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SPT2349$-$56 is a protocluster discovered in the 2500 deg$^2$ South Pole Telescope (SPT) survey. In this paper, we study the kinematics of the galaxies found in the core of SPT2349$-$56 using high-resolution (1.55 kpc spatial resolution at $z = 4.303$) redshifted [CII] 158-$\mu$m data. Using the publicly available code 3D-Barolo, we analyze the seven far-infrared (FIR) brightest galaxies within the protocluster core. Based on conventional definitions for the detection of rotating discs, we classify six sources to be rotating discs in an actively star-forming protocluster environment, with weighted mean $V_{\mathrm{rot}}/\sigma_{\mathrm{disp}} = 4.5 \pm 1.3$. The weighted mean rotation velocity ($V_{\mathrm{rot}}$) and velocity dispersion ($\sigma_{\mathrm{disp}}$) for the sample are $ 357.1 \pm 114.7$ km s$^{-1}$ and $43.5 \pm 23.5$ km s$^{-1}$, respectively. We also assess the disc stability of the galaxies and find a mean Toomre parameter of $Q_\mathrm{T} = 0.9 \pm 0.3$. The galaxies show a mild positive correlation between disc stability and dynamical support. Using the position-velocity maps, we find that five sources further classify as disturbed discs, and one classifies as a strictly rotating disc. Our sample joins several observations at similar redshift with high $V/\sigma$ values, with the exception that they are morphologically disturbed, kinematically rotating and interacting galaxies in an extreme protocluster environment., Comment: 28 pages (9 appendix pages), 14 figures (7 in appendix), 7 tables (3 in appendix). Accepted for publication in ApJ

We present wide-field mapping at 850 $\mu$m and 450 $\mu$m of the $z$ = 2.85 protocluster in the HS1549$+$19 field using the Submillimetre Common User Bolometer Array 2 (SCUBA-2). Spectroscopic follow-up of 18 bright sources selected at 850 $\mu$m, using the Nothern Extended Millimeter Array (NOEMA) and Atacama Large Millimeter Array (ALMA), confirms the majority lies near $z$ $\sim$ 2.85 and are likely members of the structure. Interpreting the spectroscopic redshifts as distance measurements, we find that the SMGs span 90 Mpc$^2$ in the plane of the sky and demarcate a 4100 Mpc$^3$ "pancake"-shaped structure in three dimensions. We find that the high star-formation rates (SFRs) of these SMGs result in a total SFR of 20,000 M$_\odot$ yr$^{-1}$ only from the brightest galaxies in the protocluster. These rapidly star-forming SMGs can be interpreted as massive galaxies growing rapidly at large cluster-centric distances before collapsing into a virialized structure. We find that the SMGs trace the Lyman-$\alpha$ surface density profile. Comparison with simulations suggests that HS1549$+$19 could be building a structure comparable to the most massive clusters in the present-day Universe.

Within the context of machine learning-based closure mappings for RANS turbulence modelling, physical realizability is often enforced using ad-hoc postprocessing of the predicted anisotropy tensor. In this study, we address the realizability issue via a new physics-based loss function that penalizes non-realizable results during training, thereby embedding a preference for realizable predictions into the model. Additionally, we propose a new framework for data-driven turbulence modelling which retains the stability and conditioning of optimal eddy viscosity-based approaches while embedding equivariance. Several modifications to the tensor basis neural network to enhance training and testing stability are proposed. We demonstrate the conditioning, stability, and generalization of the new framework and model architecture on three flows: flow over a flat plate, flow over periodic hills, and flow through a square duct. The realizability-informed loss function is demonstrated to significantly increase the number of realizable predictions made by the model when generalizing to a new flow configuration. Altogether, the proposed framework enables the training of stable and equivariant anisotropy mappings, with more physically realizable predictions on new data. We make our code available for use and modification by others., Comment: 44 pages, 21 figures

