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Frédéric Courbin

Publications and source records attributed to Frédéric Courbin.

33 records · Page 2Linked to original sources
arXiv2023

Nine lensed quasars and quasar pairs discovered through spatially-extended variability in Pan-STARRS

We present the proof-of-concept of a method to find strongly lensed quasars using their spatially-extended photometric variability through difference imaging in cadenced imaging survey data. We apply the method to Pan-STARRS, starting with an initial selection of 14 107 Gaia multiplets with quasar-like infrared colours from WISE. We identify 229 candidates showing notable spatially-extended variability during the Pan-STARRS survey period. These include 20 known lenses, alongside an additional 12 promising candidates for which we obtain long-slit spectroscopy follow-up. This process results in the confirmation of four doubly lensed quasars, four unclassified quasar pairs and one projected quasar pair. Only three are pairs of stars or quasar+star projections, the false positive rate is thereby 25%. The lenses have separations between 0.81" and 1.24" and source redshifts between z = 1.47 and z = 2.46. Three of the unclassified quasar pairs are promising dual quasars candidates with separations ranging from 6.6 to 9.3 kpc. We expect that this technique will be a particularly efficient way to select lensed variables in the upcoming Rubin-LSST, which will be crucial given the expected limitations for spectroscopic follow-up

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arXiv2023

STARRED: a two-channel deconvolution method with Starlet regularization

The spatial resolution of astronomical images is limited by atmospheric turbulence and diffraction in the telescope optics, resulting in blurred images. This makes it difficult to accurately measure the brightness of blended objects because the contributions from adjacent objects are mixed in a time-variable manner due to changes in the atmospheric conditions. However, this effect can be corrected by characterizing the Point Spread Function (PSF), which describes how a point source is blurred on a detector. This function can be estimated from the stars in the field of view, which provides a natural sampling of the PSF across the entire field of view. Once the PSF is estimated, it can be removed from the data through the so-called deconvolution process, leading to images of improved spatial resolution. The deconvolution operation is an ill-posed inverse problem due to noise and pixelization of the data. To solve this problem, regularization is necessary to guarantee the robustness of the solution. Regularization can take the form of a sparse prior, meaning that the recovered solution can be represented with only a few basis eigenvectors. STARRED is a Python package developed in the context of the COSMOGRAIL collaboration and applies to a vast variety of astronomical problems. It proposes to use an isotropic wavelet basis, called Starlets, to regularize the solution of the deconvolution problem. This family of wavelets has been shown to be well-suited to represent astronomical objects. STARRED provides two modules to first reconstruct the PSF, and then perform the deconvolution. It is based on two key concepts: i) the image is reconstructed in two separate channels, one for the point sources and one for the extended sources, and ii) the code relies on the deliberate choice of not completely removing the effect of the PSF, but rather bringing the image to a higher resolution.

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arXiv2023

The impact of human expert visual inspection on the discovery of strong gravitational lenses

We investigate the ability of human 'expert' classifiers to identify strong gravitational lens candidates in Dark Energy Survey like imaging. We recruited a total of 55 people that completed more than 25$\%$ of the project. During the classification task, we present to the participants 1489 images. The sample contains a variety of data including lens simulations, real lenses, non-lens examples, and unlabeled data. We find that experts are extremely good at finding bright, well-resolved Einstein rings, whilst arcs with $g$-band signal-to-noise less than $\sim$25 or Einstein radii less than $\sim$1.2 times the seeing are rarely recovered. Very few non-lenses are scored highly. There is substantial variation in the performance of individual classifiers, but they do not appear to depend on the classifier's experience, confidence or academic position. These variations can be mitigated with a team of 6 or more independent classifiers. Our results give confidence that humans are a reliable pruning step for lens candidates, providing pure and quantifiably complete samples for follow-up studies.

