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At least 451 records · Page 25

Spatial Decorrelation of Young Stars and Dense Gas as a Probe of the Star Formation–Feedback Cycle in Galaxies

The spatial decorrelation of dense molecular gas and young stars observed on ≲1 kpc scales in nearby galaxies indicates rapid dispersal of star-forming regions by stellar feedback. In this work, we explore the sensitivity of this decorrelation to different processes controlling the structure of the interstellar medium, the abundance of molecular gas, star formation, and feedback in a suite of simulations of an isolated dwarf galaxy with structural properties similar to NGC 300 that self-consistently model radiative transfer and molecular chemistry. Our fiducial simulation reproduces the magnitude of decorrelation and its scale dependence measured in NGC 300, and we show that this agreement is due to different aspects of feedback, including H 2 dissociation, gas heating by the locally variable UV field, early mechanical feedback, and supernovae. In particular, early radiative and mechanical feedback affects the correlation on ≲100 pc scales, while supernovae play a significant role on ≳ 100 pc scales. The correlation is also sensitive to the choice of the local star formation efficiency per free fall time, ϵ ff , which provides a strong observational constraint on ϵ ff when the global star formation rate is independent of its value. Finally, we explicitly show that the degree of correlation between the peaks of molecular gas and star formation density is directly related to the distribution of the lifetimes of star-forming regions.

79 ASTRONOMY AND ASTROPHYSICS↗

Low-dose high-resolution $\mathrm{TOF}$-$\mathrm{PET}$ using ionization-activated multi-state low-$\mathrm{Z}$ detector media

We propose PET scanners using low atomic number media that undergo a persistent local change of state along the paths of the Compton recoil electrons. Measurement of the individual scattering locations and angles, deposited energies, and recoil electron directions allows using the kinematical constraints of the 2-body Compton scattering process to perform a statistical time-ordering of the scatterings, with a high probability of precisely identifying where the gamma first interacted in the detector. In these cases the Line-of-Response is measured with high resolution, determined by the underlying physics processes and not the detector segmentation. There are multiple such media that act through different mechanisms. As an example in which the change of state is quantum-mechanical through a change in molecular configuration, rather than thermodynamic, as in a bubble chamber, we present simulations of a two-state photoswitchable organic dye, a ‘Switchillator’, that is activated to a fluorescent-capable state by the ionization of the recoil electrons. The activated state is persistent, and can be optically excited multiple times to image individual activated molecules. Energy resolution is provided by counting the activated molecules. Location along the LOR is implemented by large-area time-of-flight MCP-PMT photodetectors with single photon time resolution in the tens of ps and sub-mm spatial resolution. Simulations indicate a large reduction of dose.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Field-level reconstruction from foreground-contaminated 21-cm maps

Current and upcoming 21-cm experiments will soon be able to map 21-cm spatial fluctuations in three dimensions for a wide range of redshifts. However, bright foreground contamination and the nature of radio interferometry create significant challenges, making it difficult to access rich cosmological information from the Fourier modes that lie within the “foreground wedge”. Here, in this work, we introduce two approaches aiming to reconstruct the full 21-cm density field, including the missing modes in the wedge: (a) a field-level inference under an effective field theory (EFT) framework; (b) a diffusion-based deep generative model trained on simulations. Under the EFT framework, we implement a fully differentiable forward model that maps the initial conditions of matter fluctuations to the observed, foreground-filtered 21-cm maps. This enables a gradient-based sampler to simultaneously sample the initial conditions and bias parameters, allowing a physically motivated mode reconstruction. Alternatively, we apply a variational diffusion model to perform 21-cm density reconstruction at the map level. Our model is trained on semi-numerical simulations over a wide range of astrophysical parameters. Our results from both approaches should provide improved cosmological constraints from the field level and also enable cross-correlation between experiments that have little or no overlapping modes.

cosmological perturbation theory↗

The spatial and temporal evolution of the Portland and Tualatin forearc basins, Oregon, USA

