Global Properties Research Articles

The Redshift Evolution of the M •–M ⋆ Relation for JWST’s Supermassive Black Holes at z > 4

JWST has detected many overmassive galactic systems at z > 4, where the mass of the black hole, M •, is 10–100 times larger than expected from local relations, given the host’s stellar mass, M ⋆. This paper presents a model to describe these overmassive systems in the high-z Universe. We suggest that the black hole mass is the main driver of high-z star formation quenching. Supermassive black holes globally impact their high-z galaxies because their hosts are physically small, and the black holes have duty cycles close to unity at z > 4. In this regime, we assume that black hole mass growth is regulated by the quasar’s output, while stellar mass growth is quenched by it and uncorrelated to the global properties of the host halo. We find that the ratio M •/M ⋆ controls the average star formation efficiency: if M •/M ⋆ > 8 × 1018(nΛ/ f Edd)[(Ω b M h )/(Ω m M ⋆) − 1], then the galaxy is unable to form stars efficiently. Once this ratio exceeds the threshold, a runaway process brings the originally overmassive system toward the local M •–M ⋆ relation. Furthermore, the M •–M ⋆ relation evolves with redshift as ∝(1 + z)5/2. At z ∼ 5, we find an overmassive factor of ∼55, in excellent agreement with current JWST data and the high-z relation inferred from those. Extending the black hole horizon farther in redshift and lower in mass will test this model and improve our understanding of the early coevolution of black holes and galaxies.

Skipping without and with hurdles in bipedal macaque: global mechanics.

Macaques trained to perform bipedally used running gaits across a wide range of speeds. At higher speeds they preferred unilateral skipping (galloping). The same asymmetric stepping pattern was used while hurdling across two low obstacles placed at the distance of a stride within our experimental track. In bipedal macaques during skipping, we expected a differential use of the trailing and leading legs. The present study investigated global properties of the effective and virtual leg, the location of the virtual pivot point (VPP), and the energetics of the center of mass (CoM), with the aim of clarifying the differential leg operation during skipping in bipedal macaques. When skipping, macaques displayed minor double support and aerial phases during one stride. Asymmetric leg use was indicated by differences in leg kinematics. Axial damping and tangential leg work did not influence the indifferent peak ground reaction forces and impulses, but resulted in a lift of the CoM during contact of the leading leg. The aerial phase was largely due to the use of the double support. Hurdling amplified the differential leg operation. Here, higher ground reaction forces combined with increased double support provided the vertical impulse to overcome the hurdles. Following CoM dynamics during a stride, skipping and hurdling represented bouncing gaits. The elevation of the VPP of bipedal macaques resembled that of human walking and running in the trailing and leading phases, respectively. Because of anatomical restrictions, macaque unilateral skipping differs from that of humans, and may represent an intermediate gait between grounded and aerial running.

Testing conditional quantile independence with functional covariate.

We propose a new non-parametric conditional independence test for a scalar response and a functional covariate over a continuum of quantile levels. We build a Cramer-von Mises type test statistic based on an empirical process indexed by random projections of the functional covariate, effectively avoiding the "curse of dimensionality" under the projected hypothesis, which is almost surely equivalent to the null hypothesis. The asymptotic null distribution of the proposed test statistic is obtained under some mild assumptions. The asymptotic global and local power properties of our test statistic are then investigated. We specifically demonstrate that the statistic is able to detect a broad class of local alternatives converging to the null at the parametric rate. Additionally, we recommend a simple multiplier bootstrap approach for estimating the critical values. The finite-sample performance of our statistic is examined through several Monte Carlo simulation experiments. Finally, an analysis of an EEG data set is used to show the utility and versatility of our proposed test statistic.

Preliminary Evidence for Global Properties in Human Listeners During Natural Auditory Scene Perception.

