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The deployment of large-scale models, such as large language models (LLMs) and sophisticated image generation systems, incurs substantial costs due to their computational demands. To mitigate these costs and address challenges related to scalability and data security, there is a growing shift towards decentralized systems for deploying such models. In these decentralized environments, efficient inference acceleration becomes crucial to manage computational resources effectively and enhance system responsiveness. In this work, we address the challenge of selecting optimal acceleration methods in decentralized systems by introducing a meta-learning-based framework. This framework automates the selection process by learning from historical performance data of various acceleration techniques across different tasks. Unlike traditional methods that rely on random selection or expert intuition, our approach systematically identifies the best acceleration strategies based on the specific characteristics of each task. We demonstrate that our meta-learning framework not only streamlines the decision-making process but also consistently outperforms conventional methods in terms of efficiency and performance. Our results highlight the potential of meta-learning to revolutionize inference acceleration in decentralized AI systems, offering a path towards more democratic and economically feasible artificial intelligence solutions.

We deploy the new Arkenstone galactic wind model in cosmological simulations for the first time, allowing us to robustly resolve the evolution and impact of high specific energy winds. In a (25$\,h^{-1}\,$Mpc)$^3$ box we perform a set of numerical experiments that systematically vary the mass and energy loadings of such winds, finding that their energy content is the key parameter controlling the stellar to dark matter mass ratio. Increasing the mass loading, at fixed energy, actually results in mildly enhanced star formation, counter to prevailing wisdom but in agreement with recent analytic models. Of the simple parametrisations that we test, we find that an energy loading that scales inversely with halo mass best matches a wide range of observations, and can do so with mass loadings drastically lower than those in most previous cosmological simulations. In this scenario, much less material is ejected from the interstellar medium. Instead, winds both heat gas in the circumgalactic medium, slowing infall onto the galaxy, and also drive shocks beyond the virial radius, preventing accretion onto the halo in the first place. We have not yet tied the mass and energy loadings to high-resolution simulations (a key goal of the Learning the Universe collaboration); however, we can already report that a much lower fraction of the available supernova energy is needed in preventative galaxy regulation than required by ejective wind feedback models such as IllustrisTNG., Comment: Submitted to MNRAS. 19 pages, 14 figures. This is a Learning the Universe publication

Metals in the diffuse, ionized gas at the boundary between the Milky Way's interstellar medium (ISM) and circumgalactic medium (CGM), known as the disk-halo interface (DHI), are valuable tracers of the feedback processes that drive the Galactic fountain. However, metallicity measurements in this region are challenging due to obscuration by the Milky Way ISM and uncertain ionization corrections that affect the total hydrogen column density. In this work, we constrain the ionization corrections to neutral hydrogen column densities using precisely measured electron column densities from the dispersion measure of pulsars that lie in the same globular clusters as UV-bright targets with high-resolution absorption spectroscopy. We address the blending of absorption lines with the ISM by jointly fitting Voigt profiles to all absorption components. We present our metallicity estimates for the DHI of the Milky Way based on detailed photoionization modeling to the absorption from ionized metal lines and ionization-corrected total hydrogen columns. Generally, the gas clouds show a large scatter in metallicity, ranging between $0.04-3.2\ Z_{\odot}$, implying that the DHI consists of a mixture of gaseous structures having multiple origins. We estimate the inflow and outflow timescales of the DHI ionized clouds to be $6 - 35$ Myr. We report the detection of an infalling cloud with super-solar metallicity that suggests a Galactic fountain mechanism, whereas at least one low-metallicity outflowing cloud ($Z < 0.1\ Z_{\odot}$) poses a challenge for Galactic fountain and feedback models., Comment: 28 pages, 15 figures, accepted for publication in ApJ

We describe AthenaK: a new implementation of the Athena++ block-based adaptive mesh refinement (AMR) framework using the Kokkos programming model. Finite volume methods for Newtonian, special relativistic (SR), and general relativistic (GR) hydrodynamics and magnetohydrodynamics (MHD), and GR-radiation hydrodynamics and MHD, as well as a module for evolving Lagrangian tracer or charged test particles (e.g., cosmic rays) are implemented using the framework. In two companion papers we describe (1) a new solver for the Einstein equations based on the Z4c formalism and (2) a GRMHD solver in dynamical spacetimes also implemented using the framework, enabling new applications in numerical relativity. By adopting Kokkos, the code can be run on virtually any hardware, including CPUs, GPUs from multiple vendors, and emerging ARM processors. AthenaK shows excellent performance and weak scaling, achieving over one billion cell updates per second for hydrodynamics in three-dimensions on a single NVIDIA Grace Hopper processor and with a typical parallel efficiency of 80% on 65536 AMD GPUs on the OLCF Frontier system. Such performance portability enables AthenaK to leverage modern exascale computing systems for challenging applications in astrophysical fluid dynamics, numerical relativity, and multimessenger astrophysics., Comment: Submitted to ApJS