Fluid injection can induce seismicity by altering stresses on pre-existing faults. Here, we investigate minimizing induced seismic hazard by optimizing injection operations in a physics-based forecasting framework. We built a 3D finite element model of the poroelastic crust for the Raton Basin, Central US, and used it to estimate time dependent Coulomb stress changes due to ~25 years of wastewater injection in the region. Our finite element model is complemented by a statistical analysis of the seismogenic index (SI), a proxy for critically stressed faults affected by variations in the pore pressure. Forecasts of seismicity rate from our hybrid physics-based statistical model suggest that induced seismicity in the Raton Basin, from 2001 - 2022, is still driven by wastewater injection. Our model suggests that pore pressure diffusion is the dominant cause of Coulomb stress changes at seismogenic depth, with poroelastic stress changes contributing about 5% to the driving force. Linear programming optimization for the Raton Basin reveals that it is feasible to reduce seismic hazard for a given amount of injected fluid (safety objective) or maximize fluid injection for a prescribed seismic hazard (economic objective). The optimization tends to spread out high-rate injectors and shift them to regions of lower SI. The framework has practical importance as a tool to manage injection rate per unit field area to reduce induced seismic hazard. Our optimization framework is both flexible and adaptable to mitigate induced seismic hazard in other regions and for other types of subsurface fluid injection.

Industrial simulations of turbulent flows often rely on Reynolds-averaged Navier-Stokes (RANS) turbulence models, which contain numerous closure coefficients that need to be calibrated. In this work, we address this issue by proposing a semi-automated calibration of these coefficients using a new framework (referred to as turbo-RANS) based on Bayesian optimization. We introduce the generalized error and default coefficient preference (GEDCP) objective function, which can be used with integral, sparse, or dense reference data for the purpose of calibrating RANS turbulence closure model coefficients. Then, we describe a Bayesian optimization-based algorithm for conducting the calibration of these model coefficients. An in-depth hyperparameter tuning study is conducted to recommend efficient settings for the turbo-RANS optimization procedure. We demonstrate that the performance of the $k$-$\omega$ shear stress transport (SST) and Generalized $k$-$\omega$ (GEKO) turbulence models can be efficiently improved via turbo-RANS, for three example cases: predicting the lift coefficient of an airfoil; predicting the velocity and turbulent kinetic energy fields for a separated flow; and, predicting the wall pressure coefficient distribution for flow through a converging-diverging channel. This work is the first to propose and provide an open-source black-box calibration procedure for turbulence model coefficients based on Bayesian optimization. We propose a data-flexible objective function for the calibration target. Our open-source implementation of the turbo-RANS framework includes OpenFOAM, Ansys Fluent, STAR-CCM+, and solver-agnostic templates for user application., Comment: 24 pages, 14 figures. Published in International Journal of Numerical Methods for Heat & Fluid Flow (https://doi.org/10.1108/HFF-12-2023-0726)

We combine archival ALMA data targeting the Hubble Ultra Deep Field (HUDF) to produce the deepest currently attainable 1-mm maps of this key region. Our deepest map covers 4.2arcmin^2, with a beamsize of 1.49''x1.07'' at an effective frequency of 243GHz (1.23mm). It reaches an rms of 4.6uJy/beam, with 1.5arcmin^2 below 9.0uJy/beam, an improvement of >5% (and up to 50% in some regions) over the best previous map. We also make a wider, shallower map, covering 25.4arcmin^2. We detect 45 galaxies in the deep map down to 3.6sigma, 10 more than previously detected, and 39 of these galaxies have JWST counterparts. A stacking analysis on the positions of ALMA-undetected JWST galaxies with z<4 and stellar masses from 10^8.4 to 10^10.4 M_sun yields 10% more signal compared to previous stacking analyses, and we find that detected sources plus stacking contribute (10.0+/-0.5)Jy/deg^2 to the cosmic infrared background (CIB) at 1.23mm. Although this is short of the (uncertain) background level of about 20Jy/deg^2, we show that our measurement is consistent with the background if the HUDF is a mild (~2sigma) negative CIB fluctuation, and that the contribution from faint undetected objects is small and converging. In particular, we predict that the field contains about 60 additional 15uJy galaxies, and over 300 galaxies at the few uJy level. This suggests that JWST has detected essentially all of the galaxies that contribute to the CIB, as anticipated from the strong correlation between galaxy stellar mass and obscured star formation., Comment: Published in MNRAS. All of the combined ALMA maps described in this paper are available at https://doi.org/10.5683/SP3/YWBVWH