The Portland and Tualatin basins are part of the Salish-Puget-Willamette Lowland, a 900-km-long, forearc depression lying between the volcanic arc and the Coast Ranges of the Cascadia convergent margin. Such inland seaways are characteristic of warm, young slab subduction. We analyzed the basins to better understand their evolution and relation to Coast Range history and to provide an improved tectonic framework for the Portland metropolitan area. We model three key horizons in the basins: (1) the top of the Columbia River Basalt Group (CRBG), (2) the bottom of the CRBG, and (3) the top of Eocene basement. Isochore maps constrain basin depocenters during (1) Pleistocene to mid-Miocene time (0–15 Ma), (2) CRBG (15.5–16.5 Ma), and (3) early Miocene to late Eocene (ca. 17–35 Ma) time. Results show that the Portland and Tualatin basins have distinct mid-Miocene to Quaternary depocenters but were one continuous basin from the Eocene until mid-Miocene time. A NW-striking gravity low coincident with the NW-striking, fault-bounded Portland Hills anticline is interpreted as an older graben coincident with observed thickening of CRBG flows and underlying sedimentary rocks. Neogene transpression in the forearc structurally inverted the Sylvan-Oatfield and Portland Hills normal faults as high-angle dextral-reverse faults, separating the Portland and Tualatin basins. An eastward shift of the forearc basin depocenter and ten-fold decrease in accommodation space provide temporal constraints on the emergence of the Coast Range to the west. Clockwise rotation and northward transport of the forearc is deforming the basins and producing local earthquakes beneath the metropolitan area.

15 GEOTHERMAL ENERGY↗

Modified gravitational wave propagation with higher modes and its degeneracies with lensing

Low-energy alternatives to General Relativity (GR) generically modify the phase of gravitational waves (GWs) during their propagation. As detector sensitivities increase, it becomes key to understand how these modifications affect the GW higher modes and to disentangle possible degeneracies with astrophysical phenomena. We apply a general formalism — the WKB approach — for solving analytically wave propagation in the spatial domain with a modified dispersion relation (MDR). We compare this WKB approach to applying a stationary phase approximation (SPA) in the temporal domain with time delays associated to the group or particle velocity. To this end, we extend the SPA to generic signals with higher modes, keeping careful track of reference phases and arrival times. We find that the WKB approach coincides with the SPA using the group velocity, in agreement with the principles of wave propagation. We then explore the degeneracies between a GW propagation with an MDR and a strongly-lensed GW in GR, since the latter can introduce a frequency-independent phase shift which is not degenerate with source parameters in the presence of higher modes. We find that for a particular MDR there is an exact degeneracy for wave propagation, unlike with the SPA for particle propagation. For the other cases, we search for the values of the MDR parameters that minimize the χ 2 and conclude that strongly-lensed GR GWs could be misinterpreted as GWs in modified gravity. As a result, future MDR constraints with higher mode GWs should include the possibility of frequency-independent phase shifts, allowing for the identification of modified gravity and strong lensing distortions at the same time.

79 ASTRONOMY AND ASTROPHYSICS↗

Long-term leaf C:N ratio change under elevated CO 2 and nitrogen deposition in China: Evidence from observations and process-based modeling

Climate change, elevating atmosphere CO 2 (eCO 2 ) and increased nitrogen deposition (iNDEP) are altering the biogeochemical interactions between plants, microbes and soils, which further modify plant leaf carbon-nitrogen (C:N) stoichiometry and their carbon assimilation capability. Many field experiments have observed large sensitivity of leaf C:N ratio to eCO 2 and iNDEP. However, the large-scale pattern of this sensitivity is still unclear, because eCO 2 and iNDEP drive leaf C:N ratio toward opposite directions, which are further compounded by the complex processes of nitrogen acquisition and plant-and-microbial nitrogen competition. Here, we attempt to map the leaf C:N ratio spatial variation in the past 5 decades in China with a combination of data-driven model and process-based modeling. These two approaches showed consistent results. Over different regions, we found that leaf C:N ratio had significant but uneven changes between 2 time periods (1960-1989 and 1990-2015): a 5% ± 8% increase for temperate grasslands in northern China, a 3% ± 6% increase for boreal grasslands in western China, and by contrast, a 7% ± 6% decrease for temperate forests in southern China, and a 3% ± 5% decrease for boreal forests in northeastern China. Additionally, the structural equation models indicated that the leaf C:N change was sensitive to ΔNDEP, ΔCO 2 and ΔMAT rather than ΔMAP and ecosystem types. In this work, process-based modeling suggested that iNDEP was the main source of soil mineral nitrogen change, dominating leaf C:N ratio change in most areas in China, while eCO 2 led to leaf C:N ratio increase in low iNDEP area. This study also indicates that the long-term leaf C:N ratio acclimation was dominated by climate constraint, especially temperature, but was constrained by soil N availability over decade scale.

