Physical Time Scales Research Articles

Nonlinear studies of modifications to general relativity: Comparing different approaches

Studying the dynamical, nonlinear regime of modified theories of gravity remains a theoretical challenge that limits our ability to test general relativity. Here we consider two generally applicable, but approximate, methods for treating modifications to full general relativity that have been used to study binary black hole mergers and other phenomena in this regime, and compare solutions obtained by them to those from solving the full equations of motion. The first method evolves corrections to general relativity order by order in a perturbative expansion, while the second method introduces extra dynamical fields in such a way that strong hyperbolicity is recovered. We use shift-symmetric Einstein-scalar-Gauss-Bonnet gravity as a benchmark theory to illustrate the differences between these methods for several spacetimes of physical interest. We study the formation of scalar hair about initially nonspinning black holes, the collision of black holes with scalar charge, and the inspiral and merger of binary black holes. By directly comparing predictions, we assess the extent to which those from the approximate treatments can be meaningfully confronted with gravitational wave observations. We find that the order-by-order approach cannot faithfully track the solutions when the corrections to general relativity are non-negligible. The second approach, however, can provide consistent solutions, provided the timescale over which the dynamical fields are driven to their target values is made short compared to the physical timescales. Published by the American Physical Society 2024

Molecular Gas and the Star-Formation Process on Cloud Scales in Nearby Galaxies

Observations that resolve nearby galaxies into individual regions across multiple phases of the gas–star formation–feedback “matter cycle” have provided a sharp new view of molecular clouds, star-formation efficiencies, timescales for region evolution, and stellar feedback. We synthesize these results, covering aspects relevant to the interpretation of observables, and conclude the following: ▪The observed cloud-scale molecular gas surface density, line width, and internal pressure all reflect the large-scale galactic environment while also appearing mostly consistent with properties of a turbulent medium strongly affected by self-gravity.▪Cloud-scale data allow for statistical inference of both evolutionary and physical timescales. These suggest a period of cloud collapse on the order of the free-fall or turbulent crossing time (∼10–30 Myr) followed by forming massive stars and subsequent rapid (≲5 Myr) gas clearing after the onset of star formation. The star-formation efficiency per free-fall time is well determined over thousands of individual regions at εff ≈ 0.5−0.3 +0.7%.▪The role of stellar feedback is now measured using multiple observational approaches. The net yield is constrained by the requirement to support the vertical weight of the galaxy disk. Meanwhile, the short gas-clearing timescales suggest a large role for presupernova feedback in cloud disruption. This leaves the supernovae free to exert a large influence on the larger galaxy, including stirring turbulence, launching galactic-scale winds, and carving superbubbles.

A filtered Rankine–Hugoniot method for consistent stochastic particle LES-FDF modelling of combustion in high-speed flows

A new model consistency scheme based on the filtered form of the Rankine–Hugoniot (R–H) relation is developed for hybrid Eulerian/Lagrangian Large Eddy Simulation-Filtered Density Function (LES-FDF) methods to model combustion in compressible high-speed flows. The approach particularly pertains to the evolution of the FDF stochastic Lagrangian particles in enthalpy space, accounting for the subgrid effects in the filtered R–H relation to ensure stable solutions and model consistency with the total energy field solved by an Eulerian compressible finite volume scheme. An analytical form of the subgrid term appearing in the filtered R–H relation is derived and it is shown to have a significant effect on the ability to accurately produce the post-shock thermochemical state. Subsequently, two novel numerical schemes are proposed based on either a modelled subgrid scale kinetic energy or a relaxation over a physical timescale. In testing for 1D normal shock cases, the former approach is found to be strongly dependent on the filter width and Mach number, while the latter approach produces consistent results. The relaxation method is further tested for a turbulent 3D shock tube case and a 1D detonation case and found to produce numerically consistent and accurate temperature and species fields. It is shown that the subgrid term is critical for accurately and consistently predicting the temperature fields in both cases and for achieving the correct detonation structure involving a leading shock and autoignition in the second case.Novelty and significance statementLES-FDF methods have not been widely used for high-speed combusting flows with strong shocks. Such flows are common in aerospace combustors and accurate modelling of these is essential for their optimisation, especially with rapid transition to alternative fuels. The first novelty is the development of a filtered Rankine–Hugoniot model to ensure energy consistency between the Eulerian LES and the FDF modelled through Lagrangian particles. The inclusion of a subgrid kinetic energy term in the Lagrangian particle energy equation is shown to be essential for producing consistent solutions and accurate prediction of thermodynamics states through discontinuities. This subgrid term is not closed and, therefore, the second novelty lies in proposing a practical numerical scheme which accounts for it. The consistent model and numerical scheme is validated in canonical shock tube and detonation cases.

