Accurate Constraints Research Articles

Benchmarking chemical neural ordinary differential equations to obtain reaction network-constrained kinetic models from spectroscopic data

Kinetic model identification relies on accurate concentration measurements and physical constraints to limit solution multiplicity. Not having these measurements and prior knowledge of species and reactions creates considerable challenges that are currently unresolved. We address these by developing a data-driven framework using realtime spectroscopic data, comprising: (i) multivariate curve resolution to deconvolve the spectra of the reacting mixture into those of its pseudocomponents and their corresponding concentrations, which enables species identification without prior information, (ii) Bayesian structure learning among the pseudocomponent spectra to enable hypothesizing reaction pathways, and (iii) neural ordinary differential equations (ODE) that are physically constrained by the hypothesized reaction network and the laws of mass action and temperature dependence to learn kinetic models from the temporal concentration projections of the realtime spectra. The predictive performance of the constrained neural ODEs is limited by the accuracy of spectral deconvolution in the presence of noise, and has been benchmarked against a constrained regression approach by varying signal:noise ratios in the synthetic spectroscopic data of reacting mixtures. Although the hypothesized reaction network differs from the actual reaction template, owing to noise, the network-constrained neural ODEs are seen to result in a 75.2% and 68.15% decrease in the root mean squared error (RMSE) of the concentration profile predictions as compared to the constrained regression method, when trained on time projected concentration data of the synthetic spectra generated at a signal to noise ratio of 35 and 100, respectively.

Accurate Fairness: Improving Individual Fairness without Trading Accuracy

Accuracy and individual fairness are both crucial for trustworthy machine learning, but these two aspects are often incompatible with each other so that enhancing one aspect may sacrifice the other inevitably with side effects of true bias or false fairness. We propose in this paper a new fairness criterion, accurate fairness, to align individual fairness with accuracy. Informally, it requires the treatments of an individual and the individual's similar counterparts to conform to a uniform target, i.e., the ground truth of the individual. We prove that accurate fairness also implies typical group fairness criteria over a union of similar sub-populations. We then present a Siamese fairness in-processing approach to minimize the accuracy and fairness losses of a machine learning model under the accurate fairness constraints. To the best of our knowledge, this is the first time that a Siamese approach is adapted for bias mitigation. We also propose fairness confusion matrix-based metrics, fair-precision, fair-recall, and fair-F1 score, to quantify a trade-off between accuracy and individual fairness. Comparative case studies with popular fairness datasets show that our Siamese fairness approach can achieve on average 1.02%-8.78% higher individual fairness (in terms of fairness through awareness) and 8.38%-13.69% higher accuracy, as well as 10.09%-20.57% higher true fair rate, and 5.43%-10.01% higher fair-F1 score, than the state-of-the-art bias mitigation techniques. This demonstrates that our Siamese fairness approach can indeed improve individual fairness without trading accuracy. Finally, the accurate fairness criterion and Siamese fairness approach are applied to mitigate the possible service discrimination with a real Ctrip dataset, by on average fairly serving 112.33% more customers (specifically, 81.29% more customers in an accurately fair way) than baseline models.

Tracking Control Method for Greenhouse Environment Prediction Model Based on Real-Time Optimization Error Constraints

Model predictive control, without strict constraints on the control model, effectively overcomes problems, such as poor system dynamic quality caused by time delay, can improve control accuracy to a certain extent, and can directly process input and output constraints of the system online. It is applied in greenhouse system control. The appropriate objective optimization function and its corresponding constraint conditions have a direct impact on the solution of the optimal control rate of the model predictive control. In response to this issue, this paper proposes a simple and fast optimal predictive tracking control method. Based on the current prediction model of the greenhouse system, which reflects the dynamic relationship between various control equipment actions and greenhouse environmental factors, a multi degree of freedom discrete time state space model with tracking errors is established. Based on this model, in establishing the corresponding objective optimization function, the gradient descent theory and the two-norm definition are applied, and combined with actual constraints, iterative constraint conditions for real-time error tracking updates are established. Compared with traditional constraint ranges, a constraint function with real-time update characteristics is formed, achieving more accurate constraint conditions. By using rolling optimization and iterative methods, the optimal control rate corresponding to the minimum value of the objective optimization function within a finite time is solved. Through simulation examples, it is demonstrated that the model predictive control with optimization constraints can achieve a more accurate prediction and tracking control of indoor environmental parameters. This method has the advantages of simple control, energy-saving optimization, stable control, and accurate tracking, providing a reference for online real-time prediction and tracking control of future greenhouse environmental parameters.

