User manual and example notebooks for the pytket quantum computing toolkit

Google Collaboratory notebooks for the SDSS 2020 workshop on "Introduction to programming quantum computers"

Notebooks sobre aprendizaje de computación cuántica

A hands-on approach to quantum computing: Jupyter notebooks discussing quantum computing in Python using Qiskit.

Notebooks demonstrating how to use qBraid Lab to streamline quantum workflows, connect to quantum hardware, and leverage GPU-enabled scalable compute for hybrid algorithms.

Python (.py) and Jupyter notebook (.ipynb) implementations of Grover's Algorithm aka Quantum Search Algorithm for n qubits and m targets.

This notebooks are intended to teach the basics of quantum computing.

SO2 Emission Prediction from Diesel Engines with Quantum Technology (5G). A worldwide study has been conducted on the emission values of SO2 gases released from diesel engines in the world.

Practice notebook using Qiskit module in python and IBM quantum experience

My notebooks for QGSS 2023

Tutorial notebooks for QCE at IEEE 2023 in Bellevue, Washington

A collection of Jupyter Notebooks with explanations, insights, tutorials, exercises and showing how to use the Qiskrypt software suite, built using the IBM’s open-source Software Development Kit for quantum computing Qiskit. 📚 👨‍🏫

Notebooks exploring various features of the Rigetti Forest & Grove using pyQuil

Demonstrative Jupyter Notebook for evaluating matrix elements of observables (generic base) using Quantum Hardware (IBM Qiskit).

MIT Quantum Mechanics Class Notes

Jupyter Notebooks for quantum algorithms. Language: Python (Qiskit). Platform: IBM Quantum's backends and simulators.

Demonstrative Jupyter Notebook for evaluating inner products (braket) between two quantum states using Quantum Hardware (IBM Qiskit).

This notebook can be used as a tutorial for combining Schöning's and Grover's methods to solve k-SAT problems.

The repository contains Jupyter notebooks with detailed description of basic quantum protocols and algorithms, the math, circuits and quantum programs using Python.

Notebooks for the Seminar in ETSIT (UPM) - Master of Science in Signal Theory and Communication (Track: SIGNAL PROCESSING AND MACHINE LEARNING FOR BIG DATA).