trainable quantum feature maps
Nguyen Dinh Quyen, Vu Tuan Hai, Quoc Chuong Nguyen +2
Many quantum machine learning models employ quantum feature maps to encode classical data into quantum states. While fixed feature maps often lack sufficient expressivity for compl…
quant-ph2026
Towards Automated Selection of Quantum Encoding Circuits via Meta-Learning
Dao Duy Tung, Nguyen Quoc Chuong, Vu Tuan Hai +2
In recent years, quantum kernel methods have shown promising applications on near-term quantum devices. However, selecting an appropriate encoding circuit for a given dataset requi…
quant-ph2025
Imaginary-time-enhanced feedback-based quantum algorithms for universal ground-state preparation
Thanh Nguyen Van Long, Lan Nguyen Tran, Le Bin Ho
Preparing ground states of strongly correlated quantum systems is a central goal in quantum simulation and optimization. The feedback-based quantum algorithm (FALQON) provides an a…