We present JWST and ALMA results for the lensing system SPT0418-47, which includes a strongly-lensed, dusty star-forming galaxy at redshift z=4.225 and an associated multiply-imaged companion. JWST NIRCam and MIRI imaging observations presented in this paper were acquired as part of the Early Release Science program Targeting Extremely Magnified Panchromatic Lensed Arcs and Their Extended Star Formation (TEMPLATES). This data set provides robust, mutiwavelength detection of stellar light in both the main (SPT0418A) and companion (SPT0418B) galaxies, while the ALMA detection of [C II] emission confirms that SPT0418B lies at the same redshift as SPT0418A. From a source plane reconstruction, we infer that the projected physical separation of the two galaxies is $4.42\pm 0.05$ kpc. We derive total magnifications of $\mu=29.5\pm1.2$ and $\mu=4.2\pm 0.9$ for SPT0418A and SPT0418B, respectively. We use both CIGALE and PROSPECTOR to derive stellar masses. The stellar mass ratio of SPT0418A and SPT0418B is approximately 4 to 1 ($4.5\pm 1.0$ for CIGALE and $4.2^{+1.9}_{-1.6}$ for PROSPECTOR). We also see evidence of extended structure associated with SPT0418A in the lensing reconstruction that is suggestive of a tidal feature. Interestingly, the star formation rates and stellar masses of both galaxies are consistent with the main sequence of star-forming galaxies at this epoch, indicating that this ongoing interaction has not noticeably elevated the star formation levels., Comment: Submitted to AAS Journals,14 pages, 7 figures

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 initial results of an ongoing survey with the Karl G. Jansky Very Large Array targeting the CO($J$ = 1-0) transition in a sample of 30 submillimeter-selected, dusty star-forming galaxies at $z =$ 2-5 with existing mid--$J$ CO detections from ALMA and NOEMA, of which 17 have been fully observed. We detect CO(1-0) emission in 11 targets, along with three tentative ($\sim$1.5-2$\sigma$) detections; three galaxies are undetected. Our results yield total molecular gas masses of 6-23$\times$10$^{10}$ ($\alpha_\mathrm{CO}$/1) M$_\odot$, with gas mass fractions, $f_\mathrm{gas}$=$M_\mathrm{mol}$/($M_*$+$M_\mathrm{mol}$), of 0.1-0.8 and a median depletion time of (140$\pm$70) Myr. We find median CO excitation ratios of $r_{31}$ = 0.75$\pm$0.39 and $r_{41}$ = 0.63$\pm$0.44, with a significant scatter. We find no significant correlation between the excitation ratio and a number of key parameters such as redshift, CO(1-0) line width or $\Sigma_\mathrm{SFR}$. We only find a tentative positive correlation between $r_{41}$ and the star-forming efficiency, but we are limited by our small sample size. Finally, we compare our results to predictions from the SHARK semi-analytical model, finding a good agreement between the molecular gas masses, depletion times and gas fractions of our sources and their SHARK counterparts. Our results highlight the heterogeneous nature of the most massive star-forming galaxies at high-redshift, and the importance of CO(1--0) observations to robustly constrain their total molecular gas content and ISM properties., Comment: 10 pages, 15 figures. Accepted for publication in ApJ

