63.6k citations · 75.8k across the 24 of their papers we have counts for
9 papers · 1 filter
A Fast Template Periodogram for Detecting Non-sinusoidal Fixed-shape Signals in Irregularly Sampled Time Series
John Hoffman, Jacob Vanderplas, Joel Hartman +1
Astrophysical time series often contain periodic signals. The large and growing volume of time series data from photometric surveys demands computationally efficient methods for de…
Applying Information Theory to Design Optimal Filters for Photometric Redshifts
J. Bryce Kalmbach, Jacob T. VanderPlas, Andrew J. Connolly
In this paper we apply ideas from information theory to create a method for the design of optimal filters for photometric redshift estimation. We show the method applied to a serie…
The Astropy Project: Building an inclusive, open-science project and status of the v2.0 core package
The Astropy Collaboration, A. M. Price-Whelan, B. M. Sipőcz +134
The Astropy project supports and fosters the development of open-source and openly-developed Python packages that provide commonly-needed functionality to the astronomical communit…
Understanding the Lomb-Scargle Periodogram
Jacob T. VanderPlas
The Lomb-Scargle periodogram is a well-known algorithm for detecting and characterizing periodic signals in unevenly-sampled data. This paper presents a conceptual introduction to…
Cluster-lensing: A Python Package for Galaxy Clusters & Miscentering
Jes Ford, Jake VanderPlas
We describe a new open source package for calculating properties of galaxy clusters, including NFW halo profiles with and without the effects of cluster miscentering. This pure-Pyt…
Periodograms for Multiband Astronomical Time Series
Jacob T. VanderPlas, Zeljko Ivezic
This paper introduces the multiband periodogram, a general extension of the well-known Lomb-Scargle approach for detecting periodic signals in time-domain data. In addition to adva…
Introduction to astroML: Machine Learning for Astrophysics
Jacob T. VanderPlas, Andrew J. Connolly, Zeljko Ivezic +1
Astronomy and astrophysics are witnessing dramatic increases in data volume as detectors, telescopes and computers become ever more powerful. During the last decade, sky surveys ac…
LSST Science Book, Version 2.0
LSST Science Collaboration, Paul A. Abell, Julius Allison +245
A survey that can cover the sky in optical bands over wide fields to faint magnitudes with a fast cadence will enable many of the exciting science opportunities of the next decade.…
Reducing the Dimensionality of Data: Locally Linear Embedding of Sloan Galaxy Spectra
J. T. VanderPlas, A. J. Connolly
We introduce Locally Linear Embedding (LLE) to the astronomical community as a new classification technique, using SDSS spectra as an example data set. LLE is a nonlinear dimension…