4.7 Article

An efficient method for simulating light curves of cosmological microlensing and caustic crossing events

Journal

MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
Volume 514, Issue 2, Pages 2545-2560

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/mnras/stac1511

Keywords

galaxy clusters: general; gravitational lensing: micro; gravitational lensing: strong

Funding

  1. Ministry of Science and Technology, Israel
  2. United States-Israel Binational Science Foundation (BSF) [2020750]
  3. United States National Science Foundation (NSF) [2109066]
  4. Direct For Mathematical & Physical Scien
  5. Division Of Astronomical Sciences [2109066] Funding Source: National Science Foundation

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A new method for simulating light curves of caustic-crossing events in galaxy clusters is presented, which can provide valuable information about individual stars and small sources at cosmological distances. The method, named Adaptive Boundary Method, is shown to be more efficient and accurate than other common methods in the small-source and high-magnification regime.
A new window to observing individual stars and other small sources at cosmological distances was opened recently, with the detection of several caustic-crossing events in galaxy cluster fields. Many more such events are expected soon from dedicated campaigns with the Hubble Space Telescope and the James Webb Space Telescope. These events can not only teach us about the lensed sources themselves, such as individual high-redshift stars, star clusters, or accretion discs, but through their light curves they also hold information about the point-mass function of the lens, and thus, potentially, the composition of dark matter. We present here a simple method for simulating light curves of such events, i.e. the change in apparent magnitude of the source as it sweeps over the net of caustics generated by microlenses embedded around the critical region of the lens. The method is recursive and so any reasonably sized small source can be accommodated, down to sub-solar scales, in principle. We compare the method, which we dub Adaptive Boundary Method, with other common methods such as simple inverse ray shooting, and demonstrate that it is significantly more efficient and accurate in the small-source and high-magnification regime of interest. A python version of the code is made publicly available in an open-source fashion for simulating future events.

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