High-velocity outflows are ubiquitous in compact, massive (M$_* \sim$ 10$^{11}$ M$_{\odot}$), z $\sim$ 0.5 galaxies with extreme star formation surface densities ($\Sigma_{SFR} \sim$ 2000 M$_{\odot}$ yr$^{-1}$ kpc$^{-2}$). We have previously detected and characterized these outflows using MgII absorption lines. To probe their full extent, we present Keck/KCWI integral field spectroscopy of the [OII] and MgII emission nebulae surrounding all of the 12 galaxies in this study. We find that [OII] is more effective than MgII in tracing low surface brightness, extended emission in these galaxies. The [OII] nebulae are spatially extended beyond the stars, with radial extent R$_{90}$ between 10 and 40 kpc. The nebulae exhibit non-gravitational motions, indicating galactic outflows with maximum blueshifted velocities ranging from -335 to -1920 km s$^{-1}$. The outflow kinematics correlate with the bursty star formation histories of these galaxies. Galaxies with the most recent bursts of star formation (within the last $<$ 3 Myr) exhibit the highest central velocity dispersions ($\sigma >$ 400 km s$^{-1}$), while the oldest bursts have the lowest-velocity outflows. Many galaxies exhibit both high-velocity cores and more extended, slower-moving gas indicative of multiple outflow episodes. The slower, larger outflows occurred earlier and have decelerated as they propagate into the CGM and mix on timescales $>$ 50 Myr., Comment: Accepted for publication in The Astrophysical Journal

Traditional star formation subgrid models implemented in cosmological galaxy formation simulations, such as that of Springel & Hernquist (2003, hereafter SH03), employ adjustable parameters to satisfy constraints measured in the local Universe. In recent years, however, theory and spatially-resolved simulations of the turbulent, multiphase, star-forming ISM have begun to produce new first-principles models, which when fully developed can replace traditional subgrid prescriptions. This approach has advantages of being physically motivated and predictive rather than empirically tuned, and allowing for varying environmental conditions rather than being tied to local Universe conditions. As a prototype of this new approach, by combining calibrations from the TIGRESS numerical framework with the Pressure-Regulated Feedback-Modulated (PRFM) theory, simple formulae can be obtained for both the gas depletion time and an effective equation of state. Considering galaxies in TNG50, we compare the "native" simulation outputs with post-processed predictions from PRFM. At TNG50 resolution, the total midplane pressure is nearly equal to the total ISM weight, indicating that galaxies in TNG50 are close to satisfying vertical equilibrium. The measured gas scale height is also close to theoretical equilibrium predictions. The slopes of the effective equations of states are similar, but with effective velocity dispersion normalization from SH03 slightly larger than that from current TIGRESS simulations. Because of this and the decrease in PRFM feedback yield at high pressure, the PRFM model predicts shorter gas depletion times than the SH03 model at high densities and redshift. Our results represent a first step towards implementing new, numerically calibrated subgrid algorithms in cosmological galaxy formation simulations., Comment: 33 pages, 12 figures, Accepted for publication in ApJ. This is a Learning the Universe Publication. All codes and data used to produce this work can be found at the following $\href{https://github.com/sultan-hassan/tng50-post-processing-prfm}{GitHub \,Link.}$

Arkenstone is a new scheme that allows multiphase, stellar feedback-driven winds to be included in coarse resolution cosmological simulations. The evolution of galactic winds and their subsequent impact on the circumgalactic medium are altered by exchanges of mass, energy, momentum, and metals between their component phases. These exchanges are governed by complex, small-scale physical processes that cannot be resolved in cosmological simulations. In this second presentation paper, we describe Arkenstone's novel cloud particle approach for modelling unresolvable cool clouds entrained in hot, fast winds. This general framework allows models of the cloud-wind interaction, derived from state-of-the-art high-resolution simulations, to be applied in a large-scale context. In this work, we adopt a cloud evolution model that captures simultaneous cloud mass loss to and gain from the ambient hot phase via turbulent mixing and radiative cooling, respectively. We demonstrate the scheme using non-cosmological idealized simulations of a galaxy with a realistic circumgalactic medium component, using the Arepo code. We show that the ability of a high-specific energy wind component to perform preventative feedback may be limited by heavy loading of cool clouds coupled into it. We demonstrate that the diverging evolution of clouds of initially differing masses leads to a complex velocity field for the cool phase and a cloud mass function that varies both spatially and temporally in a non-trivial manner. These latter two phenomena can manifest in the simulation because of our choice of a Lagrangian discretisation of the cloud population, in contrast to other proposed schemes. This is a Learning the Universe publication., Comment: Submitted to MNRAS. 27 pages, 11 figures. This is a Learning the Universe publication

Nanosatellites are proliferating as low-cost dedicated sensing systems with lean development cycles. Kyushu Institute of Technology and collaborators have launched a joint venture for a nanosatellite mission, VERTECS. The primary mission is to elucidate the formation history of stars by observing the optical-wavelength cosmic background radiation. The VERTECS satellite will be equipped with a small-aperture telescope and a high-precision attitude control system to capture the cosmic data for analysis on the ground. However, nanosatellites are limited by their onboard memory resources and downlink speed capabilities. Additionally, due to a limited number of ground stations, the satellite mission will face issues meeting the required data budget for mission success. To alleviate this issue, we propose an on-orbit system to autonomously classify and then compress desirable image data for data downlink prioritization and optimization. The system comprises a prototype Camera Controller Board (CCB) which carries a Raspberry Pi Compute Module 4 which is used for classification and compression. The system uses a lightweight Convolutional Neural Network (CNN) model to classify and determine the desirability of captured image data. The model is designed to be lean and robust to reduce the computational and memory load on the satellite. The model is trained and tested on a novel star field dataset consisting of data captured by the Sloan Digital Sky Survey (SDSS). The dataset is meant to simulate the expected data produced by the 6U satellite. The compression step implements GZip, RICE or HCOMPRESS compression, which are standards for astronomical data. Preliminary testing on the proposed CNN model results in a classification accuracy of about 100\% on the star field dataset, with compression ratios of 3.99, 5.16 and 5.43 for GZip, RICE and HCOMPRESS that were achieved on tested FITS image data., Comment: 14 pages