We have observed the z=4.3 protocluster SPT2349-56 with ATCA with the aim of detecting radio-loud active galactic nuclei (AGN) amongst the ~30 submillimeter galaxies identified in the structure. We detect the central complex of SMGs at 2.2\,GHz with a luminosity of L_2.2=(4.42pm0.56)x10^{25} W/Hz. The ASKAP also detects the source at 888 MHz, constraining the radio spectral index to alpha=-1.6pm0.3, consistent with ATCA non-detections at 5.5 and 9GHz, and implying L_1.4(rest)=(2.4pm0.3)x10^{26}W/Hz. This radio luminosity is about 100 times higher than expected from star formation, assuming the usual FIR-radio correlation, which is a clear indication of an AGN driven by a forming brightest cluster galaxy (BCG). None of the SMGs in SPT2349-56 show signs of AGN in any other diagnostics available to us (notably 12CO out to J=16, OH163um, CII/IR, and optical spectra), highlighting the radio continuum as a powerful probe of obscured AGN in high-z protoclusters. No other significant radio detections are found amongst the cluster members, consistent with the FIR-radio correlation. We compare these results to field samples of radio sources and SMGs, along with the 22 SPT-SMG gravitational lenses also observed in the ATCA program, as well as powerful radio galaxies at high redshifts. Our results allow us to better understand the effects of this gas-rich, overdense environment on early supermassive black hole (SMBH) growth and cluster feedback. We estimate that (3.3pm0.7)x10^{38} W of power are injected into the growing ICM by the radio-loud AGN, whose energy over 100Myr is comparable to the binding energy of the gas mass of the central halo. The AGN power is also comparable to the instantaneous energy injection from supernova feedback from the 23 catalogued SMGs in the core region of 120kpc projected radius. The SPT2349-56 radio-loud AGN may be providing strong feedback on a nascent ICM., Comment: 31 pages, submitted to ApJ, Dec17,2022

Context. Deep spectroscopic surveys with the Atacama Large Millimeter/submillimeter Array (ALMA) have revealed that some of the brightest infrared sources in the sky correspond to concentrations of dusty star-forming galaxies (DSFG) at high redshift. Among these, the SPT2349-56 protocluster system at z = 4.304 is amongst the most extreme examples due to its high source density and integrated star formation rate. Aims. We conducted a deep Lyman-$\alpha$ line emission survey around SPT2349-56 using the Multi-Unit Spectroscopic Explorer (MUSE) at Very Large Telescope (VLT) in order to characterize this uniquely dense environment. Methods. Taking advantage of the deep three-dimensional nature of this survey, we performed a sensitive search for Lyman-$\alpha$ emitters (LAEs) toward the core and northern extension of the protocluster, which correspond to the brightest infrared regions in this field. Using a smoothed narrowband image extracted from the MUSE datacube around the protocluster redshift, we searched for possible extended structures. Results. We identify only three LAEs at z = 4.3 in this field, in concordance with expectations for blank-fields, and an extended Lyman-$\alpha$ structure spatially associated with core of the protocluster. All the previously-identified DSFGs in this field are undetected in Lyman-$\alpha$ emission, consistent with the conspicuous dust obscuration in these systems. We find an extended Lyman-$\alpha$ structure, about $60 \times 60$ kpc$^{2}$ in size, and located 56 kpc west of the protocluster core. Three DSFGs coincide spatially with the location of this structure. We conclude that either the three co-spatial DSFGs or the protocluster core itself are feeding ionizing photons to the Lyman-$\alpha$ structure., Comment: 14 pages, 9 figures, 2 tables, submitted to A&A

The COVID-19 pandemic has revealed the importance of digital fabrication to enable online learning, which remains a challenge for robotics courses. We introduce a teaching methodology that allows students to participate remotely in a hands-on robotics course involving the design and fabrication of robots. Our methodology employs 3D printing techniques with flexible filaments to create innovative soft robots; robots are made from flexible, as opposed to rigid, materials. Students design flexible robotic components such as actuators, sensors, and controllers using CAD software, upload their designs to a remote 3D printing station, monitor the print with a web camera, and inspect the components with lab staff before being mailed for testing and assembly. At the end of the course, students will have iterated through several designs and created fluidically-driven soft robots. Our remote teaching methodology enables educators to utilize 3D printing resources to teach soft robotics and cultivate creativity among students to design novel and innovative robots. Our methodology seeks to democratize robotics engineering by decoupling hands-on learning experiences from expensive equipment in the learning environment., Comment: 9 pages, 4 figures, peer reviewed and presented paper at American Society of Engineering Education, April 22-23rd, 2022 - Wentworth Institute of Technology

