Search

We report that the neutral hydrogen (HI) mass density of the Universe ($\rho_{HI}$) increases with cosmic time since $z \sim 5$, peaks at $z \sim 3$, and then decreases toward $z \sim 0$. This is the first result of Qz5, our spectroscopic survey of 63 quasars at $z \gtrsim 5$ with VLT/X-SHOOTER and Keck/ESI aimed at characterizing intervening HI gas absorbers at $z \sim 5$. The main feature of Qz5 is the high resolution ($R \sim 7000 - 9000$) of the spectra, which allows us to (1) accurately detect high column density HI gas absorbers in an increasingly neutral intergalactic medium at $z \sim 5$ and (2) determine the reliability of previous $\rho_{HI}$ measurements derived with lower resolution spectroscopy. We find 5 intervening Damped Ly$\alpha$ absorbers (DLAs) at $z > 4.5$, which corresponds to the lowest DLA incidence rate ($0.034^{0.05}_{0.02}$) at $z \gtrsim 2$. We also measure the lowest $\rho_{HI}$ at $z \gtrsim 2$ from our sample of DLAs and subDLAs, corresponding to $\rho_{HI} = 0.56^{0.82}_{0.31} \times 10^8~$M$_{\odot}~$Mpc$^{-3}$ at $z \sim 5$. Taking into account our measurements at $z \sim 5$ and systematic biases in the DLA detection rate at lower spectral resolutions, we conclude that $\rho_{HI}$ doubles from $z \sim 5$ to $z \sim 3$. From these results emerges a qualitative agreement between how the cosmic densities of HI gas mass, molecular gas mass, and star-formation rate build up with cosmic time., Comment: Accepted for publication in ApJ. Main text is composed of 18 pages and 8 figures

Context. The new giant segmented mirror telescopes will use laser guide stars (LGS) for their adaptive optics (AO) systems. Two options to use as wavefront sensors (WFS) are the Shack-Hartmann wavefront sensor (SHWFS) and the pyramid wavefront sensor (PWFS). Aims. In this paper, we compare the noise performance of the PWFS and the SHWFS. We aim to find which of the two WFS is the best to use in a single or tomographic configuration. Methods. To compute the noise performance we extended a noise model developed for the PWFS to be used with the SHWFS. To do this, we expressed the centroiding algorithm of the SHWFS as a matrix-vector multiplication, which allowed us to use the statistics of noise to compute its propagation through the AO loop. We validated the noise model with end-to-end simulations for telescopes of 8 and 16 m in diameter. Results. For an AO system with only one WFS, we found that, given the same number of subapertures, the PWFS outperforms the SHWFS. For a 40 m telescope, the limiting magnitude of the PWFS is around 1 magnitude higher than the SHWFS. When using multiple WFS and a Generalized least squares estimator to combine the signal, our model predicts that in a tomographic system, the SHWFS performs better than the PWFS having a limiting magnitude 0.3 magnitudes higher. If using sub-electron RON detectors for the PWFS, then the performances are almost identical between the two WFSs Conclusions. We conclude that when using a single WFS with LGS, the PWFS is a better alternative than the SH. However, for a tomographic system, either would have almost the same performance.

We report evidence of galaxy assembly bias - the correlation between galaxy properties and biased secondary halo properties at fixed halo mass (M$_H$) - in the stellar-to-halo mass relation (SHMR) for red central galaxies from the Sloan Digital Sky Survey. In the M$_H = 10^{11.5}-10^{13.5} h^{-1}$ M$_{\odot}$ range, central galaxy stellar mass (M$_*$) is correlated with the number density of galaxies within $10 h^{-1}$ Mpc ($\delta_{10}$), a common proxy for halo formation time. This galaxy assembly bias signal is also present when M$_H$, M$_*$, and $\delta_{10}$ are substituted with group luminosity, galaxy luminosity, and metrics of the large-scale density field. To associate differences in $\delta_{10}$ with variations in halo formation time, we fitted a model that accounts for (1) errors in the M$_H$ measured by the Tinker 2021, 2022 group catalog and (2) the level of correlation between halo formation time and M$_*$ at fixed M$_H$. Fitting of this model yields that (1) errors in M$_H$ are 0.15 dex and (2) halo formation time and M$_*$ are strongly correlated (Spearman's rank correlation coefficient ~0.85). At fixed M$_H$, variations of ~0.4 dex in M$_*$ are associated with ~1-3 Gyr variations in halo formation time and in galaxy formation time (from stellar population fitting; Oyarz\'un et al. 2022). These results are indicative that halo properties other than M$_H$ can impact central galaxy assembly., Comment: Accepted for publication in ApJ. 11 pages and 6 figures

