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At least 19 records

Tendencies of Soil Microbial NO Emissions During HI‐SCALE as Predicted by a Nitrification/Denitrification Scheme

Many atmospheric chemical processes, including the formation of secondary organic aerosol (SOA), are strongly modulated by the reactions of NO and NO 2 (NO x ). Though NO x is controlled by anthropogenic emissions near urban areas, in rural areas soil microbes can be a significant contribution to NO emission globally. The relative rates of emissions of different nitrogen-containing species (e.g., NO, N 2 O, HONO, and N 2 ) are strong functions of soil properties such as temperature, moisture content, pH, and soil carbon and nitrogen pools. However, typical large-scale biogeochemical models either express these emissions simplistically, or not at all. Here we investigate the potential impact of soil NO emissions on atmospheric chemistry and SOA formation over regional and monthly time scales, specifically the 2016 spring and summer Intensive Observational Periods (IOPs) of the Holistic Interactions of Shallow Clouds, Aerosols and Land Ecosystems (HI-SCALE) field campaign. We implement the soil NO nitrification/denitrification parameterization of Rasool et al. (2019) into the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem), supplemented by a 1-km soil moisture analysis. We then simulate both IOPs over the U.S. Great Plains, evaluating against ground stations and flight data. We show that soil NO emissions can account for a large fraction of total NO x and locally increase O 3 concentrations by up to 25%, while alleviating negative biases of gases and aerosols toward observations. Soil moisture and temperature changes between IOP1 and IOP2 lead to overall differences in emissions, but with large regional variability due to heterogeneous surface characteristics.

Atmoshpheric Chemistry

The Interstellar Mapping And Acceleration Probe High Energy (IMAP-Hi) Neutral Atom Imager

The IMAP-Hi Energetic Neutral Atom (ENA) Imager on NASA’s Interstellar Mapping and Acceleration Probe (IMAP) mission (McComas et al. 2018a, 2025) is designed to measure ENAs from the global interaction between the heliosphere and the local interstellar medium (LISM). These ENAs are initially plasma ions of solar wind origin that are neutralized by charge exchange with the cold neutral atoms of LISM that freely flow through the heliosphere-LISM interaction region. IMAP-Hi consists of two identical single-pixel sensors, each covering the ENA spectral range from 0.44 keV to 15.6 keV over nine contiguous energy passbands and having an approximately conical field-of-view (FOV) of 4.1o full width at half maximum (FWHM). The Hi-45 sensor points 45o relative to the spacecraft spin axis from the antisunward direction; each spacecraft spin, it measures ENA intensity over a circular swath with half-cone angle 45o centered on the ecliptic plane. The Hi-90 sensor points 90o relative to the spin axis; each spacecraft spin, it measures ENA intensity over a great circle in the sky, sampling both the north and south ecliptic poles. As the IMAP spin vector is re-pointed daily toward the Sun, the ecliptic longitude of the swaths moves daily by ∼1o such that a full sky map is acquired by Hi-90 every six months and a complete low latitude (−45o to +45o) map is acquired by Hi-45 annually. The IMAP-Hi sensor design has direct heritage from the IBEX-Hi imager on the Interstellar Boundary Explorer (IBEX) mission, with substantial improvements in energy range, energy resolution, angular resolution, signal-to-noise ratio, and, for ecliptic latitudes within ±45o, temporal resolution and exposure time. The global ENA maps acquired by IMAP-Hi partially overlap in energy and viewing with the ENA maps acquired by the IMAP-Lo and IMAP-Ultra ENA imagers, which we combine to answer fundamental questions about the structure and dynamics of the interaction of the heliosphere and the LISM.

79 ASTRONOMY AND ASTROPHYSICS

A New Window into the Baryon Cycle at Cosmic Noon with Line Intensity Mapping: Forecasts for auto- and cross-correlations in [CII]-158$μ$m, HI 21 cm, CO$_{J+1\rightarrow J}$, and H$α$ galaxies

