Multi-backend SDK for quantum optimisation

Implementation of Variational Quantum Factoring algorithm.

Optimize QAOA circuits for graph maxcut using tensorflow

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

Portfolio Optimization on a Quantum computer.

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.

Generate QAOA circuits with just your objective function!

Quantum algorithms for Portfolio Management.

A portfolio generator developed by QuantYantriki for the QSTH 2022 - a quantum hackathon organized by the Quantum Ecosystems and Technology Council of India (QETCI). It utilizes quantum annealing and quantum approximate optimization algorithms using a feedback-based metaheuristic that incorporates classical optimization tools to improve solutions.

Variational Quantum Factoring

Repository for the Software and Computing for Applied Physics Project

Code for the paper "Multistart Methods for Quantum Approximate Optimization"

Generate QAOA circuits with just your objective function!

An optimized implementation of the Quantum Approximate Optimization Algorithm (QAOA) with Quimb.

My reimplementation of the Variational Quantum-Classical Hybrid algorithm, the Quantum Approximate Optimization Algorithm. It features the standard implementation on the Ring of Disagrees Cost Hamiltonian, and my new implementation (called Power Iteration) that utilizes a new cost function. This Quantum Machine Learning Model outperforms QAOA on…

Quantum computational projects using the Cirq framework