Supercontinuum Generation at 1310nm in a Highly Nonlinear Photonic Crystal Fiber with a Minimum Anomalous Group Velocity Dispersion

Ashkan Ghanbari; Ali Sadr; Hadi Tat Hesari

Majlesi Journal of Electrical Engineering (Feb 2024)

Supercontinuum Generation at 1310nm in a Highly Nonlinear Photonic Crystal Fiber with a Minimum Anomalous Group Velocity Dispersion

Ashkan Ghanbari,
Ali Sadr,
Hadi Tat Hesari

Affiliations

Ashkan Ghanbari: Nano-photonic and Optoelectronic Research Laboratory (NOR Lab), Shahid Rajaee Teacher Training University, Tehran 16788-15811, Iran.
Ali Sadr: Department of Electrical Engineering, Science and Technology University of Iran, Tehran, Iran
Hadi Tat Hesari: Department of Electrical Engineering, Qazvin Islamic Azad University, Qazvin, Iran

Journal volume & issue: Vol. 7, no. 4

Abstract

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ABSTRACT:In present study ,we intend to investigate the evolution of supercontinuum generation (SCG) through triangular photonic crystal fiber (PCF) at 1310nm by using both full-vector multipole method (M.P.M) and novel concrete algorithms: symmetric split-step fourier (SSF) and fourth order runge kutta (RK4) which is an accurate method to solve the general nonlinear schrodinger equation (GNLSE). We propose an ideal solid-core PCF structure featuring a minimum anomalous group velocity dispersion (GVD), small higher order dispersions (HODs) and enhanced nonlinearity for appropriate supercontinuum generation with low input pulse energies over discrete distances of the PCF. We also investigate the impact of linear and nonlinear effects on supercontinuum spectra in detail and compare the results with different status .å¨1310çé«éç·æ§å åæ¶é«å çºçæå°åå¸¸ç¾¤éåº¦è²æ£ç¢çè¶ æè¦æè¦ï¼å¨æ¬ç ç©¶ä¸ï¼æåæç®åæä½¿ç¨å ¨ç¢éå¤æ¥µæ³ï¼MPMï¼åæ°ç©çå ·é«ç®æ³ï¼èª¿æ¥ç¢çè¶ ï¼SCGï¼ééå¨1310ä¸è§å½¢å åæ¶é«å çºï¼PCFï¼çæ¼è®ï¼å°ç¨±åæ¥å éèï¼SSFï¼åç¬¬åéé¾æ ¼åº«å¡ï¼RK4ï¼ï¼éæ¯è§£æ±ºä¸è¬éç·æ§èå®è«¤æ¹ç¨ï¼GNLSEï¼ä¸ç¨®ç²¾ç¢ºçæ¹æ³ãæåæåºä¸åçæ³çå¯¦è¯PCFçµæ§è¨ææä½åå¸¸ç¾¤éåº¦è²æ£ï¼GVDï¼ï¼å°é«éåæ£é«ï¼é¨éé¦é·ï¼åå¢å¼·çéç·æ§é©ç¶çè¶ é£çºè¶ éäºPCFçé¢æ£è·é¢ï¼ä½è¼¸å ¥çèè¡è½éãæåéç ç©¶çç·æ§åéç·æ§ææçè¶ é£çºå èè©³ç´°çå½±é¿ï¼ä¸¦èä¸åççæ çæ¯è¼çµæã

Cloud computing, DDoS attacks, Machine Learning, deep learning techniques, . ,

Published in Majlesi Journal of Electrical Engineering

ISSN: 2345-377X (Print); 2345-3796 (Online)
Publisher: OICC Press
Country of publisher: United Kingdom
LCC subjects: Technology: Engineering (General). Civil engineering (General)
Website: https://oiccpress.com/mjee/

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