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Dust grains absorb half of the radiation emitted by stars throughout the history of the universe, re-emitting this energy at infrared wavelengths. Polycyclic aromatic hydrocarbons (PAHs) are large organic molecules that trace millimeter-size dust grains and regulate the cooling of the interstellar gas within galaxies. Observations of PAH features in very distant galaxies have been difficult due to the limited sensitivity and wavelength coverage of previous infrared telescopes. Here we present JWST observations that detect the 3.3um PAH feature in a galaxy observed less than 1.5 billion years after the Big Bang. The high equivalent width of the PAH feature indicates that star formation, rather than black hole accretion, dominates the infrared emission throughout the galaxy. The light from PAH molecules, large dust grains, and stars and hot dust are spatially distinct from one another, leading to order-of-magnitude variations in the PAH equivalent width and the ratio of PAH to total infrared luminosity across the galaxy. The spatial variations we observe suggest either a physical offset between the PAHs and large dust grains or wide variations in the local ultraviolet radiation field. Our observations demonstrate that differences in the emission from PAH molecules and large dust grains are a complex result of localized processes within early galaxies., Comment: Published in Nature 5 June 2023 at https://www.nature.com/articles/s41586-023-05998-6. MIRI MRS reduction notebook is available at https://github.com/jwst-templates

We present new observations of sixteen bright ($r=19-21$) gravitationally lensed galaxies at $z\simeq 1-3$ selected from the CASSOWARY survey. Included in our sample is the $z=1.42$ galaxy CSWA-141, one of the brightest known reionization-era analogs at high redshift (g=20.5), with a large sSFR (31.2 Gyr$^{-1}$) and an [OIII]+H$\beta$ equivalent width (EW$_{\rm{[OIII]+H\beta}}$=730~\r{A}) that is nearly identical to the average value expected at $z\simeq 7-8$. In this paper, we investigate the rest-frame UV nebular line emission in our sample with the goal of understanding the factors that regulate strong CIII] emission. Whereas most of the sources in our sample show weak UV line emission, we find elevated CIII] in the spectrum of CSWA-141 (EW$_{\rm{CIII]}}$=4.6$\pm1.9$~\r{A}) together with detections of other prominent emission lines (OIII], Si III], Fe II$^\star$, Mg II). We compare the rest-optical line properties of high redshift galaxies with strong and weak CIII] emission, and find that systems with the strongest UV line emission tend to have young stellar populations and nebular gas that is moderately metal-poor and highly ionized, consistent with trends seen at low and high redshift. The brightness of CSWA-141 enables detailed investigation of the extreme emission line galaxies which become common at $z>6$. We find that gas traced by the CIII] doublet likely probes higher densities than that traced by [OII] and [SII]. Characterisation of the spectrally resolved Mg II emission line and several low ionization absorption lines suggests neutral gas around the young stars is likely optically thin, potentially facilitating the escape of ionizing radiation., Comment: 20 pages, 9 figures, Accepted for publication in MNRAS

The SPT0311-58 system at z=6.900 is an extremely massive structure within the reionization epoch, and offers a chance to understand the formation of galaxies in an extreme peak in the primordial density field. We present 70mas Atacama Large Millimeter/submillimeter Array observations of the dust continuum and CII 158um emission in the central pair of galaxies and reach physical resolution ~100-350pc, among the most detailed views of any reionization-era system to date. The observations resolve the source into at least a dozen kiloparsec-size clumps. The global kinematics and high turbulent velocity dispersion within the galaxies present a striking contrast to recent claims of dynamically cold thin-disk kinematics in some dusty galaxies just 800Myr later at z~4. We speculate that both gravitational interactions and fragmentation from massive parent disks have likely played a role in the overall dynamics and formation of clumps in the system. Each clump individually is comparable in mass to other 6