54 ENVIRONMENTAL SCIENCES↗

Kaluza-Klein graviton freeze-in and big bang nucleosynthesis

In models featuring extra spatial dimensions, particle collisions in the early Universe can produce Kaluza-Klein gravitons. Such particles will later decay, potentially impacting the process of big bang nucleosynthesis. In this paper, we consider scenarios in which gravity is free to propagate throughout n flat, compactified extra dimensions, while the fields of the Standard Model are confined to a ( 3 + 1 )-dimensional brane. We calculate the production and decay rates of the states that make up the Kaluza-Klein graviton tower and determine the evolution of their abundances in the early Universe. We then go on to evaluate the impact of these decays on the resulting light element abundances. We identify significant regions of previously unexplored parameter space that are inconsistent with measurements of the primordial helium and deuterium abundances. In particular, we find that for the case of one extra dimension (two extra dimensions), the fundamental scale of gravity must be M ⋆ ≳ 2 × 10 13 GeV ( M ⋆ ≳ 1 0 10 GeV ) unless the temperature of the early Universe was never greater than T ∼ 2 TeV ( T ∼ 1 GeV ). For larger values of n , these constraints are less stringent. For the case of n = 6 , for example, our analysis excludes all values of M ⋆ less than ∼ 10 6 GeV , unless the temperature of the Universe was never greater than T ∼ 3 TeV . The results presented here severely limit the possibility that black holes were efficiently produced through particle collisions in the early Universe’s thermal bath. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Characterization of oceanic post-cold frontal clouds and their model representation. Final report

Low-level clouds are ubiquitous over the oceans, and their impact on the Earth’ radiative budget is important. However, general circulation models (GCMs) that are used to represent our climate and its evolution still experience problems to represent their correct amount and radiative impact. In the extratropical latitudes (~30-60 N/S), cloud properties are strongly modulated by the occurrence of anti-cyclones (high pressure systems) and cyclones (low pressure systems). While deep clouds dominate in cyclones near the center and along the cold and warm fronts, low-level clouds populate the colder regions of the cyclones, and more specifically the region in the wake of the cold fronts, the post-cold frontal region (PCF). The GCMs mentioned above were found to underestimate the amount of these PCF clouds, and this caused errors in their representation of the amount of solar radiation at the surface of the southern hemisphere oceans, causing an excess in absorption and errors in long-term predictions. To better understand which processes are ill-represented in the GCMs to cause such issues, we used ground-based observations from the Eastern North Atlantic (ENA) ARM site and a high resolution regional model (called WRF) to examine the properties of PCF clouds. With the WRF model, we simulated the passage of a cold front at the ENA site using theoretically distinct representations of convection and the physics of the boundary layer. While these physical representations had little impact on the timing, structure and circulation of the cold front, we found a high sensitivity to how the large scale information was fed into the model. Errors rapidly developed if the incoming flow information was injected too far from the site, but 1000 km was found to be an optimal distance between the outer boundary and the ENA site for a realistic cold front passage. With this model, we then conducted a series of experiment where convection and boundary layer schemes were changed, and revealed that 1) the clouds were more sensitive to the convection than boundary layer schemes and 2) the interaction between the two has a large impact. Furthermore, changing the representation of the physics in the model had greater impacts on PCF clouds than changing the initial conditions. As large-scale models increase their spatial resolution, convection will eventually be resolved but it remains that their representation of the physics of the boundary layer will matter for the correct representation of shallow (low-level) clouds. Observations were used to find which large-scale information had a clear relationship with PCF cloud and precipitation properties, in view of helping with GCM parameterizations and evaluation. Both lower troposphere stability and surface forcing were found to be important for PCF clouds that experience more vigorous dynamics than their tropical or subtropical counterparts. For cloud base and top heights, a simple measure of the change in potential temperature between the surface and the 800 hPa was found to be a good predictor. This relationship was found to hold as well when using data from campaigns recently conducted in the southern ocean south of Tasmania. A recent GCM was found to succeed in representing similar relations. For cloud depth, water content, and different characteristics of precipitation both the temperature contrast between the surface and near-air and the near-surface wind speed had a strong relationship. To summarize, through observational constraints and regional model experiments, the project has provided guidance to evaluate GCMs and tools to improve their representation of low-level clouds in the extratropics. It has also highlighted differences in behavior between these clouds and those typically found in the subtropics, thus opening new avenues of research for shallow clouds in general.