Several machine learning frameworks for augmenting turbulence closure models have been recently proposed. However, the generalizability of an augmented turbulence model remains an open question. We investigate this question by systematically varying the training and test sets of several models. An optimal three-term tensor basis expansion is used to develop a model-agnostic data-driven turbulence closure approximation. Then, hyperparameter optimization was performed for a random forest, a neural network, and an eXtreme Gradient Boosting (XGBoost) model. We recommend XGBoost for data-driven turbulence closure modelling owing to its low-tuning cost and good performance. We also find that machine learning models generalize well to new parametric variations of flows seen in the training dataset, but lack generalizability to new flow types. This generalizability gap suggests that machine learning methods are most suited for developing specialized models for a given flow type, a problem often encountered in industrial applications., Comment: Article: 40 pages, 15 figures, supplemental (ancillary) file: 29 pages, 60 figures. Accepted in International Journal of Computational Fluid Dynamics

The Planck list of high-redshift source candidates (the PHz catalogue) contains 2151 peaks in the cosmic infrared background, unresolved by Planck's 5 arcmin beam. Follow-up spectroscopic observations have revealed that some of these objects are $z \approx 2$ protoclusters and strong gravitational lenses, but an unbiased survey has not yet been carried out. To this end, we have used archival Herschel-SPIRE observations to study a uniformly-selected sample of 187 PHz sources. In contrast with follow-up studies that were biased towards bright, compact sources, we find that only one of our PHz sources is a bright gravitationally-lensed galaxy (peak flux $\gtrsim 300$ mJy), indicating that such objects are rarer in the PHz catalogue than previously believed ($< 1$ per cent). The majority of our PHz sources consist of many red, star-forming galaxies, demonstrating that typical PHz sources are candidate protoclusters. However, our new PHz sources are significantly less bright than found in previous studies and differ in colour, suggesting possible differences in redshift and star-formation rate. Nonetheless, 40 of our PHz sources contain $> 3\sigma$ galaxy overdensities, comparable to the fraction of $> 3\sigma$ overdensities found in earlier biased studies. We additionally use a machine-learning approach to identify less extreme (peak flux $\sim 100$ mJy) gravitationally-lensed galaxies among Herschel-SPIRE observations of PHz sources, finding a total of seven candidates in our unbiased sample, and 13 amongst previous biased samples. Our new uniformly-selected catalogues of $> 3\sigma$ candidate protoclusters and strong gravitational lenses provide interesting targets for follow up with higher-resolution facilities, such as ALMA and JWST., Comment: 23 pages, 19 figures, 4 tables. Accepted for publication in MNRAS

Using {\it Herschel}-SPIRE imaging and the Canada-France Imaging Survey (CFIS) Low Surface Brightness data products from the Ultraviolet Near-Infrared Optical Northern Survey (UNIONS), we present a cross-correlation between the cosmic far-infrared background and cosmic optical background fluctuations. The cross-spectrum is measured for two cases: all galaxies are kept in the images; or all individually-detected galaxies are masked to produce `background' maps. We report the detection of the cross-correlation signal at $\gtrsim 18\,\sigma$ ($\gtrsim 14\,\sigma$ for the background map). The part of the optical brightness variations that are correlated with the submm emission translates to an rms brightness of $\simeq 32.5\,{\rm mag}\,{\rm arcsec}^{-2}$ in the $r$ band, a level normally unreachable for individual sources. A critical issue is determining what fraction of the cross-power spectrum might be caused by emission from Galactic cirrus. For one of the fields, the Galactic contamination is 10 times higher than the extragalactic signal; however, for the other fields, the contamination is around 20~per cent. An additional discriminant is that the cross-power spectrum is of the approximate form $P(k)\propto 1/k$, much shallower than that of Galactic cirrus. We interpret the results in a halo-model framework, which shows good agreement with independent measurements for the scalings of star-formation rates in galaxies. The approach presented in this study holds great promise for future surveys such as FYST/CCAT-prime combined with {\it Euclid} or the Vera Rubin Observatory (LSST), which will enable a detailed exploration of the evolution of star formation in galaxies., Comment: 40 pages, 26 figures, published 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