Earth system models (ESM) demand significant hardware resources and energy consumption to solve atmospheric chemistry processes. Recent studies have shown improved performance from running these models on GPU accelerators. Nonetheless, there is room for improvement in exploiting even more GPU resources. This study proposes an optimized distribution of the chemical solver's computational load on the GPU, named Block-cells. Additionally, we evaluate different configurations for distributing the computational load in an NVIDIA GPU. We use the linear solver from the Chemistry Across Multiple Phases (CAMP) framework as our test bed. An intermediate-complexity chemical mechanism under typical atmospheric conditions is used. Results demonstrate a 35x speedup compared to the single-CPU thread reference case. Even using the full resources of the node (40 physical cores) on the reference case, the Block-cells version outperforms them by 50%. The Block-cells approach shows promise in alleviating the computational burden of chemical solvers on GPU architectures., Comment: Accepted manuscript

We use the Ultraviolet Imaging of the Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey fields (UVCANDELS) to measure half-light radii in the rest-frame far-UV for $\sim$16,000 disk-like galaxies over $0.5\leq z \leq 3$. We compare these results to rest-frame optical sizes that we measure in a self-consistent way and find that the stellar mass-size relation of disk galaxies is steeper in the rest-frame UV than in the optical across our entire redshift range. We show that this is mainly driven by massive galaxies ($\gtrsim10^{10}$M$_\odot$), which we find to also be among the most dusty. Our results are consistent with the literature and have commonly been interpreted as evidence of inside-out growth wherein galaxies form their central structures first. However, they could also suggest that the centers of massive galaxies are more heavily attenuated than their outskirts. We distinguish between these scenarios by modeling and selecting galaxies at $z=2$ from the VELA simulation suite in a way that is consistent with UVCANDELS. We show that the effects of dust alone can account for the size differences we measure at $z=2$. This indicates that, at different wavelengths, size differences and the different slopes of the stellar mass-size relation do not constitute evidence for inside-out growth., Comment: Accepted for publication in ApJ. 22 pages, 12 figures, and 4 tables

We have developed a novel, compact and cost-effective magneto-optical method for quantifying the spin-orbit torque (SOT) effective field vector (hSO) in magnetic thin films subjected to spin current injection. The damping-like (hSODL) component of the vector is obtained by the polar Kerr response arising from the out-of-plane magnetization tilting, whereas the field-like component (hSODL) is obtained by current-induced hysteresis-loop shifting study, using conventional longitudinal Kerr magnetometry. We tested our method in FM/NM bilayers comprising NiFe, CoFeB (ferromagnetic layers) and Pt, Pd, Ta (non-magnetic layers). Our findings revealed a damping-like SOT efficiency xiDL of 0.089 pm 0.006,0.019 pm 0.002, and -0.132 pm 0.009 for Pt, Pd, and Ta, respectively. The hSOFL/hSODL ratio was 0.35 pm 0.02 for NiFe/Pt and 0.14 pm 0.002 for Ta/CoFeB bilayers when the ferromagnetic layer thickness is 4nm. A key advancement over the state-of-art magneto-optical methods is the use of an oblique light incidence angle, which allows switching between measuring modes for hSODL and hSOFL, without altering the experimental setup. Moreover, our approach relies exclusively on first-order Kerr effects, thereby ensuring its broad applicability to any type of ferromagnetic material., Comment: 6 pages, 3 figures, 1 table

The use of artificial Laser Guide Stars (LGS) is planned for the new generation of giant segmented mirror telescopes, to extend the sky coverage of their adaptive optics systems. The LGS, being a 3D object at a finite distance will have a large elongation that will affect its use with the Shack-Hartmann (SH) wavefront sensor. In this paper, we compute the expected performance for a Pyramid WaveFront Sensor (PWFS) using a LGS for a 40 m telescope affected by photon noise, and also extend the analysis to a flat 2D object as reference. We developed a new way to discretize the LGS, and a new, faster method of propagating the light for any Fourier Filtering wavefront sensors (FFWFS) when using extended objects. We present the use of a sensitivity model to predict the performance of a closed-loop adaptive optic system. We optimized a point source calibrated interaction matrix to accommodate the signal of an extended object, by means of computing optical gains using a convolutional model. We found that the sensitivity drop, given the size of the extended laser source, is large enough to make the system operate in a low-performance regime given the expected return flux of the LGS. The width of the laser beam, rather than the thickness of the sodium layer was identified as the limiting factor. Even an ideal, flat LGS will have a drop in performance due to the flux of the LGS, and small variations in the return flux will result in large variations in performance. We conclude that knife-edge-like wavefront sensors, such as the PWFS, are not recommended for their use with LGS for a 40 m telescope, as they will operate in a low-performance regime, given the size of the extended object.