Poissonian Cellular Potts Models Reveal Nonequilibrium Kinetics of Cell Sorting

Cellular Potts models are broadly applied across developmental biology and cancer research. We overcome limitations of the traditional approach, which reinterprets a modified Metropolis sampling as dynamics, by introducing a physical timescale through Poissonian kinetics and by applying principles of stochastic thermodynamics to separate thermal and relaxation effects from athermal noise and nonconservative forces. Our method accurately describes cell-sorting dynamics in mouse-embryo development and identifies the distinct contributions of nonequilibrium processes, e.g., cell growth and active fluctuations. Published by the American Physical Society 2024

Fractional Extended Diffusion Theory to capture anomalous relaxation from biased/accelerated molecular simulations.

Biased and accelerated molecular simulations (BAMS) are widely used tools to observe relevant molecular phenomena occurring on time scales inaccessible to standard molecular dynamics, but evaluation of the physical time scales involved in the processes is not directly possible from them. For this reason, the problem of recovering dynamics from such kinds of simulations is the object of very active research due to the relevant theoretical and practical implications of dynamics on the properties of both natural and synthetic molecular systems. In a recent paper [A. Rapallo et al., J. Comput. Chem. 42, 586-599 (2021)], it has been shown how the coupling of BAMS (which destroys the dynamics but allows to calculate average properties) with Extended Diffusion Theory (EDT) (which requires input appropriate equilibrium averages calculated over the BAMS trajectories) allows to effectively use the Smoluchowski equation to calculate the orientational time correlation function of the head-tail unit vector defined over a peptide in water solution. Orientational relaxation of this vector is the result of the coupling of internal molecular motions with overall molecular rotation, and it was very well described by correlation functions expressed in terms of weighted sums of suitable time-exponentially decaying functions, in agreement with a Brownian diffusive regime. However, situations occur where exponentially decaying functions are no longer appropriate to capture the actual dynamical behavior, which exhibits persistent long time correlations, compatible with the so called subdiffusive regimes. In this paper, a generalization of EDT will be given, exploiting a fractional Smoluchowski equation (FEDT) to capture the non-exponential character observed in the relaxation of intramolecular distances and molecular radius of gyration, whose dynamics depend on internal molecular motions only. The calculation methods, proper to EDT, are adapted to implement the generalization of the theory, and the resulting algorithm confirms FEDT as a tool of practical value in recovering dynamics from BAMS, to be used in general situations, involving both regular and anomalous diffusion regimes.

Chaotic Diffusion in a Triaxial Galactic Model: an Example of Global Stable Chaos

In this work we focus on the chaotic diffusion in the phase space of a triaxial potential resembling an elliptical galaxy. The transport process is studied in two different action-like starting spaces in order to cope with circulating and noncirculating orbits. Estimates of the diffusion rate obtained by means of the variance approach are discussed in detail and their limitations are exposed. After revisiting the Shannon-entropy-based method from a conceptual point of view in the framework of simple arguments taken from the information theory, we apply it to measure changes in the unperturbed actions or integrals of motion of the system for different sets of small ensembles of random initial conditions. For such sets of ensembles, estimates of the Lyapunov times are also provided. The results show that, within the chaotic component of the phase space, the Lyapunov times are shorter than any physical time scale as the Hubble time, but the diffusion times are much larger than the latter. Thus, we conclude that stable chaos dominates the dynamics of realistic galactic models.

