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Open source pulsar search and analysis toolkit
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PRESTO ------ http://www.cv.nrao.edu/~sransom/presto/ PRESTO is a large suite of pulsar search and analysis software developed by Scott Ransom mostly from scratch. It was primarily designed to efficiently search for binary millisecond pulsars from long observations of globular clusters (although it has since been used in several surveys with short integrations and to process a lot of X-ray data as well). It is written primarily in ANSI C, with many of the recent routines in Python. According to Steve Eikenberry, PRESTO stands for: PulsaR Exploration and Search TOolkit! Written with portability, ease-of-use, and memory efficiency in mind, it can currently handle raw data from the following pulsar machines or formats: * PSRFITS search-format data (as from GUPPI at the GBT and the Mock Spectrometers at Arecibo) * SPIGOT at the GBT * Most Wideband Arecibo Pulsar Processor (WAPP) at Arecibo * The Parkes and Jodrell Bank 1-bit filterbank formats * Berkeley-Caltech Pulsar Machine (BCPM) at the GBT (may it RIP...) * 8-bit filterbank format from SIGPROC (other formats will be added if required) * A time series composed of single precision (i.e. 4-byte) floating point data * Photon arrival times (or events) in ASCII or double-precision binary formats The software is composed of numerous routines designed to handle three main areas of pulsar analysis: 1. Data Preparation: Interference detection (rfifind) and removal (zapbirds) , de-dispersion (prepdata, prepsubband, and mpiprepsubband), barycentering (via TEMPO). 2. Searching: Fourier-domain acceleration (accelsearch), single-pulse (single_pulse_search.py), and phase-modulation or sideband searches (search_bin). 3. Folding: Candidate optimization (prepfold) and Time-of-Arrival (TOA) generation (get_TOAs.py). 4. Misc: Data exploration (readfile, exploredat, explorefft), de-dispersion planning (DDplan.py), date conversion (mjd2cal, cal2mjd), tons of python pulsar/astro libraries, average pulse creation, flux density estimation, and more... Many additional utilities are provided for various tasks that are often required when working with pulsar data such as time conversions, Fourier transforms, time series and FFT exploration, byte-swapping, etc. The Fourier-Domain acceleration search technique that PRESTO uses in the routine accelsearch is described in Ransom, Eikenberry, and Middleditch (2002), and the phase-modulation search technique used by search_bin is described in Ransom, Cordes, and Eikenberry (2003). Some other basic information about PRESTO can be found in my thesis. I will eventually get around to finishing the documentation for PRESTO, but until then you should know that each routine returns its basic usage when you call it with no arguments. I am also willing to provide limited support via email or telephone (434-296-0320). To date, PRESTO has discovered well over a hundred pulsars, including more than 70 recycled pulsars, over 50 of which are in binaries! Getting it: The PRESTO source code is released under the GPL and can be browsed or gotten from here in many different ways (including zipped or tar'd or via git). If you are too lazy to read how to get it but have git on your system do: > git clone git://github.com/scottransom/presto.git To update it on a regular basis do > cd $PRESTO > git pull and then re-make things in $PRESTO/src. If you don't want to mess with git (which means that you will need to re-install a tarball whenever there are updates) you can get it from the "Download Source" link on the github page. If you plan to tweak the code, I highly suggest that you use git and clone the directory (or fork it using an account on github). If you plan on doing any significant development, please let me know and I'll either add you as a developer, or we can push/pull changes via git/github. Code contributions and/or patches to fix bugs are most welcome! NOTE: for barycentering data, PRESTO uses TEMPO. You should get the newest version from Sourceforge. You will also need FFTW, CFITSIO, and PGPLOT. Final Thoughts: Please let me know if you decide to use PRESTO for any "real" searches. And if you find anything with it, it would be great if you would cite either my thesis or whichever of the two papers listed above is appropriate. Thanks! Acknowledgements: Big thanks go to Steve Eikenberry for his help developing the algorithms, Dunc Lorimer for the basic code which is used to process BCPM and WAPP data, David Kaplan for lots of help with the GBT SPIGOT code, Jason Hessels for many contributions to the Python routines (and along with Maggie Livingstone for the rednoise reduction routine), Anne Archibald (for significant help with the recent accelsearch improvements), and Paul Demorest, Paul Ray, Ingrid Stairs, Fernando Camilo, Cees Bassa, Patrick Lazarus, Mike Keith, Slavko Bogdanov, and Paulo Freire for many comments and suggestions (and even some patches!). Scott Ransom <sransom@nrao.edu>
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