5 papers
Neural networks learn to reconstruct multipartite entanglement from quantum marginals
Matreyee Kandpal, Arvind, Kavita Dorai
Different sets of local correlations are not equivalent: some fragments of reduced data uniquely determine a global quantum state, while others leave it ambiguous. The quantum marg…
Experimental investigation of a quantum Otto heat engine with shortcuts to adiabaticity implemented using counter-adiabatic driving
Krishna Shende, Matreyee Kandpal, Arvind +1
The finite time operation of a quantum Otto heat engine leads to a trade-off between efficiency and output power, which is due to the deviation of the system from the adiabatic pat…
Simulating Three-Flavor Neutrino Oscillations on an NMR Quantum Processor
Gayatri Singh, Arvind, Kavita Dorai
Neutrino oscillations can be efficiently simulated on a quantum computer using the Pontecorvo-Maki-Nakagawa-Sakata (PMNS) theory in close analogy to the physical processes realized…
Entanglement Classification of Arbitrary Three-Qubit States via Artificial Neural Networks
Jorawar Singh, Vaishali Gulati, Kavita Dorai +1
We design and successfully implement artificial neural networks (ANNs) to detect and classify entanglement for three-qubit systems using limited state features. The overall design…
Inferring physical laws by artificial intelligence based causal models
Jorawar Singh, Kishor Bharti, Arvind
The advances in Artificial Intelligence (AI) and Machine Learning (ML) have opened up many avenues for scientific research, and are adding new dimensions to the process of knowledg…