Galactic outflows of molecular gas are a common occurrence in galaxies and may represent a mechanism by which galaxies self-regulate their growth, redistributing gas that could otherwise have formed stars. We previously presented the first survey of molecular outflows at z > 4 towards a sample of massive, dusty galaxies. Here we characterize the physical properties of the molecular outflows discovered in our survey. Using low-redshift outflows as a training set, we find agreement at the factor-of-two level between several outflow rate estimates. We find molecular outflow rates 150-800Msun/yr and infer mass loading factors just below unity. Among the high-redshift sources, the molecular mass loading factor shows no strong correlations with any other measured quantity. The outflow energetics are consistent with expectations for momentum-driven winds with star formation as the driving source, with no need for energy-conserving phases. There is no evidence for AGN activity in our sample, and while we cannot rule out deeply-buried AGN, their presence is not required to explain the outflow energetics, in contrast to nearby obscured galaxies with fast outflows. The fraction of the outflowing gas that will escape into the circumgalactic medium (CGM), though highly uncertain, may be as high as 50%. This nevertheless constitutes only a small fraction of the total cool CGM mass based on a comparison to z~2-3 quasar absorption line studies, but could represent >~10% of the CGM metal mass. Our survey offers the first statistical characterization of molecular outflow properties in the very early universe., Comment: ApJ accepted. 25 pages, 16 figures. Data and tables from Papers I and II available at https://github.com/spt-smg/publicdata

Massive galaxy-scale outflows of gas are one of the most commonly-invoked mechanisms to regulate the growth and evolution of galaxies throughout the universe. While the gas in outflows spans a large range of temperatures and densities, the cold molecular phase is of particular interest because molecular outflows may be capable of suppressing star formation in galaxies by removing the star-forming gas. We have conducted the first survey of molecular outflows at z > 4, targeting 11 strongly-lensed dusty, star-forming galaxies (DSFGs) with high-resolution Atacama Large Millimeter Array (ALMA) observations of OH 119um absorption as an outflow tracer. In this first paper, we give an overview of the survey, focusing on the detection rate and structure of molecular outflows. We find unambiguous evidence for outflows in 8/11 (73%) galaxies, more than tripling the number known at z > 4. This implies that molecular winds in z > 4 DSFGs must have both a near-unity occurrence rate and large opening angles to be detectable in absorption. Lensing reconstructions reveal that 500pc-scale clumpy structures in the outflows are common. The individual clumps are not directly resolved, but from optical depth arguments we expect that future observations will require 50-200pc spatial resolution to do so. We do not detect high-velocity [CII] wings in any of the sources with clear OH outflows, indicating that [CII] is not a reliable tracer of molecular outflows. Our results represent a first step toward characterizing molecular outflows at z > 4 at the population level, demonstrating that large-scale outflows are ubiquitous among early massive, dusty galaxies., Comment: ApJ accepted. 28 pages, 12 figures + appendix. Data and tables from Papers I and II available at https://github.com/spt-smg/publicdata

For nearly 40 years, dark matter has been widely assumed to be cold and collisionless. Cold dark matter models make fundamental predictions for the behavior of dark matter on small (<10 kpc) scales. These predictions include cuspy density profiles at the centers of dark matter halos and a halo mass function that increases as dN/dM ~ M^-1.9 down to very small masses. We suggest two observational programs relying on extremely large telescopes to critically test these predictions, and thus shed new light on the nature of dark matter. (1) Combining adaptive optics-enabled imaging with deep spectroscopy to measure the three-dimensional motions of stars within a sample of Local Group dwarf galaxies that are the cleanest dark matter laboratories known in the nearby universe. From these observations the inner slope of the dark matter density profile can be determined with an accuracy of 0.20 dex, enabling a central cusp to be distinguished from a core at 5 sigma significance. (2) Diffraction-limited AO imaging and integral field spectroscopy of gravitationally lensed galaxies and quasars to quantify the abundance of dark substructures in the halos of the lens galaxies and along the line of sight. Observations of 50 lensed arcs and 50 multiply-imaged quasars will be sufficient to measure the halo mass function over the range 10^7 < M < 10^10 Msun at cosmological scales, independent of the baryonic and stellar composition of those structures. These two observational probes provide complementary information about the small scale structure, with a joint self-consistent analysis mitigating limitations of either probe. This program will produce the strongest existing constraints on the properties of dark matter on small scales, allowing conclusive tests of alternative warm, fuzzy, and self-interacting dark matter models., Comment: 8 pages, 2 figures. Science white paper submitted to the Astro2020 decadal survey