We present Keck Cosmic Web Imager (KCWI) Ly$\alpha$ integral field spectroscopy of the fields surrounding 14 Damped Ly$\alpha$ absorbers (DLAs) at $z \approx 2$. Of these 14 DLAs, 9 have high metallicities ([M/H]$~> -0.3$), and 4 of those 9 feature a CO-emitting galaxy at an impact parameter $\lesssim 30$ kpc. Our search reaches median Ly$\alpha$ line flux sensitivities of $\sim 2 \times 10^{-17}$ erg s$^{-1}$ cm$^{-2}$ over apertures of $\sim6$ kpc and out to impact parameters of $\sim50$ kpc. We recover the Ly$\alpha$ flux of three known Ly$\alpha$-emitting H I-selected galaxies in our sample. In addition, we find two Ly$\alpha$ emitters at impact parameters of $\approx 50-70$ kpc from the high metallicity DLA at $z \approx 1.96$ toward QSO B0551-366. This field also contains a massive CO-emitting galaxy at an impact parameter of $\approx 15$ kpc. Apart from the field with QSO B0551-366, we do not detect significant Ly$\alpha$ emission in any of the remaining 8 high-metallicity DLA fields. Considering the depth of our observations and our ability to recover previously known Ly$\alpha$ emitters, we conclude that H I-selected galaxies associated with high-metallicity DLAs at $z \approx 2$ are dusty, and therefore might feature low Ly$\alpha$ escape fractions. Our results indicate that complementary approaches -- using Ly$\alpha$, CO, H$\alpha$, and [C II] 158$\mu$m emission -- are necessary to identify the wide range of galaxy types associated with $z \approx 2$ DLAs., Comment: Accepted for publication in ApJ. 17 pages and 9 figures. Second version with corrections prior to publication

The SARS-CoV-2 pandemic has emphasised the importance of developing a universal vaccine that can protect against current and future variants of the virus. The present study proposes a novel conditional protein Language Model architecture, called Vaxformer, which is designed to produce natural-looking antigenicity-controlled SARS-CoV-2 spike proteins. We evaluate the generated protein sequences of the Vaxformer model using DDGun protein stability measure, netMHCpan antigenicity score, and a structure fidelity score with AlphaFold to gauge its viability for vaccine development. Our results show that Vaxformer outperforms the existing state-of-the-art Conditional Variational Autoencoder model to generate antigenicity-controlled SARS-CoV-2 spike proteins. These findings suggest promising opportunities for conditional Transformer models to expand our understanding of vaccine design and their role in mitigating global health challenges. The code used in this study is available at https://github.com/aryopg/vaxformer .

We combine an unprecedented MaNGA sample of over 3,000 passive galaxies in the stellar mass range 10^{9}-10^{12} Msun with the Sloan Digital Sky Survey group catalog by Tinker to quantify how central and satellite formation, quantified by radial profiles in stellar age, [Fe/H], and [Mg/Fe], depends on the stellar mass of the galaxy (M*) and the mass of the host halo (Mh). After controlling for M* and Mh, the stacked spectra of centrals and satellites beyond the effective radius (r_e) show small, yet significant differences in multiple spectral features at the 1% level. According to spectral fitting with the code alf, a primary driver of these differences appears to be [Mg/Fe] variations, suggesting that stellar populations in the outskirts of satellites formed more rapidly than the outer populations of centrals. To probe the physical mechanisms that may be responsible for this signal, we examined how satellite stellar populations depend on Mh. We find that satellites in high-Mh halos show older stellar ages, lower [Fe/H], and higher [Mg/Fe] compared to satellites in low-Mh halos, especially for M*=10^{9.5}-10^{10.5} Msun. These signals lend support to environmentally driven processes that quench satellite galaxies, although variations in the merger histories of central and satellite galaxies also emerge as a viable explanation., Comment: Accepted for publication in ApJ. 19 pages and 6 figures

The complexity of combustion simulations demands the latest high-performance computing tools to accelerate its time-to-solution results. A current trend on HPC systems is the utilization of CPUs with SIMD or vector extensions to exploit data parallelism. Our work proposes a strategy to improve the automatic vectorization of finite element-based scientific codes. The approach applies a parametric configuration to the data structures to help the compiler detect the block of codes that can take advantage of vector computation while maintaining the code portable. A detailed analysis of the computational impact of this methodology on the different stages of a CFD solver is studied on the PRECCINSTA burner simulation. Our parametric implementation has proven to help the compiler generate more vector instructions in the assembly operation: this results in a reduction of up to 9.3 times of the total executed instruction maintaining constant the Instructions Per Cycle and the CPU frequency. The proposed strategy improves the performance of the CFD case under study up to 4.67 times on the MareNostrum 4 supercomputer.