Improving the chronostratigraphic framework of the Transvaal Supergroup (South Africa) through in-situ and high-precision U-Pb geochronology

The Transvaal Supergroup, on the Kaapvaal Craton in South Africa, is widely accepted as one of the best-preserved sedimentary archives to constrain planetary-scale environmental changes during the late Archean and early Proterozoic, yet the sedimentation age for certain stratigraphic intervals remains poorly constrained. To improve the temporal control on some of the first-order global changes recorded in these rocks, we carried out U-Pb analyses of detrital zircon populations from several clastic and volcano-clastic sedimentary units of the Transvaal Supergroup. We applied the Chemical Abrasion-Isotope Dilution-Thermal Ionization Mass Spectrometry (CA-ID-TIMS) technique on detrital and volcanic zircon populations that had been previously screened using the Laser Ablation-Inductively Coupled Plasma-Mass Spectrometry (LA-ICP-MS) technique. We report new maximum depositional age estimates for the Pannetjie (2456.6 ± 7.0 Ma), the Heynskop (2451.5 ± 2.5 Ma), the Makganyene (2423.1 ± 1.0 Ma) and the Hekpoort formations (2248.0 ± 1.1 Ma).A ca. 2.25 Ga-old cluster of LA-ICP-MS analyses in the Makganyene Formation was identified to be spurious, since it was completely removed during the chemical abrasion. Thus, we speculate that circulation of hydrothermal fluids and associated Pb-loss from a radiation-damaged lattice during the emplacement of the much younger Hekpoort Formation or possibly the Ophthalmia Orogeny, recorded in Western Australia, may have reset the U-Pb system of this zircon population. This implies that the accurate maximum depositional age of the Makganyene Formation is ca. 2.42 Ga instead, which denotes the age of the oldest glacial event of global extent during the Paleoproterozoic. Therefore, we suggest that the combination of both dating techniques is essential to ensure accurate maximum depositional age constraints for ancient detrital sedimentary rocks. Additionally, our data provides temporal constraints on a period characterized by major fluctuations in atmospheric oxygen. Finally, and supporting the complex nature of the Paleoproterozoic, linkages between widespread glaciations and atmospheric oxygen fluctuations remain to be explored.

An Improved Method of Model-Free Adaptive Predictive Control: A Case of pH Neutralization in WWTP

pH neutralization reaction process plays a crucial role in Waste Water Treatment Process (WWTP). Traditional PID Proportion Integral Differential, (or even advanced PID control) algorithms have poor performance on WWTP due to the strong non-linearity, large time lag, and large inertia characteristics of pH neutralization. Therefore, finding a superior control method to maintain the pH value of wastewater within the normal range will greatly help to improve the efficiency and effectiveness of wastewater treatment. The chemical reaction mechanism of pH neutralization reaction process is first analyzed, and a mechanistic model of pH neutralization reaction process is developed based on the reaction of ions during acid-alkali neutralization and the electric balance equation. Then, combining the characteristics of generalized predictive control and Model-Free Adaptive Control (MFAC), a Model-Free Adaptive Predictive Control (MFAPC) method based on compact format dynamic linearization is introduced. An Improved Model Free Adaptive PI Predictive Control algorithm (IMFAPC) with proportional (P) and integral (I) algorithms is proposed to further improve the control performance. IMFAPC is proposed on the basis of MFAPC, combining the advantages of generalized predictive control, introducing a PI module consisting of error and error sum, and predicting the PI module, making it possible to produce more accurate constraints on the control inputs, avoiding increasing errors, and improving the control effect of delayed systems at the same time. pH neutralization process simulation experimental results show that compared with the ordinary Model-Free Adaptive Control (MFAC) and MFAPC, the IMFAPC control algorithms has the best performance in terms of accuracy, overshoot, and the robustness.