Theories of auditory and visual scene analysis suggest the perception of scenes relies on the identification and segregation of objects within it, resembling a detail-oriented processing style. However, a more global process may occur while analyzing scenes, which has been evidenced in the visual domain. It is our understanding that a similar line of research has not been explored in the auditory domain; therefore, we evaluated the contributions of high-level global and low-level acoustic information to auditory scene perception. An additional aim was to increase the field's ecological validity by using and making available a new collection of high-quality auditory scenes. Participants rated scenes on 8 global properties (e.g., open vs. enclosed) and an acoustic analysis evaluated which low-level features predicted the ratings. We submitted the acoustic measures and average ratings of the global properties to separate exploratory factor analyses (EFAs). The EFA of the acoustic measures revealed a seven-factor structure explaining 57% of the variance in the data, while the EFA of the global property measures revealed a two-factor structure explaining 64% of the variance in the data. Regression analyses revealed each global property was predicted by at least one acoustic variable (R2 = 0.33-0.87). These findings were extended using deep neural network models where we examined correlations between human ratings of global properties and deep embeddings of two computational models: an object-based model and a scene-based model. The results support that participants' ratings are more strongly explained by a global analysis of the scene setting, though the relationship between scene perception and auditory perception is multifaceted, with differing correlation patterns evident between the two models. Taken together, our results provide evidence for the ability to perceive auditory scenes from a global perspective. Some of the acoustic measures predicted ratings of global scene perception, suggesting representations of auditory objects may be transformed through many stages of processing in the ventral auditory stream, similar to what has been proposed in the ventral visual stream. These findings and the open availability of our scene collection will make future studies on perception, attention, and memory for natural auditory scenes possible.

A new inexact gradient descent method with applications to nonsmooth convex optimization

The paper proposes and develops a novel inexact gradient method (IGD) for minimizing C 1 -smooth functions with Lipschitzian gradients, i.e. for problems of C 1 , 1 optimization. We show that the sequence of gradients generated by IGD converges to zero. The convergence of iterates to stationary points is guaranteed under the Kurdyka-Łojasiewicz (KL) property of the objective function with convergence rates depending on the KL exponent. The newly developed IGD is applied to designing two novel gradient-based methods of nonsmooth convex optimization such as the inexact proximal point methods (GIPPM) and the inexact augmented Lagrangian method (GIALM) for convex programs with linear equality constraints. These two methods inherit global convergence properties from IGD and are confirmed by numerical experiments to have practical advantages over some well-known algorithms of nonsmooth convex optimization.

Flatness-based control in successive loops for VSI-fed PM synchronous motors and induction motors

Electric traction systems consisting of inverter controlled three-phase motors are widely used in electric vehicles. In this article the control problem for the nonlinear dynamics of Voltage Source Inverter-fed synchronous and asynchronous motors is solved with the use of a flatness-based control approach which is implemented in successive loops. The state–space model of these systems is separated into a series of subsystems, which are connected between them in cascading loops. Each one of these subsystems can be viewed independently as a differentially flat system and control about it can be performed with inversion of its dynamics as in the case of input–output linearised flat systems. In this chain of i = 1 , 2 , … , N subsystems, the state variables of the subsequent (i + 1th) subsystem become virtual control inputs for the preceding (ith) subsystem, and so on. In turn, exogenous control inputs are applied to the last subsystem and are computed by tracing backwards the virtual control inputs of the preceding N−1 subsystems. The whole control method is implemented in successive loops and its global stability properties are also proven through Lyapunov stability analysis. The validity of the control method is confirmed in two case studies: (a) control of a Voltage Source Inverter-fed Permanent Magnet Synchronous Motor (VSI-fed PMSM), (ii) control of a Voltage Source Inverter-fed Induction Motor (VSI-fed IM).

REGLO: Provable Neural Network Repair for Global Robustness Properties

We present REGLO, a novel methodology for repairing pretrained neural networks to satisfy global robustness and individual fairness properties. A neural network is said to be globally robust with respect to a given input region if and only if all the input points in the region are locally robust. This notion of global robustness also captures the notion of individual fairness as a special case. We prove that any counterexample to a global robustness property must exhibit a corresponding large gradient. For ReLU networks, this result allows us to efficiently identify the linear regions that violate a given global robustness property. By formulating and solving a suitable robust convex optimization problem, REGLO then computes a minimal weight change that will provably repair these violating linear regions.

Regret Analysis of Policy Gradient Algorithm for Infinite Horizon Average Reward Markov Decision Processes

In this paper, we consider an infinite horizon average reward Markov Decision Process (MDP). Distinguishing itself from existing works within this context, our approach harnesses the power of the general policy gradient-based algorithm, liberating it from the constraints of assuming a linear MDP structure. We propose a vanilla policy gradient-based algorithm and show its global convergence property. We then prove that the proposed algorithm has O(T^3/4) regret. Remarkably, this paper marks a pioneering effort by presenting the first exploration into regret bound computation for the general parameterized policy gradient algorithm in the context of average reward scenarios.

