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At least 397 records · Page 22

The response of stomatal conductance to seasonal drought in tropical forests

Stomata regulate CO2 uptake for photosynthesis and water loss through transpiration. The approaches used to represent stomatal conductance (gs) in models vary. In particular, current understanding of drivers of the variation in a key parameter in those models, the slope parameter (i.e. a measure of intrinsic plant water-use-efficiency), is still limited, particularly in the tropics. Here we collected diurnal measurements of leaf gas exchange and water potential (?leaf), and a suite of plant traits from the upper canopy of 15 tropical trees in two contrasting Panamanian forests throughout the dry season of the 2016 El Niño. The plant traits included wood density, leaf-mass-per-area (LMA), leaf carboxylation capacity (Vc,max25), leaf water content, the degree of isohydry, and predawn ?leaf. We first investigated how the choice of four commonly used leaf-level gs models with and without the inclusion of ?leaf as an additional predictor variable influence the ability to predict gs, and then explored the abiotic (i.e. month, site-month interaction) and biotic (i.e. tree-species-specific characteristics) drivers of slope parameter variation. Our results show that the inclusion of ?leaf did not improve model performance and that the models that represent the response of gs to vapor pressure deficit performed better than corresponding models that respond to relative humidity. Within each gs model, we found large variation in the slope parameter, and this variation was attributable to the biotic driver, rather than abiotic drivers. We further investigated potential relationships between the slope parameter and the six available plant traits mentioned above, and found that only one trait, LMA, had a significant correlation with the slope parameter (R2=0.66, n=15), highlighting a potential path towards improved model parameterization. This study advances understanding of gs dynamics over seasonal drought, and identifies a practical, trait-based approach to improve modeling of carbon and water exchange in tropical forests.

carbon and water exchange, stomatal conductance mo↗

The Scientific Case for Concurrent Neutron and X-ray Scattering and Spectroscopy

The interrogation of materials with X-rays or neutrons to determine the structure, energetics, and dynamics of materials is fundamental to advancing materials' physical and chemical science and developing innovative material technologies. A transcending challenge in developing novel materials is that progress hinges on understanding the structure and dynamics across multiple time and length scales in complex materials that feature multiple components, interfaces, and compositions. Despite the ever-growing demands on materials’ characterization, existing approaches are almost exclusively based on isolated X-ray or neutron scattering, i.e., an approach commensurate with the more narrowly defined needs of fifty years ago. A three-day workshop sponsored by the U.S. National Science Foundation (NSF) analyzed the demand for concurrent neutron and X-ray (NeX) experiments. It was held at the Spring Hill Suites, San Jose, California, from June 2 to 4, 2022. In this workshop, 70 national and international experts ascertained the crucial need to establish NeX capabilities to advance the science of complex materials and systems in the US. Here, we illustrate the need for NeX scattering and spectroscopy experiments by showcasing examples that span areas as diverse as biomaterials, energy science, soft matter, and nanomaterials. To provide NeX capability will require new instrumentation that enables concurrent experiments. Affected areas include chemistry, soft matter, quantum materials, pure and applied chemistry, bioscience, geoscience, and applied materials. NeX benefits research outcomes due to the complementarity of the two techniques, which is essential for better model refinement. While joint refinement of data from separate neutron and X-ray experiments is critical to avoid ambiguities, especially in multiphase-multicomponent materials, concurrent experiments overcome scientific and technical barriers associated with single measurements, separated by location and, thus, time. Among all the examples, these factors introduce uncertainties in the results that complicate data analysis. [1,2] [3] While models are strongly sample-dependent, the principles of joint refinement are generally applicable to these disciplines, including the development of advanced parameterization, modeling, and analysis techniques that also consider the temporal and spatial resolutions of the two methods, leading to unambiguous data interpretation. Solutions for technical barriers must be found to realize NeX experiments, including developing robust sample environments that meet the optical requirements of neutrons and X-rays.

