The next biannual meeting of the Rubin-LSST France community will be held 10-12 June 2024, at Hexagone on the Luminy campus near CPPM in Marseille.
The meeting will take place in the Hexagone on the Luminy Campus. The address is 172 Av. de Luminy, 13009 Marseille, France
If you arrive early or leave late, you can grab a sandwich at the hexagone’s cafeteria and do a quick hike to the calanques: for instance going to Beleverdère de Sugiton in ~30 minutes. With 30 more minutes you can go down to the sea in Sugiton.
The agendas of the most recent editions of this meeting can be found online:
I will present some results from the Euclid Early Release Observations obtained in the field of the lensing cluster A2390 in order to highlight the merits of model photometry and morphometry using SourceXtractor++ code.
In this presentation, we will describe how to access Rubin data using the Rubin Science Platform (RSP). We will cover the general features of the RSP: the notebook aspect for the interactive analysis and the portal aspect to inspect catalogs and images.
Finally, we will describe the different data accessible through three different instances of the RSP (USDF, CC-IN2P3 and IDF).
In this talk, I will describe the most recent updates from the Fink broker, describe the recent developments following the Fink-Brazil Workshop and highlight the actions done towards preparing Fink for the arrival of LSST data.
Introduction of the French involvement in the DESC official project aiming at connecting observable properties of stellar streams observed with Rubin/LSST to dark matter constraints. Presentation of the analysis preparation examining the impact of dark matter subhalos with masses ranging from $10^6$ to $10^8$ solar masses on simulated stellar streams
This presentation will summarize a work recently achieved in DESC about the design of a cohesive DDF strategy fulfilling requirements from PZ, WL, SNe Ia and accounting for the SCOC recommendations.
Orphan gamma-ray burst afterglows are good candidates to learn more about the GRB physics and progenitors or for the development of multi-messenger analysis with gravitational waves. Our objective is to identify orphan afterglows in Rubin LSST data, by using the characteristic features of their light curves. We present here the performance of our machine learning filter as implemented in the Fink broker and tested on the ELAsTiCC data set and our own simulations of orphan afterglows.
Accurate cluster mass estimates are vital for constraining cosmology with galaxy cluster abundance, one of the primary cosmological probes on LSST. We present here the second version of the Cluster Mass Modeling (CLMM) library, developed for the Dark Energy Science Collaboration (DESC), for calibrating cluster masses based on the weak lensing signal of background galaxies. This library is being developed by a large group of young career scientists with complete documentation and automatic testing, which makes the assumption of the computations transparent and the results reproducible. The new version of CLMM includes the functions for stacking clusters and more flexibility for different formats of photometric redshift inputs besides further implementations on the theoretical modeling and data operations.
Photo-z’s are a key component for some of the current DESC cluster finders, AMICO and WaZP. In this talk we discuss the effect of photo-z performance on WaZP cluster detection using the new TPZ produced photo-z catalog. We also explore the possibility of optimizing the photo-z training set towards “cluster-focused” samples.
Galaxy clusters serve as powerful probes for cosmological models. Upcoming large-scale optical and infrared surveys will reach unprecedented depths across extensive areas, necessitating highly complete and pure cluster catalogs with well-defined selection functions. We have developed a novel cluster detection algorithm called YOLO-CL. This algorithm is a modified version of the state-of-the-art object detection deep convolutional network YOLO, specifically optimized for galaxy cluster detection (Grishin, Mei, Ilic 2023). It has been adapted to the datasets from the forthcoming LSST by training on a combined sample of observed SDSS clusters and simulated galaxy cluster images from the DESC Data Challenge 2 (DESC DC2).
The YOLO-CL cluster catalog achieves 100% and 94% completeness for halo masses $M_{200c} > 10^{14.6} M_{\odot}$ at $0.2 < z < 0.8$, and $M_{200c} > 10^{14} M_{\odot}$ with redshifts $z \lesssim 1$, respectively, with only a 6% false positive rate. Additionally, we found that the YOLO-CL selection function is nearly flat with respect to halo mass within the range $0.2 \lesssim z \lesssim 0.9$. Our paper detailing the performance of YOLO-CL on DESC DC2 simulated images (Grishin, Mei, Ilic, Aguena, Boutigny et al.) has been submitted for internal review within the DESC collaboration.
We will present the Rubin Galaxies Science Collaboration, show recent activities and results and explain how to apply for membership.
The M1M3 glass mirror is now on site and has been installed on its cell and coated. Before installing the M1M3 glass mirror on the Rubin telescope, we proceeded to confirm the safety of the glass using a surrogate mirror on the telescope mount, and to verify accordance with specifications. Designed to be used for tests, the surrogate has similar mechanical properties as the glass mirror, such as mass, centre of gravity, and geometry.
The M1M3 steel surrogate was installed on the cell and on the telescope mount (TMA) in May 2023. The cell was fully equipped with the force actuators, hardpoints and various monitoring sensors. An extensive dynamic testing campaign took place until February 2024, when the surrogate and cell were dismounted from the TMA for the reception of the M1M3 glass mirror.
The test campaign was configured to validate the safe and dynamic telescope capabilities.
We also checked the position repeatability before and after a slew for different azimuth, elevation and speeds. We also investigated possible M1M3 surrogate vibrations due to the Fan Coil Units (FCU), which could have an impact on image quality.
Analysis was done on data taken during this period with dedicated dynamic tests. However, more data will be needed for the vibration analysis.
Results show that the position repeatability is almost within specifications, and that vibrations due to FCUs can be neglected.
I'll present results of the analysis of narrow beam electro-optical tests for the alignment of the camera optics.
I will present the continuation of our work on photometric redshifts using templates derived from observed spectra, extended using Stellar Population Synthesis methods.
The prospects of this work - and potential for improvement - for future studies will be presented and discussed during the talk.
Our main goal is to provide with new cosmic shear and LSS simulations that can be used for the analysis of LSST Y1 data with Higher-Order Statistics. In this presentation, we make an update on the status of the project.
A series of recent works has highlighted the potential of so-called full-field cosmological inference for the analysis of upcoming weak lensing and galaxy clustering surveys, with the promise of being able to access the non-gaussian information contained in the data. However, these approaches require a differentiable forward model of the large scale structure, which currently constitutes one of the main bottlenecks, as none of the publicly available differentiable N-body codes support large-scale distribution necessary for large cosmological volumes.
To address this, we introduce JAXPM, a JAX-powered library that facilitates multi-GPU and multi-node Particle-Mesh N-body simulations. Leveraging the capabilities of a low-level CUDA distributed computing library, JaxPM allows for the first time the simulation of the entire cosmological volume observed by LSST down to Mpc resolution with an automatically differentiable simulation code.
We will present our early scaling tests of this approach on the Jean-Zay GPU supercomputer.
The presence of bright objects, notably stars, represents a significant challenge in extracting valuable insights from LSST data. Bright objects will cause the saturation of LSST’s sensors and will bias both object detection and flux measurement in a radius which depends on the magnitude. The creation of masks to cover the most affected regions by bright stars is necessary but challenging due to the difficulty in identifying and characterizing those objects. Our work is based on the HSC-SSP method and is applied to the DC2 object catalog. The resulting masks cover about two percent of the DC2 footprint. The impact of these masks is currently being studied in DESC in the context of galaxy cluster detection algorithms such as AMICO and redMaPPer.