We compare stellar mass surface density, metallicity, age, and line-of-sight velocity dispersion profiles in massive ($M_*\geq10^{10.5}\,\mathrm{M_\odot}$) present-day early-type galaxies (ETGs) from the MaNGA survey with simulated galaxies from the TNG100 simulation of the IllustrisTNG suite. We find an excellent agreement between the stellar mass surface density profiles of MaNGA and TNG100 ETGs, both in shape and normalisation. Moreover, TNG100 reproduces the shapes of the profiles of stellar metallicity and age, as well as the normalisation of velocity dispersion distributions of MaNGA ETGs. We generally also find good agreement when comparing the stellar profiles of central and satellite galaxies between MaNGA and TNG100. An exception is the velocity dispersion profiles of very massive ($M_*\gtrsim10^{11.5}\,\mathrm{M_\odot}$) central galaxies, which, on average, are significantly higher in TNG100 than in MaNGA ($\approx50\,\mathrm{km\,s^{-1}}$). We study the radial profiles of $\mathit{in}$-$\mathit{situ}$ and $\mathit{ex}$-$\mathit{situ}$ stars in TNG100 and discuss the extent to which each population contributes to the observed MaNGA profiles. Our analysis lends significant support to the idea that high-mass ($M_*\gtrsim10^{11}\,\mathrm{M_\odot}$) ETGs in the present-day Universe are the result of a merger-driven evolution marked by major mergers that tend to homogenise the stellar populations of the progenitors in the merger remnant., Comment: 22 pages, 9 figures, accepted for publication in MNRAS

We analyze spatially resolved and co-added SDSS-IV MaNGA spectra with signal-to-noise ~100 from 2200 passive central galaxies (z~0.05) to understand how central galaxy assembly depends on stellar mass (M*) and halo mass (Mh). We control for systematic errors in Mh by employing a new group catalog from Tinker (2020a,b) and the widely-used Yang et al. (2007) catalog. At fixed M*, the strength of several stellar absorption features varies systematically with Mh. Completely model-free, this is one of the first indications that the stellar populations of centrals with identical M* are affected by the properties of their host halos. To interpret these variations, we applied full spectral fitting with the code alf. At fixed M*, centrals in more massive halos are older, show lower [Fe/H], and have higher [Mg/Fe] with 3.5 sigma confidence. We conclude that halos not only dictate how much M* galaxies assemble, but also modulate their chemical enrichment histories. Turning to our analysis at fixed Mh, high-M* centrals are older, show lower [Fe/H], and have higher [Mg/Fe] for Mh>10^{12}Msun/h with confidence > 4 sigma. While massive passive galaxies are thought to form early and rapidly, our results are among the first to distinguish these trends at fixed Mh. They suggest that high-M* centrals experienced unique early formation histories, either through enhanced collapse and gas fueling, or because their halos were early-forming and highly concentrated, a possible signal of galaxy assembly bias., Comment: Accepted for publication in ApJ. 28 pages and 12 figures

GPUs have climbed up to the top of supercomputer systems making life harder to many legacy scientific codes. Nowadays, many recipes are being used in such code's portability, without any clarity of which is the best option. We present a comparative analysis of the two most common approaches, CUDA and OpenACC, into the multi-physics CFD code Alya. Our focus is the combustion problems which are one of the most computing demanding CFD simulations. The most computing-intensive parts of the code were analyzed in detail. New data structures for the matrix assembly step have been created to facilitate a SIMD execution that benefits vectorization in the CPU and stream processing in the GPU. As a result, the CPU code has improved its performance by up to 25%. In GPU execution, CUDA has proven to be up to 2 times faster than OpenACC for the assembly of the matrix. On the contrary, similar performance has been obtained in the kernels related to vector operations used in the linear solver, where there is minimal memory reuse.

Field Programmable Gate Arrays generate algorithmic specific architectures that improve the code's FLOP per watt ratio. Such devices are re-gaining interest due to the rise of new tools that facilitate their programming, such as OmpSs. The computational fluid dynamics community is always investigating new architectures that can improve its algorithm's performance. Commonly, those algorithms have a low arithmetic intensity and only reach a small percentage of the peak performance. The sparse matrix-vector multiplication is one of the most time-consuming operations on unstructured simulations. The matrix's sparsity pattern determines the indirect memory accesses of the multiplying vector. This data path is hard to predict, making traditional implementations fail. In this work, we present an FPGA architecture that maximizes the vector's re-usability by introducing a cache-like architecture. The cache is implemented as a circular list that maintains the BRAM vector components while needed. Following this strategy, up to 16 times of acceleration is obtained compared to a naive implementation of the algorithm.