SPT0346-52 (z=5.7) is the most intensely star-forming galaxy discovered by the South Pole Telescope, with Sigma_SFR ~ 4200 Msol yr^-1 kpc^-2. In this paper, we expand on previous spatially-resolved studies, using ALMA observations of dust continuum, [NII]205 micron, [CII]158 micron, [OI]146 micron, and undetected [NII]122 micron and [OI]63 micron emission to study the multi-phase interstellar medium (ISM) in SPT0346-52. We use pixelated, visibility-based lens modeling to reconstruct the source-plane emission. We also model the source-plane emission using the photoionization code CLOUDY and find a supersolar metallicity system. We calculate T_dust = 48.3 K and lambda_peak = 80 micron, and see line deficits in all five lines. The ionized gas is less dense than comparable galaxies, with n_e < 32 cm^-3, while ~20% of the [CII]158 emission originates from the ionized phase of the ISM. We also calculate the masses of several phases of the ISM. We find that molecular gas dominates the mass of the ISM in SPT0346-52, with the molecular gas mass ~4x higher than the neutral atomic gas mass and ~100x higher than the ionized gas mass., Comment: 25 pages, 15 figures. Accepted for publication in ApJ

The demining of landmines using drones is challenging; air-releasable payloads are typically non-intelligent (e.g., water balloons or explosives) and deploying them at even low altitudes (~6 meter) is inherently inaccurate due to complex deployment trajectories and constrained visual awareness by the drone pilot. Soft robotics offers a unique approach for aerial demining, namely due to the robust, low-cost, and lightweight designs of soft robots. Instead of non-intelligent payloads, here, we propose the use of air-releasable soft robots for demining. We developed a full system consisting of an unmanned aerial vehicle retrofitted to a soft robot carrier including a custom-made deployment mechanism, and an air-releasable, lightweight (296 g), untethered soft hybrid robot with integrated electronics that incorporates a new type of a vacuum-based flasher roller actuator system. We demonstrate a deployment cycle in which the drone drops the soft robotic hybrid from an altitude of 4.5 m meters and after which the robot approaches a dummy landmine. By deploying soft robots at points of interest, we can transition soft robotic technologies from the laboratory to real-world environments., Comment: Accepted manuscript: IEEE Soft Robotics Conference, Edinburgh, 2022

Despite well-known limitations of Reynolds-averaged Navier-Stokes (RANS) simulations, this methodology remains the most widely used tool for predicting many turbulent flows, due to computational efficiency. Machine learning is a promising approach to improve the accuracy of RANS simulations. One major area of improvement is using machine learning models to represent the complex relationship between the mean flow field gradients and the Reynolds stress tensor. In the present work, modifications to improve the stability of previous optimal eddy viscosity approaches for RANS simulations are presented and evaluated. The optimal eddy viscosity is reformulated with a non-negativity constraint, which promotes numerical stability. We demonstrate that the new formulation of the optimal eddy viscosity improves the conditioning of the RANS equations for a periodic hills test case. To demonstrate the suitability of this proportional/orthogonal tensor decomposition for use in a physics-informed data-driven turbulence closure, we use two neural networks (structured on this specific tensor decomposition which is incorporated as an inductive bias into the network design) to predict the newly reformulated linear and non-linear parts of the Reynolds stress tensor. Injecting these network model predictions for the Reynolds stresses into a RANS simulation improves predictions of the velocity field, even when compared to a sophisticated (state of the art) physics-based turbulence closure model. Finally, we apply SHAP (SHapley Additive exPlanations) values to obtain insights from the learned representation for the inner workings of the neural network used to predict the optimal eddy viscosity from the input feature data., Comment: 18 pages, 23 figures. Article submitted to Physics of Fluids

