The HEPQPR.Qallse project encodes the HEP (ATLAS) pattern recognition problem into a QUBO and solves it using a D-Wave or other classical QUBO libraries (qbsolv, neal). Master's project (2019).
Open collaborative book on quadratization in discrete optimization and quantum mechanics.
Implementation of protein folding on 2D lattice on D-Wave QPU, using turn ancilla encoding (Babbush 2013). Conventional Monte Carlo Simulated Annealing is also included as a sepate approach
D-Wave Instance Generator (D-WIG)
My attempt to implement problems described "A Tutorial on Formulating and Using QUBO Models" (https://arxiv.org/pdf/1811.11538.pdf) using D-Wave Ocean SDK in Python and solving on D-Wave Quantum Computer
Python Quantum Boolean Tensor Networks
Quantum annealing knowledge base: T-Wave
⚛ Quantum Computing, for Humans.
D-Wave Ising Sample Collector (D-WISC)
Introduction to quantum annealing in D-Wave systems.
Practical applications of Quantum AI: Modeling and solving combinatorial optimization problems using D-Wave and Qiskit.
Companion code for Applied Quantum Computing for Engineers (Suresh, 2026)
Dedalus: A quantum-classical hybrid query optimizer for relational databases. Formulates join-order optimization as pruned QUBOs for D-Wave QPUs and hybrid annealers with learned, cost-guided dispatch. [VLDB 2027 Artifact]
Binary matrix factorization on D-Wave's quantum annealer.
quantium dashboard
Dedalus quantum join order optimizer demo, for fast deployment and demonstration purposes.
This repository contains the Python code associated with the scientific publication "Exploring Quantum Annealing Architectures: A Spin Glass Perspective".
Quantum Route Optimizer, made as a supplement to my bachelor thesis - uses D-Wave annealers to solve a TSP problem
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