Intermediate Polymer Relaxation Explains the Anomalous Rheology of Nanocomposites with Ultrasmall Attractive POSS Nanoparticles.

The rheological properties of entangled polymers loaded with very small, strongly attractive polyhedral oligomeric silsesquioxane (POSS) fillers differ from that of nanocomposites with larger fillers by (1) the shorter breadth of the entanglement plateau and (2) the relatively unchanged terminal viscosity with increasing POSS loading. Although such anomalous rheological properties can rewrite the property-processing map of materials (e.g., high glass transition temperature and low viscosity), their mechanism remains unclear. In this study, we report that polymer relaxations on intermediate time scales between α and entire-chain relaxation, so-called "slower processes", are responsible for this unusual rheological behavior of poly(2-vinylpyridine)/octa(aminophenyl)silsesquioxane (P2VP/OAPS) nanocomposites. To uncover the effects of entanglements on the nanocomposite dynamics, rheometry is used for variable matrix molecular weights. Results show a systematic change in the rheological response, which is independent of the molecular weight, and in turn, the presence of entanglements. This supports a physical interpretation that a slower process dominates the rheological response of the material at intermediate frequencies on length scales larger than the segment length or the OAPS diameter, while the underlying physical time scales associated with the entanglement relaxation remain unchanged. Such insights are anticipated to assist the future rational design of other highly attractive and ultrasmall nanoparticles that enable a fine-tuned rheological response of nanocomposites across multiple length scales.

A time-consistent stabilized finite element method for fluids with applications to hemodynamics

Several finite element methods for simulating incompressible flows rely on the streamline upwind Petrov–Galerkin stabilization (SUPG) term, which is weighted by tau _{text{SUPG}}. The conventional formulation of tau _{text{SUPG}} includes a constant that depends on the time step size, producing an overall method that becomes exceedingly less accurate as the time step size approaches zero. In practice, such method inconsistency introduces significant error in the solution, especially in cardiovascular simulations, where small time step sizes may be required to resolve multiple scales of the blood flow. To overcome this issue, we propose a consistent method that is based on a new definition of tau _{text{SUPG}}. This method, which can be easily implemented on top of an existing streamline upwind Petrov–Galerkin and pressure stabilizing Petrov–Galerkin method, involves the replacement of the time step size in tau _{text{SUPG}} with a physical time scale. This time scale is calculated in a simple operation once every time step for the entire computational domain from the ratio of the L2-norm of the acceleration and the velocity. The proposed method is compared against the conventional method using four cases: a steady pipe flow, a blood flow through vascular anatomy, an external flow over a square obstacle, and a fluid–structure interaction case involving an oscillatory flexible beam. These numerical experiments, which are performed using linear interpolation functions, show that the proposed formulation eliminates the inconsistency issue associated with the conventional formulation in all cases. While the proposed method is slightly more costly than the conventional method, it significantly reduces the error, particularly at small time step sizes. For the pipe flow where an exact solution is available, we show the conventional method can over-predict the pressure drop by a factor of three. This large error is almost completely eliminated by the proposed formulation, dropping to approximately 1% for all time step sizes and Reynolds numbers considered.

Universal abundance fluctuations across microbial communities, tropical forests, and urban populations.

The growth of complex populations, such as microbial communities, forests, and cities, occurs over vastly different spatial and temporal scales. Although research in different fields has developed detailed, system-specific models to understand each individual system, a unified analysis of different complex populations is lacking; such an analysis could deepen our understanding of each system and facilitate cross-pollination of tools and insights across fields. Here, we use a shared framework to analyze time-series data of the human gut microbiome, tropical forest, and urban employment. We demonstrate that a single, three-parameter model of stochastic population dynamics can reproduce the empirical distributions of population abundances and fluctuations in all three datasets. The three parameters characterizing a species measure its mean abundance, deterministic stability, and stochasticity. Our analysis reveals that, despite the vast differences in scale, all three systems occupy a similar region of parameter space when time is measured in generations. In other words, although the fluctuations observed in these systems may appear different, this difference is primarily due to the different physical timescales associated with each system. Further, we show that the distribution of temporal abundance fluctuations is described by just two parameters and derive a two-parameter functional form for abundance fluctuations to improve risk estimation and forecasting.

