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20242026
most citedAn Unsupervised Machine Learning to Optimize Hybrid Quantum Noise Clusters for Gaussian Quantum Channel

1 citations · 1 across the 5 of their papers we have counts for

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5 papers

eess.SP2026

Comparative Analysis of Differential and Collision Entropy for Finite-Regime QKD in Hybrid Quantum Noisy Channels

Mouli Chakraborty, Subhash Chandra, Avishek Nag +3

In this work, a comparative study between three fundamental entropic measures, differential entropy, quantum Renyi entropy, and quantum collision entropy for a hybrid quantum chann…

eess.SP2025

On the Achievable Rate of Satellite Quantum Communication Channel using Deep Autoencoder Gaussian Mixture Model

Mouli Chakraborty, Subhash Chandra, Avishek Nag +1

We present a comparative study of the Gaussian mixture model (GMM) and the Deep Autoencoder Gaussian Mixture Model (DAGMM) for estimating satellite quantum channel capacity, consid…

eess.SP2024

A Hybrid Noise Approach to Modelling of Free-Space Satellite Quantum Communication Channel for Continuous-Variable QKD

Mouli Chakraborty, Anshu Mukherjee, Ioannis Krikidis +2

This paper significantly advances the application of Quantum Key Distribution (QKD) in Free- Space Optics (FSO) satellite-based quantum communication. We propose an innovative sate…

eess.SP2024

Hybrid Quantum Noise Approximation and Pattern Analysis on Parameterized Component Distributions

Mouli Chakraborty, Anshu Mukherjee, Ioannis Krikidis +2

Noise is a vital factor in determining the accuracy of processing the information of the quantum channel. One must consider classical noise effects associated with quantum noise so…

eess.SP2024★ 1 cited

An Unsupervised Machine Learning to Optimize Hybrid Quantum Noise Clusters for Gaussian Quantum Channel

Mouli Chakraborty, Anshu Mukherjee, Ioannis Krikidis +2

This work focuses on optimizing the hybrid quantum noise model to improve the capacity of Gaussian quantum channels using Machine Learning (ML) generated clusters. The work specifi…