Network-based prediction of drug combinations with quantum annealing

arXiv:2512.20199 · quant-ph · Submitted 2025-12-23 · Read on arXiv

quant-ph

Submitted: 2025-12-23

Updated: 2026-09-23

Comments: 23 pages, 9 figures

Journal ref: Quantum Mach. Intell. 8, 70 (2026)

DOI: 10.1007/s42484-026-00411-7

Code: https://github.com/dmrapk/Drug-Combinations-using-Quantum-Annealers

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Average Precision — 7× in this paper
• Benchmark — 5× in this paper · explained in 2 episodes
• Benchmarking — 3× in this paper · explained in 3 episodes
• Calibration — 2× in this paper · explained in 7 episodes
• Adiabatic Evolution — 1× in this paper · explained in 2 episodes
• Clustering — 1× in this paper · explained in 2 episodes
• Core — 1× in this paper · explained in 2 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Quantum Annealing (QA) — 1× in this paper · explained in 2 episodes
• Spectral Gap — 1× in this paper · explained in 5 episodes
• Theoretical Guarantees — 1× in this paper · explained in 2 episodes

Sources

• Quantum Network-Based Prediction of Cancer Driver Genes
• Quantum Computation by Adiabatic Evolution

Related papers

• Reconquering Bell sampling on qudits: stabilizer learning and testing, quantum pseudorandomness bounds, and more
• Encrypted clones can leak: Classification of informative subsets in Quantum Encrypted Cloning
• Polynomial-time classical and quantum simulation of quantum impurity models
• A quasiparticle-protected superconducting qubit
• Theory of quantum-enhanced interferometry with general Markovian light sources
• A convergent hierarchy of spectral gap certificates for qubit Hamiltonians