The investigation of multiple factors on elastic anisotropy of artificial shale based on the orthogonal experiment

Elastic anisotropy of shales is critical to accurate constraints for rock physical models, quantitative interpretation and hydraulic fracturing. However, the causes of elastic anisotropy of shales are very complicated, and the understanding of how multiple influence factors affect the elastic anisotropy of shales is still not clear. Hence, the orthogonal experiment, as an effective multiple factors experimental method, is adopted in this study to analyze the effect of multiple factors for shale elastic anisotropy. Three factors, clay content, organic matter (OM) content and compaction stress are selected as independent variables, the orthogonal test table L16(43) with four levels for each factor is adopted. According to the designed orthogonal table, sixteen artificial shales are constructed based on the cold-pressing method, and all the dry artificial shales are measured by the ultrasonic measurements. The influence of each factor on the elastic anisotropy and the sensitivity orders of three factors are obtained using the range analysis. The orders of sensitivity for selected factors follow the sequence clay content > compaction stress > OM content for velocity anisotropy parameters. The compaction mechanism of artificial shales is also discussed by the compaction factor, which are positively correlated with the velocity anisotropy parameters. The clay platelets orientation distribution function (ODF) of samples is evaluated by a theoretical model, the ODF coefficients are significantly affected by the clay content and compaction stress, and W200 are much more sensitive to these factors than W400. The results can provide a critical rock physics basis for quantitative interpretation and reservoir prediction of the low-maturity or maturity shale reservoir.

Physicochemical Conditions of the Devonian-Jurassic Continental Deep Biosphere Tracked by Carbonate Clumped Isotope Temperatures of Granite-Hosted Carbonate Veins

Previous studies have shown that microorganisms thrive in oligotrophic fracture systems, and metabolisms include consumption and production of methane. In the Laxemar, Götemar, and Forsmark areas of Sweden, ancient microbial activity has previously been demonstrated by large δ13CVPDB variability of carbonate vein infillings within granitic host rocks. Here, we apply carbonate clumped isotope thermometry to reconstruct the temperature of precipitation of the carbonate within these veins. The carbonate clumped isotope temperatures indicate that mineralization took place between 46°C and 108°C, in line with previously published fluid inclusion data (<50°C to 113°C). The new carbonate clumped isotope data more accurately narrows temperatures at the lower end of this range as fluid inclusions are not easily applicable below 80°C, a temperature regime of high importance for paleobiological reconstructions. Our results demonstrate that large volumes of biogenic carbonate cement were formed from low-temperature microbial processes in low-salinity water, succeeding calcite of deep brine origin. The known burial and thermal history of the region combined with our carbonate clumped isotope data place the microbial activity at the end of the Variscan orogeny and later events (e.g., Jurassic). Thus, carbonate clumped isotope thermometry reduces uncertainties in deep biosphere studies by providing more accurate temperature constraints in the low-temperature regime, the biogenic processes, and the origin of the diagenetic fluids.

Asymmetric leptoquark pair production at LHC

We investigate asymmetric leptoquark pair production mechanism at the Large Hadron Collider to advocate its potential relevance to establish reliable constraints on the leptoquark parameter space and its ability to aid in correct identification of these attractive sources of new physics. The main feature of asymmetric pair production that genuinely distinguishes it from the usual leptoquark pair production is given by the fact that the two leptoquarks that are produced in proton-proton collisions through a t-channel lepton exchange are not charge conjugates of each other. Hence the proposed name of asymmetric leptoquark pair production for this type of process. We spell out prerequisite conditions for the asymmetric leptoquark pair production mechanism to be operational and enumerate all possible combinations of leptoquark multiplets that can potentially generate it. We finally reinterpret existing leptoquark pair production search results within several simple scalar leptoquark extensions of the Standard Model, assuming that the leptoquarks exclusively couple to either electrons or muons and the first generation quarks, to demonstrate proper inclusion of asymmetric pair production. We consequently present accurate parameter space constraints for the S1, S3, R2, S1+S3, and S1+R2 leptoquark scenarios.