We derive ages, metallicities, and individual element abundances of early- and late-type galaxies (ETGs and LTGs) out to 1.5 R$_e$. We study a large sample of 1900 galaxies spanning $8.6 - 11.3 \log M/M_{\odot}$ in stellar mass, through key absorption features in stacked spectra from the SDSS-IV/MaNGA survey. We use mock galaxy spectra with extended star formation histories to validate our method for LTGs and use corrections to convert the derived ages into luminosity- and mass-weighted quantities. We find flat age and negative metallicity gradients for ETGs and negative age and negative metallicity gradients for LTGs. Age gradients in LTGs steepen with increasing galaxy mass, from $-0.05\pm0.11~\log$ Gyr/R$_e$ for the lowest mass galaxies to $-0.82\pm0.08~\log$ Gyr/R$_e$ for the highest mass ones. This strong gradient-mass relation has a slope of $-0.70\pm0.18$. Comparing local age and metallicity gradients with the velocity dispersion $\sigma$ within galaxies against the global relation with $\sigma$ shows that internal processes regulate metallicity in ETGs but not age, and vice versa for LTGs. We further find that metallicity gradients with respect to local $\sigma$ show a much stronger dependence on galaxy mass than radial metallicity gradients. Both galaxy types display flat [C/Fe] and [Mg/Fe], and negative [Na/Fe] gradients, whereas only LTGs display gradients in [Ca/Fe] and [Ti/Fe]. ETGs have increasingly steep [Na/Fe] gradients with local $\sigma$ reaching $6.50\pm0.78$ dex/$\log$ km/s for the highest masses. [Na/Fe] ratios are correlated with metallicity for both galaxy types across the entire mass range in our sample, providing support for metallicity dependent supernova yields., Comment: 21 pages, 21 figures, 4 tables + Appendix

Magnetic skyrmions are nontrivial spin textures which resist external perturbations, being promising candidates for the next generation recording devices. Nevertheless, a major challenge in realizing skyrmion-based devices is the stabilization of ordered arrays of these spin textures under ambient conditions and zero applied field. Here, we demonstrate for the first time the formation and stabilization of magnetic skyrmions on arrays of self-assembled hexagonal nanodomes taking advantage of the intrinsic properties of its curved geometry. Magnetic force microscopy images from the arrays of 100 nm nanodomes showed stable skyrmions at zero field that are arranged following the topography of the nanostructure. Micromagnetic simulations are compared to the experiments to determine the correlation of the domain textures with the topography of the samples. We propose a simple method to nucleate and annihilate skyrmions, opening the possibility for ultra-dense data storage based on the high stability and low energy consumption of the skyrmionic textures.

Metabolic heterogeneity is widely recognised as the next challenge in our understanding of non-genetic variation. A growing body of evidence suggests that metabolic heterogeneity may result from the inherent stochasticity of intracellular events. However, metabolism has been traditionally viewed as a purely deterministic process, on the basis that highly abundant metabolites tend to filter out stochastic phenomena. Here we bridge this gap with a general method for prediction of metabolite distributions across single cells. By exploiting the separation of time scales between enzyme expression and enzyme kinetics, our method produces estimates for metabolite distributions without the lengthy stochastic simulations that would be typically required for large metabolic models. The metabolite distributions take the form of Gaussian mixture models that are directly computable from single-cell expression data and standard deterministic models for metabolic pathways. The proposed mixture models provide a systematic method to predict the impact of biochemical parameters on metabolite distributions. Our method lays the groundwork for identifying the molecular processes that shape metabolic heterogeneity and its functional implications in disease., Comment: 5 Figures, 3 Tables

Modern supercomputers allow the simulation of complex phenomena with increased accuracy. Eventually, this requires finer geometric discretizations with larger numbers of mesh elements. In this context, and extrapolating to the Exascale paradigm, meshing operations such as generation, adaptation or partition, become a critical bottleneck within the simulation workflow. In this paper, we focus on mesh partitioning. In particular, we present some improvements carried out on an in-house parallel mesh partitioner based on the Hilbert Space-Filling Curve. Additionally, taking advantage of its performance, we present the application of the SFC-based partitioning for dynamic load balancing. This method is based on the direct monitoring of the imbalance at runtime and the subsequent re-partitioning of the mesh. The target weights for the optimized partitions are evaluated using a least-squares approximation considering all measurements from previous iterations. In this way, the final partition corresponds to the average performance of the computing devices engaged., Comment: 10 pages, 9 figures. arXiv admin note: text overlap with arXiv:2005.05899

The evolution of the structural and kinematic properties of early-type galaxies (ETGs), their scaling relations, as well as their stellar metallicity and age contain precious information on the assembly history of these systems. We present results on the evolution of the stellar mass-velocity dispersion relation of ETGs, focusing in particular on the effects of some selection criteria used to define ETGs. We also try to shed light on the role that in-situ and ex-situ stellar populations have in massive ETGs, providing a possible explanation of the observed metallicity distributions., Comment: 5 pages, 2 figures. To appear in Proceedings of IAU Symposium 359 (T. Storchi-Bergmann, R. Overzier, W. Forman & R. Riffel, eds.)

Metabolism plays a central role in cell physiology because it provides the molecular machinery for growth. At the genome-scale, metabolism is made up of thousands of reactions interacting with one another. Untangling this complexity is key to understand how cells respond to genetic, environmental, or therapeutic perturbations. Here we discuss the roles of two complementary strategies for the analysis of genome-scale metabolic models: Flux Balance Analysis (FBA) and network science. While FBA estimates metabolic flux on the basis of an optimisation principle, network approaches reveal emergent properties of the global metabolic connectivity. We highlight how the integration of both approaches promises to deliver insights on the structure and function of metabolic systems with wide-ranging implications in discovery science, precision medicine and industrial biotechnology.