Recent flow cessation experiments on soft materials have shown a counter-intuitive non-monotonic relaxation of the shear stress: following the switch-off of a steady imposed shear flow, the stress initially decays before later increasing again. By simulating the soft glassy rheology model in a form extended to allow steady state shear banding, we show that the presence of shear bands prior to flow cessation can give rise to this phenomenon. We give a mechanistic understanding of the basic physics involved, in terms of (i) the decay of the shear bands after flow cessation, and (ii) the evolution of frustrated local stresses, governed by different time scales for plastic relaxation in each band. In particular, an elastic recoil in the unsheared band gives rise to negative local frustrated stresses, the slow release of which can cause an increase in macroscopic stress. Given that shear banding and frustrated local stresses arise widely across disordered soft solids, we argue that non-monotonic stress relaxation after flow cessation may occur in many different materials.

We show theoretically that essentially perfect elastostatic mechanical cloaking of a circular inclusion in a homogeneous surrounding medium can be achieved by means of a simple cloak comprising three concentric annuli, each formed of a homogeneous isotropic linear elastic material of prescribed shear modulus. Importantly, we find that the same combination of annuli will cloak any possible mode of imposed deformation or loading, for any randomly chosen admixture of imposed compression, pure shear and simple shear, without the need to re-design the cloak for different deformation modes. A full range of circular inclusions can be cloaked in this way, from soft to stiff. In consequence, we suggest that an inclusion of any arbitrary shape can also be cloaked, by first enveloping it in a stiff circle, then cloaking the combined structure with three annuli as described. Given that a single inclusion can be fully cloaked in this way, even at near field close to the cloaking perimeter, it also follows that multiple such neutral inclusions arranged with arbitrarily high packing fraction in a surrounding medium can also be cloaked. We confirm this by direct simulation. This indicates a possible route to fabricating composite materials with the same global mechanical response as a counterpart homogeneous material, and with uniform strain and stress fields outwith the cloaked inclusions., Comment: 9 pages, 7 figures

The rapid growth of large-scale AI models, particularly large language models has brought significant challenges in data privacy, computational resources, and accessibility. Traditional centralized architectures often struggle to meet required data security and scalability needs which hinders the democratization of AI systems. Nesa introduces a model-agnostic sharding framework designed for decentralized AI inference. Our framework uses blockchain-based sequential deep neural network sharding to distribute computational tasks across a diverse network of nodes based on a personalised heuristic and routing mechanism. This enables efficient distributed training and inference for recent large-scale models even on consumer-grade hardware. We use compression techniques like dynamic blockwise quantization and mixed matrix decomposition to reduce data transfer and memory needs. We also integrate robust security measures, including hardware-based trusted execution environments to ensure data integrity and confidentiality. Evaluating our system across various natural language processing and vision tasks shows that these compression strategies do not compromise model accuracy. Our results highlight the potential to democratize access to cutting-edge AI technologies by enabling secure and efficient inference on a decentralized network.

The need for data security and model integrity has been accentuated by the rapid adoption of AI and ML in data-driven domains including healthcare, finance, and security. Large models are crucial for tasks like diagnosing diseases and forecasting finances but tend to be delicate and not very scalable. Decentralized systems solve this issue by distributing the workload and reducing central points of failure. Yet, data and processes spread across different nodes can be at risk of unauthorized access, especially when they involve sensitive information. Nesa solves these challenges with a comprehensive framework using multiple techniques to protect data and model outputs. This includes zero-knowledge proofs for secure model verification. The framework also introduces consensus-based verification checks for consistent outputs across nodes and confirms model integrity. Split Learning divides models into segments processed by different nodes for data privacy by preventing full data access at any single point. For hardware-based security, trusted execution environments are used to protect data and computations within secure zones. Nesa's state-of-the-art proofs and principles demonstrate the framework's effectiveness, making it a promising approach for securely democratizing artificial intelligence., Comment: 25 pages, 5 figures

We use particle simulations to map comprehensively the shear rheology of dry and wet granular matter, in both fixed pressure and fixed volume protocols. At fixed pressure we find non-monotonic constitutive curves that are shear thinning, whereas at fixed volume we find non-monotonic constitutive curves that are shear thickening. We show that the presence of one non-monotonicity does not imply the other. Instead, there exists a signature in the volume fraction measured under fixed pressure that, when present, ensures non-monotonic constitutive curves at fixed volume. In the context of dry granular flow we show that gradient and vorticity bands arise under fixed pressure and volume respectively, as implied by the constitutive curves. For wet systems our results are consistent with a recent experimental observation of shear thinning at fixed pressure. We furthermore predict discontinuous shear thickening in the absence of critical load friction., Comment: 6 pages, 4 figures

