Addressed smart city transportation complexities using quantum-centric supercomputing. Implemented Grover’s, QAOA and Quantum Walk algorithms
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Updated
May 15, 2024 - Python
Addressed smart city transportation complexities using quantum-centric supercomputing. Implemented Grover’s, QAOA and Quantum Walk algorithms
Code for the paper "Multistart Methods for Quantum Approximate Optimization"
Solution of the Bin-Packing problem using QAOA and Qiskit optimization library
Generate QAOA circuits with just your objective function!
Quantum computing course project: Implementing Quantum Approximate Optimisation Algorithm (QAOA) for exact cover problem using IBM qiskit
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
Simulate Adiabatic Process in Qiskit and similarly use QAOA
The Quantum Maxcut Solver is the first webapp that allows anyone to run a quantum machine learning algorithm no-code.
Variational Quantum Factoring
Reproducing results in QAOA (Quantum Approximate Optimization Algorithm).
The max-cut problem on a random graph with 7 nodes is solved using QAOA, ED, Monte-Carlo, and simulated annealing.
Fixed-Schedule QAOA.
Repository for the Software and Computing for Applied Physics Project
An optimized implementation of the Quantum Approximate Optimization Algorithm (QAOA) with Quimb.
Implementation of Quantum Approximate Thermalization using Qiskit which involves performing approximated simulation of annealing to do Gibbs sampling of the given system. Based on https://arxiv.org/pdf/1712.05304.pdf
This repository holds implementations of QAOA-specific compilation policies on top of the Qiskit compiler.
Compare QAOA and Quantum Annealing using 127 qubit higher order Ising problems
Quantum algorithms for Portfolio Management.
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