Astrophysical observations currently provide the only robust, empirical measurements of dark matter. In the coming decade, astrophysical observations will guide other experimental efforts, while simultaneously probing unique regions of dark matter parameter space. This white paper summarizes astrophysical observations that can constrain the fundamental physics of dark matter in the era of LSST. We describe how astrophysical observations will inform our understanding of the fundamental properties of dark matter, such as particle mass, self-interaction strength, non-gravitational interactions with the Standard Model, and compact object abundances. Additionally, we highlight theoretical work and experimental/observational facilities that will complement LSST to strengthen our understanding of the fundamental characteristics of dark matter., Comment: 11 pages, 2 figures, Science Whitepaper for Astro 2020, more information at https://lsstdarkmatter.github.io

Astrophysical and cosmological observations currently provide the only robust, empirical measurements of dark matter. Future observations with Large Synoptic Survey Telescope (LSST) will provide necessary guidance for the experimental dark matter program. This white paper represents a community effort to summarize the science case for studying the fundamental physics of dark matter with LSST. We discuss how LSST will inform our understanding of the fundamental properties of dark matter, such as particle mass, self-interaction strength, non-gravitational couplings to the Standard Model, and compact object abundances. Additionally, we discuss the ways that LSST will complement other experiments to strengthen our understanding of the fundamental characteristics of dark matter. More information on the LSST dark matter effort can be found at https://lsstdarkmatter.github.io/ ., Comment: 96 pages, 22 figures, 1 table

We present Atacama Large Millimeter/submillimeter Array (ALMA) observations of high-J CO lines ($J_\mathrm{up}=6$, 7, 8) and associated dust continuum towards five strongly lensed, dusty, star-forming galaxies (DSFGs) at redshift $z = 2.7$-5.7. These galaxies, discovered in the South Pole Telescope survey, are observed at $0.2''$-$0.4''$ resolution with ALMA. Our high-resolution imaging coupled with the lensing magnification provides a measurement of the structure and kinematics of molecular gas in the background galaxies with spatial resolutions down to kiloparsec scales. We derive visibility-based lens models for each galaxy, accurately reproducing observations of four of the galaxies. Of these four targets, three show clear velocity gradients, of which two are likely rotating disks. We find that the reconstructed region of CO emission is less concentrated than the region emitting dust continuum even for the moderate-excitation CO lines, similar to what has been seen in the literature for lower-excitation transitions. We find that the lensing magnification of a given source can vary by 20-50% across the line profile, between the continuum and line, and between different CO transitions. We apply Large Velocity Gradient (LVG) modeling using apparent and intrinsic line ratios between lower-J and high-J CO lines. Ignoring these magnification variations can bias the estimate of physical properties of interstellar medium of the galaxies. The magnitude of the bias varies from galaxy to galaxy and is not necessarily predictable without high resolution observations., Comment: 19 pages, 12 figures, accepted by ApJ

We present a machine learning method for the reconstruction of the undistorted images of background sources in strongly lensed systems. This method treats the source as a pixelated image and utilizes the Recurrent Inference Machine (RIM) to iteratively reconstruct the background source given a lens model. Our architecture learns to minimize the likelihood of the model parameters (source pixels) given the data using the physical forward model (ray tracing simulations) while implicitly learning the prior of the source structure from the training data. This results in better performance compared to linear inversion methods, where the prior information is limited to the 2-point covariance of the source pixels approximated with a Gaussian form, and often specified in a relatively arbitrary manner. We combine our source reconstruction network with a convolutional neural network that predicts the parameters of the mass distribution in the lensing galaxies directly from telescope images, allowing a fully automated reconstruction of the background source images and the foreground mass distribution., Comment: Submitted to ApJ