Most numerical simulations of galaxy formation and evolution are unable to properly resolve the turbulent cascade at or below the resolution scale and turbulence models are required to capture the motion of eddies on those unresolved scales. In this study, we investigate the impact of turbulent metal diffusion models on multiphase outflows originating from dwarf galaxies ($M_{\rm halo} \sim 10^{10} - 10^{11}$ M$_\odot$). We use our state-of-the-art numerical model for the formation of single stars and non-equilibrium cooling and hydrogen chemistry. Our simulations are carried out at a mass resolution of $\sim$1 M$_{\odot}$, where the individual supernova explosions are resolved in terms of hot-phase generation and momentum input. We find that mass, energy, and metal loading factors are only weakly affected by the inclusion of a metal diffusion model. The metal enrichment factor at low altitude above the galactic disk is higher by around 20 per cent when the metal diffusion model is included. Specifically, we find more efficient cooling in the cold interstellar medium, as higher amounts of metals are kept in the cold dense phase. The most striking effect of the metal diffusion model is that, without metal diffusion, there is more rapid cooling in the hot phase and a reduced sound speed by a factor of two. Specifically, we find that the hot phase is more metal enriched in the case without metal diffusion leading to more rapid (over) cooling of that phase which is consistent with the higher sound speed we find in the runs with metal diffusion., Comment: 19 pages, 11 figures, submitted to ApJ, comments welcome!

We use the GIBLE suite of cosmological zoom-in simulations of Milky Way-like galaxies with additional super-Lagrangian refinement in the circumgalactic medium (CGM) to quantify the origin and evolution of CGM cold gas clouds. The origin of $z$\,$=$\,$0$ clouds can be traced back to recent ($\lesssim$\,$2$\,Gyr) outflows from the central galaxy ($\sim$\,45\,$\%$), condensation out of the hot phase of the CGM in the same time frame ($\sim$\,45\,$\%$), and to a lesser degree to satellite galaxies ($\lesssim$\,5\,$\%$). We find that in-situ condensation results from rapid cooling around local over-densities primarily seeded by the dissolution of the previous generation of clouds into the hot halo. About $\lesssim$\,10\,$\%$ of the cloud population is long lived, with their progenitors having already assembled $\sim$\,$2$\,Gyr ago. Collective cloud-cloud dynamics are crucial to their evolution, with coalescence and fragmentation events occurring frequently ($\gtrsim$\,20\,Gyr$^{-1}$). These interactions are modulated by non-vanishing pressure imbalances between clouds and their interface layers. The gas content of clouds is in a constant state of flux, with clouds and their surroundings exchanging mass at a rate of \mbox{$\gtrsim$\,$10^3$\,M$_\odot$\,Myr$^{-1}$}, depending on cloud relative velocity and interface vorticity. Furthermore, we find that a net magnetic tension force acting against the density gradient is capable of inhibiting cloud-background mixing. Our results show that capturing the distinct origins of cool CGM clouds, together with their physical evolution, requires high-resolution, cosmological galaxy formation simulations with both stellar and supermassive black hole feedback-driven outflows., Comment: Submitted to A&A

The scaling of galaxy properties with halo mass suggests that feedback loops regulate star formation, but there is no consensus yet about how those feedback loops work. To help clarify discussions of galaxy-scale feedback, Paper I presented a very simple model for supernova feedback that it called the minimalist regulator model. This followup paper interprets that model and discusses its implications. The model itself is an accounting system that tracks all of the mass and energy associated with a halo's circumgalactic baryons--the central galaxy's atmosphere. Algebraic solutions for the equilibrium states of that model reveal that star formation in low-mass halos self-regulates primarily by expanding the atmospheres of those halos, ultimately resulting in stellar masses that are insensitive to the mass-loading properties of galactic winds. What matters most is the proportion of supernova energy that couples with circumgalactic gas. However, supernova feedback alone fails to expand galactic atmospheres in higher-mass halos. According to the minimalist regulator model, an atmospheric contraction crisis ensues, which may be what triggers strong black-hole feedback. The model also predicts that circumgalactic medium properties emerging from cosmological simulations should depend largely on the specific energy of the outflows they produce, and we interpret the qualitative properties of several numerical simulations in light of that prediction., Comment: 15 pages, 3 figures, Submitted to ApJ

This paper presents a new framework for understanding the relationship between a galaxy and its circumgalactic medium (CGM). It focuses on how imbalances between heating and cooling cause either expansion or contraction of the CGM. It does this by tracking \textit{all} of the mass and energy associated with a halo's baryons, including their gravitational potential energy, even if feedback has pushed some of those baryons beyond the halo's virial radius. We show how a star-forming galaxy's equilibrium state can be algebraically derived within the context of this framework, and we analyze how the equilibrium star formation rate depends on supernova feedback. We consider the consequences of varying the mass loading parameter etaM = Mdot_wind / Mdot_* relating a galaxy's gas mass outflow rate (Mdot_wind) to its star formation rate (Mdot_*) and obtain results that challenge common assumptions. In particular, we find that equilibrium star formation rates in low-mass galaxies are generally insensitive to mass loading, and when mass loading does matter, increasing it actually results in \textit{more} star formation because more supernova energy is needed to resist atmospheric contraction., Comment: 18 pages, 5 figures, submitted to ApJ

