Author Archives: Alice Allen

August 2024 additions to the ASCL

Fifteen codes were added to the ASCL in August, 2024:

21cmFirstCLASS: Generate initial conditions at recombination
Astronify: Astronomical data sonification
BELTCROSS2: Calculate the closest approaches of asteroids to meteoroid streams
Cue: Nebular emission modeling
GRBoondi: AMR-based code to evolve generalized Proca fields on arbitrary fixed backgrounds

HaloFlow: Simulation-Based Inference (SBI) using forward modeled galaxy photometry
LADDER: Learning Algorithm for Deep Distance Estimation and Reconstruction
M_SMiLe: Magnification Statistics of Micro-Lensing
pySDR: Wrapper for sharpened dimensionality reduction
RadioSED: Radio SED fitting for AGN

Sailfish: GPU-accelerated grid-based astrophysics gas dynamics code
SAQQARA: Stochastic gravitational wave background analysis
SDR: Sharpened Dimensionality Reduction
SHARC: SHArpened Dimensionality Reduction and Classification
SonAD: Sonification of astronomical data

July 2024 additions to the ASCL

Twenty codes were added to the ASCL in July, 2024:

AstroCLIP: Multimodal contrastive pretraining for astronomical data
ATM: Asteroid Thermal Modeling
BaCoN: BAyesian COsmological Network
bigfile: A reproducible massively parallel IO library for hierarchical data
cola_halo: Parallel cosmological N-body simulator

Fof: Friends-of-friends code to find groups
Forklens: Deep learning weak lensing shear
GRDzhadzha: Evolve matter on curved spacetimes
Heimdall: GPU accelerated transient detection pipeline for radio astronomy
hipipe: VLT/HiRISE reduction pipeline

MAKEE: MAuna Kea Echelle Extraction
Package-X: Calculate Feynman loop integrals
PFFT: Parallel fast Fourier transforms
photGalIMF: Stellar mass and luminosity evolution calculator
pony3d: Efficient island-finding tool for radio spectral line imaging

provabgs: SED modeling tools for PROVABGS
pycosie: Python analysis code used on Technicolor Dawn
pyFAT: Python Fully Automated TiRiFiC
RealSim: Statistical observational realism for synthetic images from galaxy simulations
UFalcon: Ultra Fast Lightcone

Resources for IAU GA Unconference session on improving software citation

Discussion last week with IAU GA attendees, including software authors and data and journal editors, resulted in a proposal to hold an unconference session on improving software citation, this intended to be a discussion that results in ideas that can be implements. The session was held  on Tuesday, August 13 at 12:30 PM SAST.

This post is to capture resources that may be useful for this discussion and subsequent output. The list will grow over the next few days, so check back for additional information.

Session video
This session was recorded as part of the day’s Unconference events and can be found on YouTube.

Articles
Ten simple rules for recognizing data and software contributions in hiring, promotion, and tenure
Research Software Engineers: Career Entry Points and Training Gaps
Characterizing Role Models in Software Practitioners’ Career: An Interview Study
Research Software Science: Expanding the Impact of Research Software Engineering

Session slides

ASCL poster at 2024 IAU General Assembly

Poster title: How Important is Software to Astronomy? Poster text: Software is the most used instrument in astronomy All astronomers use software Robust research requires reproducibility and transparency Computational methods are methods, and should be easily discoverable and open to examination Releasing source code demonstrates confidence in your results and improves efficiency in the discipline Astrophysics Source Code Library (ASCL, ascl.net) • Is a free curated online registry and repository for astro research source codes • Has over 3400 entries • Is indexed by ADS and Web of Science • Includes all major codes that have enabled astro research • Makes it easy to find this software • Advocates for open source and FAIR practices • Is citable and citations to its entries are tracked by major indexers • Adds new and old codes monthly ASCL entries have been cited more than 16,000 times in over 240 journals How to use the ASCL Register your code with the ASCL to make it easier for others to find and to get an ASCL ID to use for citing the software Search for useful downloadable software Find preferred citation information for software you’ve used in research Introduce students to variety of methods available for solving common astronomical problems e community Provides a curated resource for software methods Links research articles with the software that enables that research; links are passed to ADS, so also appear in that resource Allows for citation to software on its own merits without the need to write a separate article for it References [1] Momcheva, I. & Tollerud, E., 2015. Software Use in Astronomy: an Informal Survey, doi:10.48550/arXiv.1507.03989 [2] ASCL dashboard, https://ascl.net/dashboard, retrieved 16 July 2024Software is by far the most used instrument in astronomy, and as robust research requires reproducibility and transparency, computational methods should be easily discoverable and open to examination. The Astrophysics Source Code Library (ASCL, ascl.net) makes the software that drives our discipline discoverable. The ASCL is a free online registry and repository for astrophysics research software. Containing over 3300 entries, it not only includes all the major codes that have enabled astro science, thus making it easy to find this software, it also advocates for open source and FAIR practices, and enables trackable formal software citation. Its entries have been cited more than 16,000 times in over 200 journals, and are indexed by ADS and Web of Science. This presentation covers how to use the ASCL and how it benefits the community.