An implicit time integration approach for simulation of corona discharges

Corona discharge is a type of electric discharge that occurs when a small conductor carries a voltage strong enough to ionize the surrounding air. The resultant ions are drifted by the electric field and transfer their momentum to neutral particles via elastic collisions, creating a flow effect known as ionic wind that has promising application in flow control. Over the last two decades, a large amount of numerical works have been realized to study this effect. However, simulation of corona discharges with explicit time integration usually requires an excessive amount of time to finish, ranging from days to months in two dimensions, depending on mesh size and physical end time. The reason lies in the profound disparity between physical time scales in a discharge: for example, electron density evolves on the order of picoseconds while the time scale of airflow dynamics is on the order of milliseconds. The objective of this work is therefore to reduce the CPU time of corona discharges. We propose an implicit time strategy in the scope of the Local Field Approximation plasma model. We investigate some algorithms, namely the Lie operator splitting, the Douglas-Rachford method and a nonlinear variant of the Gauss-Seidel algorithm, to solve the system of discrete equations, which are adapted to take into consideration a constraint on the electron density. This constraint is introduced to compensate for sources of electrons from physical processes that are not accounted for in the plasma model; it is expressed by a minimum density, or floor density, imposed on the electrons. Therefore, simplified plasma models can be employed for discharge simulations, for instance a four-specie, four-reaction model is used in this article. The investigation is done on a one-dimensional wire-to-wire corona discharge. After having identified the most suitable algorithm, we carry on to two-dimensional simulations and compare the numerical results with experiment data for different levels of floor density.

Correction to: The climate and compositional variation of the highly eccentric planet HD 80606 b – the rise and fall of carbon monoxide and elemental sulfur

The gas giant HD 80606 b has a highly eccentric orbit (e $\sim$ 0.93). The variation due to the rapid shift of stellar irradiation provides a unique opportunity to probe the physical and chemical timescales and to study the interplay between climate dynamics and atmospheric chemistry. In this work, we present integrated models to study the atmospheric responses and the underlying physical and chemical mechanisms of HD 80606 b. We first run three-dimensional general circulation models (GCMs) to establish the atmospheric thermal and dynamical structures for different atmospheric metallicities and internal heat. Based on the GCM output, we then adopted a 1D time-dependent photochemical model to investigate the compositional variation along the eccentric orbit. The transition of the circulation patterns of HD 80606 b matched the dynamics regimes in previous works. Our photochemical models show that efficient vertical mixing leads to deep quench levels of the major carbon and nitrogen species and the quenching behavior does not change throughout the eccentric orbit. Instead, photolysis is the main driver of the time-dependent chemistry. While CH$_4$ dominates over CO through most of the orbits, a transient state of [CO]/[CH$_4$}] $>$ 1 after periastron is confirmed for all metallicity and internal heat cases. The upcoming JWST Cycle 1 GO program will be able to track this real-time CH$_4$--CO conversion and infer the chemical timescale. Furthermore, sulfur species initiated by sudden heating and photochemical forcing exhibit both short-term and long-term cycles, opening an interesting avenue for detecting sulfur on exoplanets.

The climate and compositional variation of the highly eccentric planet HD 80606 b – the rise and fall of carbon monoxide and elemental sulfur

