63 citations · 65 across the 3 of their papers we have counts for
4 papers · 1 filter
ADAPT: Mitigating Idling Errors in Qubits via Adaptive Dynamical Decoupling
Poulami Das, Swamit Tannu, Siddharth Dangwal +1
The fidelity of applications on near-term quantum computers is limited by hardware errors. In addition to errors that occur during gate and measurement operations, a qubit is susce…
An Algorithm for Fast Supervised Learning in Variational Circuits through Simultaneous Processing of Multiple Samples
Siddharth Dangwal, Ritvik Sharma, Debanjan Bhowmik
We propose a novel algorithm for fast training of variational classifiers by processing multiple samples parallelly. The algorithm can be adapted for any ansatz used in the variati…
Supervised Learning Using a Dressed Quantum Network with "Super Compressed Encoding": Algorithm and Quantum-Hardware-Based Implementation
Saurabh Kumar, Siddharth Dangwal, Debanjan Bhowmik
Implementation of variational Quantum Machine Learning (QML) algorithms on Noisy Intermediate-Scale Quantum (NISQ) devices is known to have issues related to the high number of qub…
Supervised learning with a quantum classifier using a multi-level system
Soumik Adhikary, Siddharth Dangwal, Debanjan Bhowmik
We propose a quantum classifier, which can classify data under the supervised learning scheme using a quantum feature space. The input feature vectors are encoded in a single qu…