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arXiv2022

Using wavelets to capture deviations from smoothness in galaxy-scale strong lenses

Modeling the mass distribution of galaxy-scale strong gravitational lenses is a task of increasing difficulty. The high-resolution and depth of imaging data now available render simple analytical forms ineffective at capturing lens structures spanning a large range in spatial scale, mass scale, and morphology. In this work, we address the problem with a novel multiscale method based on wavelets. We tested our method on simulated Hubble Space Telescope (HST) imaging data of strong lenses containing the following different types of mass substructures making them deviate from smooth models: (1) a localized small dark matter subhalo, (2) a Gaussian random field (GRF) that mimics a nonlocalized population of subhalos along the line of sight, and (3) galaxy-scale multipoles that break elliptical symmetry. We show that wavelets are able to recover all of these structures accurately. This is made technically possible by using gradient-informed optimization based on automatic differentiation over thousands of parameters, which also allow us to sample the posterior distributions of all model parameters simultaneously. By construction, our method merges the two main modeling paradigms - analytical and pixelated - with machine-learning optimization techniques into a single modular framework. It is also well-suited for the fast modeling of large samples of lenses. All methods presented here are publicly available in our new Herculens package.

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arXiv2022

Deep Learning-based galaxy image deconvolution

With the onset of large-scale astronomical surveys capturing millions of images, there is an increasing need to develop fast and accurate deconvolution algorithms that generalize well to different images. A powerful and accessible deconvolution method would allow for the reconstruction of a cleaner estimation of the sky. The deconvolved images would be helpful to perform photometric measurements to help make progress in the fields of galaxy formation and evolution. We propose a new deconvolution method based on the Learnlet transform. Eventually, we investigate and compare the performance of different Unet architectures and Learnlet for image deconvolution in the astrophysical domain by following a two-step approach: a Tikhonov deconvolution with a closed-form solution, followed by post-processing with a neural network. To generate our training dataset, we extract HST cutouts from the CANDELS survey in the F606W filter (V-band) and corrupt these images to simulate their blurred-noisy versions. Our numerical results based on these simulations show a detailed comparison between the considered methods for different noise levels.

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arXiv2022

Rubin-Euclid Derived Data Products: Initial Recommendations

This report is the result of a joint discussion between the Rubin and Euclid scientific communities. The work presented in this report was focused on designing and recommending an initial set of Derived Data products (DDPs) that could realize the science goals enabled by joint processing. All interested Rubin and Euclid data rights holders were invited to contribute via an online discussion forum and a series of virtual meetings. Strong interest in enhancing science with joint DDPs emerged from across a wide range of astrophysical domains: Solar System, the Galaxy, the Local Volume, from the nearby to the primaeval Universe, and cosmology.

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arXiv2022

Snowmass2021 Cosmic Frontier CF6 White Paper: Multi-Experiment Probes for Dark Energy -- Transients

This invited Snowmass 2021 White Paper highlights the power of joint-analysis of astronomical transients in advancing HEP Science and presents research activities that can realize the opportunities that come with current and upcoming projects. Transients of interest include gravitational wave events, neutrino events, strongly-lensed quasars and supernovae, and Type~Ia supernovae specifically. These transients can serve as probes of cosmological distances in the Universe and as cosmic laboratories of extreme strong-gravity, high-energy physics. Joint analysis refers to work that requires significant coordination from multiple experiments or facilities so encompasses Multi-Messenger Astronomy and optical transient discovery and distributed follow-up programs.

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arXiv2021

Faint objects in motion: the new frontier of high precision astrometry

Sky survey telescopes and powerful targeted telescopes play complementary roles in astronomy. In order to investigate the nature and characteristics of the motions of very faint objects, a flexibly-pointed instrument capable of high astrometric accuracy is an ideal complement to current astrometric surveys and a unique tool for precision astrophysics. Such a space-based mission will push the frontier of precision astrometry from evidence of Earth-mass habitable worlds around the nearest stars, to distant Milky Way objects, and out to the Local Group of galaxies. As we enter the era of the James Webb Space Telescope and the new ground-based, adaptive-optics-enabled giant telescopes, by obtaining these high precision measurements on key objects that Gaia could not reach, a mission that focuses on high precision astrometry science can consolidate our theoretical understanding of the local Universe, enable extrapolation of physical processes to remote redshifts, and derive a much more consistent picture of cosmological evolution and the likely fate of our cosmos. Already several missions have been proposed to address the science case of faint objects in motion using high precision astrometry missions: NEAT proposed for the ESA M3 opportunity, micro-NEAT for the S1 opportunity, and Theia for the M4 and M5 opportunities. Additional new mission configurations adapted with technological innovations could be envisioned to pursue accurate measurements of these extremely small motions. The goal of this White Paper is to address the fundamental science questions that are at stake when we focus on the motions of faint sky objects and to briefly review instrumentation and mission profiles.

