Lensed stars in galaxy-galaxy strong lensing -- a JWST prediction for the Cosmic Horseshoe

TL;DR

This work predicts that JWST can detect numerous lensed star transients in the galaxy-galaxy strong lensing system Cosmic Horseshoe ($z=2.381$), driven by an exceptionally high recent star-formation rate and a well-constrained lens model. By deriving a delensed stellar luminosity function from HST data via non-parametric SFH fitting and folding it through microlensing magnification distributions from the M25 GGSL model, the authors estimate per-filter transient detection rates across the arc, finding up to about 60–110 transients per JWST pointing at a $5\sigma$ depth of $m_{AB}\sim29$ mag (varied by filter). The results indicate that the Cosmic Horseshoe is an excellent laboratory for testing dark matter scenarios (e.g., ultra-light axions) through the spatial distribution and width of transients along the critical curve, and for constraining the high-mass end of the stellar IMF during the cosmic noon. The study also discusses archival searches, uncertainties (lensing magnification, microlensing, SFH), and extensions to other GGSL systems with implications for future JWST campaigns and synergy with Euclid/LSST surveys.

Abstract

We explore for the first time the possibility of detecting lensed star transients in galaxy-galaxy strong lensing systems upon repeated, deep imaging using the {\it James-Webb Space Telescope} ({\it JWST}). Our calculation predicts that the extremely high recent star formation rate of $\sim 100\,M_{\odot}\textrm{yr}^{-1}$ over the last 50 Myr (not accounting for image multiplicity) in the ``Cosmic Horseshoe'' lensed system ($z = 2.381$) generates many young, bright stars, of which their large abundance is expected to lead to a detection rate of $\sim 60$ transients per pointing in {\it JWST} observations with a $5σ$ limiting magnitude of $\sim 29\,m_{AB}$. With the high expected detection rate and little room for uncertainty for the lens model compared with cluster lenses, our result suggests that the Cosmic Horseshoe could be an excellent tool to test the nature of Dark Matter based on the spatial distribution of transients, and can be used to constrain axion mass if Dark Matter is constituted of ultra-light axions. We also argue that the large distance modulus of $\sim46.5\,$mag at $z \approx 2.4$ can act as a filter to screen out less massive stars as transients and allow one to better constrain the high-mass end of the stellar initial mass function based on the transient detection rate. Follow-up {\it JWST} observations of the Cosmic Horseshoe with would allow one to better probe the nature of Dark Matter and the star formation properties, such as the initial mass function at the cosmic noon, via lensed star transients.

Figures (13)

• Figure 1: RGB composite image of the Cosmic Horseshoe, featuring F814W in the R channel; F606W in the G channel; and F475W in the B channel. On the left, we show the entire lensing system, overlaid with the critical curve predicted by the M25 lens model in red. On the right, we show the same RGB image, but with everything except the arc itself masked out. This is the region where we consider the arc, and predict the transient detection rate upon. The image is oriented North-up and East-right.
• Figure 2: Spectral energy distribution (SED) of the Cosmic Horseshoe, after correcting for lensing magnification as predicted by M25. We used Bagpipes to fit a non-parametric star formation history to the observed SED, whereas the best-fitting photometry and best-fitting spectrum are shown as black dots and gray curve, respectively. Notice that the error bars are very small except in F275W, where they are not clearly visible in the SED.
• Figure 3: Inferred star formation history for the Cosmic Horseshoe, based on the SED fitting as shown earlier in Figure \ref{['fig: SED']}. The mean star formation rate over the last $\sim 50\,$Myr is estimated at $\sim 140 M_{\odot}\textrm{yr}^{-1}$. The shaded regions overlaying the three age bins (which are too small to be shown clearly in the first two bins) represent the $\pm 1\sigma$ uncertainty of the star formation rate inferred from Bagpipes's Markov-Chain Monte-Carlo sampling. The best-fitting parameters and the associated uncertainties are shown in Table \ref{['tab: SED']}.
• Figure 4: Simulated stellar luminosity function of the Cosmic Horseshoe at eight selected JWST filters (with different colours) based on the star formation history shown in Figure \ref{['fig: SFH']}, as inferred from the SED fitting shown in Figure \ref{['fig: SED']}. The uncertainties are propagated from the SED fitting, as well as from the sampling uncertainty during the 30 realizations of stellar population synthesis via SPISEA. The fluctuation in the sLF is owing to the intrinsic variation in stellar evolution, as described by the isochrones. We only show those with absolute magnitude brighter than $-7.5$, as stars dimmer than this limit would never be detected, limited by the maximum lensing magnification they can attain.
• Figure 5: Predicted tangential magnification (left), radial magnification (middle), and stellar surface mass density (right) from the M25 lens model.