Unsharp measurement-based hybrid feature extraction for image classification
Hybrid quantum-classical model classifies MNIST digits by encoding grayscale pixels into quantum states, extracting features via unsharp measurements, and using a classical neural network; state reuse and measurement unsharpness affect accuracy.
Unsharp Measurement based Edge-detection using Photonic Quantum Computer
Photonic quantum-inspired framework uses beam splitters and unsharp measurements for image generation, optimized with COBYLA to minimize errors, achieving high quality; applicable to pattern recognition.
Analysis of PT-Symmetric with Vanishing Real and Imaginary Components
Studied a PT-invariant potential with zero V1,2(x), analyzing conditions for unbroken PT symmetry and real eigenvalues; identified symmetry-breaking thresholds and developed solvable models for quantum optics and wave mechanics applications.
Detection of Variables using Gravitational Microlensing and Plotting Color magnitude diagram
Studied globular cluster NGC4147 using microlensing and differential imaging to detect transient events, aiming to find low-mass dark objects like free-floating planets and intermediate-mass black holes. Processed raw images with IRAF and DIAPL2.
Investigation of starbursts in interacting spirals
Studied 20 spiral galaxy interactions, calculating star formation rates and using BPT diagrams to classify changes in luminosity caused by interaction-driven star formation variations