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quant-ph2025

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…

quant-ph2025

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…

quant-ph2024

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…

quant-ph2024

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…

quant-ph2024

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…

quant-ph2024

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…