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arXiv2020

Cosmic dissonance: new physics or systematics behind a short sound horizon?

Persistent tension between low-redshift observations and the Cosmic Microwave Background radiation (CMB), in terms of two fundamental distance scales set by the sound horizon $r_d$ and the Hubble constant $H_0$, suggests new physics beyond the Standard Model or residual systematics. We examine recently updated distance calibrations from Cepheids, gravitational lensing time-delay observations, and the Tip of the Red Giant Branch. Calibrating the Baryon Acoustic Oscillations (BAO) and Type Ia supernovae with combinations of the distance indicators, we obtain a joint and self-consistent measurement of $H_0$ and $r_d$ at low redshift, independent of cosmological models and CMB inference. In an attempt to alleviate the tension between late-time and CMB-based measurements, we consider four extensions of the standard $Λ$CDM model. The sound horizon from our different measurements is $r_d=(137\pm3^{stat.}\pm2^{syst.})$~Mpc. Depending on the adopted distance indicators, the $combined$ tension in $H_0$ and $r_d$ ranges between 2.3 and 5.1 $σ$. We find that modifications of $Λ$CDM that change the physics after recombination fail to solve the problem, for the reason that they only resolve the tension in $H_0$, while the tension in $r_d$ remains unchanged. Pre-recombination extensions (with early dark energy or the effective number of neutrinos $\rm{N}_{\rm{eff}}=3.24 \pm 0.16$) are allowed by the data, unless the calibration from Cepheids is included. Results from time-delay lenses are consistent with those from distance-ladder calibrations and point to a discrepancy between absolute distance scales measured from the CMB (assuming the standard cosmological model) and late-time observations. New proposals to resolve this tension should be examined with respect to reconciling not only the Hubble constant but also the sound horizon derived from the CMB and other cosmological probes.

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arXiv2019

Quasi-Stellar Objects acting as potential Strong Gravitational Lenses in the SDSS-III BOSS survey

We present a sample of 12 Quasi-Stellar Objects (QSOs) potentially acting as strong gravitational lenses on background Emission Line Galaxies (ELG) or Lyman-$α$ Emitters (LAEs) selected selected through a systematic search of the 297301 QSOs in the Sloan Digital Sky Survey (SDSS)-III Data Release 12. Candidates are identified by looking for compound spectra, where emission lines at a redshift larger than that of the quasar can be identified in the residuals after a QSO spectral template is subtracted from the observed spectra. The narrow diameter of BOSS fibers (2") then ensures that the object responsible for the additional emission lines must lie close to the line of sight of the QSO and hence provides a high probability of lensing. Among the 12 candidates identified, 9 have definite evidence for the presence of a background ELG identified by at least 4 higher-redshift nebular emission lines. The remaining $3$ probable candidates present a strong asymmetrical emission line attributed to a background Lyman-$α$ emitter (LAE). The QSO-ELG (QSO-LAE) lens candidates have QSO lens redshifts in the range $0.24\lesssim z_{QSO} \lesssim 0.66$ ($0.75 \lesssim z_{QSO} \lesssim 1.23$ ) and background galaxy redshifts in the range $0.48 \lesssim z_{S,ELG} \lesssim 0.94$ ($2.17 \lesssim z_{S,LAE} \lesssim 4.48$). We show that the algorithmic search is complete at >90% for QSO-ELG systems, whereas it falls at 40-60% for QSO-LAE, depending on the redshift of the source. Upon confirmation of the lensing nature of the systems, this sample may quadruple the number of known QSOs acting as strong lenses. We have determined the completeness of our search, which allows future studies to compute lensing probabilities of galaxies by QSOs and differentiate between different QSO models. (Abridged)