Due to advances in observation and imaging technologies, modern astronomical satellites generate large volumes of data. This necessitates efficient onboard data processing and high-speed data downlink. Reflecting this trend is the VERTECS 6U Astronomical Nanosatellite. Designed for the observation of Extragalactic Background Light (EBL), this mission is expected to generate a substantial amount of image data, particularly within the confines of CubeSat capabilities. This paper introduces the VERTECS Camera Control Board (CCB), an open-source payload interface board leveraging Commercial Off-The-Shelf (COTS) components, with a Raspberry Pi Compute Module 4 at its core. The VERTECS CCB hardware and software have been designed from the ground up to serve as the sole interface between the VERTECS bus system and astronomical imaging payload, while providing compute capability not usually seen in nanosatellites of this class. Responsible for mission data processing, it will facilitate high-speed data transfer from the imaging payload via gigabit Ethernet, while also providing a high-bitrate serial connection to the payload X-band transmitter for mission data downlink. Additional interfaces for secondary payloads are provided via USB-C and standard 15-pin camera connectors. The Raspberry Pi embedded within the VERTECS CCB operates on a standard Linux distribution, streamlining the software development process. Beyond addressing the current mission's payload control and data handling requirements, the CCB sets the stage for future missions with heightened data demands. Furthermore, it supports the adoption of machine learning and other compute-intensive applications in orbit. This paper delves into the development of the VERTECS CCB, offering insights into the design and validation of this next-generation payload interface, to ensure that it can survive the rigors of space flight., Comment: 10 pages, to be presented at SPIE Software and Cyberinfrastructure for Astronomy VIII

We present a new simulation suite for the star-forming interstellar medium (ISM) in galactic disks using the TIGRESS-NCR framework. Distinctive aspects of our simulation suite are: (1) sophisticated and comprehensive numerical treatments of essential physical processes including magnetohydrodynamics, self-gravity, and galactic differential rotation, as well as photochemistry, cooling, and heating coupled with ray-tracing UV radiation transfer and resolved supernova feedback and (2) wide parameter coverage including metallicity over $Z'\equiv Z/Z_\odot\sim0.1-3$, gas surface density $\Sigma_{\rm gas}\sim5-150 M_{\odot}{\rm pc^{-2}}$, and stellar surface density $\Sigma_{\rm star}\sim 1-50 M_{\odot}{\rm pc^{-2}}$. The range of emergent star formation rate surface density is $\Sigma_{\rm SFR}\sim 10^{-4}-0.5 M_{\odot}{\rm kpc^{-2}yr^{-1}}$ and ISM total midplane pressure is $P_{\rm tot}/k_B=10^3-10^6{\rm cm^{-3}K}$, with $P_{\rm tot}$ equal to the ISM weight $W$. For given $\Sigma_{\rm gas}$ and $\Sigma_{\rm star}$, we find $\Sigma_{\rm SFR} \propto Z'^{0.3}$. We provide an interpretation based on the pressure-regulated feedback-modulated (PRFM) star formation theory. We characterize feedback modulation in terms of the yield $\Upsilon$, defined as the ratio of each stress to $\Sigma_{\rm SFR}$. The thermal feedback yield varies sensitively with both weight and metallicity as $\Upsilon_{\rm th}\propto W^{-0.46}Z'^{-0.53}$, while the combined turbulent and magnetic feedback yield shows weaker dependence $\Upsilon_{\rm turb+mag}\propto W^{-0.22}Z'^{-0.18}$. The reduction in $\Sigma_{\rm SFR}$ at low metallicity is due mainly to enhanced thermal feedback yield, resulting from reduced attenuation of UV radiation. With the metallicity-dependent calibrations we provide, PRFM theory can be used for a new subgrid star formation prescription in cosmological simulations where the ISM is unresolved., Comment: Resubmitted to ApJ after minor revision

In this paper we study the filamentary substructure of 3.3 $\mu$m PAH emission from JWST/NIRCam observations in the base of the M82 star-burst driven wind. We identify plume-like substructure within the PAH emission with widths of $\sim$50 pc. Several of the plumes extend to the edge of the field-of-view, and thus are at least 200-300 pc in length. In this region of the outflow, the vast majority ($\sim$70\%) of PAH emission is associated with the plumes. We show that those structures contain smaller scale "clouds" with widths that are $\sim$5-15 pc, and they are morphologically similar to the results of "cloud-crushing" simulations. We estimate the cloud-crushing time-scales of $\sim$0.5-3 Myr, depending on assumptions. We show this time scale is consistent with a picture in which these observed PAH clouds survived break-out from the disk rather than being destroyed by the hot wind. The PAH emission in both the midplane and the outflow is shown to tightly correlate with that of Pa$\alpha$ emission (from HST/NICMOS data), at the scale of both plumes and clouds, though the ratio of PAH-to-Pa$\alpha$ increases at further distances from the midplane. Finally, we show that the outflow PAH emission is suppressed in regions of the M82 wind that are bright in X-ray emission. Overall, our results are broadly consistent with a picture in which cold gas in galactic outflows is launched via hierarchically structured plumes, and those small scale clouds are more likely to survive the wind environment when collected into the larger plume structure., Comment: Submitted to MNRAS

