---
aliases:
  - '/publication/2025-patent_rl_qpu_design/'
title: "Reinforced Learning for Quantum Design"
date: 2025-02-01
authors:
  - "Juan Cruz-Benito"
  - "Zlatko Kristev Minev"
  - "Francisco Jose Martin Fernandez"
  - "Ismael Faro Sertage"
abstract: "A computer-implemented process for generating a policy for design of quantum devices using a quantum hardware design kit including instructions and parameters associated with the instructions includes the following operations. An environment for a reinforcement learning architecture that includes a neural network as at least part of an agent is defined. A policy is generated by training the neural network using the environment. The defining the environment includes: defining actions of the neural network from a set of the instructions and parameters combinations associated with the quantum hardware design kit; and defining a reward function for generation of the policy."
publication_types:
  - "patent"
selected: false
publication: "*US Patent App. US18/463240*"
tags:
  - "design"
  - "artificial neural network"
  - "neural network model"
  - "reinforcement learning"
  - "quantu, hardware"
links:
- type: pdf
  url: "https://ppubs.uspto.gov/pubwebapp/authorize.html?redirect=print/pdfRedirectDownload/20250005368"
- type: source
  url: "https://patentcenter.uspto.gov/applications/18463240"
---