Effectiveness of Machine Learning in Assessing QoT Impairments of Photonics Integrated Circuits to Reduce System Margin

被引：0

作者：

Khan, Ihtesham ^{[1
]}

Chalony, Maryvonne ^{[2
]}

Ghillino, Enrico ^{[3
]}

Masood, M. Umar ^{[1
]}

Patel, Jigesh ^{[3
]}

Richards, Dwight ^{[4
]}

Mena, Pablo ^{[3
]}

Bardella, Paolo ^{[1
]}

Carena, Andrea ^{[1
]}

Curri, Vittorio ^{[1
]}

机构：

[1] Politecn Torino DET, Turin, Italy

[2] Light Tec SARL, Hyeres, France

[3] Synopsys Inc, New York, NY USA

[4] CUNY Coll Staten Isl, New York, NY USA

来源：

2020 IEEE PHOTONICS CONFERENCE (IPC) | 2020年

关键词：

Machine learning; Photonic Integrated Circuits; Q-factor;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

We propose machine learning technique for assessment of QoT impairments of integrated circuits. We consider margin reduction problem applied to a switching component. Overall results and data sets for machine-learning training are obtained by leveraging the integrated software environment of the Synopsys Photonic Design Suite.

引用

页数：2

共 50 条

[41] A comprehensive review: Machine learning and its application in integrated power system
Kumbhar, Aanand
Dhawale, Pravin G.
Kumbhar, Shobha
Patil, Uday
Magdum, Pravin
ENERGY REPORTS, 2021, 7 : 5467 - 5474
[42] Hybrid machine learning system for integrated yield management in semiconductor manufacturing
Kang, BS
Lee, JH
Shin, CK
Yu, SJ
Park, SC
EXPERT SYSTEMS WITH APPLICATIONS, 1998, 15 (02) : 123 - 132
[43] Assessing Levodopa Effectiveness in Parkison's Disease During Gait Using Electroencephalogram and Machine Learning
Pires, Rafael Goncalves
Pereira, Clayton Reginaldo
Penedo, Tiago
Papa, Joao Paulo
Roder, Mateus
Barbieri, Fabio Augusto
2024 31ST INTERNATIONAL CONFERENCE ON SYSTEMS, SIGNALS AND IMAGE PROCESSING, IWSSIP 2024, 2024,
[44] Machine-learning-aided abstraction of photonic integrated circuits in software-defined optical transport
Khan, Ihtesham
Tunesi, Lorenzo
Chalony, Maryvonne
Ghillino, Enrico
Masood, Muhammad Umar
Patel, Jigesh
Bardella, Paolo
Carena, Andrea
Curri, Vittorio
NEXT-GENERATION OPTICAL COMMUNICATION: COMPONENTS, SUB-SYSTEMS, AND SYSTEMS X, 2021, 11713
[45] Quantum photonics based health monitoring system using music data analysis by machine learning models
Zhu, Jing
OPTICAL AND QUANTUM ELECTRONICS, 2024, 56 (04)
[46] From Policy to Prediction: Assessing Forecasting Accuracy in an Integrated Framework with Machine Learning and Disease Models
Chakraborty, Amit K.
Wang, Hao
Ramazi, Pouria
JOURNAL OF COMPUTATIONAL BIOLOGY, 2024, 31 (11) : 1104 - 1117
[47] Assessing the effectiveness of micro-spring technology to reduce initial and peak loading rates when integrated into running footwear
University of Central Lancashire, Preston, United Kingdom
Footwear Sci., (S72-S73):
[48] Assessing the effectiveness of hydrogen pathways: A techno-economic optimisation within an integrated energy system
Bellocchi, Sara
Colbertaldo, Paolo
Manno, Michele
Nastasi, Benedetto
ENERGY, 2023, 263
[49] Machine Learning-Based Soft-Error-Rate Evaluation for Large-Scale Integrated Circuits
Song, Ruiqiang
Shao, Jinjin
Chi, Yaqing
Liang, Bin
Chen, Jianjun
Wu, Zhenyu
ELECTRONICS, 2023, 12 (24)
[50] Enhancing counterfeit detection of integrated circuits through machine learning-assisted THz-TDS analysis
University of Florida, Gainesville
FL, United States
Proc SPIE Int Soc Opt Eng,

← 1 2 3 4 5 →