We use convolutional neural networks (CNNs) and recurrent neural networks (RNNs) to estimate the parameters of strong gravitational lenses from interferometric observations. We explore multiple strategies and find that the best results are obtained when the effects of the dirty beam are first removed from the images with a deconvolution performed with an RNN-based structure before estimating the parameters. For this purpose, we use the recurrent inference machine (RIM) introduced in Putzky & Welling (2017). This provides a fast and automated alternative to the traditional CLEAN algorithm. We obtain the uncertainties of the estimated parameters using variational inference with Bernoulli distributions. We test the performance of the networks with a simulated test dataset as well as with five ALMA observations of strong lenses. For the observed ALMA data we compare our estimates with values obtained from a maximum-likelihood lens modeling method which operates in the visibility space and find consistent results. We show that we can estimate the lensing parameters with high accuracy using a combination of an RNN structure performing image deconvolution and a CNN performing lensing analysis, with uncertainties less than a factor of two higher than those achieved with maximum-likelihood methods. Including the deconvolution procedure performed by RIM, a single evaluation can be done in about a second on a single GPU, providing a more than six orders of magnitude increase in analysis speed while using about eight orders of magnitude less computational resources compared to maximum-likelihood lens modeling in the uv-plane. We conclude that this is a promising method for the analysis of mm and cm interferometric data from current facilities (e.g., ALMA, JVLA) and future large interferometric observatories (e.g., SKA), where an analysis in the uv-plane could be difficult or unfeasible., Comment: To be submitted to ApJ

In Hezaveh et al. 2017 we showed that deep learning can be used for model parameter estimation and trained convolutional neural networks to determine the parameters of strong gravitational lensing systems. Here we demonstrate a method for obtaining the uncertainties of these parameters. We review the framework of variational inference to obtain approximate posteriors of Bayesian neural networks and apply it to a network trained to estimate the parameters of the Singular Isothermal Ellipsoid plus external shear and total flux magnification. We show that the method can capture the uncertainties due to different levels of noise in the input data, as well as training and architecture-related errors made by the network. To evaluate the accuracy of the resulting uncertainties, we calculate the coverage probabilities of marginalized distributions for each lensing parameter. By tuning a single hyperparameter, the dropout rate, we obtain coverage probabilities approximately equal to the confidence levels for which they were calculated, resulting in accurate and precise uncertainty estimates. Our results suggest that neural networks can be a fast alternative to Monte Carlo Markov Chains for parameter uncertainty estimation in many practical applications, allowing more than seven orders of magnitude improvement in speed., Comment: submitted to ApJL

Quantifying image distortions caused by strong gravitational lensing and estimating the corresponding matter distribution in lensing galaxies has been primarily performed by maximum likelihood modeling of observations. This is typically a time and resource-consuming procedure, requiring sophisticated lensing codes, several data preparation steps, and finding the maximum likelihood model parameters in a computationally expensive process with downhill optimizers. Accurate analysis of a single lens can take up to a few weeks and requires the attention of dedicated experts. Tens of thousands of new lenses are expected to be discovered with the upcoming generation of ground and space surveys, the analysis of which can be a challenging task. Here we report the use of deep convolutional neural networks to accurately estimate lensing parameters in an extremely fast and automated way, circumventing the difficulties faced by maximum likelihood methods. We also show that lens removal can be made fast and automated using Independent Component Analysis of multi-filter imaging data. Our networks can recover the parameters of the Singular Isothermal Ellipsoid density profile, commonly used to model strong lensing systems, with an accuracy comparable to the uncertainties of sophisticated models, but about ten million times faster: 100 systems in approximately 1s on a single graphics processing unit. These networks can provide a way for non-experts to obtain lensing parameter estimates for large samples of data. Our results suggest that neural networks can be a powerful and fast alternative to maximum likelihood procedures commonly used in astrophysics, radically transforming the traditional methods of data reduction and analysis., Comment: Accepted for publication in Nature. Under press embargo till 18:00 GMT (1300 US Eastern Time) on Wednesday August 30th

