My personal quantum paper library

Welcome to this community-driven, open-source website for learning about all aspects of quantum computing, from hardware to algorithms to everything in between and adjacent! Whether you are new to quantum science, building your foundation of knowledge, or supplementing a course, our goal is to help you learn based on your interests and background.

Tutorials on quantum technologies

Master Thesis Project: Neuromorphic Hardware Design IISER Bhopal, Dept. Electrical Engineering and Computer Science

A curated list of awesome libraries, learning resources, frameworks, and tools for quantum computing.

# Casimir Tunable Permittivity Stacks — Research Prototype

This simulation demonstrates how a Fabry–Pérot cavity acts as a narrowband spectral filter for single-photon wavepackets. It includes frequency-domain and time-domain examples showing how an input photon spectrum is shaped by the cavity transfer function.

High-fidelity quantum computing simulation platform for exploring BB84, Shor Code, Grover's Algorithm and other quantum protocols and algorithms

Quantum-Based Portfolio Diversification (QBPD) is a quantum algorithm designed to optimize and diversify investment portfolios using quantum computing principles.

Code associated with the manuscript: "Optimal squeezing for quantum target detection" by G. Spedalieri and S. Pirandola, Phys. Rev. Research 3, L042039 (2021). This work was funded by the EU Horizon 2020 Research and Innovation Action under grant agreement No. 862644 (FET Open project: Quantum readout techniques and technologies, QUARTET)

RL Agents to Control an Universal quantum gate set {H, T, CNOT}

Simulations of ion beam spot size and methods of measurement, specifically in the comparison of error function fitting and 80:20 rule in knife edge measurements as a method of approximating imaging resolution and spot size of focussed ion beams.

Tunable permittivity stacks enable precise electromagnetic control through advanced metamaterials. Explore our digital twin framework for sub-1% accuracy. 🌐💻

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