54 ENVIRONMENTAL SCIENCES↗

ARES. V. No Evidence For Molecular Absorption in the HST WFC3 Spectrum of GJ 1132 b

We present a study on the spatially scanned spectroscopic observations of the transit of GJ 1132 b, a warm (∼500 K) super-Earth (1.13 R {sub ⊕}) that was obtained with the G141 grism (1.125–1.650 μm) of the Wide Field Camera 3 (WFC3) on board the Hubble Space Telescope. We used the publicly available Iraclis pipeline to extract the planetary transmission spectra from the five visits and produced a precise transmission spectrum. We analyzed the spectrum using the TauREx3 atmospheric retrieval code, with which we show that the measurements do not contain molecular signatures in the investigated wavelength range and are best fit with a flat-line model. Our results suggest that the planet does not have a clear primordial, hydrogen-dominated atmosphere. Instead, GJ 1132 b could have a cloudy hydrogen-dominated atmosphere, have a very enriched secondary atmosphere, be airless, or have a tenuous atmosphere that has not been detected. Due to the narrow wavelength coverage of WFC3, these scenarios cannot be distinguished yet, but the James Webb Space Telescope may be capable of detecting atmospheric features, although several observations may be required to provide useful constraints.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Measuring cosmological distances using cluster edges as a standard ruler

ABSTRACT The line-of-sight velocity dispersion profile of galaxy clusters exhibits a ‘kink’ corresponding to the spatial extent of orbiting galaxies. Because the spatial extent of a cluster is correlated with the amplitude of the velocity dispersion profile, we can utilize this feature as a gravity-calibrated standard ruler. Specifically, the amplitude of the velocity dispersion data allows us to infer the physical cluster size. Consequently, observations of the angular scale of the ‘kink’ in the profile can be translated into a distance measurement to the cluster. Assuming the relation between cluster radius and cluster velocity dispersion can be calibrated from simulations, we forecast that with existing data from the Sloan Digital Sky Survey we will be able to measure the Hubble constant with 3.0 per cent precision. Implementing our method with data from the Dark Energy Spectroscopic Instrument (DESI) will result in a 1.3 per cent measurement of the Hubble constant. Adding cosmological supernova data improves the uncertainty of the DESI measurement to 0.7 per cent. While these error estimates are statistical only, they provide strong motivation for pursuing the necessary simulation program required to characterize and calibrate the systematic uncertainties impacting our proposed measurement. Whether or not our proposed measurement can in fact result in competitive H0 constraints will depend on what the eventual systematics floor for this method is.