ABSTRACTThe gas giant HD 80606 b has a highly eccentric orbit (e ∼ 0.93). The variation due to the rapid shift of stellar irradiation provides a unique opportunity to probe the physical and chemical timescales and to study the interplay between climate dynamics and atmospheric chemistry. In this work, we present integrated models to study the atmospheric responses and the underlying physical and chemical mechanisms of HD 80606 b. We first run 3D general circulation models (GCMs) to establish the atmospheric thermal and dynamical structures for different atmospheric metallicities and internal heat. Based on the GCM output, we then adopted a 1D time-dependent photochemical model to investigate the compositional variation along the eccentric orbit. The transition of the circulation patterns of HD 80606 b matched the dynamics regimes in previous works. Our photochemical models show that efficient vertical mixing leads to deep quench levels of the major carbon and nitrogen species and the quenching behaviour does not change throughout the eccentric orbit. Instead, photolysis is the main driver of the time-dependent chemistry. While CH4 dominates over CO through most of the orbits, a transient state of [CO]/[CH4] > 1 after periastron is confirmed for all metallicity and internal heat cases. The upcoming JWST Cycle 1 GO program will be able to track this real-time CH4–CO conversion and infer the chemical timescale. Furthermore, sulfur species initiated by sudden heating and photochemical forcing exhibit both short-term and long-term cycles, opening an interesting avenue for detecting sulfur on exoplanets.

REQUIEM-2D: A Diversity of Formation Pathways in a Sample of Spatially Resolved Massive Quiescent Galaxies at z ∼ 2

REQUIEM-2D (Resolving Quiescent Magnified Galaxies with 2D Grism Spectroscopy) comprises a sample of eight massive () strongly lensed quiescent galaxies at z ∼ 2. REQUIEM-2D combines the natural magnification from strong gravitational lensing with the high-spatial-resolution grism spectroscopy of the Hubble Space Telescope through a spectrophotometric fit to study spatially resolved stellar populations. We show that quiescent galaxies in the REQUIEM-2D survey have diverse formation histories with age gradients at the 1σ–3σ level, including examples of (1) a younger central region supporting outside-in formation, (2) flat age gradients that show evidence for both spatially uniform early formation and inside-out quenching, and (3) regions at a fixed radial distance having different ages (such asymmetries cannot be recovered when averaging stellar population measurements azimuthally). The typical dust attenuation curve for the REQUIEM-2D galaxies is constrained to be steeper than Calzetti’s law in the UV and generally consistent with A V < 1. Combined together and accounting for the different physical radial distances and formation timescales, we find that the REQUIEM-2D galaxies that formed earlier in the universe exhibit slow and uniform growth in their inner core, whereas the galaxies that formed later have rapid inner growth in their inner core with younger ages than the outskirts. These results challenge the currently accepted paradigm of how massive quiescent galaxies form, where the earliest galaxies are thought to form most rapidly. Significantly larger samples close to the epoch of formation with similar data quality and higher spectral resolution are required to validate this finding.

Accumulative reservoir construction: Bridging continuously relaxed and periodically refreshed extended reservoirs

The simulation of open many-body quantum systems is challenging, requiring methods to both handle exponentially large Hilbert spaces and represent the influence of (infinite) particle and energy reservoirs. These two requirements are at odds with each other: Larger collections of modes can increase the fidelity of the reservoir representation but come at a substantial computational cost when included in numerical many-body techniques. An increasingly utilized and natural approach to control the growth of the reservoir is to cast a finite set of reservoir modes themselves as an open quantum system. There are, though, many routes to do so. Here, we introduce an accumulative reservoir construction -- an ARC -- that employs a series of partial refreshes of the extended reservoirs. Through this series, the representation accumulates the character of an infinite reservoir. This provides a unified framework for both continuous (Lindblad) relaxation and a recently introduced periodically refresh approach (i.e., discrete resets of the reservoir modes to equilibrium). In the context of quantum transport, we show that the phase space for physical behavior separates into discrete and continuous relaxation regimes with the boundary between them set by natural, physical timescales. Both of these regimes "turnover" into regions of over- and under-damped coherence in a way reminiscent of Kramers' crossover. We examine how the range of behavior impacts errors and the computational cost, including within tensor networks. These results provide the first comparison of distinct extended reservoir approaches, showing that they have different scaling of error versus cost (with a bridging ARC regime decaying fastest). Exploiting the enhanced scaling, though, will be challenging, as it comes with a substantial increase in (operator space) entanglement entropy.