High fidelity Computational Fluid Dynamics simulations are generally associated with large computing requirements, which are progressively acute with each new generation of supercomputers. However, significant research efforts are required to unlock the computing power of leading-edge systems, currently referred to as pre-Exascale systems, based on increasingly complex architectures. In this paper, we present the approach implemented in the computational mechanics code Alya. We describe in detail the parallelization strategy implemented to fully exploit the different levels of parallelism, together with a novel co-execution method for the efficient utilization of heterogeneous CPU/GPU architectures. The latter is based on a multi-code co-execution approach with a dynamic load balancing mechanism. The assessment of the performance of all the proposed strategies has been carried out for airplane simulations on the POWER9 architecture accelerated with NVIDIA Volta V100 GPUs.

Heterologous gene expression draws resources from host cells. These resources include vital components to sustain growth and replication, and the resulting cellular burden is a widely recognised bottleneck in the design of robust circuits. In this tutorial we discuss the use of computational models that integrate gene circuits and the physiology of host cells. Through various use cases, we illustrate the power of host-circuit models to predict the impact of design parameters on both burden and circuit functionality. Our approach relies on a new generation of computational models for microbial growth that can flexibly accommodate resource bottlenecks encountered in gene circuit design. Adoption of this modelling paradigm can facilitate fast and robust design cycles in synthetic biology.

The late assembly of massive galaxies is thought to be dominated by stellar accretion in their outskirts (beyond 2 effective radii Re) due to dry, minor galaxy mergers. We use observations of 1010 passive early-type galaxies (ETGs) within z<0.15 from SDSS IV MaNGA to search for evidence of this accretion. The outputs from the stellar population fitting codes FIREFLY, pPXF, and Prospector are compared to control for systematic errors in stellar metallicity (Z) estimation. We find that the average radial logZ/Zsun profiles of ETGs in various stellar mass (M) bins are not linear. As a result, these profiles are poorly characterized by a single gradient value, explaining why weak trends reported in previous work can be difficult to interpret. Instead, we examine the full radial extent of stellar metallicity profiles and find them to flatten in the outskirts of M>10^{11}Msun ETGs. This is a signature of stellar accretion. Based on a toy model for stellar metallicity profiles, we infer the ex-situ stellar mass fraction in ETGs as a function of M and galactocentric radius. We find that ex-situ stars at 2Re make up 20% of the projected stellar mass of M<10^{10.5}Msun ETGs, rising up to 80% for M>10^{11.5}Msun ETGs., Comment: Accepted for publication in ApJ. 13 pages, 6 figures. Fixed date of acceptance

The possibility of prescribing local interactions between nano- and microscopic components that direct them to assemble in a predictable fashion is a central goal of nanotechnology research. In this article we advance a new paradigm in which self-assembly of DNA-functionalized colloidal particles is programmed using linker oligonucleotides dispersed in solution. We find a phase diagram that is surprisingly rich compared to phase diagrams typical of other DNA-functionalized colloidal particles that interact by direct hybridization, including a re-entrant melting transition upon increasing linker concentration, and show that multiple linker species can be combined together to prescribe many interactions simultaneously. A new theory predicts the observed phase behavior quantitatively without any fitting parameters. Taken together, these experiments and model lay the groundwork for future research in programmable self-assembly, enabling the possibility of programming the hundreds of specific interactions needed to assemble fully-addressable, mesoscopic structures, while also expanding our fundamental understanding of the unique phase behavior possible in colloidal suspensions., Comment: 10 pages, 6 figures, supporting information

We use a sample of ~3000 galaxies from the MaNGA MPL-7 internal data release to study the alpha abundance distribution within low-redshift galaxies. We use the Lick index ratio Mgb/ as an alpha abundance indicator to study relationships between the alpha abundance distribution and galaxy properties such as effective stellar velocity dispersion within 0.3 effective radii (sigma_*), galaxy environment, and dark matter halo formation time (z_f). We find that (1) all galaxies show a tight correlation between Mgb/ and sigma_*; (2) `old' (H_beta < 3) low-sigma_* galaxies in high local density environment and inner regions within galaxy groups are enhanced in Mgb/, while `young' (H_beta>3) galaxies and high-mass galaxies show no or less environmental dependence; (3) `old' galaxies with high-z_f show enhanced Mgb/ over low- and medium-z_f; (4) Mgb/ gradients are close to zero and show dependence on sigma_* but no obvious dependence on the environment or z_f. Our study indicates that stellar velocity dispersion or galaxy mass is the main parameter driving the Mgb/ enhancement, although environments appear to have modest effects, particularly for low- and medium-mass galaxies., Comment: Accepted for publication in ApJ

