Multi-backend SDK for quantum optimisation

Source code for the book "Quantum Computing for Programmers", Cambridge University Press

Implementation of Variational Quantum Factoring algorithm.

qTorch (Quantum Tensor Contraction Handler) https://arxiv.org/abs/1709.03636 -> for quantum simulation using tensor networks

This package is a flexible python implementation of the Quantum Approximate Optimization Algorithm /Quantum Alternating Operator ansatz (QAOA) aimed at researchers to readily test the performance of a new ansatz, a new classical optimizers, etc.

Optimize QAOA circuits for graph maxcut using tensorflow

Algorithms for optimization tasks (operations research)

Application of Variational Quantum Eigensolver (VQE) and Quantum Approximate Optimisation Algorithm (QAOA) to the Travelling Salesman Problem (TSP) and the Quadratic Assignment Problem (QAP) using Qiskit on IBM's quantum devices.

Portfolio Optimization on a Quantum computer.

Solving the Travelling Salesman Problem, with applying the hard constraints using the QAutoencoder

QAOA is one of the flavors of VQA, and it is considered to assert so-called "Quantum Supremacy". I have implemented a Quantum circuit to solve Max-Cut problem. I have written a report of my work.

Lectures on hybrid quantum-classical machine learning given during "VI Pyrenees Winter School Quantum Information Meeting for Barcelona's Community" on 14-17.02.2023, Setcases, Spain

Some tests with QAOA, VQE, annealers and other procedures for NISQ quantum computers

This repository contains a quantum computing framework implemented in TypeScript.

Implementation for QAOA: MaxCut for weighted graph

Compare QAOA and Quantum Annealing using 127 qubit higher order Ising problems

Generate QAOA circuits with just your objective function!

Here we will compare one well-known (ED) and another new method (QAOA) for quantum simulations of many-body physics.

A project making use of the Variational Quantum Eigensolver ( VQE ) and Quantum Approximate Optimization Algorithms ( QAOA ) in qiskit to optimize an endowment portfolio, with weights defined by risk-parity analysis..

Quantum version of the classical Nim game. An automatic opponent allows to game to not be as easy as it seems.