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When strong gravitational lenses are to be used as an astrophysical or cosmological probe, models of their mass distributions are often needed. We present a new, time-efficient automation code for the uniform modeling of strongly lensed quasars withGLEE, a lens-modeling software for multiband data. By using the observed positions of the lensed quasars and the spatially extended surface brightness distribution of the host galaxy of the lensed quasar, we obtain a model of the mass distribution of the lens galaxy. We applied this uniform modeling pipeline to a sample of nine strongly lensed quasars for which images were obtained with the Wide Field Camera 3 of theHubbleSpace Telescope. The models show well-reconstructed light components and a good alignment between mass and light centroids in most cases. We find that the automated modeling code significantly reduces the input time during the modeling process for the user. The time for preparing the required input files is reduced by a factor of 3 from ~3 h to about one hour. The active input time during the modeling process for the user is reduced by a factor of 10 from ~ 10 h to about one hour per lens system. This automated uniform modeling pipeline can efficiently produce uniform models of extensive lens-system samples that can be used for further cosmological analysis. A blind test that compared our results with those of an independent automated modeling pipeline based on the modeling softwareLenstronomyrevealed important lessons. Quantities such as Einstein radius, astrometry, mass flattening, and position angle are generally robustly determined. Other quantities, such as the radial slope of the mass density profile and predicted time delays, depend crucially on the quality of the data and on the accuracy with which the point spread function is reconstructed. Better data and/or a more detailed analysis are necessary to elevate our automated models to cosmography grade. Nevertheless, our pipeline enables the quick selection of lenses for follow-up and further modeling, which significantly speeds up the construction of cosmography-grade models. This important step forward will help us to take advantage of the increase in the number of lenses that is expected in the coming decade, which is an increase of several orders of magnitude. 

The importance of alternative methods for measuring the Hubble constant, such as time-delay cosmography, is highlighted by the recent Hubble tension. It is paramount to thoroughly investigate and rule out systematic biases in all measurement methods before we can accept new physics as the source of this tension. In this study, we perform a check for systematic biases in the lens modelling procedure of time-delay cosmography by comparing independent and blind time-delay predictions of the system WGD 2038−4008 from two teams using two different software programs:GLEEandLENSTRONOMY. The predicted time delays from the two teams incorporate the stellar kinematics of the deflector and the external convergence from line-of-sight structures. The un-blinded time-delay predictions from the two teams agree within 1.2σ, implying that once the time delay is measured the inferred Hubble constant will also be mutually consistent. However, there is a ∼4σdiscrepancy between the power-law model slope and external shear, which is a significant discrepancy at the level of lens models before the stellar kinematics and the external convergence are incorporated. We identify the difference in the reconstructed point spread function (PSF) to be the source of this discrepancy. When the same reconstructed PSF was used by both teams, we achieved excellent agreement, within ∼0.6σ, indicating that potential systematics stemming from source reconstruction algorithms and investigator choices are well under control. We recommend that future studies supersample the PSF as needed and marginalize over multiple algorithms or realizations for the PSF reconstruction to mitigate the systematics associated with the PSF. A future study will measure the time delays of the system WGD 2038−4008 and infer the Hubble constant based on our mass models. 

Abstract A bright (m_F150W,AB= 24 mag),z= 1.95 supernova (SN) candidate was discovered in JWST/NIRCam imaging acquired on 2023 November 17. The SN is quintuply imaged as a result of strong gravitational lensing by a foreground galaxy cluster, detected in three locations, and remarkably is the second lensed SN found in the same host galaxy. The previous lensed SN was called “Requiem,” and therefore the new SN is named “Encore.” This makes the MACS J0138.0−2155 cluster the first known system to produce more than one multiply imaged SN. Moreover, both SN Requiem and SN Encore are Type Ia SNe (SNe Ia), making this the most distant case of a galaxy hosting two SNe Ia. Using parametric host fitting, we determine the probability of detecting two SNe Ia in this host galaxy over a ∼10 yr window to be ≈3%. These observations have the potential to yield a Hubble constant (H₀) measurement with ∼10% precision, only the third lensed SN capable of such a result, using the three visible images of the SN. Both SN Requiem and SN Encore have a fourth image that is expected to appear within a few years of ∼2030, providing an unprecedented baseline for time-delay cosmography. 