Drell-Yan production in third-generation gauge vector leptoquark models at NLO+PS in QCD

Motivated by the long-standing hints of lepton-flavour non-universality in the b → cℓν and b → sℓ+ℓ− channels, we study Drell-Yan ditau production at the Large Hadron Collider (LHC). In the context of models with third-generation gauge vector leptoquarks (LQs), we calculate the complete mathcal{O} (αs) corrections to the pp → τ+τ− process, achieving next-to-leading order (NLO) plus parton shower (NLO+PS) accuracy using the POWHEG method. We provide a dedicated Monte Carlo code that evaluates the NLO QCD corrections on-the-fly in the event generation and use it to study the numerical impact of NLO+PS corrections on the kinematic distributions that enter the existing experimental searches for non-resonant ditau final states. Based on our phenomenological analysis we derive NLO accurate constraints on the masses and couplings of third-generation gauge vector LQs using the latest LHC ditau search results corresponding to an integrated luminosity of around 140 fb−1 of proton-proton collisions at sqrt{s} = 13 TeV. The presented NLO+PS generator allows for an improved signal modelling, making it an essential tool for future ATLAS and CMS searches for vector LQs in τ+τ− final states at LHC Run III and beyond.

PHANGS–JWST First Results: Dust-embedded Star Clusters in NGC 7496 Selected via 3.3 μm PAH Emission

The earliest stages of star formation occur enshrouded in dust and are not observable in the optical. Here we leverage the extraordinary new high-resolution infrared imaging from JWST to begin the study of dust-embedded star clusters in nearby galaxies throughout the Local Volume. We present a technique for identifying dust-embedded clusters in NGC 7496 (18.7 Mpc), the first galaxy to be observed by the PHANGS–JWST Cycle 1 Treasury Survey. We select sources that have strong 3.3 μm PAH emission based on a F300M − F335M color excess and identify 67 candidate embedded clusters. Only eight of these are found in the PHANGS-HST optically selected cluster catalog, and all are young (six have SED fit ages of ∼1 Myr). We find that this sample of embedded cluster candidates may significantly increase the census of young clusters in NGC 7496 from the PHANGS-HST catalog; the number of clusters younger than ∼2 Myr could be increased by a factor of 2. Candidates are preferentially located in dust lanes and are coincident with the peaks in the PHANGS-ALMA CO (2–1) maps. We take a first look at concentration indices, luminosity functions, SEDs spanning from 2700 Å to 21 μm, and stellar masses (estimated to be between ∼104 and 105 M ⊙). The methods tested here provide a basis for future work to derive accurate constraints on the physical properties of embedded clusters, characterize the completeness of cluster samples, and expand analysis to all 19 galaxies in the PHANGS–JWST sample, which will enable basic unsolved problems in star formation and cluster evolution to be addressed.

Adaptive mixed-constraint Gerchberg-Saxton algorithm for phase-only holographic display

At present, spatial light modulators are incapable of modulating both the amplitude and phase of the wavefront simultaneously. Therefore, when a spatial light modulator is used for holographic display, it is necessary to encode the complex amplitude of the object wave into amplitude-only or phase-only computer-generated-hologram. The phase-only holographic display has attracted much attention of researchers due to its characteristics of high diffraction efficiency and no conjugate image. However, current optimization algorithms for generating phase-only hologram have the problems of iterative divergence, slow convergence speed, and poor reconstruction quality, which is difficult to satisfy the requirements for high-quality holographic display. In this work, we propose an accurate adaptive mixed constraint Gerchberg-Saxton algorithm by constraining the frequency bandwidth in the hologram plane and adaptively constraining the amplitude of the reconstructed image in the image plane based on the angular spectrum propagation theory. Firstly, we use the angular spectrum propagation model without paraxial approximation to simulate the forward and backward propagation of the light wave for ensuring the accuracy of the wavefront propagation. Secondly, dividing the image plane into signal area and noise area according to the spatial distribution of target image, and different adaptive feedback strategies are set up for the two regions based on the optimized effect of the phase-only hologram. The adaptive feedback strategy is established, which can accelerate the convergence speed of the proposed algorithm and enhance the hologram of freedom of the optimization. Finally, the frequency bandwidth constraint strategy is introduced in the hologram plane to optimize the edge pixels and compensate for the frequency information loss of the phase-only computer-generated hologram, which improves the reconstruction quality of the hologram. After 100 iterations, the average correlation coefficient of the holographic reconstructed image of the proposed algorithm is about 0.9857, and the average peak signal-to-noise ratio is about 31.02 dB. The correlation coefficient and the peak signal-to-noise ratio of the reconstructed images of the proposed algorithm are better than those of the Gerchberg-Saxton algorithm with only frequency bandwidth constraint strategy, and the proposed algorithm has clearer texture and better display effect. The results of numerical simulations and optical experiments show the feasibility and effectiveness of the proposed method. The proposed adaptive mixed constraint Gerchberg-Saxton algorithm is a promising technology for high-quality holographic display.