Phenotypic variation is a hallmark of cellular physiology. Metabolic heterogeneity, in particular, underpins single-cell phenomena such as microbial drug tolerance and growth variability. Much research has focussed on transcriptomic and proteomic heterogeneity, yet it remains unclear if such variation permeates to the metabolic state of a cell. Here we propose a stochastic model to show that complex forms of metabolic heterogeneity emerge from fluctuations in enzyme expression and catalysis. The analysis predicts clonal populations to split into two or more metabolically distinct subpopulations. We reveal mechanisms not seen in deterministic models, in which enzymes with unimodal expression distributions lead to metabolites with a bimodal or multimodal distribution across the population. Based on published data, the results suggest that metabolite heterogeneity may be more pervasive than previously thought. Our work casts light on links between gene expression and metabolism, and provides a theory to probe the sources of metabolite heterogeneity.

Galaxy clusters trace the largest structures of the Universe and provide ideal laboratories for studying galaxy evolution and cosmology. Clusters with extended X-ray emission have been discovered at redshifts up to z ~ 2.5. Meanwhile, there has been growing interest in hunting for protoclusters, the progenitors of clusters, at higher redshifts. It is, however, very challenging to find the largest protoclusters at early times when they start to assemble. Here we report a giant protocluster of galaxies at redshift z = 5.7, when the Universe was only one billion years old. This protocluster occupies a volume of about 35x35x35 cubic co-moving megaparsecs. It is embedded in an even larger overdense region with at least 41 spectroscopically confirmed, luminous Lyman-alpha emitting galaxies (Lyman-alpha Emitters, or LAEs), including several previously reported LAEs. Its LAE density is 6.6 times the average density at z ~ 5.7. It is the only one of its kind in an LAE survey in four square degrees on the sky. Such a large structure is also rarely seen in current cosmological simulations. This protocluster will collapse into a galaxy cluster with a mass of (3.6+/-0.9) x 10^{15} solar masses, comparable to those of the most massive clusters or protoclusters known to date., Comment: Published in Nature Astronomy on Oct 15, 2018 (DOI: 10.1038/s41550-018-0587-9)

We describe a deep, systematic imaging study of satellites in the outer halo of the Milky Way. Our sample consists of 58 stellar overdensities --- i.e., substructures classified as either globular clusters, classical dwarf galaxies, or ultra-faint dwarf galaxies --- that are located at Galactocentric distances of R$_{\rm GC}$ > 25 kpc (outer halo) and out to ~400 kpc. This includes 44 objects for which we have acquired deep, wide-field, $g-$ and $r-$band imaging with the MegaCam mosaic cameras on the 3.6m Canada-France-Hawaii Telescope and the 6.5m Magellan-Clay telescope. These data are supplemented by archival imaging, or published $gr$ photometry, for an additional 14 objects, most of which were discovered recently in the Dark Energy Survey (DES). We describe the scientific motivation for our survey, including sample selection, observing strategy, data reduction pipeline, calibration procedures, and the depth and precision of the photometry. The typical 5$\sigma$ point-source limiting magnitudes for our MegaCam imaging --- which collectively covers an area of ~52 deg$^{2}$ --- are $g_{\rm lim}$ ~25.6 and $r_{\rm lim}$ ~25.3 AB mag. These limits are comparable to those from the coadded DES images and are roughly a half-magnitude deeper than will be reached in a single visit with LSST. Our photometric catalog thus provides the deepest and most uniform photometric database of Milky Way satellites available for the foreseeable future. In other papers in this series, we have used these data to explore the blue straggler populations in these objects, their density distributions, star formation histories, scaling relations and possible foreground structures., Comment: Accepted for publication in ApJ

We present structural parameters from a wide-field homogeneous imaging survey of Milky Way satellites carried out with the MegaCam imagers on the 3.6m Canada-France-Hawaii Telescope (CFHT) and 6.5m Magellan-Clay telescope. Our survey targets an unbiased sample of "outer halo" satellites (i.e., substructures having Galactocentric distances greater than 25 kpc) and includes classical dSph galaxies, ultra-faint dwarfs, and remote globular clusters. We combine deep, panoramic $gr$ imaging for 44 satellites and archival $gr$ imaging for 14 additional objects (primarily obtained with the DECam instrument as part of the Dark Energy Survey), to measure photometric and structural parameters for 58 outer halo satellites. This is the largest and most uniform analysis of Milky Way satellites undertaken to date and represents roughly three quarters ($58/81 \simeq$72\%) of all known outer halo satellites. We use a maximum-likelihood method to fit four density laws to each object in our survey: exponential, Plummer, King and Sersic models. We examine systematically the isodensity contour maps and color magnitude diagrams for each of our program objects, present a comparison with previous results, and tabulate our best-fit photometric and structural parameters, including ellipticities, position angles, effective radii, Sersic indices, absolute magnitudes, and surface brightness measurements. We investigate the distribution of outer halo satellites in the size-magnitude diagram, and show that the current sample of outer halo substructures spans a wide range in effective radius, luminosity and surface brightness, with little evidence for a clean separation into star cluster and galaxy populations at the faintest luminosities and surface brightnesses., Comment: Accepted for publication in ApJ