The protocluster SPT2349$-$56 at $z\,{=}\,4.3$ contains one of the most actively star-forming cores known, yet constraints on the total stellar mass of this system are highly uncertain. We have therefore carried out deep optical and infrared observations of this system, probing rest-frame ultraviolet to infrared wavelengths. Using the positions of the spectroscopically-confirmed protocluster members, we identify counterparts and perform detailed source deblending, allowing us to fit spectral energy distributions in order to estimate stellar masses. We show that the galaxies in SPT2349$-$56 have stellar masses proportional to their high star-formation rates, consistent with other protocluster galaxies and field submillimetre galaxies (SMGs) around redshift 4. The galaxies in SPT2349$-$56 have on average lower molecular gas-to-stellar mass fractions and depletion timescales than field SMGs, although with considerable scatter. We construct the stellar-mass function for SPT2349$-$56 and compare it to the stellar-mass function of $z\,{=}\,1$ galaxy clusters, finding consistent shapes between the two. We measure rest-frame galaxy ultraviolet half-light radii from our HST-F160W imaging, finding that on average the galaxies in our sample are similar in size to typical star-forming galaxies at these redshifts. However, the brightest HST-detected galaxy in our sample, found near the luminosity-weighted centre of the protocluster core, remains unresolved at this wavelength. Hydrodynamical simulations predict that the core galaxies will quickly merge into a brightest cluster galaxy, thus our observations provide a direct view of the early formation mechanisms of this class of object., Comment: Submitted to MNRAS Sept. 3, 2021 Accepted by MNRAS Dec, 4, 2021

SPT0311-58 is the most massive infrared luminous system discovered so far during the Epoch of Reionization (EoR). In this paper, we present a detailed analysis of the molecular interstellar medium at z = 6.9, through high-resolution observations of the CO(6-5), CO(7-6), CO(10-9), [CI](2-1), and p-H2O(211-202) lines and dust continuum emission with the Atacama Large Millimeter/submillimeter Array (ALMA). The system consists of a pair of intensely star-forming gravitationally lensed galaxies (labelled West and East). The intrinsic far-infrared luminosity is (16 $\pm$ 4)$\times\rm 10^{12} \ \rm L_{\odot}$ in West and (27 $\pm$ 4)$\times\rm 10^{11} \ \rm L_{\odot}$ in East. We model the dust, CO, and [CI] using non-local thermodynamic equilibrium radiative transfer models and estimate the intrinsic gas mass to be (5.4 $\pm$ 3.4)$\times\rm 10^{11} \ \rm M_{\odot}$ in West and (3.1 $\pm$ 2.7)$\times\rm 10^{10} \ \rm M_{\odot}$ in East. We find that the CO spectral line energy distribution in West and East are typical of high-redshift sub-millimeter galaxies (SMGs). The CO-to-H2 conversion factor ($\alpha_{CO}$) and the gas depletion time scales estimated from the model are consistent with the high-redshift SMGs in the literature within the uncertainties. We find no evidence of evolution of depletion time with redshift in SMGs at z > 3. This is the most detailed study of molecular gas content of a galaxy in the EoR to-date, with the most distant detection of H2O in a galaxy without any evidence for active galactic nuclei in the literature., Comment: Accepted for publication in The Astrophysical Journal. 34 pages, 17 figures

The recent surge in machine learning augmented turbulence modelling is a promising approach for addressing the limitations of Reynolds-averaged Navier-Stokes (RANS) models. This work presents the development of the first open-source dataset, curated and structured for immediate use in machine learning augmented turbulence closure modelling. The dataset features a variety of RANS simulations with matching direct numerical simulation (DNS) and large-eddy simulation (LES) data. Four turbulence models are selected to form the initial dataset: $k$-$\varepsilon$, $k$-$\varepsilon$-$\phi_t$-$f$, $k$-$\omega$, and $k$-$\omega$ SST. The dataset consists of 29 cases per turbulence model, for several parametrically sweeping reference DNS/LES cases: periodic hills, square duct, parametric bumps, converging-diverging channel, and a curved backward-facing step. At each of the 895,640 points, various RANS features with DNS/LES labels are available. The feature set includes quantities used in current state-of-the-art models, and additional fields which enable the generation of new feature sets. The dataset reduces effort required to train, test, and benchmark new models. The dataset is available at https://doi.org/10.34740/kaggle/dsv/2044393 ., Comment: 21 pages, 20 figures, 15 tables. Article yet to be submitted to a journal