Retrieving C and O Abundance of HR 8799 c by Combining High- and Low-resolution Data

Abstract The formation and evolution pathway for the directly imaged multiplanetary system HR 8799 remains mysterious. Accurate constraints on the chemical composition of the planetary atmosphere(s) are key to solving the mystery. We perform a detailed atmospheric retrieval on HR 8799 c to infer the chemical abundances and abundance ratios using a combination of photometric data along with low- and high-resolution spectroscopic data (R ∼ 20–35,000). We specifically retrieve [C/H], [O/H], and C/O and find them to be 0.55 − 0.39 + 0.36 , 0.47 − 0.32 + 0.31 , and 0.67 − 0.15 + 0.12 at 68% confidence. The superstellar C and O abundances, yet a stellar C/O ratio, reveal a potential formation pathway for HR 8799 c. Planet c, and likely the other gas giant planets in the system, formed early on (likely within ∼1 Myr), followed by further atmospheric enrichment in C and O through the accretion of solids beyond the CO ice line. The enrichment either preceded or took place during the early phase of the inward migration to the current planet locations.

Understanding structure in line-driven stellar winds using ultraviolet spectropolarimetry in the time domain

The most massive stars are thought to lose a significant fraction of their mass in a steady wind during the main-sequence and blue supergiant phases. This in turn sets the stage for their further evolution and eventual supernova, with consequences for ISM energization and chemical enrichment. Understanding these processes requires accurate observational constraints on the mass-loss rates of the most luminous stars, which can also be used to test theories of stellar wind generation. In the past, mass-loss rates have been characterized via collisional emission processes such as H$\alpha$ and free-free radio emission, but these so-called "density squared" diagnostics require correction in the presence of widespread clumping. Recent observational and theoretical evidence points to the likelihood of a ubiquitously high level of such clumping in hot-star winds, but quantifying its effects requires a deeper understanding of the complex dynamics of radiatively driven winds. Furthermore, large-scale structures arising from surface anisotropies and propagating throughout the wind can further complicate the picture by introducing further density enhancements, affecting mass-loss diagnostics. Time series spectroscopy of UV resonance lines with high resolution and high signal-to-noise are required to better understand this complex dynamics, and help correct "density squared" diagnostics of mass-loss rates. The proposed Polstar mission easily provides the necessary resolution at the sound-speed scale of 20 km s$^{-1}$, on three dozen bright targets with signal-to noise an order of magnitude above that of the celebrated IUE MEGA campaign, via continuous observations that track structures advecting through the wind in real time.

Adaptive Neural Network Output Feedback Control of Uncertain Underactuated Systems With Actuated and Unactuated State Constraints

Underactuated systems are widely applied in industry, construction, manufacturing, etc., and the complex working environment puts forward higher demands for safety and transient performance. Hence, it is necessary to consider how to simultaneously ensure actuated and unactuated motion constraints by fewer control inputs, especially when systems suffer from model uncertainties, unavailable velocities, etc. Unfortunately, it is still a significant challenge to overcome in real applications and theoretical analysis. Additionally, most existing studies merely consider the specific control objects and few general methods are applicable to a class of underactuated systems. To this end, we design a new adaptive output-feedback controller for a class of uncertain underactuated systems. Compared with existing methods only handling actuated constraints, an important merit of this article is that by introducing the elaborately designed coupling term composed of actuated and unactuated constraints together, all state variables are kept within the preset time-variant ranges and converge to their desired values. Furthermore, a new Lyapunov function candidate is utilized to provide a theoretical guarantee. As far as we know, without the need of exact model knowledge and velocity feedback, this article provides the first solution to achieve accurate motion control and state constraints for both actuated and unactuated variables, which is meaningful both theoretically and practically. Meanwhile, the asymptotic stability of the equilibrium point for the closed-loop system is proven by utilizing Lyapunov techniques and Barbalat’s lemma. For verification, the presented controller is applied to underactuated overhead and rotary cranes, respectively, together with detailed theoretical analysis and experimental validations.

