Mocking the Weak Lensing universe: the LensTools python computing package

Abstract

We present a newly developed software package which implements a wide range of routines frequently used in Weak Gravitational Lensing (WL). With the continuously increasing size of the WL scientific community we feel that easy to use Application Program Interfaces (APIs) for common calculations are a necessity to ensure efficiency and coordination across different working groups. Coupled with existing open source codes, such as CAMB and Gadget2, LensTools brings together a cosmic shear simulation pipeline which, complemented with a variety of WL feature measurement tools and parameter sampling routines, provides easy access to the numerics for theoretical studies of WL as well as for experiment forecasts. Being implemented in python, LensTools takes full advantage of a range of state--of--the art techniques developed by the large and growing open--source software community (scipy,pandas,astropy,scikit-learn,emcee). We made the LensTools code available on the Python Package Index and published its documentation on http://lenstools.readthedocs.io

9 pages, 6 figures, accepted for publication on Elsevier Astronomy & Computing

References in corpus (2)

• Emulating the CFHTLenS Weak Lensing data: Cosmological Constraints from moments and Minkowski functionals
• Analytic Minkowski Functionals of the Cosmic Microwave Background: Second-order Non-Gaussianity with Bispectrum and Trispectrum

Cited by in corpus (44)

• Cosmological constraints with deep learning from KiDS-450 weak lensing maps
• A new approach to observational cosmology using the scattering transform
• Non-Gaussian information from weak lensing data via deep learning
• MassiveNuS: Cosmological Massive Neutrino Simulations
• CosmoGAN: creating high-fidelity weak lensing convergence maps using Generative Adversarial Networks
• Weak lensing cosmology with convolutional neural networks on noisy data
• On the connectivity of the cosmic web: theory and implications for cosmology and galaxy formation
• Cosmological constraints from noisy convergence maps through deep learning
• Constraining neutrino mass with tomographic weak lensing one-point probability distribution function and power spectrum
• CMB weak-lensing beyond the Born approximation: a numerical approach
• On the validity of the Born approximation for beyond-Gaussian weak lensing observables
• Constraining neutrino mass with weak lensing Minkowski Functionals
• Constraining Neutrino Mass with the Tomographic Weak Lensing Bispectrum
• Constraining neutrino mass with tomographic weak lensing peak counts
• Weak lensing scattering transform: dark energy and neutrino mass sensitivity
• Parameters Estimation for the Cosmic Microwave Background with Bayesian Neural Networks
• CMB Lensing Beyond the Power Spectrum: Cosmological Constraints from the One-Point PDF and Peak Counts
• On the effect of non-Gaussian lensing deflections on CMB lensing measurements
• Weak Lensing Minima and Peaks: Cosmological Constraints and the Impact of Baryons
• On the dissection of degenerate cosmologies with machine learning
• The Accuracy of Weak Lensing Simulations
• ABC-CDE: Towards Approximate Bayesian Computation with Complex High-Dimensional Data and Limited Simulations
• Do dark matter halos explain lensing peaks?
• Cosmology with photometric weak lensing surveys: constraints with redshift tomography of convergence peaks and moments
• The Impact of Baryons on Cosmological Inference from Weak Lensing Statistics
• Starlet l1-norm for weak lensing cosmology
• Early results from GLASS-JWST. XXVII. The mass-metallicity relation in lensed field galaxies at cosmic noon with NIRISS
• A comparative study of cosmological constraints from weak lensing using Convolutional Neural Networks
• The self similarity of weak lensing peaks
• Geometry and growth contributions to cosmic shear observables
• Optimizing simulation parameters for weak lensing analyses involving non-Gaussian observables
• Flow-Based Likelihoods for Non-Gaussian Inference
• UNIONS: The impact of systematic errors on weak-lensing peak counts
• Cosmological Constraints from Weak Lensing Peaks: Can Halo Models Accurately Predict Peak Counts?
• ShapePipe: A modular weak-lensing processing and analysis pipeline
• A roadmap to cosmological parameter analysis with third-order shear statistics II: Analytic covariance estimate
• Skewing the CMB$\times$LSS: a Fast Method for Bispectrum Analysis
• Accurate Measurement of the Lensing Magnification by BOSS CMASS Galaxies and Its Implications for Cosmology and Dark Matter
• Accurate relativistic observables from post-processing light cone catalogues
• The Impact of Photometric Redshift Errors on Lensing Statistics in Ray-Tracing Simulations
• Constraining cosmology with thermal Sunyaev-Zel'dovich maps: Minkowski functionals, peaks, minima, and moments
• Accelerating MCMC algorithms through Bayesian Deep Networks
• A Hamiltonian, post-Born, three-dimensional, on-the-fly ray tracing algorithm for gravitational lensing
• Generative modeling of convergence maps based on predicted one-point statistics