DarpanX: A Python Package for Modeling X-ray Reflectivity of Multilayer Mirrors
Biswajit Mondal, Santosh V. Vadawale, N.P.S. Mithun, C.S. Vaishnava,, Neeraj K. Tiwari, S.K. Goyal, Singam S. Panini, Vinita Navalkar, Chiranjit, Karmakar, Mansukhlal R. Patel, R.B. Upadhyay

TL;DR
DarpanX is a Python package designed for modeling and fitting X-ray reflectivity data of multilayer mirrors, aiding in the design of advanced X-ray optical components for astronomical applications.
Contribution
It introduces a Python-based tool that models multilayer X-ray mirrors and integrates with XSPEC for accurate experimental data fitting, advancing X-ray mirror design capabilities.
Findings
Validated DarpanX against different multilayer structures.
Demonstrated effective fitting of experimental X-ray reflectivity data.
Enabled design optimization of multilayer X-ray mirrors.
Abstract
Multilayer X-ray mirrors consist of a coating of a large number of alternate layers of high Z and low Z materials with a typical thickness of 10-100 Angstrom, on a suitable substrate. Such coatings play an important role in enhancing the reflectivity of X-ray mirrors by allowing reflections at angles much larger than the critical angle of X-ray reflection for the given materials. Coating with an equal thickness of each bilayer enhances the reflectivity at discrete energies, satisfying Bragg condition. However, by systematically varying the bilayer thickness in the multilayer stack, it is possible to design X-ray mirrors having enhanced reflectivity over a broad energy range. One of the most important applications of such a depth graded multilayer mirror is to realize hard X-ray telescopes for astronomical purposes. Design of such multilayer X-ray mirrors and their characterization with…
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