User manual and example notebooks for the pytket quantum SDK

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

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

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

Notebooks sobre aprendizaje de computación cuántica

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

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. 📚 👨‍🏫

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

Tutorial notebooks for QCE at IEEE 2023 in Bellevue, Washington

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

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

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

MIT Quantum Mechanics Class Notes

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

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

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

A public repository for my quantum-computing documents and Jupyter notebooks. Along with that, most of the quantum-computing content in this repository will be based on the content in PY536 (BU) and Physics 229 (Caltech), along with QCQI notes. Please read the comments inside the files for more information.