36 MATERIALS SCIENCE↗

Cations impact radical reaction dynamics in concentrated multicomponent aqueous solutions

Ultraviolet (UV) photolysis of nitrite ions (NO 2 – ) in aqueous solutions produces a suite of radicals, viz., NO · , O – , · OH, and · NO 2 . The O – and NO · radicals are initially formed from the dissociation of photoexcited NO 2 – . The O – radical undergoes reversible proton transfer with water to generate · OH. Both · OH and O – oxidize the NO 2 – to · NO 2 radicals. The reactions of · OH occur at solution diffusion limits, which are influenced by the nature of the dissolved cations and anions. Here, we systematically varied the alkali metal cation, spanning the range from strongly to weakly hydrating ions, and measured the production of NO · , · OH, and · NO 2 radicals during UV photolysis of alkaline nitrite solutions using electron paramagnetic resonance spectroscopy with nitromethane spin trapping. Comparing the data for the different alkali cations revealed that the nature of the cation had a significant effect on production of all three radical species. Radical production was inhibited in solutions with high charge density cations, e.g., lithium, and promoted in solutions containing low charge density cations, e.g., cesium. Through complementary investigations with multinuclear single pulse direct excitation nuclear magnetic resonance (NMR) spectroscopy and pulsed field gradient NMR diffusometry, cation-controlled solution structures and extent of NO 2 – solvation were determined to alter the initial yields of · NO and · OH radicals as well as alter the reactivity of NO 2 – toward · OH, impacting the production of · NO 2 . The implications of these results for the retrieval and processing of low-water, highly alkaline solutions that comprise legacy radioactive waste are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A portable and monoenergetic 24 keV neutron source based on 124Sb-9Be photoneutrons and an iron filter

A portable monoenergetic 24 keV neutron source based on the 124Sb-9Be photoneutron reaction and an iron filter has been constructed and characterized. The coincidence of the neutron energy from SbBe and the low interaction cross-section with iron (mean free path up to 29 cm) makes pure iron specially suited to shield against gamma rays from 124Sb decays while letting through the neutrons. To increase the 124Sb activity and thus the neutron flux, a >1 GBq 124Sb source was produced by irradiating a natural Sb metal pellet with a high flux of thermal neutrons in a nuclear reactor. The design of the source shielding structure makes for easy transportation and deployment. A hydrogen gas proportional counter is used to characterize the neutrons emitted by the source and a NaI detector is used for gamma background characterization. At the exit opening of the neutron beam, the characterization determined the neutron flux in the energy range 20–25 keV to be 6.00±0.30 neutrons per cm2 per second and the total gamma flux to be 245±8 gammas per cm2 per second (numbers scaled to 1 GBq activity of the 124Sb source). A liquid scintillator detector is demonstrated to be sensitive to neutrons with incident kinetic energies from 8 to 17 keV, so it can be paired with the source as a backing detector for neutron scattering calibration experiments. This photoneutron source provides a good tool for in-situ low energy nuclear recoil calibration for dark matter experiments and coherent elastic neutrino-nucleus scattering experiments.

Dark Matter detectors (WIMPs, axions, etc.)↗

2025 EIC-France Workshop: Physics Highlights and Perspectives

This document presents a synthesis of the theory contributions and discussions from the 2nd EIC-France Workshop, held at IJCLab (Orsay) on 1-3 December 2025. The workshop brought together members of the French hadron-physics community to review recent theoretical developments relevant to the future Electron-Ion Collider (EIC) and to coordinate national efforts in preparation for its early physics program. The report first summarizes the collider's initial running conditions and luminosity performance, as outlined in the EIC Early Science Matrix. It then provides concise overviews of the theoretical presentations on inclusive, semi-inclusive, exclusive, heavy-flavor, and small-x physics. Based on these discussions, two measurements emerged as especially well suited for early EIC operation and strongly aligned with areas of established French expertise: inclusive diffraction and inclusive quarkonium production. These channels offer clean signatures, robust theoretical interpretability, and direct sensitivity to fundamental QCD phenomena such as gluon saturation, heavy-quark dynamics, and the small-x structure of hadrons and nuclei. In addition, the workshop identified longer-term physics opportunities that will benefit from the full capabilities of the EIC after its ramp-up phase. These include accessing the three-dimensional structure of the pion through the Sullivan process and a broader program of exclusive three-body final states, both of which represent high-impact avenues for exploring hadronic structure and non-perturbative QCD. Together, the elements summarized in this report provide a coherent overview of the strategic priorities and scientific ambitions shaping the French community's contribution to the EIC physics program.