Recoverable strain is the strain recovered once a stress is removed from a body, in the direction opposite to that in which the stress had acted. To date, the phenomenon has been understood as being elastic in origin: polymer chains stretched in the direction of an imposed stress will recoil after the stress is removed, for example. Any unrecoverable strain is instead attributed to irreversible plastic deformations. Here we study theoretically recoverable and unrecoverable strain within the soft glassy rheology model, aimed at describing the rheology of elastoplastic yield stress fluids and amorphous soft solids. We consider a material subject to the switch-on of a shear stress that is held constant before later being set back to zero, after which the strain recovery is observed. After an initially fast recoil that is indeed elastic in nature, consistent with the usual intuition, we find that significant subsequent strain recovery then arises not via further recoil of elasticity but instead by `reverse plasticity', in a sense that we discuss carefully. Also unexpectedly, although in rare parameter regimes, this plastic part of the strain post switch-off does not always in fact recover in the negative direction, counter to that of the previously imposed stress, but can sometimes continue to accumulate in the forward direction. The recovery is then non-monotonic overall, reminiscent of recent observations of non-monotonic stress relaxation after straining, which have been attributed to complex material memory effects. We elucidate the mechanisms underlying these behaviours in terms of the evolution of the SGR model's population of elastoplastic elements, and suggest connections with the notion of `reversible plasticity', as discussed in the recent physics literature., Comment: submitted for publication, 11 pages, 6 figures

We present the results of direct-method metallicity measurements in the disk and outflow of the low-metallicity starburst galaxy NGC 1569. We use Keck Cosmic Web Imager observations to map the galaxy across 54$\arcsec$ (800 pc) along the major axis and 48$\arcsec$ (700 pc) along the minor axis with a spatial resolution of 1$\arcsec$ ($\sim$15 pc). We detect common strong emission lines ([\ion{O}{III}] $\lambda$5007, H$\beta$, [\ion{O}{II}] $\lambda$3727) and the fainter [\ion{O}{III}] $\lambda$4363 auroral line, which allows us to measure electron temperature ($T_e$) and metallicity. Theory suggests that outflows drive metals out of the disk driving observed trends between stellar mass and gas-phase metallicity. Our main result is that the metallicity in the outflow is similar to that of the disk, $Z_{\rm out} / Z_{\rm ISM} \approx 1$. This is consistent with previous absorption line studies in higher mass galaxies. Assumption of a mass-loading factor of $\dot{M}_{\rm out}/{\rm SFR}\sim3$ makes the metal-loading of NGC 1569 consistent with expectations derived from the mass-metallicity relationship. Our high spatial resolution metallicity maps reveal a region around a supermassive star cluster (SSC-B) with distinctly higher metallicity and higher electron density, compared to the disk. Given the known properties of SSC-B the higher metallicity and density of this region are likely the result of star formation-driven feedback acting on the local scale. Overall, our results are consistent with the picture in which metal-enriched winds pollute the circumgalactic medium surrounding galaxies, and thus connect the small-scale feedback processes to large-scale properties of galaxy halos., Comment: 15 pages, 11 figures, accepted by MNRAS

We use a cosmological zoom-in simulation of a Milky Way-like galaxy to study and quantify the topology of magnetic field lines around cold gas clouds in the circumgalactic medium (CGM). This simulation is a new addition to Project GIBLE, a suite of cosmological magnetohydrodynamical simulations of galaxy formation with preferential super-Lagrangian refinement in the CGM, reaching an unprecedented (CGM) gas mass resolution of $\sim$ $225$ M$_\odot$. To maximize statistics and resolution, we focus on a sample of $\sim$ $200$ clouds with masses of $\sim$ $10^6$ M$_\odot$. The topology of magnetic field lines around clouds is diverse, from threading to draping, and there is large variation in the magnetic curvature ($\kappa$) within cloud-background interfaces. We typically find little variation of $\kappa$ between upstream and downstream cloud faces, implying that strongly draped configurations are rare. In addition, $\kappa$ correlates strongly with multiple properties of the interface and the ambient background, including cloud overdensity and relative velocity, suggesting that cloud properties impact the topology of interface magnetic fields., Comment: Accepted for publication (A&A Letters); 5 pages, 4 figures

