MRLens

 

Authors: S. Pires, J-L. Starck, A. Réfrégier
Language: C++ (IDL wrapper)
Download: mrle.tar.gz
Description: A weak lensing mass-mapping tool.
Notes: Documentation: ManualMRLens.pdf


Weak Lensing provides a unique method to directly map the distribution of dark matter in the universe. Ongoing efforts are made to improve the detection of cosmic shear on existing telescopes and future instruments dedicated to survey are planned. Several methods are used to derive the lensing shear from the shapes of background galaxies. But the shear map obtained is always noisy, and when it is converted into a map of the projected mass map, the result is dominated by the noise.

MRLens offers a new algorithm for the reconstruction of Weak Lensing mass maps.

Convergence Map in the COSMOS field reconstructed with MRLens

Description 

MRLens (Multi-Resolution tools for gravitational Lensing) is a software written in C++ with an IDL interface. This method uses the Multiscale Entropy concept (which is based on wavelets) and the False Discovery Rate (FDR) which allows us to derive robust detection levels in wavelet space. MRLens has been used to process the COSMOS map (see Figure above)..

User Manual

More than a software dedicated to a new reconstruction method, MRLens software includes many other tools useful to process, analyze and visualize lensing data. The user manual introduces Weak Lensing field and describes the MRLENS tools. Some results are presented and an accurate description of IDL routines are available.

Downloads

Fast download :  (Only binaries)

Standard Download :  (Binaries and data)

System Requirements : 1- Make sure you have approximately 400 MB of disk space available. After installation MRLENS package occupies approximately 56 MB or 205MB (version with data) of disk space.
2- The binaries C++ called by IDL routines are not available under all the systems therefore you cannot use the package on all platforms. The supported platforms are : SUN-Solaris, PC-Linux, Mac OS X. Next release will include PC Windows.

Software Requirements : The IDL MRLENS software requires that IDL (version 6.0 or later) to be installed on your computer. Starting IDL using the script program mrl.pro allows the user to add the MRLENS software to the IDL environment.
Thus, all routines described in the user manual can be called.
An online help is available by using the mrh.pro program.oftwares are required:

References

This package is a compilation of some algorithms and methods which were developed and/or used successfully in the applications reported in the 2 following publications:

Weak Lensing Mass Reconstruction using Wavelets, J.-L. Starck, S. Pires and A. Réfrégier, Astronomy and Astrophysics, March 2006

Map of the universe's Dark Matter scaffolding, R. Massey, J. Rhodes, R. Ellis, N. Scoville, A. Leathaud, A. Finoguenov, P. Capak, D. Bacon, H. Aussel, J.-P. Kneib, A. Koekemoer, H. McCracken, B. Mobasher, S. Pires, A. Réfrégier, S. Sasaki, ,J.-L. Starck, Y. Taniguchi and J. Taylor, Nature, January 2007

Sunyaev-Zeldovich cluster reconstruction in multiband bolometer camera surveys, S. Pires, J.-B. Juin, D. Yvon, Y. Moudden, S. Anthoine and E. Pierpaoli, Astronomy and Astrophysics, April 2006
More than a software dedicated to a new reconstruction method, this package includes many other tools useful to process, analyze and visualize lensing data.

Acknowledging MRLens

Please acknowledge use of the code in any resulting work, citing Starck, et al, 2006. We would be interested to collaborate with anyone requiring more advanced applications, and are always interested to hear about new applications. For questions and feedback or to be informed of the forthcoming versions, send an email to Sandrine Pires.

Contact information

Authors:

Last modified on January 6th, 2015 by Sandrine Pires
For questions and feedback or to be informed of the forthcoming versions, send an email to Sandrine Pires

FASTLens

 

Authors: S. Pires, J-L. Starck, A. Amara, A. Réfrégier, J. Fadili
Language: C++ (IDL wrapper)
Download: CEA_Inpainting.tar.gzCEA_PolarSpectrum.tar.gz
Description: A weak lensing mass-mapping tool.
Notes: Documentation: doc_fastlens.pdf


The analysis of weak lensing data requires to account for missing data such as masking out of bright stars. To date, the majority of lensing analyses uses the two point-statistics of the cosmic shear field. These can either be studied directly using the two-point correlation function, or in Fourier space, using the power spectrum. The two-point correlation function is unbiased by missing data but its direct calculation will soon become a burden with the exponential growth of astronomical data sets. The power spectrum is fast to estimate but a mask correction should be estimated. Others statistics can be used but these are strongly sensitive to missing data. 

