Monit Sharma
Quantum Classroom/Research notebook
Research notebook

Medium Articles Code

Code, walkthroughs, and experiments from Monit’s technical writing and research.

Open repository ↗Explore the work ↓
Overview

Understand the project, then explore the work.

Resources open inside this site. Guides, papers, figures, notebooks, and source files are organized around the project’s story.

About this project

Welcome to my open lab! This repository contains code, walkthroughs, and hands-on experiments from my Medium articles, ongoing research, and explorations in:

- ⚛️ Quantum Optimization on Classically Hard Problems - 🔠 Transformers, LLMs & Attention Mechanisms - 🤖 Reinforcement Learning and Decision Making

Each subfolder here corresponds to a topic I’ve written about or am actively researching. Every notebook is designed to be educational, reproducible, and practically useful.

📄 Find the theory + storytelling on Medium:

Collections
01
Module

Quantum communication

1 curated item · 7 result figures

Figure 1 Bb 84 Qber Detection
Figure 1 Bb 84 Qber Detection
Figure 2 Qber Vs Eavesdropping
Figure 2 Qber Vs Eavesdropping
Figure 3 Key Rate Vs Distance
Figure 3 Key Rate Vs Distance
Figure 4 Global Qkd Comparison
Figure 4 Global Qkd Comparison
Figure 5 Attack Taxonomy
Figure 5 Attack Taxonomy
Figure 6 India Nqm Timeline
Figure 6 India Nqm Timeline
SourceQkd Blog Figures
02
Module

Quantum optimization benchmarks

4 curated items · 3 result figures

Section notes

This folder accompanies both our arXiv paper and a four-part Medium article series focused on using quantum algorithms to solve classically hard combinatorial problems. Each subfolder includes QUBO formulations, algorithm implementations, and benchmarking results.

> 🧠 These problems are NP-hard and serve as practical benchmarks to test the feasibility, scalability, and resource efficiency of quantum optimization techniques.

📰 Medium Article Series (2024)

Each article walks through the theory, QUBO formulation, and quantum optimization results using Qiskit.

🧪 Algorithms Implemented

Feasibility Plot
Feasibility Plot
Keyword Frequency Plot
Keyword Frequency Plot
Output
Output
NotebookMdkp ImplementationNotebookMis ImplementationNotebookPlotsUnavailableHp 1
03
Module

The cost of Shor

13 curated items · 17 result figures

Section notes

This project runs small Shor-style order-finding experiments in Qiskit and summarizes them with strict post-processing metrics.

The workflow is:

1. Build QPE order-finding circuits for semiprimes N. 2. Run on Aer simulator or IBM hardware. 3. Post-process bitstrings with strict order checks. 4. Enrich and plot results with strict and exploratory diagnostics.

What is in this repo

- shor/modexp.py: modular-multiplication oracle builders.

Depth Vs Bits
Depth Vs Bits
Memory Vs Number
Memory Vs Number
Runtime Vs Bits
Runtime Vs Bits
Depth Vs Bits
Depth Vs Bits
Memory Vs Number
Memory Vs Number
Runtime Vs Bits
Runtime Vs Bits
NotebookQuantum Token InitalizationUnavailableResults Hardware 20260228UnavailableResults Simulator 20260228SourceAnalyze ResultsSourceRun SweepSourceIsing Stunt Analysis
Supporting material in The cost of Shor7 items
SourceGenerate Figures 2SourceResource EstimationSourceScorecard EngineSourceModexpSourcePostprocessSourceQpeSourceRuntime
04
Module

Quantum machine learning

Project notes and supporting data

Section notes

Work Soon

05
Module

Transformers and reinforcement learning

Project notes and supporting data

Section notes

Work Soon