Dual-Window Multiscale Transformer for Hyperspectral Snapshot Compressive Imaging

Coded aperture snapshot spectral imaging (CASSI) system is an effective manner for hyperspectral snapshot compressive imaging. The core issue of CASSI is to solve the inverse problem for the reconstruction of hyperspectral image (HSI). In recent years, Transformer-based methods achieve promising performance in HSI reconstruction. However, capturing both long-range dependencies and local information while ensuring reasonable computational costs remains a challenging problem. In this paper, we propose a Transformer-based HSI reconstruction method called dual-window multiscale Transformer (DWMT), which is a coarse-to-fine process, reconstructing the global properties of HSI with the long-range dependencies. In our method, we propose a novel U-Net architecture using a dual-branch encoder to refine pixel information and full-scale skip connections to fuse different features, enhancing the extraction of fine-grained features. Meanwhile, we design a novel self-attention mechanism called dual-window multiscale multi-head self-attention (DWM-MSA), which utilizes two different-sized windows to compute self-attention, which can capture the long-range dependencies in a local region at different scales to improve the reconstruction performance. We also propose a novel position embedding method for Transformer, named con-abs position embedding (CAPE), which effectively enhances positional information of the HSIs. Extensive experiments on both the simulated and the real data are conducted to demonstrate the superior performance, stability, and generalization ability of our DWMT. Code of this project is at https://github.com/chenx2000/DWMT.

Global Mapping Properties of Some Functions of Class S

The Lemma of Schwarz is one of the most surprising results in complex analysis in the sense that some very weak conditions on an analytic function in the unit disk |z| < 1 imply a very strict behavior of that function in the respective disk. What about the behavior of the function outside the unit disk? This is the question we deal with in this paper. The theory we presented in some previous publications was about univalent functions, not necessarily in the unit disk, but in the most general setting, namely in the fundamental domains of arbitrary analytic functions. Naturally, connections can be expected between the two fields of complex analysis. The purpose of this paper is to explore these connections and take advantage of the well established theory of univalent functions in order to advance the theory of fundamental domains.

Assessing the impact of information-induced self-protection on Zika transmission: A mathematical modeling approach

Abstract As per the World Health Organization’s (WHO’s) suggestions, personal protection via adopting precautionary measures is one of the most effective control aspects to avoid Zika infection in the absence of suitable medical treatment. This personal protection further can be enhanced and explored by propagating information about disease prevalence. Therefore, in this study, we wish to see the effect of information on Zika transmission by formulating a compartmental mathematical model that quantifies the effect of an individual’s behavioral response as self-protection due to information. Furthermore, the basic reproduction number was calculated using the next-generation matrix technique. The model analysis was carried out to determine the local and global stability properties of equilibrium points. In addition, the model shows the occurrence of forward bifurcation when the reproduction number crosses unity. To understand the impact of various model parameters, we conducted a sensitivity analysis using both the normalized sensitivity index and the partial rank correlation coefficient methods. Moreover, we performed numerical simulations to assess the influence of important parameters on the model’s behavior for Zika prevalence. Our study accentuates that as information-induced self-protection increases, the prevalence of Zika infection will be at a very minimum level, and this observation is in line with WHO suggestions.

Search for radio halos in starburst galaxies

Starburst galaxies are undergoing intense episodes of star formation. In these galaxies, gas is ejected into the surrounding environment through winds created by the effect of hot stars and supernova explosions. When interacting with the intergalactic medium, these winds can produce strong shocks capable of accelerating cosmic rays. The radiation from these cosmic rays mainly occurs in radio and gamma rays. The radio halo can be characterized using the scale height, which is an important parameter for understanding cosmic ray acceleration and transport. We searched for the presence of radio halos in a sample of edge-on starburst galaxies gathered from the MeerKAT 1.28 GHz Atlas of Southern Sources in the IRAS Revised Bright Galaxy Sample. The investigation of how the radio halos relate to the global properties of the galaxies can shed light on the understanding of the halo origin and the underlying cosmic ray population. We selected a sample of 25 galaxies with inclinations $i>80^ circ $ from the original sample and modeled their disk and halo contributions. We determined the scale heights and the radio luminosity of the halos when detected. We have detected and characterized 11 radio halos from a sample of 25 edge-on galaxies. Seven of them are reported here for the first time. The average radio scale height is sim 1 kpc. We found that the halo scale heights increase linearly with the radio diameters and this relation does not depend on the star formation rate. All galaxies in our sample follow the radio-infrared relation with a $q$ parameter value of 2.5$ The halo luminosity linearly increases with the infrared luminosity and star formation rate. The dependence of the halo luminosity on the star formation rate and the infrared luminosity supports the hypothesis that the radio halos are the result of synchrotron radiation produced by relativistic electrons and points toward the fact that the star formation activity plays a crucial role in halo creation. The average scale height of 1 kpc implies a dynamical range of 4 Myr, several orders of magnitude greater than the synchrotron losses for electrons of 10 TeV. This suggests that some process must exist to reaccelerate cosmic rays in the halo if gamma-ray emission of a leptonic origin is detected from the halo. According to the relation between the radio and gamma-ray luminosities, we found that NGC 4666 is a potential gamma-ray source for future observations.