Predicting surfactant phase behavior with a molecularly informed field theory

HypothesisThe computational study of surfactants and self-assembly is challenging because 1) models need to reflect chemistry-specific interactions, and 2) self-assembled structures are difficult to equilibrate with conventional molecular dynamics. We propose to overcome these challenges with a multiscale simulation approach where relative entropy minimization transfers chemically-detailed information from all-atom (AA) simulations to coarse-grained (CG) models that can be simulated using field-theoretic methods. Field-theoretic simulations are not limited by intrinsic physical time scales like diffusion and allow for rigorous equilibration via free energy minimization. This approach should enable the study of properties that are difficult to obtain by particle-based simulations. Simulation WorkWe apply this workflow to sodium dodecylsulfate. To ensure chemical fidelity we present an AA force field calibrated against interfacial tension experiments. We generate CG models from AA simulation trajectories and show that particle-based and field-theoretic simulations of the CG model reproduce AA simulations and experimental measurements. FindingsThe workflow captures the complex balance of interactions in a multicomponent system ultimately described by an atomistic model. The resulting CG models can study complex 3D phases like double or alternating gyroids, and reproduce salt effects on properties like aggregation number and shape transitions.

The hierarchy of low-dimensional manifolds in the context of multiple mapping conditioning mixing model

A new model to couple the multiple mapping conditioning (MMC) mixing model with manifold based simplified chemistry is proposed. The concept is based on the fact that the system state can be locally confined to a manifold with lower dimension, which is embedded in the manifold with higher dimension. Therefore, in the framework of the MMC mixing model, particles to be mixed must be selected such that they are localized in the reference variable space with the dimension which corresponds to the minimum number of the progress variables describing the thermo-kinetic states locally. This can be achieved by comparing the physical mixing time-scale with the chemical time-scales describing the movement on the slow manifold, and the dimension of the necessary reference variables can be determined automatically. The present work uses an IEM-based MMC mixing model and Reaction-Diffusion Manifolds (REDIMs) as the simplified chemistry, but it can be extended easily to other mixing models. The proposed methodology is validated by testing the well-known non-premixed Sandia Flame D and F, and the results show good agreement with experimental results and those obtained using the detailed chemistry.

Real-time thermoacoustic data assimilation

Low-order thermoacoustic models are qualitatively correct, but typically, they are quantitatively inaccurate. We propose a time-domain bias-aware method to make qualitatively low-order models quantitatively (more) accurate. First, we develop a Bayesian ensemble data assimilation method for a low-order model to self-adapt and self-correct any time that reference data become available. Second, we apply the methodology to infer the thermoacoustic states and heat-release parameters on the fly without storing data (real time). We perform twin experiments using synthetic acoustic pressure measurements to analyse the performance of data assimilation in all nonlinear thermoacoustic regimes, from limit cycles to chaos, and interpret the results physically. Third, we propose practical rules for thermoacoustic data assimilation. An increase, reject, inflate strategy is proposed to deal with the rich nonlinear behaviour; and physical time scales for assimilation are proposed in non-chaotic regimes (with the Nyquist–Shannon criterion) and in chaotic regimes (with the Lyapunov time). Fourth, we perform data assimilation using data from a higher-fidelity model. We introduce an echo state network to estimate in real time the forecast bias, which is the model error of the low-fidelity model. We show that: (i) the correct acoustic pressure, parameters, and model bias can be inferred accurately; (ii) the learning is robust as it can tackle large uncertainties in the observations (up to 50 % of the mean values); (iii) the uncertainty of the prediction and parameters is naturally part of the output; and (iv) both the time-accurate solution and statistics can be inferred successfully. Data assimilation opens up new possibility for real-time prediction of thermoacoustics by combining physical knowledge and experimental data synergistically.