FOS: Physical sciences↗

New approach to precisely measure γ-ray intensities for long-lived fission products, with results for the decay of 95 Zr

For many fission products, the rays emitted following decay provide an easily-detectable signature that can be used to identify their quantities and distributions in a sample. As a result, γ-ray spectroscopy is often exploited to study fission-product yields, provided sufficiently accurate information on the γ-ray intensity is available. However, in many cases, the uncertainties in the existing nuclear data are large enough that they compromise the precision achievable for modern experiments and applications. To address this need, we have developed a new experimental method that is well suited to precisely measure absolute γ-ray intensities in the β decay of long-lived fission products. The approach involves the production of a radiopure sample by implantation of a mass-separated ion beam from the CAlifornium Rare Isotope Breeder Upgrade (CARIBU) facility on a thin carbon foil. The emitted β-decay radiation is detected with a 4π gas proportional counter and a meticulously efficiency-calibrated high-purity germanium (HPGe) detector. As a first measurement to demonstrate the approach, we studied the absolute γ-ray intensities of the strongest transitions following the β decay of 95 Zr and its decay-daughter 95 Nb, and determined them to fractional precisions of better than 1–2%. In addition, with a larger sample of activity produced through neutron irradiation of an isotopically-enriched Zr foil, we performed a high-precision measurement of the relative γ-ray intensities following the decay of 95 Zr with just the HPGe detector. Here, the sample-production method at CARIBU and the coincidence detection approach demonstrated here can be applied to study fission products with half-lives longer than a day, which includes isotopes important not only for nuclear-energy and national-security applications, but also for medical-isotope research and environmental monitoring.

4π↗

Evaluating the Structural Response of Amphiphilic Monolayers to Environmental Stimuli

Amphiphilic monolayers composed of end groups with distinct polar and nonpolar functional groups offer rapid and reversible interfacial adaptation in response to environmental stimuli such as a change in interfacial medium polarity. We have synthesized and characterized a suite of monolayers with functional groups of competing polarity designed to reconfigure their interfacial chemical composition in response to solvent polarity. In these films, the end group is designed to be able to reorient and expose the functional groups that minimize the interfacial free energy between the film and the environment. Using a combination of spectroscopic, computational, and wettability studies, we have investigated the responsive interfacial behavior of different end groups upon exposure to environments with varying polarities. Contact angle measurements across a series of polar and dispersive probe liquids reveal trends that reflect the underlying molecular flexibility and composition. Vibrational sum frequency generation (SFG) spectroscopy and atomistic molecular dynamics (MD) simulations confirm solvent-driven reorientation of the end groups, with restructuring observed at the interface. To quantify these effects, we have developed a surface energy calculation model that incorporates solvent-induced surface rearrangements into the estimations. Our findings reveal a strong dependence of surface energy and switching behavior on the length and flexibility of the functionalities in the end group, which affects the exposure of certain interfacial compositions under different solvents. These results offer new insights into the design of adaptive monolayers and provide a framework for evaluating solvent-responsive surfaces.

functional groups↗

Dark Energy Survey Year 3 results: Simulation-based 𝑤CDM inference from weak lensing and galaxy clustering maps with deep learning: Analysis design

Data-driven approaches using deep learning are emerging as powerful techniques to extract non-Gaussian information from cosmological large-scale structure. Here, this work presents the first simulation-based inference (SBI) pipeline that combines weak lensing and galaxy clustering maps in a realistic Dark Energy Survey Year 3 (DES Y3) configuration and serves as preparation for a forthcoming analysis of the survey data. We develop a scalable forward model based on the CosmoGridV1 suite of N-body simulations to generate over one million self-consistent mock realizations of DES Y3 at the map level. Leveraging this large dataset, we train deep graph convolutional neural networks on the full survey footprint in spherical geometry to learn low-dimensional features that approximately maximize mutual information with target parameters. These learned compressions enable neural density estimation of the implicit likelihood via normalizing flows in a ten-dimensional parameter space spanning cosmological 𝑤CDM, intrinsic alignment, and linear galaxy bias parameters, while marginalizing over baryonic, photometric redshift, and shear bias nuisances. To ensure robustness, we extensively validate our inference pipeline using synthetic observations derived from both systematic contaminations in our forward model and independent Buzzard galaxy catalogs. Our forecasts yield significant improvements in cosmological parameter constraints, achieving 2−3× higher figures of merit in the 𝛺 𝑚 − 𝑆 8 plane relative to our implementation of baseline two-point statistics and effectively breaking parameter degeneracies through probe combination. These results demonstrate the potential of SBI analyses powered by deep learning for upcoming Stage-IV wide-field imaging surveys.