We study the abundance of substructure in the matter density near galaxies using ALMA Science Verification observations of the strong lensing system SDP.81. We present a method to measure the abundance of subhalos around galaxies using interferometric observations of gravitational lenses. Using simulated ALMA observations, we explore the effects of various systematics, including antenna phase errors and source priors, and show how such errors may be measured or marginalized. We apply our formalism to ALMA observations of SDP.81. We find evidence for the presence of a $M=10^{8.96\pm 0.12} M_{\odot}$ subhalo near one of the images, with a significance of $6.9\sigma$ in a joint fit to data from bands 6 and 7; the effect of the subhalo is also detected in both bands individually. We also derive constraints on the abundance of dark matter subhalos down to $M\sim 2\times 10^7 M_{\odot}$, pushing down to the mass regime of the smallest detected satellites in the Local Group, where there are significant discrepancies between the observed population of luminous galaxies and predicted dark matter subhalos. We find hints of additional substructure, warranting further study using the full SDP.81 dataset (including, for example, the spectroscopic imaging of the lensed carbon monoxide emission). We compare the results of this search to the predictions of $\Lambda$CDM halos, and find that given current uncertainties in the host halo properties of SDP.81, our measurements of substructure are consistent with theoretical expectations. Observations of larger samples of gravitational lenses with ALMA should be able to improve the constraints on the abundance of galactic substructure., Comment: 18 pages, 13 figures, Comments are welcome

We examine the prospects of detecting demagnified images of gravitational lenses in observations of strongly lensed mm-wave molecular emission lines with ALMA. We model the lensing galaxies as a superposition of a dark matter component, a stellar component, and a central supermassive black hole and assess the detectability of the central images for a range of relevant parameters (e.g., stellar core, black hole mass, and source size). We find that over a large range of plausible parameters, future deep observations of lensed molecular lines with ALMA should enable detection of the central images at $\gtrsim 3\sigma$ significance. We use a Fisher analysis to examine the constraints that could be placed on these parameters in various scenarios and find that for large stellar cores, both the core size and the mass of the central SMBHs can be accurately measured. We also study the prospects for detecting binary SMBHs with such observations and find that only under rare conditions and with very long integrations ($\sim$40-hr) the masses of both SMBHs may be measured using the distortions of central images., Comment: ApJL, in press

Application of the most robust method of measuring black hole masses, spatially resolved kinematics of gas and stars, is presently limited to nearby galaxies. The Atacama Large Millimeter/sub-millimeter Array (ALMA) and thirty meter class telescopes (the Thirty Meter Telescope, the Giant Magellan Telescope, and the European Extremely Large Telescope) with milli-arcsecond resolution are expected to extend such measurements to larger distances. Here, we study the possibility of exploiting the angular magnification provided by strong gravitational lensing to measure black hole masses at high redshifts (z~ 1-6), using resolved gas kinematics with these instruments. We show that in ~15% and ~20% of strongly lensed galaxies, the inner 25 and 50 pc could be resolved, allowing the mass of ~$10^8 M_{\odot}$ black holes to be dynamically measured with ALMA, if moderately bright molecular gas is present at these small radii. Given the large number of strong lenses discovered in current millimeter surveys and future optical surveys, this fraction could constitute a statistically significant population for studying the evolution of the M-$\sigma$ relation at high redshifts., Comment: 5 pages, 5 figures. Published in ApJ letters

We address two selection effects that operate on samples of gravitationally lensed dusty galaxies identified in millimeter- and submillimeter-wavelength surveys. First, we point out the existence of a "size bias" in such samples: due to finite source effects, sources with higher observed fluxes are increasingly biased towards more compact objects. Second, we examine the effect of differential lensing in individual lens systems by modeling each source as a compact core embedded in an extended diffuse halo. Considering the ratio of magnifications in these two components, we find that at high overall magnifications the compact component is amplified by a much larger factor than the diffuse component, but at intermediate magnifications (~10) the probability of a larger magnification for the extended region is higher. Lens models determined from multi-frequency resolved imaging data are crucial to correct for this effect., Comment: 7 pages, 6 figures

We study the effects of strong lensing on the observed number counts of mm sources using a ray tracing simulation and two number count models of unlensed sources. We employ a quantitative treatment of maximum attainable magnification factor depending on the physical size of the sources, also accounting for effects of lens halo ellipticity. We calculate predicted number counts and redshift distributions of mm galaxies including the effects of strong lensing and compare with the recent source count measurements of the South Pole Telescope (SPT). The predictions have large uncertainties, especially the details of the mass distribution in lens galaxies and the finite extent of sources, but the SPT observations are in good agreement with predictions. The sources detected by SPT are predicted to largely consist of strongly lensed galaxies at z>2. The typical magnifications of these sources strongly depends on both the assumed unlensed source counts and the flux of the observed sources.