Quantum Approximate Optimization

9 papers with code • 0 benchmarks • 0 datasets

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TensorFlow Quantum: A Software Framework for Quantum Machine Learning

tensorflow/quantum 6 Mar 2020

We introduce TensorFlow Quantum (TFQ), an open source library for the rapid prototyping of hybrid quantum-classical models for classical or quantum data.

Meta-Learning Quantum Approximate Optimization

PennyLane: Automatic differentiation of hybrid quantum-classical computations

PennyLaneAI/pennylane 12 Nov 2018

PennyLane is a Python 3 software framework for optimization and machine learning of quantum and hybrid quantum-classical computations.

Quantum Approximate Optimization

Learning to learn with quantum neural networks via classical neural networks

dumkar/learning-to-learn-qnn 11 Jul 2019

Quantum Neural Networks (QNNs) are a promising variational learning paradigm with applications to near-term quantum processors, however they still face some significant challenges.

Meta-Learning Quantum Approximate Optimization

Natural evolution strategies and variational Monte Carlo

Ericolony/QAOA 9 May 2020

A notion of quantum natural evolution strategies is introduced, which provides a geometric synthesis of a number of known quantum/classical algorithms for performing classical black-box optimization.

Combinatorial Optimization Quantum Approximate Optimization

Classical symmetries and QAOA

rsln-s/Classical-symmetries-and-QAOA 8 Dec 2020

Our approach formalizes the connection between quantum symmetry properties of the QAOA dynamics and the group of classical symmetries of the objective function.

Quantum Approximate Optimization

Policy Gradient based Quantum Approximate Optimization Algorithm

AaronBarbosa12/RL_QAOA 4 Feb 2020

Taking such constraints into account, we show that policy-gradient-based reinforcement learning (RL) algorithms are well suited for optimizing the variational parameters of QAOA in a noise-robust fashion, opening up the way for developing RL techniques for continuous quantum control.

Quantum Approximate Optimization

Exploiting Symmetry Reduces the Cost of Training QAOA

rsln-s/Exploiting_Symmetry_Reduces_the_Cost_of_Training_QAOA 25 Jan 2021

We show how by considering only the terms that are not connected by symmetry, we can significantly reduce the cost of evaluating the QAOA energy.

Quantum Approximate Optimization Quantum Physics

Local classical MAX-CUT algorithm outperforms $p=2$ QAOA on high-girth regular graphs

marwahaha/qaoa-local-competitors 14 Jan 2021

We show that for all degrees $D \ge 2$ and every $D$-regular graph $G$ of girth $> 5$, QAOA$_2$ has a larger expected cut fraction than QAOA$_1$ on $G$.

Combinatorial Optimization Quantum Approximate Optimization Quantum Physics

Quantum Approximation for Multi-Scale Scheduling

lytzV/QAOA arXiv 2020

Then, for the given MWIS, the proposed QAOS designs the Hamiltonian of the problem.

Quantum Approximate Optimization