79 ASTRONOMY AND ASTROPHYSICS↗

On the gamma-ray emission from the core of the Sagittarius dwarf galaxy

ABSTRACT We use Fermi-LAT data to analyse the faint gamma-ray source located at the centre of the Sagittarius (Sgr) dwarf spheroidal galaxy. In the 4FGL-DR3 catalogue, this source is associated with the globular cluster, M54. We investigate the spectral energy distribution and spatial extension of this source, with the goal of testing two hypotheses: (1) the emission is due to millisecond pulsars within M54, or (2) the emission is due to annihilating dark matter from the Sgr halo. For the pulsar interpretation, we consider a two-component model which describes both the lower-energy magnetospheric emission and possible high-energy emission arising from inverse Compton scattering. We find that this source has a point-like morphology at low energies, consistent with magnetospheric emission, and find no evidence for a higher-energy component. For the dark matter interpretation, we find the signal favours a dark matter mass of mχ = 29.6 ± 5.8 GeV and an annihilation cross section of $\sigma v = (2.1 \pm 0.59) \times 10^{-26} \, \text{cm}^3$ s−1 for the $b \bar{b}$ channel (or mχ = 8.3 ± 3.8 GeV and $\sigma v = (0.90 \pm 0.25) \times 10^{-26} \, \text{cm}^3$ s−1 for the τ+τ− channel), when adopting a J-factor of $J=10^{19.6} \, \text{GeV}^2 \, \text{cm}^{-5}$. This parameter space is consistent with gamma-ray constraints from other dwarf galaxies and with dark matter interpretations of the Galactic Centre Gamma-Ray Excess.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Toward Better Understanding of Microphysical Processes and Resulting Precipitation Physics: A Merger Of Observations and Cloud Models (Final Report)

A large database of global disdrometer observations and a diverse set of simulations from the Regional Atmospheric Modeling System (RAMS) were compared using principal component analysis (PCA) in order to better understand warm and ice-based precipitation processes. The analysis demonstrated that six distinct precipitation groups (PGs) with common characteristics were revealed in both the observations and model simulations. These PGs were defined by similar co-variability of rain parameters. However, the model showed large concentrations of drops with a given size compared to the observations. Detailed investigations determined the parameterization of drop breakup was forcing the drops to an equilibrium size with a stronger constraint than was indicated by the observations. A series of sensitivity studies permutating the rain shape parameter in the RAMS 2-moment bulk scheme demonstrated how the assumed shape of the rain distribution influences the microphysics as well as precipitation characteristics. Results were compared to the same simulations performed with a bin microphysics scheme where the rain shape parameter is freely evolving. In the bin scheme, a wide range of shape parameters were found, with horizontal and vertical variability, in addition to being a function of storm lifetime. The results of this study highlight the limitations of a fixed assumed rain distribution in 2-moment microphysics schemes. Model simulations were used to probe the microphysical origins of the six PGs. Rain budgets from a supercell case showed that several of the groups hypothesized to be associated with strong ice microphysical processes had significant contributions from melting hail, but the complexity of ice and warm-rain processes in the supercell precluded definitive determination of microphysical origins for many of the PGs. A case study from the Mid-latitude Continental Convection and Clouds Experiment (MC3E) compared the model PGs to disdrometer observations, and demonstrated the spatial and temporal variability of the PGs which is not possible from disdrometer point measurements alone. The analyses performed during this project demonstrated how statistical analysis can provide a robust method for comparing model simulations and observations, which ultimately resulted identification of limitations in some current microphysics parameterizations as well as insights into precipitation variability which ultimately benefits both observations and modeling efforts.

54 ENVIRONMENTAL SCIENCES↗

Resonant scattering at the center of the galaxy cluster PKS 0745-191 with XRISM

We report evidence of the resonant scattering effect at the center of the galaxy cluster PKS 0745-191 with XRISM. We analyzed XRISM/Resolve commissioning-phase observations of the distant cluster PKS 0745-191 ($z = 0.103$) with a $54$ ks exposure. The gain drift was corrected using the onboard modulated X-ray source (MXS), and spectra were extracted from all the pixels that were well illuminated by MXS, the core region (four central pixels, $\sim$100 kpc), and the surrounding region. A single-temperature collisional ionization equilibrium (CIE) model fits the full field-of-view spectrum with $kT \approx 6$ keV and a turbulent velocity of ${\approx}120$ km s$^{-1}$. From the core ($r < 50$ kpc) spectrum, we detected a ${\approx}22\%$ suppression of the Fe xxv He$\alpha$ resonance (w) line relative to the CIE prediction. We performed a Monte Carlo simulation to calculate the resonant scattering (RS) effect using radial profiles from Chandra data. The RS-inferred turbulence agrees with that by Resolve line-broadening, demonstrating that RS provides an independent and consistent constraint on ICM turbulence. These results highlight XRISM/Resolve’s potential for turbulence studies in galaxy clusters.