Thomsen, A. [Zurich, ETH] (ORCID:0000000203099021)↗

Galaxy clustering in harmonic space from the dark energy survey year 1 data: compatibility with real-space results

ABSTRACT We perform an analysis in harmonic space of the Dark Energy Survey Year 1 Data (DES-Y1) galaxy clustering photometric data using products obtained for the real-space analysis. We test our pipeline with a suite of lognormal simulations, which are used to validate scale cuts in harmonic space as well as to provide a covariance matrix that takes into account the DES-Y1 mask. We then apply this pipeline to DES-Y1 data taking into account survey property maps derived for the real-space analysis. We compare with real-space DES-Y1 results obtained from a similar pipeline. We show that the harmonic space analysis we develop yields results that are compatible with the real-space analysis for the bias parameters. This verification paves the way to performing a harmonic space analysis for the upcoming DES-Y3 data.

79 ASTRONOMY AND ASTROPHYSICS↗

Carbon management technology pathways for reaching a U.S. Economy-Wide net-Zero emissions goal

The Carbon Management Study Group of the 37 th Energy Modeling Forum (EMF 37) designed seven scenarios to explore the role of three potentially key technology suites – point source carbon dioxide capture and storage (PSCCS), direct air capture of carbon dioxide (DACCS), and hydrogen systems (H 2 ) – in shaping the broader technology pathways to reaching net-zero carbon dioxide (CO 2 ) emissions in United States by 2050. Each scenario was run by up to 13 models participating in the EMF 37 study. Results show that carbon dioxide removal technologies were consistently a major part of successful pathways to net-zero U.S. CO 2 emissions in 2050. Achieving this net-zero CO 2 goal without any form of carbon dioxide capture and storage was found to be impossible for most models; some models also found it impossible to reach net-zero without DACCS. The marginal cost of achieving net-zero CO 2 emissions in 2050 was between two and 10 times higher without PSCCS and/or DACCS available. The carbon price at which DACCS was deployed as a backstop technology depended upon the assumed cost at which DACCS was available at scale. Carbon prices were between $\$$250 and $\$$500 per ton CO 2 when DACCS deployed as a backstop. The average CO 2 capture rate across all models in 2050 in the central net-zero scenario was 1.3 GtCO 2 /year, which implies a substantial upscaling of capacity to move and store CO 2 . Finally, hydrogen sensitivity scenarios showed that H 2 typically constituted a relatively small share of the overall U.S. energy system; however, H 2 deployed in applications that are considered hard to decarbonize, facilitating transition towards net-zero emissions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

A comparison of effective field theory models of redshift space galaxy power spectra for DESI 2024 and future surveys

In preparation for the next generation of galaxy redshift surveys, and in particular the year-one data release from the Dark Energy Spectroscopic Instrument (DESI), we investigate the consistency of a variety of effective field theory models that describe the galaxy-galaxy power spectra in redshift space into the quasi-linear regime using 1-loop perturbation theory. These models are employed in the pipelines velocileptors, PyBird, and Folpsν. While these models have been validated independently, a detailed comparison with consistent choices has not been attempted. After briefly discussing the theoretical differences between the models we describe how to provide a more apples-to-apples comparison between them. We present the results of fitting mock spectra from the AbacusSummit suite of N-body simulations provided in three redshift bins to mimic the types of dark time tracers targeted by the DESI survey. We show that the theories behave similarly and give consistent constraints in both the forward-modeling and ShapeFit compressed fitting approaches. We additionally generate (noiseless) synthetic data from each pipeline to be fit by the others, varying the scale cuts in order to show that the models agree within the range of scales for which we expect 1-loop perturbation theory to be applicable. Finally, this work lays the foundation of Full-Shape analysis with DESI Y1 galaxy samples where in the tests we performed, we found no systematic error associated with the modeling of the galaxy redshift space power spectrum for this volume.