Alice Allen, Astrophysics Source Code Library/University of Maryland, MD, USA/Michigan Technological University, MI, USA

Download poster

New ASCL team member!

Dr. Oindabi Mukherjee joined the ASCL team in June. She recently received her Ph.D. in Physics from Michigan Technological University (MTU, home of the ASCL; go, Huskies!). She specializes in detecting similarities in the light curves of Gamma-ray Bursts, and is assisting the ASCL with a number of projects. She is also our Social Media Maven. Welcome, Oindabi!

June 2024 additions to the ASCL

Thirty codes were added to the ASCL in June, 2024:

AAD: ALeRCE Anomaly Detector
AARD: Automatic detection of solar active regions
anzu: Measurements and emulation of Lagrangian bias models for clustering and lensing cross-correlations
AutoPhOT: Rapid publication-quality photometry of transients
BiaPy: Bioimage analysis pipeline builder

candl: Differentiable likelihood framework for analyzing CMB power spectrum measurements
CARDiAC: Anisotropic Redshift Distributions in Angular Clustering
CBiRd: Bias tracers In Redshift space
CTC: Color transformations calculator
EVA: Excess Variability-based Age

Faceted-HyperSARA: Parallel faceted imaging in radio interferometry
FLORAH: Galaxy merger tree generator with machine learning
GAStimator: Python MCMC gibbs-sampler with adaptive stepping
GRINN: Gravity Informed Neural Network for studying hydrodynamical systems
LeHaMoC: Leptonic-Hadronic Modeling Code for high-energy astrophysical sources

Lenser: Measure weak gravitational flexion
MBE: Magnification bias estimation
phazap: Low-latency identification of strongly lensed signals
phi-GPU: Parallel Hermite Integration on GPU
photochem: Chemical model of planetary atmospheres

PowerSpecCovFFT: FFTLog-based computation of non-Gaussian analytic covariance of galaxy power spectrum multipoles
PRyMordial: Precise computations of BBN within and beyond the Standard Model
QMC: Quadratic Monte Carlo
Redback: Bayesian inference package for fitting electromagnetic transients
SMART: Spectral energy distributions Markov chain Analysis with Radiative Transfer models

sphereint: Integrate data on a grid within a sphere
SRF: Scaling Relations Finder
SuperLite: Spectral synthesis code for interacting transients
WinNet: Flexible, multi-purpose, single-zone nuclear reaction network
ytree: yt-based merger-tree code

May 2024 additions to the ASCL

Twenty-five codes were added to the ASCL in May, 2024:

ABBHI: Autoregressive binary black hole inference
AFINO: Automated Flare Inference of Oscillations
blackthorn: Spectra from right-handed neutrino decays
coronagraph_noise: Coronagraph noise modeling routines
coronagraph: Python noise model for directly imaging exoplanets

CosmoPower: Machine learning-accelerated Bayesian inference
DirectSHT: Direct spherical harmonic transform
EF-TIGRE: Effective Field Theory of Interacting dark energy with Gravitational REdshift
fitramp: Likelihood-based jump detection
GauPro: R package for Gaussian process modeling

i-SPin: Multicomponent Schrodinger-Poisson systems with self-interactions
ICPertFLRW: Cactus Code thorn for initial conditions
LTdwarfIndices: Variable brown dwarf identifier
morphen: Astronomical image analysis and processing functions
ndcube: Multi-dimensional contiguous and non-contiguous coordinate-aware arrays

nessai: Nested sampling with artificial intelligence
PALpy: Python positional astronomy library
pyADfit: Nested sampling approach to quasi-stellar object (QSO) accretion disc fitting
pySPEDAS: Python-based Space Physics Environment Data Analysis Software
raccoon: Radial velocities and Activity indicators from Cross-COrrelatiON with masks

raynest: Parallel nested sampling based on ray
riddler: Type Ia supernovae spectral time series fitter
SPEDAS: Space Physics Environment Data Analysis System
sunbather: Escaping exoplanet atmospheres and transit spectra simulator
tapify: Multitaper spectrum for time-series analysis

