4 papers
A Quantum-Inspired Approach to MaxCut Based on Sparse Walsh/Pauli-Correlation Encoding
Cesar Augusto do Amaral, Marcos Vinicius Reballo, Marcus Ritt +2
We present a quantum-inspired Walsh/PCE solver for MaxCut based on sparse Pauli-correlation encodings. Instead of assigning one qubit or one variable to each graph vertex directly,…
A hybrid quantum-classical neural network for learning to route
Marcus Rolf Peter Ritt, Alexsandro Santos da Rosa Júnior, Marcos Vinicius Reballo +2
This work studies hybrid quantum-classical neural networks for learning routing heuristics. Specifically, this paper asks whether small quantum neural networks can replace paramete…
Evaluating Parameter Transfer in FALQON Across Graph Families
Alisson dos Passos Fumaco, Marcos Vinicius Reballo, Fernando Augusto Caletti de Barros +2
We evaluate FALQON parameter transfer for Max-Cut, transferring sequences from small donors () to 14-node recipients. Using 3-regular and Erdős-Rényi families, w…
Accelerating State-Vector Quantum Simulation on Integrated GPUs via Cache Locality Optimization: A Cross-Architecture Evaluation
Gabriel Fernandes Thomaz, Jerusa Marchi, Eduarda Rodrigues Monteiro +2
The classical simulation of quantum algorithms is a crucial tool for circuit development, testing, and validation. Although acceleration using GPUs significantly reduces simulation…