The solution that is proposed by FASTLens is to properly fill-in the gaps with only NlogN operations, leading to a complete weak lensing mass map from which we can compute straight forwardly and with a very good accuracy any kind of statistics like power spectrum or bispectrum. The inpainting method relies strongly on the notion of sparsity and on the construction of sparse representations in large redundant dictionaries.

Simulated mass map with the mask pattern of CFHTLS data on D1 field (on the left), inpainted maps map (on the right).
 

Description

FASTLens (Fast STatistics for weak Lensing) is a package written in C++ that includes:

- An inpainting code to derive complete weak lensing mass maps from incomplete shear maps

- A power spectrum estimator 

- A bispectrum estimator (for equilateral and isoscele configurations)

We propose also a new method to compute fastly and accurately the power spectrum and the bispectrum with a polar FFT algorithm.

User Manual

The user manual introduces the missing data problem in statistic estimation and presents the available routines. An accurate description of IDL routines is given.

Downloads

The IDL FASTlens software requires IDL (version 6.0 or later) to be installed on your computer. 
The binaries C++ called by IDL routines are not available under all the systems therefore you cannot use the package on all platforms. The supported platforms are : PC-Linux and Mac OS X.

Inpainting routines (inpainting for weak lensing) 

Statistic routines (power spectrum and bispectrum estimators)

References

FASTLens (FAst STatistics for weak Lensing) : Fast method for weak lensing statistics and map making, S. Pires, J.-L. Starck, A. Amara, A. Refregier and J. Fadili, MNRAS,  395, 1265-1279, 2009

Acknowledging FASTLens

Please acknowledge use of the code in any resulting work, citing Pires, et al, 2009. We would be interested to collaborate with anyone requiring more advanced applications, and are always interested to hear about new applications. For questions and feedback or to be informed of the forthcoming versions, send an email to Sandrine Pires.

Contact information

Authors:

Last modified on January 6th, 2015 by Sandrine Pires 
For questions and feedback or to be informed of the forthcoming versions, send an email to Sandrine Pires

 

Paper accepted : New inpainting method to handle colored-noise data to test the weak equivalence principle

The context

The MICROSCOPE space mission, launched on April 25, 2016, aims to test the weak equivalence principle (WEP) with a 1015 precision. To reach this performance requires an accurate and robust data analysis method, especially since the possible WEP violation signal will be dominated by a strongly colored noise. An important complication is brought by the fact that some values will be missing –therefore, the measured time series will not be strictly regularly sampled. Those missing values induce a spectral leakage that significantly increases the noise in Fourier space, where the WEP violation signal is looked for, thereby complicating scientific returns.

fig1
FIG. 1 (from Pires et al, 2016): The black curve shows the MICROSCOPE PSD es- timate for a 120 orbits simulation. An example of a possible EPV signal of 3 × 10−15 in the inertial mode is shown by the peak at 1.8 × 10−4 Hz. The grey curve shows the spectral leakage affecting the PSD estimate when gaps are present in the data.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

The results

Recently, we developed an inpainting algorithm to correct the MICROSCOPE data for missing values (in red, fig 4). This code has been integrated in the official MICROSCOPE data processing and analysis pipeline because it enables us to significantly measure an equivalence principle violation (EPV) signal in a model-independent way, in the inertial satellite configuration. In this work, we present several improvements to the method that may allow us now to reach the MICROSCOPE requirements for both inertial and spin satellite configurations (green curve, fig. 4).