We present a simple, top-down approach for the calculation of minimum energy consumption of electrosorptive ion separation using variational form of the (Gibbs) free energy. We focus and expand on the case of electrostatic capacitive deionization (CDI), and the theoretical framework is independent of details of the double-layer charge distribution and is applicable to any thermodynamically consistent model, such as the Gouy-Chapman-Stern (GCS) and modified Donnan (mD) models. We demonstrate that, under certain assumptions, the minimum required electric work energy is indeed equivalent to the free energy of separation. Using the theory, we define the thermodynamic efficiency of CDI. We explore the thermodynamic efficiency of current experimental CDI systems and show that these are currently very low, less than 1% for most existing systems. We applied this knowledge and constructed and operated a CDI cell to show that judicious selection of the materials, geometry, and process parameters can be used to achieve a 9% thermodynamic efficiency (4.6 kT energy per removed ion). This relatively high value is, to our knowledge, by far the highest thermodynamic efficiency ever demonstrated for CDI. We hypothesize that efficiency can be further improved by further reduction of CDI cell series resistances and optimization of operational parameters.

We present a new simulation technique to study systems of polymers functionalized by reactive sites that bind/unbind forming reversible linkages. Functionalized polymers feature self-assembly and responsive properties that are unmatched by systems lacking selective interactions. The scales at which the functional properties of these materials emerge are difficult to model, especially in the reversible regime where such properties result from many binding/unbinding events. This difficulty is related to large entropic barriers associated with the formation of intra-molecular loops. In this work we present a simulation scheme that sidesteps configurational costs by dedicated Monte Carlo moves capable of binding/unbinding reactive sites in a single step. Cross-linking reactions are implemented by trial moves that reconstruct chain sections attempting, at the same time, a dimerization reaction between pairs of reactive sites. The model is parametrized by the reaction equilibrium constant of the reactive species free in solution. This quantity can be obtained by means of experiments or atomistic/quantum simulations. We use the proposed methodology to study self-assembly of single--chain polymeric nanoparticles, starting from flexible precursors carrying regularly or randomly distributed reactive sites. During a single run, almost all pairs of reactive monomers interact at least once. We focus on understanding differences in the morphology of chain nanoparticles when linkages are reversible as compared to the well studied case of irreversible reactions. Intriguingly, we find that the size of regularly functionalsized chains, in good solvent conditions, is non-monotonous as a function of the degree of functionalization. We clarify how this result follows from excluded volume interactions and is peculiar of reversible linkages and regular functionalizations., Comment: to appear in The Journal of Chemical Physics

We study radial profiles in H$\alpha$ equivalent width and specific star formation rate (sSFR) derived from spatially-resolved SDSS-IV MaNGA spectroscopy to gain insight on the physical mechanisms that suppress star formation and determine a galaxy's location in the SFR-$\rm M_\star$ diagram. Even within the star-forming `main sequence', the measured sSFR decreases with stellar mass, both in an integrated and spatially-resolved sense. Flat sSFR radial profiles are observed for $\rm log(M_\star/ M_\odot) < 10.5$, while star-forming galaxies of higher mass show a significant decrease in sSFR in the central regions, a likely consequence of both larger bulges and an inside-out growth history. Our primary focus is the green valley, constituted by galaxies lying below the star formation main sequence, but not fully passive. In the green valley we find sSFR profiles that are suppressed with respect to star-forming galaxies of the same mass at all galactocentric distances out to 2 effective radii. The responsible quenching mechanism therefore appears to affect the entire galaxy, not simply an expanding central region. The majority of green valley galaxies of $\rm log(M_\star/ M_\odot) > 10.0$ are classified spectroscopically as central low-ionisation emission-line regions (cLIERs). Despite displaying a higher central stellar mass concentration, the sSFR suppression observed in cLIER galaxies is not simply due to the larger mass of the bulge. Drawing a comparison sample of star forming galaxies with the same $\rm M_\star$ and $\rm \Sigma_{1~kpc}$ (the mass surface density within 1 kpc), we show that a high $\rm \Sigma_{1~kpc}$ is not a sufficient condition for determining central quiescence., Comment: accepted in MNRAS

We present a spectroscopic survey of high-redshift, luminous galaxies over four square degrees on the sky, aiming to build a large and homogeneous sample of Ly$\alpha$ emitters (LAEs) at $z\approx5.7$ and 6.5, and Lyman-break galaxies (LBGs) at $5.5