Accurate modelling of extragalactic microlensing by compact objects

Microlensing of extragalactic sources, in particular the probability of significant amplifications, is a potentially powerful probe of the abundance of compact objects outside the halo of the Milky Way. Accurate experimental constraints require an equally accurate theoretical model for the amplification statistics produced by such a population. In this article, we argue that the simplest (strongest-lens) model does not meet this demanding requirement. We thus propose an elaborate practical modelling scheme for extragalactic microlensing. We derive from first principles an expression for the amplification probability that consistently allows for: (i) the coupling between microlenses; (ii) realistic perturbations from the cosmic large-scale structure; (iii) extended-source corrections. An important conclusion is that the external shear applied on the dominant microlens, both by the other lenses and by the large-scale structure, is practically negligible. Yet, the predictions of our approach can still differ by a factor of a few with respect to existing models of the literature. Updated constraints on the abundance of compact objects accounting for such discrepancies may be required.

Fuzzy Superpixel-based Image Segmentation

This article presents a multi-phase image segmentation methodology based on fuzzy superpixel decomposition, aggregation and merging. First, a collection of layers of dense fuzzy superpixels is generated by the variational fuzzy decomposition algorithm. Then a layer of refined superpixels is extracted by aggregating various layers of dense fuzzy superpixels using the hierarchical normalized cuts. Finally, the refined superpixels are projected into the low dimensional feature spaces by the multidimensional scaling and the segmentation result is obtained via the mean-shift-based merging approach with the spatial bandwidth adjustment strategy. Our algorithm utilizes the superimposition of fuzzy superpixels to impose more accurate spatial constraints on the final segmentation through the fuzzy superpixel aggregation. The fuzziness of superpixels also provides spatial features to measure affinities between fuzzy superpixels and refined superpixels, and guide the merging process. Comparative experiments with the existing approaches reveal a superior performance of the proposed method.

Location, extent, and magnitude of dynamic topography in the Late Cretaceous Cordilleran Foreland Basin, USA: New insights from 3D flexural backstripping

AbstractMantle‐induced dynamic topography (i.e., subsidence and uplift) has been increasingly recognized as an important process in foreland basin development. However, characterizing and distinguishing the effects (i.e., location, extent and magnitude) of dynamic topography in ancient foreland basins remains challenging because the spatio‐temporal footprint of dynamic topography and flexural topography (i.e., generated by topographic loading) can overlap. This study employs 3D flexural backstripping of Upper Cretaceous strata in the central part of the North American Cordilleran foreland basin (CFB) to better quantify the effects of dynamic topography. The extensive stratigraphic database and good age control of the CFB permit the regional application of 3D flexural backstripping in this basin for the first time. Dynamic topography started to influence the development of the CFB during the late Turonian to middle Campanian (90.2–80.2 Ma) and became the dominant subsidence mechanism during the middle to late Campanian (80.2–74.6 Ma). The area influenced by >100 m dynamic subsidence is approximately 400 by 500 km, within which significant (>200 m) dynamic subsidence occurs in an irregular‐shaped (i.e., lunate) subregion. The maximum magnitude of dynamic subsidence is 300 ± 100 m based on the 80.2–74.6 Ma tectonic subsidence maps. With the maximum magnitude of dynamic uplift being constrained to be 200–300 m, the gross amount of dynamic topography in the Late Cretaceous CFB is 500–600 m. Although the location of dynamic subsidence revealed by tectonic subsidence maps is generally consistent with isopach map trends, tectonic subsidence maps developed through 3D flexural backstripping provide more accurate constraints of the areal extent, magnitude and rate of dynamic topography (as well as flexural topography) in the CFB through the Late Cretaceous. This improved understanding of dynamic topography in the CFB is critical for refining current geodynamic models of foreland basins and understanding the surface expression of mantle processes.

