Name: Time-Domain Cosmology with Strong Gravitational Lensing
Start: 2021-01-25T11:25:00+09:00
End: 2021-02-02T23:59:00+09:00
Location: Online via Zoom & Slack

Time-Domain Cosmology with Strong Gravitational Lensing

from Monday, 25 January 2021 (11:25) to Tuesday, 2 February 2021 (23:59)

Monday, 25 January 2021
22:00 Welcome - Kenneth Wong
Welcome
- Kenneth Wong
22:00 - 22:05
22:05 Cosmology and Stellar Physics with Lensed Supernovae - Sherry Suyu
Cosmology and Stellar Physics with Lensed Supernovae
- Sherry Suyu
22:05 - 22:30
Strongly lensed supernovae (SNe) provide great opportunities for constraining cosmological parameters and SN progenitors. The time delays between the multiple images of a lensed SN allow a measurement of the Hubble constant (H0), which is complementary to lensed-quasar studies. An independent measurement of H0 is important for assessing the current H0 tension and the possible need for new physics. I will present the results of a new program on lensed SNe, including recent developments in the search for these rare events, and new techniques for analyzing such systems for cosmography. The time delays also facilitate early-phase observations of SNe, which are crucial for deciphering SN progenitors. Using various models of SN explosions, I will quantify the impact of microlensing on SN for both progenitor and cosmological studies. I will show the bright prospects of lensed SNe as an independent and competitive probe of cosmology and SN progenitors.
22:30 Lessons learned from iPTF16geu - Ariel Goobar
Lessons learned from iPTF16geu
- Ariel Goobar
22:30 - 22:55
Wide-field time domain surveys are well-suited to find strongly lensed systems, without the need for high spatial resolution, as demonstrated by the discovery of the first multiply-imaged Type Ia supernova, iPTF16geu. Yet, in spite of significant efforts, four years have passed without a sequel. I will summarize the circumstances surrounding the discovery of SN2016geu using the Palomar Transient Facility and the follow-up with HST and ground-based facilities, with focus on the observational challenges.
22:55 Break
Break
22:55 - 23:00
23:00 Lens Searches for transients and variable sources - Anupreeta More
Lens Searches for transients and variable sources
- Anupreeta More
23:00 - 23:25
I will give an overview of systematic lens searches (including machine learning based approaches) being conducted in the ongoing imaging surveys to find transients or variable sources which can allow us to put constraints on cosmological parameters or often times, give insight into the astrophysics. I will also talk about new methods proposed to be used in upcoming surveys such as LSST, their strengths, complementarity and possible directions for improvements.
23:25 Lens searches with Gaia and variability - Cameron Lemon
Lens searches with Gaia and variability
- Cameron Lemon
23:25 - 23:35
Lens searches with Gaia and variability
23:35 Galaxy lens models with offset mass components: implications for time delays and H0. - Liliya Williams
Galaxy lens models with offset mass components: implications for time delays and H0.
- Liliya Williams
23:35 - 00:00
Accurate determination of the Hubble parameter from strong lensing depends critically on the mass model of the lensing galaxy. There is evidence that the commonly used elliptically symmetric lenses may not adequately represent the lens galaxy population. I will discuss the recent modeling of the quad Supernova iPTF16geu. Simple models suffer from a few deficiencies: the center and the position angle of the recovered mass are not the same as those of the observed light, and the density profile required by microlensing considerations is rather shallow. We model the lensing galaxy as a superposition of two mass components; allowing them to be offset from each other by up to 0.25 kpc alleviates most of the problems of simple models, and leads to predictions for microlensing magnification and time delays that differ from those of simple models. I will discuss the implications of two offset components lens modeling for H0 estimation.
Tuesday, 26 January 2021
22:00 Constraining the Hubble constant -- some lessons learnt from using lensing simulations - Dandan Xu
Constraining the Hubble constant -- some lessons learnt from using lensing simulations
- Dandan Xu
22:00 - 22:25
Time-domain lensing observations and modeling have turn out to serve an increasingly important role in providing independent constraints on the Hubble constant and cosmology. A couple of issues regarding the modeling technique remain not entirely clear and many good efforts have been made in order to understand various possible key systematics. In this talk, I will briefly discuss a few interesting and potentially important lessons that we learnt from using lensing simulations.
22:25 Where my DAEMON hides -- one explanation to rule all lens models - Jenny Wagner
Where my DAEMON hides -- one explanation to rule all lens models
- Jenny Wagner
22:25 - 22:35