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arXiv2019

Weak-lensing shear measurement with machine learning: teaching artificial neural networks about feature noise

Cosmic shear is a primary cosmological probe for several present and upcoming surveys investigating dark matter and dark energy, such as Euclid or WFIRST. The probe requires an extremely accurate measurement of the shapes of millions of galaxies based on imaging data. Crucially, the shear measurement must address and compensate for a range of interwoven nuisance effects related to the instrument optics and detector, noise, unknown galaxy morphologies, colors, blending of sources, and selection effects. This paper explores the use of supervised machine learning (ML) as a tool to solve this inverse problem. We present a simple architecture that learns to regress shear point estimates and weights via shallow artificial neural networks. The networks are trained on simulations of the forward observing process, and take combinations of moments of the galaxy images as inputs. A challenging peculiarity of this ML application is the combination of the noisiness of the input features and the requirements on the accuracy of the inverse regression. To address this issue, the proposed training algorithm minimizes bias over multiple realizations of individual source galaxies, reducing the sensitivity to properties of the overall sample of source galaxies. Importantly, an observational selection function of these source galaxies can be straightforwardly taken into account via the weights. We first introduce key aspects of our approach using toy-model simulations, and then demonstrate its potential on images mimicking Euclid data. Finally, we analyze images from the GREAT3 challenge, obtaining competitively low shear biases despite the use of a simple training set. We conclude that the further development of ML approaches is of high interest to meet the stringent requirements on the shear measurement in current and future surveys. A demonstration implementation of our technique is publicly available.

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arXiv2018

Cosmological distance indicators

We review three distance measurement techniques beyond the local universe: (1) gravitational lens time delays, (2) baryon acoustic oscillation (BAO), and (3) HI intensity mapping. We describe the principles and theory behind each method, the ingredients needed for measuring such distances, the current observational results, and future prospects. Time delays from strongly lensed quasars currently provide constraints on $H_0$ with < 4% uncertainty, and with 1% within reach from ongoing surveys and efforts. Recent exciting discoveries of strongly lensed supernovae hold great promise for time-delay cosmography. BAO features have been detected in redshift surveys up to z <~ 0.8 with galaxies and z ~ 2 with Ly-$α$ forest, providing precise distance measurements and $H_0$ with < 2% uncertainty in flat $Λ$CDM. Future BAO surveys will probe the distance scale with percent-level precision. HI intensity mapping has great potential to map BAO distances at z ~ 0.8 and beyond with precisions of a few percent. The next years ahead will be exciting as various cosmological probes reach 1% uncertainty in determining $H_0$, to assess the current tension in $H_0$ measurements that could indicate new physics.

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arXiv2017

Proximity Operators for Phase Retrieval

We present a new formulation of a family of proximity operators that generalize the projector step for phase retrieval. These proximity operators for noisy intensity measurements can replace the classical "noise free" projection in any projection-based algorithm. They are derived from a maximum likelihood formulation and admit closed form solutions for both the Gaussian and the Poisson cases. In addition, we extend these proximity operators to undersampled intensity measurements. To assess their performance, these operators are exploited in a classical Gerchberg Saxton algorithm. We present numerical experiments showing that the reconstructed complex amplitudes with these proximity operators perform always better than using the classical intensity projector while their computational overhead is moderate.

astro-ph.IM↗
arXiv2017

A test for skewed distributions of dark matter and a possible detection in galaxy cluster Abell 3827

Simulations of self-interacting dark matter (SIDM) predict that dark matter should lag behind galaxies during a collision. If the interaction is mediated by a high-mass force carrier, the distribution of dark matter can also develop asymmetric dark matter tails. To search for this asymmetry, we compute the gravitational lensing properties of a mass distribution with a free {\em skewness} parameter. We apply this to the dark matter around the four central galaxies in cluster Abell~3827. In the galaxy whose dark matter peak has previously been found to be offset, we tentatively measure a skewness $s=0.23^{+0.05}_{-0.22}$ in the same direction as the peak offset. Our method may be useful in future gravitational lensing analyses of colliding galaxy clusters and merging galaxies.

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