Efficient Simulation of Freezing of Water in Large Tanks Including Expansion of Ice

Abstract A liquid water-urea mixture is stored onboard diesel vehicles and used for exhaust aftertreatment. In cold weather conditions, the mixture may freeze and the freezing process may span over a day. In the first part of our study (Journal of Thermal Science and Engineering Applications—Transactions of the ASME, Vol. 13, p. 011008, 2021), it was shown that traditional computational methods are impractical for modeling such large-duration freezing processes because of restrictions in the time-step size posed by numerical stability and physical time scale considerations. A model, in which natural convection driven thermal transport is treated as a diffusive process, was developed and demonstrated. Since the flow field was not computed in this model, the computations were found to be orders of magnitude more efficient than traditional methods. This preliminary model did not account for the expansion of ice. Here, a new model that accounts for the expansion of ice, and the consequent rise of the initial air-water/ice interface (ice dome formation) is presented. An additional conservation equation for excess volume fraction is introduced to this end and is solved using the unstructured finite-volume procedure and sub-time-stepping. Since the flow field is not computed, the air-water/ice interface is tracked using a new algorithm similar to the traditional volume-of-fluid (VOF) method, but one that constructs fluxes using a diffusive formulation rather than an advective one. Validation studies in full-scale three-dimensional tanks show good agreement with measured temperature-time data. It is found that the air-water/ice interface first evolves to a concave shape before finally becoming a convex ice dome after full solidification.

The Gas–Star Formation Cycle in Nearby Star-forming Galaxies. II. Resolved Distributions of CO and Hα Emission for 49 PHANGS Galaxies

Abstract The relative distribution of molecular gas and star formation in galaxies gives insight into the physical processes and timescales of the cycle between gas and stars. In this work, we track the relative spatial configuration of CO and Hα emission at high resolution in each of our galaxy targets and use these measurements to quantify the distributions of regions in different evolutionary stages of star formation: from molecular gas without star formation traced by Hα to star-forming gas, and to H ii regions. The large sample, drawn from the Physics at High Angular resolution in Nearby GalaxieS ALMA and narrowband Hα (PHANGS-ALMA and PHANGS-Hα) surveys, spans a wide range of stellar masses and morphological types, allowing us to investigate the dependencies of the gas‒star formation cycle on global galaxy properties. At a resolution of 150 pc, the incidence of regions in different stages shows a dependence on stellar mass and Hubble type of galaxies over the radial range probed. Massive and/or earlier-type galaxies in our sample exhibit a significant reservoir of molecular gas without star formation traced by Hα, while lower-mass galaxies harbor substantial H ii regions that may have dispersed their birth clouds or formed from low-mass, more isolated clouds. Galactic structures add a further layer of complexity to the relative distribution of CO and Hα emission. Trends between galaxy properties and distributions of gas traced by CO and Hα are visible only when the observed spatial scale is ≪500 pc, reflecting the critical resolution requirement to distinguish stages of the star formation process.

Vertical Transport Timescale of Surface‐Produced Particulate Material in the Chesapeake Bay

AbstractAccumulation and remineralization of surface‐produced particulate organic matter (POM) in the water column and seabed link closely to hypoxia and the health of aquatic ecosystems. The POM retention time provides a key timescale to interpret biochemical reaction processes. In this study, we investigated the spatiotemporal variations in the vertical particulate age (VPA) of surface‐produced POM, which is the mean time elapsed since the particulates last contact the surface, by incorporating major physical processes including sinking, resuspension, and deposition in the Chesapeake Bay. It was found that the vertical transport time for the particulates (i.e., VPA) is much longer than the dissolved counterparts as the former consists of new material from the surface and the resuspended aged material that has elongated resting on the seabed after deposition. The VPA is sensitive to settling velocity, especially in low‐frequent resuspension environments, and varies over 2 orders of magnitude with settling velocity from 0 to 10 m/day. Slow‐sinking material can remain in suspension and seldom settle to the seabed, thus mainly contribute to pelagic processes, while the fast‐sinking material connects closely with benthic processes. The seasonality of VPA decreases as the settling velocity increases. No significant difference in VPA was found between wet and dry years, yet the episodic strong flood events entrain old materials from the depositional lateral shoals to increase VPA in the channel. The transport age bridges cross disciplinaries by providing the fourth‐dimensional age information as a common currency to compare the physical transport timescale with the timescales for biochemical reactions.