# Neural predictor based quantum architecture search

@article{Zhang2021NeuralPB, title={Neural predictor based quantum architecture search}, author={Shi-Xin Zhang and Chang-Yu Hsieh and Shengyu Zhang and Hong Yao}, journal={Machine Learning: Science and Technology}, year={2021}, volume={2} }

Variational quantum algorithms (VQAs) are widely speculated to deliver quantum advantages for practical problems under the quantum–classical hybrid computational paradigm in the near term. Both theoretical and practical developments of VQAs share many similarities with those of deep learning. For instance, a key component of VQAs is the design of task-dependent parameterized quantum circuits (PQCs) as in the case of designing a good neural architecture in deep learning. Partly inspired by the… Expand

#### 6 Citations

Quantum Architecture Search with Meta-learning

- Physics
- 2021

Variational quantum algorithms (VQAs) have been successfully applied to quantum approximate optimization algorithms, variational quantum compiling and quantum machine learning models. The… Expand

Variational Quantum-Neural Hybrid Eigensolver

- Physics
- 2021

The variational quantum eigensolver (VQE) is one of the most representative quantum algorithms in the noisy intermediate-size quantum (NISQ) era, and is generally speculated to deliver one of the… Expand

Accelerating variational quantum algorithms with multiple quantum processors

- Computer Science, Physics
- ArXiv
- 2021

An efficient distributed optimization scheme, called QUDIO, that can be readily mixed with other advanced VQAs-based techniques to narrow the gap between the state of the art and applications with quantum advantage. Expand

QuantumNAS: Noise-Adaptive Search for Robust Quantum Circuits

- Computer Science, Physics
- ArXiv
- 2021

This paper proposes and experimentally implements QuantumNAS, a comprehensive framework for noise-adaptive cosearch of the variational circuit and qubit mapping and proposes to decouple the parameter training and circuit search by introducing a novel gate-sharing SuperCircuit. Expand

Probing many-body localization by excited-state VQE

- Physics
- 2021

Non-equilibrium physics including many-body localization (MBL) has attracted increasing attentions, but theoretical approaches of reliably studying non-equilibrium properties remain quite limited. In… Expand

Quantum Architecture Search via Deep Reinforcement Learning

- Physics, Computer Science
- ArXiv
- 2021

A quantum architecture search framework with the power of deep reinforcement learning (DRL) to address the challenge of generation of quantum gate sequences for multiqubit GHZ states without encoding any knowledge of quantum physics in the agent. Expand

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