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The power of one clean qubit in supervised machine learning.

ABSTRACT: This paper explores the potential benefits of quantum coherence and quantum discord in the non-universal quantum computing model called deterministic quantum computing with one qubit (DQC1) in supervised machine learning. We show that the DQC1 model can be leveraged to develop an efficient method for estimating complex kernel functions. We demonstrate a simple relationship between coherence consumption and the kernel function, a crucial element in machine learning. The paper presents an implementation of a binary classification problem on IBM hardware using the DQC1 model and analyzes the impact of quantum coherence and hardware noise. The advantage of our proposal lies in its utilization of quantum discord, which is more resilient to noise than entanglement.

SUBMITTER: Karimi M

PROVIDER: S-EPMC10651850 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature

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The power of one clean qubit in supervised machine learning.

Karimi Mahsa M Javadi-Abhari Ali A Simon Christoph C Ghobadi Roohollah R

Scientific reports 20231115 1

This paper explores the potential benefits of quantum coherence and quantum discord in the non-universal quantum computing model called deterministic quantum computing with one qubit (DQC1) in supervised machine learning. We show that the DQC1 model can be leveraged to develop an efficient method for estimating complex kernel functions. We demonstrate a simple relationship between coherence consumption and the kernel function, a crucial element in machine learning. The paper presents an implemen ...[more]

PMID: 37968292

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