Interplay of stellar and gas-phase metallicities: unveiling insights for stellar feedback modelling with Illustris, IllustrisTNG, and EAGLE

ABSTRACT The metal content of galaxies provides a window into their formation in the full context of the cosmic baryon cycle. In this study, we examine the relationship between stellar mass and stellar metallicity (MZ*R) in the hydrodynamic simulations Illustris, TNG, and EAGLE (Evolution and Assembly of GaLaxies and their Environment) to understand the global properties of stellar metallicities within the feedback paradigm employed by these simulations. Interestingly, we observe significant variations in the overall normalization and redshift evolution of the MZ*R across the three simulations. However, all simulations consistently demonstrate a tertiary dependence on the specific star formation rate (sSFR) of galaxies. This finding parallels the relationship seen in both simulations and observations between stellar mass, gas-phase metallicity, and some proxy of galaxy gas content (e.g. SFR, gas fraction, and atomic gas mass). Since we find this correlation exists in all three simulations, each employing a subgrid treatment of the dense, star-forming interstellar medium (ISM) to simulate smooth stellar feedback, we interpret this result as a fairly general feature of simulations of this kind. Furthermore, with a toy analytic model, we propose that the tertiary correlation in the stellar component is sensitive to the extent of the ‘burstiness’ of feedback within galaxies.

A New Approach to Multiroot Vectorial Problems: Highly Efficient Parallel Computing Schemes

In this article, we construct an efficient family of simultaneous methods for finding all the distinct as well as multiple roots of polynomial equations. Convergence analysis proves that the order of convergence of newly constructed family of simultaneous methods is seventeen. Fractal-based simultaneous iterative algorithms are thoroughly examined. Using self-similar features, fractal-based simultaneous schemes can converge to solutions faster, saving computational time and resources necessary for solving nonlinear equations. Fractals analysis illustrates the newly developed method’s global convergence behavior when compared to single root-finding procedures for solving fractional order polynomials that arise in complex engineering applications. Some real problems from various branches of engineering along with some higher degree polynomials are considered as test examples to show the global convergence property of simultaneous methods, performance and efficiency of the proposed family of methods. Further computational efficiencies, CPU time and residual graphs are also drawn to validate the efficiency, robustness of the newly introduced family of methods as compared to the existing methods in the literature.

Dynamic identification of important nodes in complex networks based on the KPDN–INCC method

This article focuses on the cascading failure problem and node importance evaluation method in complex networks. To address the issue of identifying important nodes in dynamic networks, the method used in static networks is introduced and the necessity of re-evaluating node status during node removal is proposed. Studies have found that the methods for identifying dynamic and static network nodes are two different directions, and most literature only uses dynamic methods to verify static methods. Therefore, it is necessary to find suitable node evaluation methods for dynamic networks. Based on this, this article proposes a method that integrates local and global correlation properties. In terms of global features, we introduce an improved k-shell method with fusion degree to improve the resolution of node ranking. In terms of local features, we introduce Solton factor and structure hole factor improved by INCC (improved network constraint coefficient), which effectively improves the algorithm’s ability to identify the relationship between adjacent nodes. Through comparison with existing methods, it is found that the KPDN–INCC method proposed in this paper complements the KPDN method and can accurately identify important nodes, thereby helping to quickly disintegrate the network. Finally, the effectiveness of the proposed method in identifying important nodes in a small-world network with a random parameter less than 0.4 was verified through artificial network experiments.