79 ASTRONOMY AND ASTROPHYSICS↗

Hygrothermal Aging and Thermomechanical Characterization of As-Manufactured Tidal Turbine Blade Composites

This study investigates the hygrothermal aging behavior and thermomechanical properties of as-manufactured glass fiber-reinforced epoxy and thermoplastic composite tidal turbine blades. The blades were previously deployed in a marine environment and subsequently analyzed through a comprehensive suite of material characterization techniques, including hygrothermal aging, dynamic mechanical analysis (DMA), tensile testing and X-ray computed tomography (XCT). Hygrothermal aging experiments revealed that while thermoplastic composites exhibited lower overall water absorption (0.78% vs. 0.47%), they had significantly higher diffusion coefficients than epoxy (2.1 vs. 12.1 × 10 −13 m 2 s −1 ), suggesting faster saturation in operational environments. DMA results demonstrated that water ingress caused plasticization in epoxy matrices, reducing the glass transition temperature and increasing damping (112 °C to 104 °C), while thermoplastic composites showed more stable thermal behavior (87 °C glass transition temperature). Tensile testing revealed substantial reductions in ultimate strength (>40%) for both materials after prolonged water exposure, with minimal change in elastic modulus, highlighting the role of matrix degradation over fiber reinforcement. XCT image analysis showed that both composites were manufactured with high quality: no large voids or cracks were present, and the degree of misalignment was low. These findings inform future marine renewable energy composite designs by emphasizing the critical influence of moisture on long-term structural integrity and the need for optimized material systems in harsh marine environments. This work provides a rare real-world comparison of epoxy and recyclable thermoplastic tidal turbine blades, showing how laboratory aging tests and advanced imaging reveal the influence of material and manufacturing choices on long-term marine durability.

16 TIDAL AND WAVE POWER↗

Synthetic light-cone catalogues of modern redshift and weak lensing surveys with abacussummit

ABSTRACT The joint analysis of different cosmological probes, such as galaxy clustering and weak lensing, can potentially yield invaluable insights into the nature of the primordial Universe, dark energy, and dark matter. However, the development of high-fidelity theoretical models is a necessary stepping stone. Here, we present public high-resolution weak lensing maps on the light-cone, generated using the N-body simulation suite abacussummit, and accompanying weak lensing mock catalogues, tuned to the Early Data Release small-scale clustering measurements of the Dark Energy Spectroscopic Instrument. Available in this release are maps of the cosmic shear, deflection angle, and convergence fields at source redshifts ranging from z = 0.15 to 2.45 as well as cosmic microwave background convergence maps for each of the 25 base-resolution simulations ($L_{\rm box} = 2000\, h^{-1}\, {\rm Mpc}$ and Npart = 69123) as well as for the two huge simulations ($L_{\rm box} = 7500\, h^{-1}\, {\rm Mpc}$ and Npart = 86403) at the fiducial abacussummit cosmology. The pixel resolution of each map is 0.21 arcmin, corresponding to a healpix Nside of 16 384. The sky coverage of the base simulations is an octant until z ≈ 0.8 (decreasing to about 1800 deg2 at z ≈ 2.4), whereas the huge simulations offer full-sky coverage until z ≈ 2.2. Mock lensing source catalogues are sampled matching the ensemble properties of the Kilo-Degree Survey, Dark Energy Survey, and Hyper Suprime-Cam data sets. The mock catalogues are validated against theoretical predictions for various clustering and lensing statistics, such as correlation multipoles, galaxy–shear, and shear–shear, showing excellent agreement. All products can be downloaded via a Globus endpoint (see Data Availability section).