Abstract Supernova (SN) SN H0pe is a gravitationally lensed, triply imaged, Type Ia SN (SN Ia) discovered in James Webb Space Telescope imaging of the PLCK G165.7+67.0 cluster of galaxies. Well-observed multiply imaged SNe provide a rare opportunity to constrain the Hubble constant (H₀), by measuring the relative time delay between the images and modeling the foreground mass distribution. SN H0pe is located atz= 1.783 and is the first SN Ia with sufficient light-curve sampling and long enough time delays for anH₀inference. Here we present photometric time-delay measurements and SN properties of SN H0pe. Using JWST/NIRCam photometry, we measure time delays of Δt_ab= $-{116.6}_{-9.3}^{+10.8}$observer-frame days and Δt_cb= $-{48.6}_{-4.0}^{+3.6}$observer-frame days relative to the last image to arrive (image 2b; all uncertainties are 1σ), which corresponds to a ∼5.6% uncertainty contribution forH₀assuming 70 km s⁻¹Mpc⁻¹. We also constrain the absolute magnification of each image toμ_a= ${4.3}_{-1.8}^{+1.6}$,μ_b= ${7.6}_{-2.6}^{+3.6}$,μ_c= ${6.4}_{-1.5}^{+1.6}$by comparing the observed peak near-IR magnitude of SN H0pe to the nonlensed population of SNe Ia. 

ABSTRACT SN 2018hti was a very nearby (z = 0.0614) superluminous supernova with an exceedingly bright absolute magnitude of −21.7 mag in r band at maximum. The densely sampled pre-maximum light curves of SN 2018hti show a slow luminosity evolution and constrain the rise time to ∼50 rest-frame d. We fitted synthetic light curves to the photometry to infer the physical parameters of the explosion of SN 2018hti for both the magnetar and the CSM-interaction scenarios. We conclude that one of two mechanisms could be powering the luminosity of SN 2018hti; interaction with ∼10 M⊙ of circumstellar material or a magnetar with a magnetic field of Bp∼ 1.3 × 1013 G, and initial period of Pspin∼ 1.8 ms. From the nebular spectrum modelling we infer that SN 2018hti likely results from the explosion of a $${\sim}40\, \mathrm{M}_\odot$$ progenitor star. 

ABSTRACT Gravitational time delays provide a powerful one-step measurement of H0, independent of all other probes. One key ingredient in time-delay cosmography are high-accuracy lens models. Those are currently expensive to obtain, both, in terms of computing and investigator time (105–106 CPU hours and ∼0.5–1 yr, respectively). Major improvements in modelling speed are therefore necessary to exploit the large number of lenses that are forecast to be discovered over the current decade. In order to bypass this roadblock, we develop an automated modelling pipeline and apply it to a sample of 31 lens systems, observed by the Hubble Space Telescope in multiple bands. Our automated pipeline can derive models for 30/31 lenses with few hours of human time and <100 CPU hours of computing time for a typical system. For each lens, we provide measurements of key parameters and predictions of magnification as well as time delays for the multiple images. We characterize the cosmography-readiness of our models using the stability of differences in the Fermat potential (proportional to time delay) with respect to modelling choices. We find that for 10/30 lenses, our models are cosmography or nearly cosmography grade (<3 per cent and 3–5 per cent variations). For 6/30 lenses, the models are close to cosmography grade (5–10 per cent). These results utilize informative priors and will need to be confirmed by further analysis. However, they are also likely to improve by extending the pipeline modelling sequence and options. In conclusion, we show that uniform cosmography grade modelling of large strong lens samples is within reach.