ApJ overtakes MNRAS in number of ASCL citations

In looking at the ASCL dashboard yesterday, I realized that the Astrophysical Journal (ApJ) now has the most citations to ASCL entries, having overtaken (by a hair) Monthly Notices of the Royal Astronomical Society (MNRAS), which has held the top spot since at least 2015. MNRAS‘s early (and enduring) lead in software citations was initially the result of one editor, Dr. Keith T. Smith (now a senior editor at Science), who strongly encouraged article authors to cite the software they had used to generate their results. (Though I obviously saw the effect of his work in MNRAS, I had no idea one person was responsible for it until I saw a post in the Astronomers Facebook group and later queried Keith, who was unknown to me at the time.)

AAS Journals, which publishes ApJ, has three data editors, Greg Schwarz, August Muench, and Katie Merrell, who, though primarily consumed with data work, also encourage software citation, obviously to good effect. And so it grows!
Pie chart showing number of citations to ASCL entries by journal: ApJ, 4158, 27% MNRAS, 4156, 27% A&A, 2022, 13% AJ, 1328, 9% arXiv, 1135, 8% Other, 2351, 16%

April 2024 additions to the ASCL

Thirty codes were added to the ASCL in April, 2024:

astroNN: Deep learning for astronomers with Tensorflow
BayeSN: NumPyro implementation of BayeSN
binary_precursor: Light curve model of supernova precursors powered by compact object companions
cbeam: Coupled-mode propagator for slowly-varying waveguides
cudisc: CUDA-accelerated 2D code for protoplanetary disc evolution simulations

EBWeyl: Compute the electric and magnetic parts of the Weyl tensor
EffectiveHalos: Matter power spectrum and cluster counts covariance modeler
ExoPlex: Thermodynamically self-consistent mass-radius-composition calculator
GalMOSS: GPU-accelerated Galaxy Profile Fitting
GPUniverse: Quantum fields in finite dimensional Hilbert spaces modeler

jetsimpy: Hydrodynamic model of gamma-ray burst jet and afterglow
KCWIKit: KCWI Post-Processing and Improvements
LensIt: CMB lensing delensing tools
LEO-vetter: Automated vetting for TESS planet candidates
Mean_offset: Photometric image alignment with row and column means

mhealpy: Object-oriented healpy wrapper with support for multi-resolution maps
MLTPC: Machine Learning Telescope Pointing Correction
NbodyIMRI: N-body solver for intermediate-mass ratio inspirals of black holes and dark matter spikes
pAGN: AGN disk model equations solver
Panphasia: Create cosmological and resimulation initial conditions

PIPE: Extracting PSF photometry from CHEOPS data
PolyBin3D: Binned polyspectrum estimation for 3D large-scale structure
pyilc: Needlet ILC in Python
PySSED: Python Stellar Spectral Energy Distributions
RhoPop: Small-planet populations identifier

s2fft: Differentiable and accelerated spherical transforms
stringgen: Scattering based cosmic string emulation
superABC: Cosmological constraints from SN light curves using Approximate Bayesian Computation
TAT: Timing Analysis Toolkit for high-energy pulsar astrophysics
WignerFamilies: Compute families of wigner symbols with recurrence relations

Hand-crafted spam

Nearly every month, ASCL editors notify software authors that their code has been registered in the ASCL. Each editor sends out notifications for the code entries she worked on. I say “nearly every month” because I sometimes get behind in the prep work for the notifications, and that delays all editors who send out these notifications. Editors create their own processes for handling this correspondence.

I refer to my process as “hand-crafted spam.” I send out two types of notifications, one to authors who submitted their software to the ASCL, and another to authors for code entries I created. I have standard text into which I add, one by one, the necessary details for each email, by cutting and pasting the info from an Excel spreadsheet I create just for this purpose. I also check the emails against the ASCL entries to make sure I’ve got the right code and author. This sounds laborious, but it actually doesn’t take much time. This afternoon, I sent out 34 emails covering 39 code entries (some authors had two codes added to the ASCL) for code entries processed in February, March, and April, and it took me, working at a steady but unhurried pace, exactly one hour from the first missive to the last.

I’m putting this here to remind future me that this task goes pretty quickly, so, future me, do this more promptly!