79 ASTRONOMY AND ASTROPHYSICS↗

Flexible, integrated modeling of tokamak stability, transport, equilibrium, and pedestal physics

The STEP (Stability, Transport, Equilibrium, and Pedestal) integrated-modeling tool has been developed in OMFIT to predict stable, tokamak equilibria self-consistently with core-transport and pedestal calculations. STEP couples theory-based codes to integrate a variety of physics, including magnetohydrodynamic stability, transport, equilibrium, pedestal formation, and current-drive, heating, and fueling. The input/output of each code is interfaced with a centralized ITER-Integrated Modelling & Analysis Suite data structure, allowing codes to be run in any order and enabling open-loop, feedback, and optimization workflows. This paradigm simplifies the integration of new codes, making STEP highly extensible. STEP has been verified against a published benchmark of six different integrated models. Core-pedestal calculations with STEP have been successfully validated against individual DIII-D H-mode discharges and across more than 500 discharges of the H98,y2 database, with a mean error in confinement time from experiment less than 19%. STEP has also reproduced results in less conventional DIII-D scenarios, including negative-central-shear and negative-triangularity plasmas. Predictive STEP modeling has been used to assess performance in several tokamak reactors. Simulations of a high-field, large-aspect-ratio reactor show significantly lower fusion power than predicted by a zero-dimensional study, demonstrating the limitations of scaling-law extrapolations. STEP predictions have found promising scenarios for an EXhaust and Confinement Integration Tokamak Experiment, including a high-pressure, 80%-bootstrap-fraction plasma. ITER modeling with STEP has shown that pellet fueling enhances fusion gain in both the baseline and advanced-inductive scenarios. Finally, STEP predictions for the SPARC baseline scenario are in good agreement with published results from the physics basis.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

ForestFlow: predicting the Lyman-α forest clustering from linear to nonlinear scales

On large scales, the Lyman-α forest provides insights into the expansion history of the Universe, while on small scales, it imposes strict constraints on the growth history, the nature of dark matter, and the sum of neutrino masses. This work introduces ForestFlow, a novel framework that bridges the gap between large- and small-scale analyses, which have traditionally relied on distinct modeling approaches. Using conditional normalizing flows, ForestFlow predicts the two Lyman-α linear biases (b δ and b η ) and six parameters describing small-scale deviations of the three-dimensional flux power spectrum (P 3D ) from linear theory as a function of cosmology and intergalactic medium physics. These are then combined with a Boltzmann solver to make consistent predictions, from arbitrarily large scales down to the nonlinear regime, for P 3D and any other statistics derived from it. Trained on a suite of 30 fixed-and-paired cosmological hydrodynamical simulations spanning redshifts from z = 2 to 4.5, ForestFlow achieves 3 and 1.5% precision in describing P 3D and the one-dimensional flux power spectrum (P 1D ) from linear scales to k = 5 Mpc −1 and k ∥ = 4 Mpc −1 , respectively. Thanks to its conditional parameterization, ForestFlow shows similar performance for ionization histories and two ΛCDM model extensions – massive neutrinos and curvature – even though none of these are included in the training set. This framework will enable full-scale cosmological analyses of Lyman-α forest measurements from the DESI survey.

79 ASTRONOMY AND ASTROPHYSICS↗

In situ x-ray studies of the incipient ZnO atomic layer deposition on In 0.53 Ga 0.47 As

We describe in detail how ZnO films grow on In 0.53 Ga 0.47 As substrates by atomic layer deposition (ALD), employing a suite of in situ synchrotron x-ray techniques. Combining results from different measurements allows the distinguishment of three different growth behaviors: an initial, slow linear growth, often referred to as a growth delay (regime I), followed by a nonlinear growth (regime II), and finally, a steady, linear growth (regime III), the last of which is the self-limited growth behavior characteristic of ALD. By the end of regime I, the In 0.53 Ga 0.47 As surface is covered with an ultrathin, poorly ordered Zn oxide layer. The transition from regime I to II is clearly evidenced by the appearance in the x-ray absorption spectra of characteristic features of the wurtzite structure, as well as the nucleation and growth of ZnO grains (three-dimensional) on top of the poorly ordered Zn oxide layer. Regime II ends when the growth per cycle reaches a constant level. We show that the water pressure during growth has an impact on the duration of the growth delay (regime I), unlike the substrate temperature. In the regime of steady growth, we observe that the rate of deposition obtained for all temperatures inside the ALD window is 0.17 nm cy(-1). The deposition temperature has clear effects on the film texture and initial crystallization behavior, as well as the final crystallinity and thicknesses of the layers adjacent to the In 0.53 Ga 0.47 As substrate. Based on the experimental results and earlier ab initio calculations and Monte Carlo simulations of ZnO ALD on ZnO, we suggest reaction mechanisms consistent with our findings, and we present a model of growth starting from the very earliest stages of deposition to the steady growth regime.