We measure resolved (kiloparsec-scale) outflow properties in a sample of 10 starburst galaxies from the DUVET sample, using Keck/KCWI observations of H$\beta$ and [OIII]~$\lambda$5007. We measure $\sim450$ lines-of-sight that contain outflows, and use these to study scaling relationships of outflow velocity ($v_{\rm out}$), mass-loading factor ($\eta$; mass outflow rate per SFR) and mass flux ($\dot{\Sigma}_{\rm out}$; mass outflow rate per area) with co-located SFR surface density ($\Sigma_{\rm SFR}$) and stellar mass surface density ($\Sigma_{\ast}$). We find strong, positive correlations of $\dot{\Sigma}_{\rm out} \propto \Sigma_{\rm SFR}^{1.2}$ and $\dot{\Sigma}_{\rm out} \propto \Sigma_{\ast}^{1.7}$. We also find shallow correlations between $v_{\rm out}$ and both $\Sigma_{\rm SFR}$ and $\Sigma_{\ast}$. Our resolved observations do not suggest a threshold in outflows with $\Sigma_{\rm SFR}$, but rather we find that the local specific SFR ($\Sigma_{\rm SFR}/\Sigma_\ast$) is a better predictor of where outflows are detected. We find that outflows are very common above $\Sigma_{\rm SFR}/\Sigma_\ast\gtrsim 0.1$~Gyr$^{-1}$ and rare below this value. We argue that our results are consistent with a picture in which outflows are driven by supernovae, and require more significant injected energy in higher mass surface density environments to overcome local gravity. The correlations we present here provide a statistically robust, direct comparison for simulations and higher redshift results from JWST., Comment: 14 pages, 7 figures, plus 4 figures in appendix, submitted to MNRAS

We make an in-depth analysis of different AGN jet models' signatures, inducing quiescence in galaxies with a halo mass of $10^{12} M_\odot$. Three jet models, including cosmic ray-dominant, hot thermal, and precessing kinetic jets, are studied at two energy flux levels each, compared to a jet-free, stellar feedback-only simulation. We examine the distribution of Mg II, O VI, and O VIII ions, alongside gas temperature and density profiles. Low-energy ions, like Mg II, concentrate in the ISM, while higher energy ions, e.g., O VIII, prevail at the AGN jet cocoon's edge. High-energy flux jets display an isotropic ion distribution with lower overall density. High-energy thermal or cosmic ray jets pressurize at smaller radii, significantly suppressing core density. The cosmic ray jet provides extra pressure support, extending cool and warm gas distribution. A break in the ion-to-mass ratio slope in O VI and O VIII is demonstrated in the ISM-to-CGM transition (between 10-30 kpc), growing smoothly towards the CGM at greater distances., Comment: 17 pages, 13 figures

Soft amorphous materials are viscoelastic solids ubiquitously found around us, from clays and cementitious pastes to emulsions and physical gels encountered in food or biomedical engineering. Under an external deformation, these materials undergo a noteworthy transition from a solid to a liquid state that reshapes the material microstructure. This yielding transition was the main theme of a workshop held from January 9 to 13, 2023 at the Lorentz Center in Leiden. The manuscript presented here offers a critical perspective on the subject, synthesizing insights from the various brainstorming sessions and informal discussions that unfolded during this week of vibrant exchange of ideas. The result of these exchanges takes the form of a series of open questions that represent outstanding experimental, numerical, and theoretical challenges to be tackled in the near future., Comment: 21 pages, 7 figures, perspective on the workshop 'Yield stress and fluidization in brittle and ductile amorphous systems' held from January 9 to 13, 2023 at the Lorentz Center in Leiden

Motivated by recent experiments studying the creep and breakup of a protein gel under stress, we introduce a simple mesoscopic model for the irreversible failure of gels and fibrous materials, and demonstrate it to capture much of the phenomenology seen experimentally. This includes a primary creep regime in which the shear rate decreases as a power law over several decades of time, a secondary crossover regime in which the shear rate attains a minimum, and a tertiary regime in which the shear rate increases dramatically up to a finite time singularity, signifying irreversible material failure. The model also captures a linear Monkman-Grant scaling of the failure time with the earlier time at which the shear rate attained its minimum, and a Basquin-like power law scaling of the failure time with imposed stress, as seen experimentally. The model furthermore predicts a slow accumulation of low levels of material damage during primary creep, followed by the growth of fractures leading to sudden material failure, as seen experimentally., Comment: 4 pages, 5 figures. Accepted for publication, Soft Matter

We present CloudFlex, a new open-source tool for predicting the absorption-line signatures of cool gas in galaxy halos with complex small-scale structure. Motivated by analyses of cool material in hydrodynamical simulations of turbulent, multiphase media, we model individual cool gas structures as assemblies of cloudlets with a power-law distribution of cloudlet mass $\propto m_{\rm cl}^{-\alpha}$ and relative velocities drawn from a turbulent velocity field. The user may specify $\alpha$, the lower limit of the cloudlet mass distribution ($m_{\rm cl,min}$), and several other parameters that set the total mass, size, and velocity distribution of the complex. We then calculate the MgII 2796 absorption profiles induced by the cloudlets along pencil-beam lines of sight. We demonstrate that at fixed metallicity, the covering fraction of sightlines with equivalent widths $W_{2796} < 0.3$ Ang increases significantly with decreasing $m_{\rm cl,min}$, cool cloudlet number density ($n_{\rm cl}$), and cloudlet complex size. We then present a first application, using this framework to predict the projected $W_{2796}$ distribution around ${\sim}L^*$ galaxies. We show that the observed incidences of $W_{2796}>0.3$ Ang sightlines within 10 kpc < $R_{\perp}$ < 50 kpc are consistent with our model over much of parameter space. However, they are underpredicted by models with $m_{\rm cl,min}\ge100M_{\odot}$ and $n_{\rm cl}\ge0.03$ $\rm cm^{-3}$, in keeping with a picture in which the inner cool circumgalactic medium (CGM) is dominated by numerous low-mass cloudlets ($m_{\rm cl}\lesssim100M_{\odot}$) with a volume filling factor ${\lesssim}1\%$. When used to simultaneously model absorption-line datasets built from multi-sightline and/or spatially-extended background probes, CloudFlex will enable detailed constraints on the size and velocity distributions of structures comprising the photoionized CGM., Comment: 22 pages, 7 figures. Submitted to AAS Journals, with minor modifications. Comments welcome. (1) Co-first authors who made equal contributions to this work

