JOURNAL ARTICLE
Self-focusing of a Bessel–Gaussian laser beam in plasma under density transition.
Published In: Journal of Nonlinear Optical Physics & Materials, 2024, v. 33, n. 3. P. 1 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Thakur, Vishal; Kumar, Sandeep; Kant, Niti 3 of 3
Abstract
The model given by Patil et al., for the self-focusing of lowest-order Bessel–Gaussian laser beam, is revisited by introducing the exponential plasma density ramp in this paper. Plasma density changes due to combined effect of the relativistic and ponderomotive nonlinearities, which arise due to the nonuniform spatial profile of the laser beam leading to stronger self-focusing. Under paraxial ray approximation, the expression for the evolution of laser-beam width parameter is obtained and solved numerically in order to achieve self-focusing. We have observed that as Bessel beam propagates through the plasma, it does not diffract and spread out, which is in contrast to the usual behavior of light that spreads out after being focused down to the small spot. Laser spot size decreases considerably under the presence of exponential density ramp. This study will be useful for better understanding the self-focusing mechanism of lasers as it becomes effective for the optimized parameters under the proposed situation. Bessel laser beams play an important role in enhancing the energy gain in laser-driven accelerators. In addition, for all laser-driven plasma-based accelerators, it appears possible to guide a laser beam over large distances using a plasma density channel, thus enhancing the acceleration length and the energy gain. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Journal of Nonlinear Optical Physics & Materials. 2024/09, Vol. 33, Issue 3, p1
- Document Type:Article
- Subject Area:Engineering
- Publication Date:2024
- ISSN:0218-8635
- DOI:10.1142/S0218863523500388
- Accession Number:177481372
- Copyright Statement:Copyright of Journal of Nonlinear Optical Physics & Materials is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Looking to go deeper into this topic? Look for more articles on EBSCOhost.