---
title: "Predictive profiling framework for quantum environments"
date: 2026-06-18
authors:
  - "Francisco Jose Martin Fernandez"
  - "Ivan Duran Martinez"
  - "David Kremer Garcia"
  - "Juan Cruz-Benito"
  - "Iskandar Sitdikov"
  - "David Garcia Valiñas"
  - "Alexandra Rivero Garcia"
  - "Ismael Faro Sertage"
abstract: "One or more systems, devices, computer program products and/or computer-implemented methods of use provided herein relate to predictive profiling of quantum environments. The system can comprise a memory that can store computer-executable components. The system can further comprise a processor, operably coupled to the memory, that executes at least one of the computer executable components that can generate a profiling prediction of a quantum environment based on a profiling matrix using a hybrid time series model, wherein the profiling prediction predicts resource consumption of the quantum environment for a portion of an execution in the quantum environment using a hybrid time series model. In various embodiments, the at least one of the computer executable components can further allocate resources between classical components and quantum components of the quantum environment for the portion of the execution based on the profiling prediction."
publication_types:
  - "patent"
selected: false
publication: "*US Patent App. US20260170376A1*"
tags:
  - "quantum computing"
  - "profiling"
  - "resource allocation"
  - "time series"
  - "hybrid quantum-classical"
links:
- type: pdf
  url: "https://ppubs.uspto.gov/pubwebapp/authorize.html?redirect=print/pdfRedirectDownload/20260170376"
- type: source
  url: "https://patentcenter.uspto.gov/applications/19052588"
---