UV slopes of Starforming Galaxies in Strong Lensing fields at the Epoch of Reionization with JWST

Abstract

UV slopes ($β$) are a powerful diagnostics for galaxies at the Epoch of Reionization, tracing star formation, ISM ionization, and the escape fraction $f_{esc}$ of ionizing photons. Studies at low and intermediate z find a gradual $β$ reddening with time and steeper slopes for fainter galaxies, however recent JWST studies reveal a flattening of this trend at $z>7$. We want measure $β$ for galaxies at $z>7.5$ using the strong lensing around massive galaxy clusters to observe high-redshift and faint galaxies. The low-brightness regime is of particular interest for reionization, as most of the recent models of this process posit that numerous faint galaxies are the prime drivers of reionization. We use NIRCam and NIRSpec data from CANUCS, Technicolor, JUMPS, Silver Bullet, UNCOVER and MEGASCIENCE across 7 strong lensing fields. We find galaxies down to $M_{UV}\sim-16$ and 7.5<z<12.5. We measure \b{eta} with a forward-modelling procedure and estimate $f_{esc}$ for a subsample with emission line data using a relation, calibrated from a low-z sample, with UV slope, galaxy size and H$β$ equivalent width. We find 378 galaxies (45 with spectrum), yielding average values $β=-2.3\pm0.4$, $z=8.5\pm1.0$, and $M_{UV}=-18\pm1$. We find no significant $β$ evolution across our redshift range, suggesting a flattening of the $β-z$ trend above $z\sim7.5$. We find a weak negative trend between $β$ and $M_{UV}$. For 14 galaxies we estimate an average $f_{esc}=0.26\pm0.22$. The flat trend of $β$ at $z>7.5$ suggests similar properties between $300$ and $600 Myr$ after the Big Bang. The weak trend between $β$ and $M_{UV}$ suggests an analogous composition for low- and high-mass galaxies' ISM, likely due to a lack of time for dust buildup. While average $f_{esc}$ is higher than necessary to ionize the IGM by z~6, the model extrapolated at low-z may overestimate its value.

Figures (6)

• Figure 1: Top panel: NIRCam and ACS images of an example object (CANUCS ID 4117358) in the MACS1423 cluster in the CLU pointing, in all of the filters available for this pointing. Middle: NIRCam photometry overlaid with the throughput of each NIRCam filter, with the fitted $\beta$ slope in yellow. The JWST filters' throughput functions are also overlaid in different colours. Vertical dashed (dotted) lines represent the lower (upper) limit for the filters to be used. A hard limit for the lower wavelength threshold, and a soft limit, only limiting the filter's pivot wavelength, for the upper threshold, were applied; in this case, the F150W, F200W and F277W filters were used to fit the UV slope. Bottom panel: 2D and 1D spectrum for the same object. In the 1D spectrum, the gray line represents the signal, while the red line represents the noise at each wavelength of the spectrum.
• Figure 2: Example of a galaxy at $z=7.87$ from the NCF pointing of the MACS0416 field, whose $\beta$ was calculated from 8 NIRCam filters: F140M, F150W, F162M, F182M, F200W, F210M, and F250M
• Figure 3: Main: Comparison between photometric and spectroscopic values for the UV slope's $\beta$ index, for 14 galaxies in our sample; the dashed blue line represents $\beta_{phot}=\beta_{spec}$.
• Figure 4: $\beta-z$ diagram for our high-redshift sample. Objects for which only photometric estimates of $\beta$ are available are plotted in blue, and spectral estimates of $\beta$ are in orange; for objects that have both we only plot spectral estimates. A linear fit of the trend and its shaded 1-$\sigma$ confidence level, obtained via a bootstrap method, is also represented.
• Figure 5: $\beta$-$M_{UV}$ diagram, color code is the same as in \ref{['fig:beta-z']}. The green dashed line represents the relationship found between $\beta$ and $M_{UV}$ for the whole sample, with the green shaded region representing a 1-$\sigma$ confidence band. Plot points representing galaxies in the UNCOVER sample are reported with blue diamonds, as we calculated their $M_{UV}$ with a different process with respect to the CANUCS clusters.