3 papers
cs.ET2026
Eliminating Vendor Lock-In in Quantum Machine Learning via Framework-Agnostic Neural Networks
Poornima Kumaresan, Shwetha Singaravelu, Lakshmi Rajendran +1
Quantum machine learning (QML) stands at the intersection of quantum computing and artificial intelligence, offering the potential to solve problems that remain intractable for cla…
cs.ET2026
Adaptive Tensor Network Simulation via Entropy-Feedback PID Control and GPU-Accelerated SVD
Harshni Kumaresan, Gayathri Muruganantham, Lakshmi Rajendran +1
Tensor network methods, particularly those based on Matrix Product States (MPS), provide a powerful framework for simulating quantum many-body systems. A persistent computational c…
quant-ph2026
GPU-Accelerated Quantum Simulation: Empirical Backend Selection, Gate Fusion, and Adaptive Precision
Poornima Kumaresan, Pavithra Muruganantham, Lakshmi Rajendran +1
Classical simulation of quantum circuits remains indispensable for algorithm development, hardware validation, and error analysis in the noisy intermediate-scale quantum (NISQ) era…