Extending GRMHD for thin disks to non-Kerr spacetimes

Black hole based tests of general relativity have proliferated in recent times with new and improved detectors and telescopes. Modeling of the black hole neighborhood, where most of the radiation carrying strong-field signature originates, is of utmost importance for robust and accurate constraints on possible violations of general relativity. As a first step, this paper presents the extension of general relativistic magnetohydrodynamic simulations of thin accretion disks to parametrically deformed black holes that generalize the Kerr solution. The extension is based on harmpi, a publicly available member of the harm family of codes, and uses a phenomenological metric to study parametric deviations away from Kerr. The extended model is used to study the disk structure, stability, and radiative efficiency. We also compute the Fe $\mathrm{K}\ensuremath{\alpha}$ profiles in simplified scenarios and present an outlook for the future.

Elucidating galaxy assembly bias in SDSS

We investigate the level of galaxy assembly bias in the Sloan Digital Sky Survey (SDSS) main galaxy sample using ELUCID, a state-of-the-art constrained simulation that accurately reconstructed the initial density perturbations within the SDSS volume. On top of the ELUCID haloes, we develop an extended HOD model that includes the assembly bias of central and satellite galaxies, parameterized as $\mathcal{Q}_\mathrm{cen}$ and $\mathcal{Q}_\mathrm{sat}$, respectively, to predict a suite of one- and two-point observables. In particular, our fiducial constraint employs the probability distribution of the galaxy number counts measured on $8\,\mathrm{Mpc}\,h^{-1}$ scales $N_8^g$ and the projected cross-correlation functions of quintiles of galaxies selected by $N_8^g$ with our entire galaxy sample. We perform extensive tests of the efficacy of our method by fitting the same observables to mock data using both constrained and non-constrained simulations. We discover that in many cases the level of cosmic variance between the two simulations can produce biased constraints that lead to an erroneous detection of galaxy assembly bias if the non-constrained simulation is used. When applying our method to the SDSS data, the ELUCID reconstruction effectively removes an otherwise strong degeneracy between cosmic variance and galaxy assembly bias in SDSS, enabling us to derive an accurate and stringent constraint on the latter. Our fiducial ELUCID constraint, for galaxies above a stellar mass threshold $M_*{=}10^{10.2}\,h^{-2}\,M_\odot$, is $\mathcal{Q}_\mathrm{cen}{=}{-}0.09\pm{0.05}$ and $\mathcal{Q}_\mathrm{sat}{=}0.09\pm{0.10}$, indicating no evidence for a significant~($>2\sigma$) galaxy assembly bias in the local Universe probed by SDSS. Finally, our method provides a promising path to the robust modelling of the galaxy-halo connection within future surveys like DESI and PFS.

Low-energy cosmic rays: regulators of the dense interstellar medium

Low energy cosmic rays (up to the GeV energy domain) play a crucial role in the physics and chemistry of the densest phase of the interstellar medium. Unlike interstellar ionising radiation, they can penetrate large column densities of gas, and reach molecular cloud cores. By maintaining there a small but not negligible gas ionisation fraction, they dictate the coupling between the plasma and the magnetic field, which in turn affects the dynamical evolution of clouds and impacts on the process of star and planet formation. The cosmic-ray ionisation of molecular hydrogen in interstellar clouds also drives the rich interstellar chemistry revealed by observations of spectral lines in a broad region of the electromagnetic spectrum, spanning from the submillimetre to the visual band. Some recent developments in various branches of astrophysics provide us with an unprecedented view on low energy cosmic rays. Accurate measurements and constraints on the intensity of such particles are now available both for the very local interstellar medium and for distant interstellar clouds. The interpretation of these recent data is currently debated, and the emerging picture calls for a reassessment of the scenario invoked to describe the origin and/or the transport of low energy cosmic rays in the Galaxy.