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  • Фотонный рефлектометр во временной области на основе сверхпроводящего нанопроводникового однофотонного детектора и время-цифрового преобразователя
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News
May 25, 2026
HSE Scientists Train Neural Network to 'Hear' Faults in Electric Motors
Researchers at the AI and Digital Science Institute of the HSE Faculty of Computer Science have developed a new method—the Signature-Guided Data Augmentation (SGDA) framework—that achieves 99% accuracy in motor fault detection and 86% accuracy in fault classification. The application of this approach can reduce industrial equipment repair costs, minimise downtime, and improve production safety. The study results have been published in Engineering Applications of Artificial Intelligence.
May 25, 2026
'The Humanities Serve as a Conscience'
Maria Mizernaia studies Soviet literature and the history of book publishing. In this interview for the HSE Young Scientists project, she discusses plans to publish a novel about besieged Leningrad, AI-provoked reflections on what it means to be human, and how novels can help satisfy our dopamine hunger.
May 25, 2026
Is It Possible to Predict a Citys Life Based on the Shape of Its Neighbourhoods?
Is it possible to predict, based on the configuration of streets and buildings, where a café will open or where traffic congestion will occur? Participants in the Spatial Analysis and Modelling of Urban Processes research and study group use open data and machine learning to identify universal patterns. Alexander Sheludkov and Eduard Somov discuss the purpose of comparing cities, the need for new forms of urban statistics, and how open data is transforming approaches to urban studies.

 

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Фотонный рефлектометр во временной области на основе сверхпроводящего нанопроводникового однофотонного детектора и время-цифрового преобразователя

Прикладная фотоника. 2025. Т. 12. № 3. С. 40–55.
Махлуф М.

The Optical Time-Domain Reflectometer (OTDR) plays a key role in the diagnostics of fiber-optic networks and distributed fiber-optic sensing systems, enabling precise fault localization and performance optimization of long-haul communication links. This work presents a significant advancement in OTDR technology, achieved through the integration of a superconducting nanowire single-photon detector (SNSPD) and a field-programmable gate array (FPGA)-based time-to-digital converter (TDC). The SNSPD exhibits an efficiency of 63% at a wavelength of 1550 nm with a temporal jitter of 25 ps, while the FPGA-TDC provides a high temporal accuracy of 17.0 ± 1.3 ps at a high data acquisition rate. Experimental results demonstrate a dynamic range of 22.87 dB with a spatial resolution of 7.5 cm (at 25 km) and 1.6 m (at 100 km), confirming the system's high accuracy in determining fiber characteristics. This research lays the groundwork for the further development of real-time signal processing and automatic fault detection in fiber-optic networks, expanding their potential for applications in optical sensing.

Research target: Physics Electronics and Electrical Engineering
Language: Russian
Full text
DOI
Keywords: SNSPDTDCField-Programmable Gate ArrayОптический Рефлектометр во Временной Области.сверхпроводящий нанопроволочный однофотонный детектор
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