PQC-HEP-Binary_Classification/CITATION.cff at main · APCF-git/PQC-HEP-Binary_Classification · GitHub

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cff-version: 1.2.0
message: "If you use this software, please cite it as below."
type: software
title: "PQC-HEP-Binary_Classification"
abstract: >
  Parametrized quantum circuit (PQC) binary classifier for high-energy physics
  signal/background separation. Four implementations across Qiskit and PyQuil,
  covering Gram-Schmidt, QR-decomposition, pytket, and native Qiskit amplitude
  embedding, with exact parameter shift rule gradients and Adam optimisation.
  All nineteen variational forms from Sim et al. (2019) are implemented across
  four qubits with amplitude embedding of twelve kinematic features per event.
authors:
  - family-names: "Fonseca"
    given-names: "Adriano"
    affiliation: "Instituto Superior Técnico, Universidade de Lisboa"
    email: "apcf@topfonseca.com"
version: "1.0.0"
date-released: "2026-06-24"
doi: "10.5281/zenodo.20929885"
repository-code: "https://github.com/APCF-git/PQC-HEP-Binary_Classification"
license: MIT
keywords:
  - quantum computing
  - quantum machine learning
  - high-energy physics
  - parametrized quantum circuits
  - amplitude embedding
  - parameter shift rule
  - binary classification
  - variational quantum circuits
  - qiskit
  - pyquil
  - pytket