DESTNOSIM

Introduction

This repository contains the DES TNO survey simulator, as well as a bunch of tools for generating synthethic TNO populations, and for dealing with DES exposure information. This software has been described in detail in:

• Bernardinelli et. al. 2020, the Y4 data release
• Bernardinelli et. al. 2022, the Y6 data release

While this software can handle both the Y4 and Y6 releases, we suggest that only Y6 is used for any statistical studies.

Dependencies

Python:

• numpy
• astropy
• scipy
• numba
• spacerocks (https://github.com/kjnapier/spacerocks)
• Optional: pixmappy (https://github.com/gbernstein/pixmappy). This is only required if you wish to access some of the WCS functionalities of this package. If all you intend to do with this package is TNO simulations, you don't need pixmappy.

External:

• Optional: orbitspp (https://github.com/gbernstein/orbitspp) and dependencies

Installation

The Python package can be installed in a standard way:

    pip install destnosim

In order to use the des-specific functions, you'll need the correspondent exposure and ccd corner files (located in the data directory). Their location should be specified by defining an environment variable called DESDATA. The data folder needs to be downloaded separately from the cloning/download of the repository, as the files sizes are a bit too large for GitHub's standard file system.

The orbitspp installation is detailed in that package's page. It can be a bit tricky, and requires many different pieces to be put together. Make sure your environment has a ORBITSPP variable pointing to the bin folder of your orbitspp installation. This will link the C++ software with some of the tools present here.

If you do not install orbitspp, you necessarily have to use spacerocks for ephemerides generation. See here for a discussion.

Usage

A simple tutorial for the software included here is included here. This tutorial projects the almost 70 thousand synthethic objects from the CFEPS-L7 model into the DES exposures and evaluates the detectability of all objects. For more advanced usage, the user is encouraged to delve into the files and the documentation.

WARNING

In some versions of MacOS, there is a safety feature that does not propagate environment variables to shells that are generated inside other processes. What this means for destnosim is that orbitspp calls from inside python shells do not load orbitspp correctly. This is unfortunate, and a fix is forthcoming. In the meanwhile, the code will print the correct command line calls to orbitspp, and you can run these in your own shell. We apologize for the somewhat messy problem!