Astronomy and AstroPhysics↗

Thermal exchange-correlation functionals: Capturing quantum electron behavior in warm, dense plasmas

We summarize and give perspective upon recent progress in developing non-empirical constraint-based thermal (i.e., free energy) exchange-correlation (XC) density functionals essential for accurate description of the quantum behavior of electrons in warm, dense plasmas. After delineating the critical role of ground-state functionals for zero-temperature, time-dependent DFT, we outline the underpinnings of local density approximation, generalized gradient approximation (GGA), and meta-GGA XC free-energy functionals. Two basic thermalization principles for upgrading ground-state XC functionals to successful thermal ones are emphasized. Then, we turn to a long-standing challenge, assessment of the accuracy of well-founded functionals. Unlike the ground state, there are a few exact results for large T and P. An exception is path integral Monte Carlo (PIMC) data for dense H/D and He plasmas. For those, we did ab initio molecular dynamics simulations under selected thermodynamic conditions employing five thermal XC functionals: two approximate thermal GGAs, fully thermal GGA, an approximate meta-GGA, and fully thermal meta-GGA. Comparisons with the PIMC data show that functionals thermalized by augmenting a non-thermal functional with a lower-level thermal contribution are inferior to functionals with thermal XC and spatial inhomogeneity effects taken into account at the same level of refinement. We believe this and similar evidence should be convincing to the high-energy density physics community of the necessity of use of proper thermal XC functionals in simulation studies of finite-temperature quantum effects in warm, dense plasmas.

Ab-initio molecular dynamics↗

Changes in Future Precipitation Mean and Variability across Scales

Changes in precipitation variability can have large societal consequences, whether at the short time scales of flash floods or the longer time scales of multiyear droughts. Recent studies have suggested that in future climate projections, precipitation variability rises more steeply than does its mean, leading to concerns about societal impacts. Here we evaluate changes in mean precipitation over a broad range of spatial and temporal scales using a range of models from high-resolution regional simulations to millennial-scale global simulations. Results show that changes depend on the scale of aggregation and involve strong regional differences. On local scales that resolve individual rainfall events (hours and tens of kilometers), changes in precipitation distributions are complex and variances rise substantially more than means, as is required given the well-known disproportionate rise in precipitation intensity. On scales that aggregate across many events, distributional changes become simpler and variability changes smaller. At regional scale, future precipitation distributions can be largely reproduced by a simple transformation of present-day precipitation involving a multiplicative shift and a small additive term. The “extra” broadening is negatively correlated with changes in mean precipitation: in strongly “wetting” areas, distributions broaden less than expected from a simple multiplicative mean change; in “drying” areas, distributions narrow less. Precipitation variability changes are therefore of especial concern in the subtropics, which tend to dry under climate change. Outside the tropics, variability changes are similar on time scales from days to decades (i.e., show little frequency dependence). This behavior is highly robust across models, suggesting it may stem from some fundamental constraint.

