6 papers · 1 filter
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…
Quantum resource reduction for quantum-centric supercomputing via correlated mean-field downfolding framework
Thien Ngoc Tran, Lan Nguyen Tran
We present OBDF-SQD, a hybrid quantum-classical method that combines one-body downfolding~(OBDF) based on one-body Møller--Plesset second-order perturbation theory (OBMP2) with sam…
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…
Feedback-Based Quantum Control for Safe and Synergistic Drug Combination Design
Mai Nguyen Phuong Nhi, Lan Nguyen Tran, Le Bin Ho
Drug-drug interactions (DDIs) strongly affect the safety and efficacy of combination therapies. Despite the availability of large DDI databases, selecting optimal multi-drug combin…
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…
Multi-target quantum compilation algorithm
Vu Tuan Hai, Nguyen Tan Viet, Jesus Urbaneja +3
Quantum compilation is the process of converting a target unitary operation into a trainable unitary represented by a quantum circuit. It has a wide range of applications, includin…