For a list of software gadgets I am working on, please check out my github.

JAVELIN

Just Another Vehicle for Estimating Lags In Nuclei

Introduction



JAVELIN, formerly known as SPEAR, is a new approach to reverberation mapping that computes the lags between the AGN continuum and emission line (spectroscopic or photometric) light curves and their statistical confidence limits. It uses a damped random walk model to describe the quasar continuum variability and the ansatz that emission line variability is a scaled, smoothed and displaced version of the continuum. While currently configured only to simultaneously fit light curve means, it includes a general linear parameters formalism to fit more complex trends or calibration offsets. The noise matrix can be modified to allow for correlated errors, and the correlation matrix can be modified to use a different stochastic process. The transfer function model is presently a tophat, but this can be altered by changing the line-continuum covariance matrices. It is also able to cope with some problems in traditional reverberation mapping, such as irregular sampling, correlated errors and seasonal gaps.


Documents



Get JAVELIN


Download

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3.15MB .tar.gz

User Manual

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hosted on github


Citation


You are welcome to use and modify JAVELIN, however please acknowledge its use either as is or with modifications with citations to:

Zu, Y., Kochanek, C.S., Kozlowski, S., & Udalski, A. 2013, ApJ, 765, 106

for quasar optical variability studies, to

Zu, Y., Kochanek, C.S., & Peterson, B.M. 2011, ApJ, 735, 80

for spectroscopic reverberation mapping, and/or to

Zu, Y., Kochanek, C.S., Kozlowski, S., & Peterson, B.M. 2016, ApJ, 819, 122

for photometric reverberation mapping.


SPEAR

Stochastic Process Estimation for AGN Reverberations

SPEAR has evolved



SPEAR, which was originally written in Fortran, has been superseded by its Python version JAVELIN. However, the old versoin of SPEAR (v3.1.2) can still be downloaded from here, and the original documentation can be found in Howto for SPEAR.


Kindlize



Kindlize is a python package to generate, manage, and sync Kindle-friendly arXiv pre-prints with your Kindle DX device. It provides perfect astro-ph reading experience on my Kindle DX and saves me from printing stacks of papers that I never read.


Download

click to begin

1.2MB .tar.gz

User Manual

click to view

hosted on github