"A big obstacle to efficiently determine H0 from time-delay cosmography is the lens modelling. When choosing a mass density profile as lens model, we have to select from a multitude of lens model classes and ranges for the model parameter values. A specific choice may bias the confidence bounds on H0 low, a marginalisation over many model classes and parameter ranges is computationally very intensive. As a first step towards one general mass density profile that replaces the heuristically inferred fitting function lens models, I will introduce the ""DArk Emergent Matter halO explanatioN"" (DAEMON) which is able to explain the self-similar dark matter halo morphologies forming under scale-free gravitational interaction. DAEMON thus allows us to base the power-law mass density profiles and composites thereof, like the famous Navarro-Frenk-White profile on sound mathematically and physically fundamental principles. Consequently, choosing and marginalising over classes of lens models can be simplified to reduce computational costs and obtain realistic confidence bounds on H0 at the same time."
22:35 Auto-identification of unphysical source reconstructions in strong lens modelling - Jacob Maresca
Auto-identification of unphysical source reconstructions in strong lens modelling
- Jacob Maresca
22:35 - 22:45
With the advent of next-generation surveys and the expectation of discovering huge numbers of strong gravitational lens systems, much effort is being invested into developing automated procedures for handling the data. The several orders of magnitude increase in the number of strong galaxy-galaxy lens systems is an insurmountable challenge for traditional modelling techniques. Whilst machine learning techniques have dramatically improved the efficiency of lens modelling, parametric modelling of the lens mass profile remains an important tool for dealing with complex lensing systems. In particular, source reconstruction methods are necessary to cope with the irregular structure of high-redshift sources. In this paper, we consider a Convolutional Neural Network (CNN) that analyses the outputs of semi-analytic methods which parametrically model the lens mass and linearly reconstruct the source surface brightness distribution. We show the unphysical source reconstructions that arise as a result of incorrectly initialised lens models can be effectively caught by our CNN. Furthermore, the CNN predictions can be used to automatically re-initialise the parametric lens model, avoiding unphysical source reconstructions. The CNN accurately classifies source reconstructions with a precision P>0.99 and recall R>0.99. Using the CNN predictions to re-initialise the lens modelling procedure, we achieve a 69 per cent decrease in the occurrence of unphysical source reconstructions. This combined CNN and parametric modelling approach can greatly improve the automation of lens modelling.
22:45 Real-time cosmology with lensed repeating Fast Radio Bursts - Adi Zitrin
Real-time cosmology with lensed repeating Fast Radio Bursts
- Adi Zitrin
22:45 - 22:55
Real-time cosmology refers to measuring the evolution of the universe in real time. Given the short human lifetime compared to the age of the universe, measuring such changes is very challenging. Thanks to their short duration and the typical time delays involved, lensed repeating FRBs may offer a unique opportunity to do so. I will review this possibility and discuss its feasibility using existing and upcoming facilities.
22:55 Large-Scale Gravitational Lens Modeling with Bayesian Neural Networks for Accurate and Precise Inference of the Hubble Constant - Ji Won Park
Large-Scale Gravitational Lens Modeling with Bayesian Neural Networks for Accurate and Precise Inference of the Hubble Constant
- Ji Won Park
22:55 - 23:05
We investigate the use of approximate Bayesian neural networks (BNNs) in modeling hundreds of time-delay gravitational lenses for Hubble constant (H0) determination. Our BNN was trained on synthetic HST-quality images of strongly lensed active galactic nuclei (AGN) with lens galaxy light included. The BNN can accurately characterize the posterior PDFs of model parameters governing the elliptical power-law mass profile in an external shear field. We then propagate the BNN-inferred posterior PDFs into ensemble H0 inference, using simulated time delay measurements from a plausible dedicated monitoring campaign. Assuming well-measured time delays and a reasonable set of priors on the environment of the lens, we achieve a median precision of 9.3\% per lens in the inferred H0. A simple combination of 200 test-set lenses results in a precision of 0.5 km s−1 Mpc−1 (0.7%), with no detectable bias in this H0 recovery test. The computation time for the entire pipeline -- including the training set generation, BNN training, and H0 inference -- translates to 9 minutes per lens on average for 200 lenses and converges to 6 minutes per lens as the sample size is increased. Being fully automated and efficient, our pipeline is a promising tool for exploring ensemble-level systematics in lens modeling for H0 inference.
23:05 Break
Break
23:05 - 23:10
23:10 Panel Discussion: Time-Delay Cosmography - Sherry Suyu Liliya Williams Nan Li Tommaso Treu Simon Birrer Dominique Sluse
Panel Discussion: Time-Delay Cosmography
- Sherry Suyu
- Liliya Williams
- Nan Li
- Tommaso Treu
- Simon Birrer
- Dominique Sluse
23:10 - 00:05
Wednesday, 27 January 2021
Thursday, 28 January 2021
Friday, 29 January 2021
Saturday, 30 January 2021
Sunday, 31 January 2021