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Research PaperResearchia:202603.27088

Adaptive Negativity Estimation via Collective Measurements

Martin Zeman

Abstract

This paper explores an efficient method for entanglement quantification in two-qubit and qubit-qutrit quantum systems based upon the framework of collective measurements in conjunction with machine learning. We introduce an adaptive measurement procedure in which measurement settings are dynamically adjusted based on prior measurement outcomes aiming to optimize the inference precision given a limited number of these measurement settings. The procedure makes use of the Long Short-Term Memory net...

Submitted: March 27, 2026Subjects: Quantum Physics; Quantum Computing

Description / Details

This paper explores an efficient method for entanglement quantification in two-qubit and qubit-qutrit quantum systems based upon the framework of collective measurements in conjunction with machine learning. We introduce an adaptive measurement procedure in which measurement settings are dynamically adjusted based on prior measurement outcomes aiming to optimize the inference precision given a limited number of these measurement settings. The procedure makes use of the Long Short-Term Memory networks to recurrently process collective measurements on two copies of the investigated states. Obtained results demonstrate the tangible benefits of the adaptive measurements in comparison to previously described non-adaptive strategies.


Source: arXiv:2603.25560v1 - http://arxiv.org/abs/2603.25560v1 PDF: https://arxiv.org/pdf/2603.25560v1 Original Link: http://arxiv.org/abs/2603.25560v1

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Submission Info
Date:
Mar 27, 2026
Topic:
Quantum Computing
Area:
Quantum Physics
Comments:
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