36 MATERIALS SCIENCE↗

PAC in DESI. II. Galaxy-halo connection into the $10^{6}{\rm M}_{\odot}$ frontier

Understanding dwarf galaxy formation is crucial for testing dark matter models and reionization physics. However, constructing stellar-mass complete spectroscopic samples at low masses is increasingly difficult, and the potential existence of a local void complicates studies in an average environment. The Photometric object Around Cosmic webs (PAC) method, which combines deep photometric and spectroscopic data to measure the excess surface density $\bar{n}_2w_{\rm{p}}(r_{\rm{p}})$ of photometric objects around spectroscopic tracers, offers a promising path forward. We model 349 $\bar{n}_2w_{\rm{p}}(r_{\rm{p}})$ measurements from DESI Y1 BGS and DECaLS, reaching $M_*=10^{6.4}\,{\rm M}_{\odot}$, using a stellar mass-halo mass relation (SHMR)-based subhalo abundance matching framework applied to two high-resolution $N$-body simulations from the Jiutian suite. The resulting SHMR is constrained down to $M_{\rm h}\simeq10^{8.0}\,h^{-1}{\rm M}_{\odot}$, revealing a clear upturn at $\sim10^{10.0}\,h^{-1}{\rm M}_{\odot}$ toward lower masses, indicating rising star-formation efficiency (SFE) in small haloes. This feature persists under extensions of the model that allow mass-dependent scatter, reionization-induced suppression of the halo occupation fraction, galaxy assembly bias, and alternative cosmologies. Combining with the results from Paper I, we find that central red galaxies dominate the low-mass regime. Our results motivate a hypothesis in which SFE is significantly higher than previously thought prior to reionization, enabling relatively massive galaxies to form in small haloes. These systems are subsequently quenched by the UV background, producing the central red dwarf galaxies observed. Finally, we obtain $3σ$ and $5σ$ upper mass bounds of $10^{8.80}\,h^{-1}{\rm M}_{\odot}$ and $10^{10.24}\,h^{-1}{\rm M}_{\odot}$ on the smallest haloes required to exist.

Xu, Kun [Pennsylvania U.; Durham U., ICC; Tsung-Da↗

Combining Observations and Models: A Review of the CARDAMOM Framework for Data‐Constrained Terrestrial Ecosystem Modeling

The rapid increase in the volume and variety of terrestrial biosphere observations (i.e., remote sensing data and in situ measurements) offers a unique opportunity to derive ecological insights, refine process‐based models, and improve forecasting for decision support. However, despite their potential, ecological observations have primarily been used to benchmark process‐based models, as many past and current models lack the capability to directly integrate observations and their associated uncertainties for parameterization. In contrast, data assimilation frameworks such as the CARbon DAta MOdel fraMework (CARDAMOM) and its suite of process‐based models, known as the Data Assimilation Linked Ecosystem Carbon Model (DALEC), are specifically designed for model‐data fusion. This review, motivated by a recent CARDAMOM community workshop, examines the development and applications of CARDAMOM, with an emphasis on its role in advancing ecosystem process understanding. CARDAMOM employs a Bayesian approach, using a Markov Chain Monte Carlo algorithm to enable data‐driven calibration of DALEC parameters and initial states (i.e., carbon pool sizes) through observation operators. CARDAMOM's unique ability to retrieve localized model process parameters from diverse datasets—ranging from in situ measurements to global satellite observations—makes it a highly flexible tool for analyzing spatially variable ecosystem responses to environmental change. However, assimilating these data also presents challenges, including data quality issues that propagate into model skill, as well as trade‐offs between model complexity, parameter equifinality, and predictive performance. We discuss potential solutions to these challenges, such as reducing parameter equifinality by incorporating new observations. This review also offers community recommendations for incorporating emerging datasets, integrating machine learning techniques, strengthening collaboration with remote sensing, field, and modeling communities, and expanding CARDAMOM's relevance for localized ecosystem monitoring and decision‐making. CARDAMOM enables a deep, mechanistic understanding of terrestrial ecosystem dynamics that cannot be achieved through empirical analyses of observational datasets or weakly constrained models alone.

Bayesian inference↗