54 ENVIRONMENTAL SCIENCES↗

Stable Machine‐Learning Parameterization of Subgrid Processes in a Comprehensive Atmospheric Model Learned From Embedded Convection‐Permitting Simulations

Modern climate projections often suffer from inadequate spatial and temporal resolution due to computational limitations, resulting in inaccurate representations of sub-grid processes. A promising technique to address this is the multiscale modeling framework (MMF), which embeds a kilometer-resolution cloud-resolving model (CRM) within each atmospheric column of a host climate model to replace traditional convection and cloud parameterizations. Machine learning offers a unique opportunity to make MMF more accessible by emulating the embedded CRM and reducing its substantial computational cost. Although many studies have demonstrated proof-of-concept success of achieving stable hybrid simulations, it remains a challenge to achieve near operational-level success with real geography and comprehensive variable emulation that includes, for example, explicit cloud condensate coupling. In this study, we present a stable hybrid model capable of integrating for at least 5 years with near operational-level complexity, including coarse-grid geography, seasonality, explicit cloud condensate and wind predictions, and land coupling. Our model demonstrates skillful online performance, achieving a 5-year zonal mean tropospheric temperature bias within 2 K, water vapor bias within 1 g/kg, and a precipitation root mean square error of 0.96 mm/day. Key factors contributing to our online performance include an expressive U-Net architecture and physical thermodynamic constraints for microphysics. With microphysical constraints mitigating unrealistic cloud formation, our work is the first to demonstrate realistic multi-year cloud condensate climatology under the MMF framework. Despite these advances, online diagnostics reveal persistent biases in certain regions, highlighting the need for innovative strategies to further optimize online performance.

Hu, Zeyuan [NVIDIA Corporation, Santa Clara, CA (U↗

Machine learning enables national assessment of wind plant controls with implications for land use

Summary As deployment of wind energy continues to expand, computationally efficient tools for predicting wind plant performance over a wide range of layout designs, technology innovations, and spatial locations are increasingly important for policy and investment decisions. We demonstrate two approaches to training a surrogate model to predict annual energy production (AEP) of parameterized wind plant layouts: one using a Gaussian process (GP) and the other using a fully convolutional neural network (FCNN). We leverage the powerful FCNN architecture by encoding wind plant design parameters and output response surface as an image. The FCNN produces more accurate results than the GP with mean absolute errors equivalent to 1% and 1.9% of plant rated power, respectively, although the GP performs well under limited training data and provides useful uncertainty information. We also evaluate a surrogate model for wake steering, enabling a nationwide assessment of the impact of plant control strategies and plant layout decisions. Across two million locations, we find that wake steering strategies boost AEP with relative gains upwards of 3%. Gains are most pronounced at sites without a dominant wind direction and where layout optimization is less fruitful. Additionally, we perform a nationwide sensitivity analysis showing that wake steering can mitigate wake losses from higher density plant layouts. Our results suggest that regions which have not been previously viable for wind deployment due to moderate wind resources are especially well enhanced by wake steering strategies that could help overcome land constraints and inflexible layout options, potentially identifying new deployment opportunities.

17 WIND ENERGY↗

Evidence of galaxy assembly bias in SDSS DR7 galaxy samples from count statistics

We present observational constraints on the galaxy–halo connection, focusing particularly on galaxy assembly bias from a novel combination of counts-in-cylinders statistics, P(N CIC ), with the standard measurements of the projected two-point correlation function w p (r p ), and number density n gal of galaxies. We measure n gal , w p (r p ), and P(N CIC ) for volume-limited, luminosity-threshold samples of galaxies selected from SDSS DR7, and use them to constrain halo occupation distribution (HOD) models, including a model in which galaxy occupation depends upon a secondary halo property, namely halo concentration. We detect significant positive central assembly bias for the M r < -20.0 and M r <-19.5 samples. Central galaxies preferentially reside within haloes of high concentration at fixed mass. Positive central assembly bias is also favoured in the M r < -20.5 and M r < -19.0 samples. We find no evidence of central assembly bias in the M r < -21.0 sample. We observe only a marginal preference for negative satellite assembly bias in the M r < -20.0 and M r < -19.0 samples, and non-zero satellite assembly bias is not indicated in other samples. Our findings underscore the necessity of accounting for galaxy assembly bias when interpreting galaxy survey data, and demonstrate the potential of count statistics in extracting information from the spatial distribution of galaxies, which could be applied to both galaxy–halo connection studies and cosmological analyses.

79 ASTRONOMY AND ASTROPHYSICS↗