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Real-time Measurements, Rogue Phenomena, and Single-Shot Applications

Quantum temporal optics

Moti Fridman, Eliahu Cohen

Published Mar 12, 2024• 0 citations
Publisher

Abstract

This manuscript introduces and shares MATLAB code for simulating the behavior of a temporal SU(1,1) interferometer, offering a valuable resource for researchers and practitioners in the field. The provided code facilitates comprehensive simulations of the interferometer’s dynamics, enabling the exploration of its response to various parameters and scenarios. The simulations delve into the interferometer’s performance, emphasizing its sensitivity to ultrafast phase changes and its concurrent operation in both the time and spectral domains. By making the MATLAB code openly available, this contribution aims to foster collaboration, enhance reproducibility, and serve as a foundational tool for researchers delving into the design and analysis of temporal SU(1,1) interferometers. The manuscript provides detailed documentation on code usage, empowering users to adapt and extend the simulations for their specific research inquiries.

DOI
10.1117/12.3005761

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This manuscript introduces and shares MATLAB code for simulating the behavior of a temporal SU(1,1) interferometer, offering a valuable resource for researchers and practitioners in the field. The provided code facilitates comprehensive simulations of the interferometer’s dynamics, enabling the exploration of its response to various parameters and scenarios. The simulations delve into the interferometer’s performance, emphasizing its sensitivity to ultrafast phase changes and its concurrent operation in both the time and spectral domains. By making the MATLAB code openly available, this contribution aims to foster collaboration, enhance reproducibility, and serve as a foundational tool for researchers delving into the design and analysis of temporal SU(1,1) interferometers. The manuscript provides detailed documentation on code usage, empowering users to adapt and extend the simulations for their specific research inquiries.
In this proceeding, we expand upon our recent work on the temporal Aharonov-Bohm (AB) effect, focusing on the joint temporal function (JSF) analysis to enhance the sensitivity and understanding of the system’s performance. Our original paper demonstrated the existence of a temporal analog of the Aharonov-Bohm effect using entangled photons and a temporal SU(1,1) interferometer. Here, we provide a more detailed exploration of the JSF, highlighting its role in improving signal-to-noise ratios (SNR) and its impact on measuring fast phase changes with enhanced temporal resolution. By leveraging the quantum properties of the system and utilizing the JSF between the signal and idler beams, we show that this approach allows for unprecedented sensitivity in detecting temporal phase shifts. This proceeding will also discuss how the JSF contributes to the interferometer’s ability to resolve femto-second dynamics and its potential applications for simulating space-time phenomena, including rotating black holes and gravitational frame dragging. Our analysis offers deeper insights into the interplay between the quantum characteristics of the system and its utility for high-precision measurements in spatio-temporal dynamics.
This review offers a comprehensive exploration and synthesis of recent advancements in the domain of quantum correlation sharing facilitated through sequential measurements. We initiate our inquiry by delving into the interpretation of the joint probability, laying the foundation for an examination of quantum correlations within the context of specific measurement methods. The subsequent section meticulously explores nonlocal sharing under diverse measurement strategies and scenarios, with a specific focus on investigating the impact of these strategies on the dissemination of quantum nonlocality. Key perspectives such as "asymmetry" and "weak value" are scrutinized through detailed analyses across various scenarios, allowing us to evaluate the potential of nonlocality sharing. We also provide a retrospective overview of experimental endeavors associated with this phenomenon. The third part of our exploration presents research findings on steering sharing, offering clarity on the feasibility of steering sharing and summarizing the distinctive properties of quantum steering sharing in different scenarios. Continuing our journey, the fourth section delves into discussions on the sharing of diverse quantum correlations, encompassing network nonlocality, quantum entanglement, and quantum contextuality. Moving forward, the fifth section conducts a comprehensive review of the progress in the application of quantum correlation sharing, specifically based on sequential measurement strategies. Applications such as quantum random access coding, random number generation, and self-testing tasks are highlighted. Finally, we discuss and list some of the key unresolved issues in this research field, and conclude the entire article.
Feature selection was a critical process in machine learning that enhances model performance by identifying the most relevant features from high-dimensional datasets. This book chapter delves into various feature selection methodologies, emphasizing the significance of hybrid approaches that leverage the strengths of different techniques, including filter, wrapper, and embedded methods. It critically examines the advantages and limitations of each method, providing insights into their applicability across diverse domains. The chapter also explores future directions in hybrid feature selection, including the integration of advanced algorithms, adaptation to varying data types, and the incorporation of domain knowledge. Emphasizing computational efficiency and real-time application potential, this work serves as a comprehensive guide for researchers and practitioners aiming to enhance machine learning models through effective feature selection. The findings and discussions presented herein contribute to the ongoing discourse in the field and provide a roadmap for future research initiatives.