6 citations · 8 across the 11 of their papers we have counts for
8 papers · 1 filter
Capturing Quantum Snapshots from a Single Copy via Mid-Circuit Measurement and Dynamic Circuit
Debarshi Kundu, Avimita Chatterjee, Archisman Ghosh +1
We propose Quantum Snapshot with Dynamic Circuit (QSDC), a hardware-agnostic, learning-driven framework for capturing quantum snapshots: non-destructive estimates of quantum states…
Guess, SWAP, Repeat : Capturing Quantum Snapshots in Classical Memory
Debarshi Kundu, Avimita Chatterjee, Swaroop Ghosh
We introduce a novel technique that enables observation of quantum states without direct measurement, preserving them for reuse. Our method allows multiple quantum states to be obs…
Guardians of the Quantum GAN
Archisman Ghosh, Debarshi Kundu, Avimita Chatterjee +1
Quantum Generative Adversarial Networks (qGANs) are at the forefront of image-generating quantum machine learning models. To accommodate the growing demand for Noisy Intermediate-S…
Application of Quantum Tensor Networks for Protein Classification
Debarshi Kundu, Archisman Ghosh, Srinivasan Ekambaram +3
We show that protein sequences can be thought of as sentences in natural language processing and can be parsed using the existing Quantum Natural Language framework into parameteri…
Q-Embroidery: A Study on Weaving Quantum Error Correction into the Fabric of Quantum Classifiers
Avimita Chatterjee, Debarshi Kundu, Swaroop Ghosh
Quantum computing holds transformative potential for various fields, yet its practical application is hindered by the susceptibility to errors. This study makes a pioneering contri…
MITS: A Quantum Sorcerer Stone For Designing Surface Codes
Avimita Chatterjee, Debarshi Kundu, Swaroop Ghosh
In the evolving landscape of quantum computing, determining the most efficient parameters for Quantum Error Correction (QEC) is paramount. Various quantum computers possess varied…
Evaluating Efficacy of Model Stealing Attacks and Defenses on Quantum Neural Networks
Satwik Kundu, Debarshi Kundu, Swaroop Ghosh
Cloud hosting of quantum machine learning (QML) models exposes them to a range of vulnerabilities, the most significant of which is the model stealing attack. In this study, we ass…
DyPP: Dynamic Parameter Prediction to Accelerate Convergence of Variational Quantum Algorithms
Satwik Kundu, Debarshi Kundu, Swaroop Ghosh
The exponential run time of quantum simulators on classical machines and long queue times and high costs of real quantum devices present significant challenges in the efficient opt…