CORTEXA
← Browse

Pranav Vaidhyanathan

2 papers indexed

arxivcs.LGcond-mat.mes-hall2026-07-10

Action-Factored Multi-Agent Reinforcement Learning for Scalable Quantum Device Tuning

Edwin De Nicolo, Rahul Marchand, Cornelius Carlsson, Pranav Vaidhyanathan, Natalia Ares

Cooperative multi-agent reinforcement learning is well suited to problems with large parameter spaces and exploitable local structure, such as the tuning of electrostatically-defined quantum-dot arrays. However, if parameter cross-talk is strong, a non-stationary environment from…

View free PDFSource page
arxivcs.ROcs.LG2026-07-07

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts

Aristotelis Papatheodorou, Pranav Vaidhyanathan, Natalia Ares, Ioannis Havoutis, Gerard J. Milburn

Physics-informed learning promises data-efficient and stable dynamics prediction, yet its strongest geometric guarantees have largely remained confined to closed conservative systems. This excludes robotic systems of interest, where actuation, dissipation, and constraints exchang…

View free PDFSource page