arXiv subjects

John Rozario Jegaraj

Publications and source records attributed to John Rozario Jegaraj.

2 recordsLinked to original sources

arXiv2025

Adaptive Laser Beam Engineering with Coherent Beam Combining for Efficient Power Delivery

High-power laser technologies are essential in precision manufacturing, defense, and scientific research, where accurate control of the beam profile is paramount. Although several beam-shaping methods exist, they often face implementation and scalability challenges. To address these limitations, we introduce a comprehensive and versatile framework for on-demand beam engineering through coherent beam combining (CBC) systems to precisely craft far-field intensity distributions. The proposed approach integrates limitless key capabilities: (i) dynamic beam shaping through sequential steering, (ii) structured static beam shaping allowing the direct formation of target-defined profiles, and (iii) high-speed dynamic beam sequencing without mechanical movement. Thus, the proposed approach could be a potential one-stop solution to meet wide manufacturing requirements. Rapid reconfiguration is achieved through optimized phase control of the CBC channels, supported by a deep-learning-inspired optimization algorithm. This unified CBC framework significantly improves beam uniformity, power delivery efficiency, and scalability compared to conventional techniques, thus establishing a robust platform for next-generation laser systems in industrial manufacturing, materials processing, and directed-energy systems.

physics.optics↗

arXiv2025

Dynamic Beam Shaping Using a Wavelength-Adaptive Diffractive Neural Network for Laser-Assisted Manufacturing

Laser-based manufacturing has emerged as a promising alternative to conventional thermal and mechanical processing owing to its precision, versatility, and ability to work across diverse materials. In particular, tailoring the spatial intensity distribution of laser beams on the fly is pivotal for ensuring keyhole stability, minimizing defects, and enhancing processing quality. To address this need, we propose a multifunctional optical platform designed through a Diffractive Neural Network that provides wavelength adaptability for three industrially relevant wavelengths - 915 nm, 1064 nm, and 1550 nm - while dynamically generating distinct beam profiles at specified propagation planes. The proposed platform not only enables static beam shaping but also supports dynamic beam engineering, including programmable sequencing between profiles, which is highly desirable for optimal manufacturing solutions. With its multifunctionality and adaptability, the DNN-based architecture establishes a transformative pathway for next-generation laser manufacturing, aligning with the industrial revolution while unlocking opportunities in biomedical optics, free-space communications, and sensing.

physics.optics↗