Qiskit Variational Quantum Classifier on the Pulsar Classification Problem

• URL: http://arxiv.org/abs/2505.15600v1
• Date: Wed, 21 May 2025 14:53:29 GMT
• Title: Qiskit Variational Quantum Classifier on the Pulsar Classification Problem
• Authors: Anna B. M. Souza, Clebson Cruz, Marcelo A. Moret,
• Abstract summary: We apply the Variational Quantum computing algorithm to the problem of pulsar classification candidates from the High Time Universe 2 dataset.<n>We use Qiskit Machine Learning to compare performance circuits of the model using different feature selection methods.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Quantum Machine Learning is a new computational tool that combines the quantum properties from quantum computing with the pattern recognition from machine learning. In this paper, we apply the Variational Quantum Classifier algorithm to the problem of pulsar classification of candidates from the High Time Resolution Universe 2 dataset. We use Qiskit Machine Learning circuits to compare the performance of the model using different feature selection methods, various number of features and training data size. Comparisons on the model from changing the data encoding and ansatz options are also reported. Keywords: Quantum Computing, Quantum Machine Learning, Astrophysics, Pulsars

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