Learning with Density Matrices

Faculty: Chiranjib Bhattacharya (CSA)  and Apoorva Khare (Math)

Summary: With the advent of Quantum Computers there has been significant interest in Quantum Machine Learning(QML), a field which is at the intersection of Machine Learning and Quantum Computing. There is urgent need to develop formalisms and attendant algorithms in QML. The project proposes to extend existing formalisms in Machine Learning to Operator Valued random variables. We aim to develop models and Algorithms on Density matrices, which are  Operator valued random variables, both  in supervised and unsupervised setting.

One of the key goals will be to develop algorithms which are compatible with existing or in near term realizable Quantum Hardware.