3 papers
quant-ph2025
Extending quantum annealing to continuous domains: a hybrid method for quadratic programming
Hristo N. Djidjev
We propose Quantum Enhanced Simulated Annealing (QESA), a novel hybrid optimization framework that integrates quantum annealing (QA) into simulated annealing (SA) to tackle continu…
quant-ph2025
A quantum annealing approach to graph node embedding
Hristo N. Djidjev
Node embedding is a key technique for representing graph nodes as vectors while preserving structural and relational properties, which enables machine learning tasks like feature e…
quant-ph2024
Increasing the Hardness of Posiform Planting Using Random QUBOs for Programmable Quantum Annealer Benchmarking
Elijah Pelofske, Georg Hahn, Hristo Djidjev
Posiform planting is a method for constructing QUBO problems with a single unique planted solution that can be tailored to arbitrary connectivity graphs. In this study we investiga…