4 papers
Quantum Hamiltonian Learning using Time-Resolved Measurement Data and its Application to Gene Regulatory Network Inference
Mohammad Aamir Sohail, Ranga R. Sudharshan, S. Sandeep Pradhan +1
We present a new Hamiltonian-learning framework based on time-resolved measurement data from a fixed local IC-POVM and its application to inferring gene regulatory networks. We int…
QubitLens: An Interactive Learning Tool for Quantum State Tomography
Mohammad Aamir Sohail, Ranga Sudharshan, S. Sandeep Pradhan +1
Quantum state tomography is a fundamental task in quantum computing, involving the reconstruction of an unknown quantum state from measurement outcomes. Although essential, it is t…
Quantum Natural Stochastic Pairwise Coordinate Descent
Mohammad Aamir Sohail, Mohsen Heidari, S. Sandeep Pradhan
Variational quantum algorithms, optimized using gradient-based methods, often exhibit sub-optimal convergence performance due to their dependence on Euclidean geometry. Quantum nat…
When Wyner and Ziv Met Bayes in Quantum-Classical Realm
Mohammad Aamir Sohail, Touheed Anwar Atif, S. Sandeep Pradhan
In this work, we address the lossy quantum-classical source coding with the quantum side-information (QC-QSI) problem. The task is to compress the classical information about a qua…