 

 

fig4
FIG. 4 (from Pires et al, 2016): MICROSCOPE differential acceleration PSD estimates averaged over 100 simulations in the inertial mode (upper panel) and in the spin mode (lower panel). The black lines show the PSD estimated when all the data is available, the red lines show the PSD estimated from data filled with the inpainting method developed in Paper I and the green lines show the PSD estimated from data filled with the new inpainting method (ICON) presented in this paper.

The code ICON

The code corresponding to the paper is available for download here.

Although, the inpainting method presented in this paper has been optimized to the MICROSCOPE data, it remains sufficiently general to be used in the general context of missing data in time series dominated by an unknown colored-noise.

References

 Dealing with missing data in the MICROSCOPE space mission: An adaptation of inpainting to handle colored-noise data, S. Pires, J. Bergé, Q. Baghi, P. Touboul, G. Métris, accepted in Physical Review D, December 2016

Dealing with missing data: An inpainting application to the MICROSCOPE space mission, J. Bergé, S. Pires, Q. Baghi, P. Touboul, G. Metris, Physical Review D, 92, 11, December 2015 

Dealing with missing data in the MICROSCOPE space mission: An adaptation of inpainting to handle colored-noise data

Authors: S. Pires, B. Joël, Q. Baghi, P. Touboul, G. Metris
Journal: Physical Review D
Year: 2016
Download: ADS | arXiv


Abstract

The MICROSCOPE space mission, launched on April 25, 2016, aims to test the weak equivalence principle (WEP) with a 10-15 precision. Reaching this performance requires an accurate and robust data analysis method, especially since the possible WEP violation signal will be dominated by a strongly colored noise. An important complication is brought by the fact that some values will be missing—therefore, the measured time series will not be strictly regularly sampled. Those missing values induce a spectral leakage that significantly increases the noise in Fourier space, where the WEP violation signal is looked for, thereby complicating scientific returns. Recently, we developed an inpainting algorithm to correct the MICROSCOPE data for missing values. This code has been integrated in the official MICROSCOPE data processing and analysis pipeline because it enables us to significantly measure an equivalence principle violation (EPV) signal in a model-independent way, in the inertial satellite configuration. In this work, we present several improvements to the method that may allow us now to reach the MICROSCOPE requirements for both inertial and spin satellite configurations. The main improvement has been obtained using a prior on the power spectrum of the colored noise that can be directly derived from the incomplete data. We show that after reconstructing missing values with this new algorithm, a least-squares fit may allow us to significantly measure an EPV signal with a 0.96 ×10-15 precision in the inertial mode and 1.20 ×10-15 precision in the spin mode. Although, the inpainting method presented in this paper has been optimized to the MICROSCOPE data, it remains sufficiently general to be used in the general context of missing data in time series dominated by an unknown colored noise. The improved inpainting software, called inpainting for colored-noise dominated signals, is freely available at http://www.cosmostat.org/software/icon.

High Resolution Weak Lensing Mass-Mapping Combining Shear and Flexion

Authors: F. Lanusse, J.-L. Starck, A. Leonard, S. Pires
Journal: A&A
Year: 2016
Download: ADS | arXiv


Abstract

Aims: We propose a new mass mapping algorithm, specifically designed to recover small-scale information from a combination of gravitational shear and flexion. Including flexion allows us to supplement the shear on small scales in order to increase the sensitivity to substructures and the overall resolution of the convergence map without relying on strong lensing constraints.
Methods: To preserve all available small scale information, we avoid any binning of the irregularly sampled input shear and flexion fields and treat the mass mapping problem as a general ill-posed inverse problem, which is regularised using a robust multi-scale wavelet sparsity prior. The resulting algorithm incorporates redshift, reduced shear, and reduced flexion measurements for individual galaxies and is made highly efficient by the use of fast Fourier estimators.
Results: We tested our reconstruction method on a set of realistic weak lensing simulations corresponding to typical HST/ACS cluster observations and demonstrate our ability to recover substructures with the inclusion of flexion, which are otherwise lost if only shear information is used. In particular, we can detect substructures on the 15'' scale well outside of the critical region of the clusters. In addition, flexion also helps to constrain the shape of the central regions of the main dark matter halos.