In the absence of supplementary heat, the radiative cooling of halo gas around massive galaxies (Milky Way mass and above) leads to an excess of cold gas or stars beyond observed levels. AGN jet-induced heating is likely essential, but the specific properties of the jets remain unclear. Our previous work (Su et al. 2021) concludes from simulations of a halo with $10^{14} M_\odot$ that a successful jet model should have an energy flux comparable to the free-fall energy flux at the cooling radius and should inflate a sufficiently wide cocoon with a long enough cooling time. In this paper, we investigate three jet modes with constant fluxes satisfying the criteria, including high-temperature thermal jets, cosmic ray (CR)-dominant jets, and widely precessing kinetic jets in $10^{12}-10^{15}\,{\rm M}_{\odot}$ halos using high-resolution, non-cosmological MHD simulations with the FIRE-2 (Feedback In Realistic Environments) stellar feedback model, conduction, and viscosity. We find that scaling the jet energy according to the free-fall energy at the cooling radius can successfully suppress the cooling flows and quench galaxies without obviously violating observational constraints. We investigate an alternative scaling method in which we adjust the energy flux based on the total cooling rate within the cooling radius. However, we observe that the strong interstellar medium (ISM) cooling dominates the total cooling rate in this scaling approach, resulting in a jet flux that exceeds the amount needed to suppress the cooling flows. With the same energy flux, the CR-dominant jet is most effective in suppressing the cooling flow across all the surveyed halo masses due to the enhanced CR pressure support. We confirm that the criteria for a successful jet model, which we proposed in Su et al. (2021), work across a much wider range, encompassing halo masses of $10^{12}-10^{15} {\rm M_\odot}$., Comment: 15 pages, 10 figures, Submitted to MNRAS; comments welcome!

A new class of extragalactic astronomical sources discovered in 2021, named Odd Radio Circles (ORCs, Norris et al. 2021), are large rings of faint, diffuse radio continuum emission spanning ~1 arcminute on the sky. Galaxies at the centers of several ORCs have photometric redshifts of z~0.3-0.6, implying physical scales of several 100 kiloparsecs in diameter for the radio emission, the origin of which is unknown. Here we report spectroscopic data on an ORC including strong [OII] emission tracing ionized gas in the central galaxy of ORC4 at z=0.4512. The physical extent of the [OII] emission is ~40 kpc in diameter, larger than expected for a typical early-type galaxy (Pandya et al, 2017) but an order of magnitude smaller than the large-scale radio continuum emission. We detect a ~200 km/s velocity gradient across the [OII] nebula, as well as a high velocity dispersion of ~180 km/s. The [OII] equivalent width (EW, ~50 Ang) is extremely high for a quiescent galaxy. The morphology, kinematics, and strength of the [OII] emission are consistent with the infall of shock ionized gas near the galaxy, following a larger-scale, outward moving shock driven by a galactic wind. Both the extended optical and radio emission, while observed on very different scales, may therefore result from the same dramatic event., Comment: 7 figures, accepted to Nature

The origin of the cold phase in the CGM is a highly debated question. We investigate the contribution of satellite galaxies to the cold gas budget in the circumgalactic medium (CGM)of a Milky Way-like host galaxy. We perform controlled experiments with three different satellite mass distributions and identify several mechanisms by which satellites can add cold gas to the CGM, including ram pressure stripping and induced cooling in the mixing layer of the stripped cold gas. These two mechanisms contribute a comparable amount of cold gas to the host CGM. We find that the less massive satellites ($\leq 10^9 M_\odot$) not only lose all of their cold gas in a short period ($\sim$ 0.5-1 Gyr), but their stripped cold clouds also mix with the hot CGM gas and get heated up quickly. However, stellar feedback from these less massive satellites can hugely alter the fate of their stripped gas. Feedback speeds up the destruction of the stripped cold clouds from these satellites by making them more diffuse with more surface area. On the other hand, the more massive satellites (LMC or SMC-like $\sim 10^{10} M_\odot$) can add cold gas to the total gas budget of the host CGM for several Gyrs., Comment: 17 pages, 12 figures, 2 tables Accepted for publication in MNRAS on Oct 6, 2023

British Antarctic Survey (BAS) researchers launch annual expeditions to the Antarctic in order to estimate Antarctic Krill biomass and assess the change from previous years. These comparisons provide insight into the effects of the current environment on this key component of the marine food chain. In this work we have developed tools for automating the data collection and analysis process, using web-based image annotation tools and deep learning image classification and regression models. We achieve highly accurate krill instance segmentation results with an average 77.28% AP score, as well as separate maturity stage and length estimation of krill specimens with 62.99% accuracy and a 1.98mm length error respectively., Comment: Accepted to MVEO @ BMVC 2023