How galaxy properties vary with filament proximity in the Simba simulations

ABSTRACT We explore the dependence of global galaxy properties in the Simba simulation as a function of distance from filaments identified using DisPerSE. We exclude haloes with mass Mh > 1013 M⊙ to mitigate the impact of group and cluster environments. Galaxies near filaments are more massive and have more satellites, which we control for by examining deviations from best-fitting scaling relations. At z = 0, star formation (SF) is significantly suppressed within $\lesssim 100$ kpc of filaments, more strongly for satellites, indicating substantial pre-processing in filaments. By z = 2, the trend is weak and if anything indicates an increase in SF activity close to filaments. The suppression at $z\lesssim 1$ is accompanied by lowered H i fractions, and increased metallicities, quenched fractions, and dispersion-dominated systems. H2 fractions are not strongly suppressed when controlling for stellar mass, suggesting that SF efficiency drives the drop in SF. By comparing amongst different Simba feedback variant runs, we show that the majority of SF suppression owes to filamentary shock-heating, but there is a non-trivial additional effect from AGN feedback. When looking around massive (Mh > 1013 M⊙) haloes, those galaxies near filaments behave somewhat differently, indicating that filaments provide an additional environmental effect relative to haloes. Finally, we compare Simba results to EAGLE and IllustrisTNG at z = 0, showing that all models predict SF suppression within $\lesssim 100$ kpc of filaments, none the less, detailed differences may be observationally testable.

Global convergence properties of a Dai-Liao-type CGM for unconstrained optimization

Global convergence properties of a Dai-Liao-type CGM for unconstrained optimization

Brief category learning distorts perceptual space for complex scenes.

The formation of categories is known to distort perceptual space: representations are pushed away from category boundaries and pulled toward categorical prototypes. This phenomenon has been studied with artificially constructed objects, whose feature dimensions are easily defined and manipulated. How such category-induced perceptual distortions arise for complex, real-world scenes, however, remains largely unknown due to the technical challenge of measuring and controlling scene features. We address this question by generating realistic scene images from a high-dimensional continuous space using generative adversarial networks and using the images as stimuli in a novel learning task. Participants learned to categorize the scene images along arbitrary category boundaries and later reconstructed the same scenes from memory. Systematic biases in reconstruction errors closely tracked each participant's subjective category boundaries. These findings suggest that the perception of global scene properties is warped to align with a newly learned category structure after only a brief learning experience.

Conformal geodesics and the evolution of spacetimes with positive Cosmological constant.

This article provides a discussion on the construction of conformal Gaussian gauge systems to study the evolution of solutions to the Einstein field equations with positive Cosmological constant. This is done by means of a gauge based on the properties of conformal geodesics. The use of this gauge, combined with the extended conformal Einstein field equations, yields evolution equations in the form of a symmetric hyperbolic system for which standard Cauchy stability results can be employed. This strategy is used to study the global properties of de Sitter-like spacetimes with constant negative scalar curvature. It is then adapted to study the evolution of the Schwarzschild-de Sitter spacetime in the static region near the conformal boundary. This review is based on Minucci et al. 2021 Class. Quantum Grav. 38, 145026. (doi:10.1088/1361-6382/ac0356) and Minucci et al. 2023 Class. Quantum Grav. 40, 145005. (doi:10.1088/1361-6382/acdb3f). This article is part of a discussion meeting issue 'At the interface of asymptotics, conformal methods and analysis in general relativity'.

The EDGE-CALIFA Survey: An Extragalactic Database for Galaxy Evolution Studies

The EDGE-CALIFA survey provides spatially resolved optical integral-field unit and CO spectroscopy for 125 galaxies selected from the Calar Alto Legacy Integral Field Area Survey (CALIFA) Data Release 3 sample. The Extragalactic Database for Galaxy Evolution (EDGE) presents the spatially resolved products of the survey as pixel tables that reduce the oversampling in the original images and facilitate comparison of pixels from different images. By joining these pixel tables to lower-dimensional tables that provide radial profiles, integrated spectra, or global properties, it is possible to investigate the dependence of local conditions on large-scale properties. The database is freely accessible and has been utilized in several publications. We illustrate the use of this database and highlight the effects of CO upper limits on the inferred slopes of the local scaling relations between the stellar mass, star formation rate (SFR), and H2 surface densities. We find that the correlation between H2 and SFR surface density is the tightest among the three relations.