Across the peak of cosmic star formation at $z\sim1-2$, inflow, processing, and feedback drive rapid changes in the spatial distribution and chemical composition of baryons in galaxies and surrounding reservoirs; this baryon cycle can be tomographically mapped by line intensity mapping (LIM) of atomic hydrogen, ionized carbon, and carbon monoxide. We present a simulation-based forecasting framework for detecting auto- and cross-power spectra between spectroscopic surveys of four such tracers at $z\sim0.5-1.7$ mapping the same deep field - TIM, EoRSpec/FYST, MeerKAT, & Euclid. We forward-model 3-D distributions for these tracers from magnetohydrodynamic simulations, directly capturing the two-halo, one-halo, and shot statistics without relying on analytical decompositions. We further detail a signal-to-noise formalism, tailored to LIM surveys with highly anisotropic geometries and Fourier-space coverage. We demonstrate that galaxy cross-correlations will be the dominant discovery channel for current-generation surveys. These instruments will detect the auto-spectra for CO and HI 21 cm and the CO $\times$ 21 cm cross-spectrum at modest S/N $\sim 1-10$, while placing upper limits on the [CII]-158$μ$m signals. [CII], CO, and HI LIM will be $\sim3-30\times$ ($0.5-1.5$ dex) more sensitive to cross-correlation with the Euclid survey, however, than their respective auto-correlations, constraining all three models of line emission at high significance (S/N $\sim 10-40$) within this decade. Finally, we formulate a staged instrumental trajectory with planned or reasonable improvements, including the as-proposed SKA-Mid. We forecast advancing the per-$k$-mode sensitivities of each auto-, galaxy-line, and line-line spectrum by several orders of magnitude, enabling new percent- and sub-percent level constraints on cosmology and the redshift evolution of star formation and the baryon cycle.

Agrawal, Shubh [Pennsylvania U., Dept. Math.]

Improving cosmological analyses of HI clustering by reducing stochastic noise

High-number-density tracers of large-scale structure, such as the HI-rich galaxies measured by 21 cm intensity mapping, have low sampling noise, making them particularly promising as cosmological probes. At large scales, this sampling noise can be subdominant to other scale-independent contributions to the power spectrum; such contributions arise from nonlinear bias, and exceed the sampling noise if at least one of the associated bias coefficients is sufficiently large. This has important consequences for cosmological constraints obtained from such tracers, since it indicates that using the power spectrum does not lead to optimal constraints even in the linear regime. In this paper, we provide a conservative estimate of the possible improvement in constraining power of a 21 cm survey if one were to use an optimal analysis strategy (such as field-level analysis), where only the true sampling noise enters the error budget. We find that improvements in uncertainties on some cosmological parameters can be as large as 50%, depending on redshift, foreground cleaning efficiency, scales used in the analysis, and instrumental noise. One byproduct of our work is measurements of bias parameters and stochasticity for neutral hydrogen in the IllustrisTNG simulation over a wide range of redshifts; we provide simple fitting formulas for these measurements. Furthermore, our results motivate further exploration of new optimal analysis techniques and provide important insights into the constraining power of current and future 21 cm surveys.

79 ASTRONOMY AND ASTROPHYSICS

Characterization of Fine-Pitch Interconnects for Long-Lifetime HI Applications

This conference talk discusses optimizing gold-gold and gold-ENIG fine-pitch interconnections for Heterogeneous Integration applications, with a focus on longevity. We first look at electrical data from gold-gold bumps subjected to highly accelerated lifetime testing. Then, we discuss using chemical and physical data as a predictor for ENIG bump flip-chip success.

Humphrey, Nicholas James [Sandia National Laborato

HI Lumi LHC Project

Explore the source record for details and available documents.

Franz, Molly [Fermilab]

H I Depletion Begins Well Beyond the Virial Radius: A FAST Stacking Study of 36 Galaxy Clusters to 5 × R 200

Abstract We present a stacking study of the neutral atomic hydrogen (H i ) content in and around 36 local galaxy clusters at z < 0.07, using a combination of the FAST All Sky H i survey (FASHI) and the extensive spectroscopic catalog mainly from the Dark Energy Spectroscopic Instrument (DESI). We employ spectral stacking techniques to probe the average H i mass and HI-to-stellar mass ratio ( M HI / M * ) for member galaxies down to stellar masses of M * ∼ 10 9 M ⊙ , spanning a projected cluster-centric distance of up to 5 R 200 . Our analysis reveals a pronounced environmental effect; both M HI and M HI / M * decrease steadily toward the cluster center, dropping by ∼0.5 dex on average from the outskirts to the core. Crucially, we find that M HI / M * of galaxies remain lower than the field galaxies even at the 5 R 200 . This provides direct, statistical evidence for substantial gas stripping and preprocessing in the cluster outskirts, likely occurring in infalling groups and large-scale filaments. By further splitting the sample by g − r color, we show that the H i deficiency persists at fixed galaxy color; even the bluest cluster members exhibit ∼0.5 dex lower M HI / M * than field galaxies of similar color, reflecting environmental effects on the cold gas reservoir prior to full optical transformation. The total H i mass within clusters and their outskirts agrees broadly with predictions from cosmological simulations. Our results underscore the critical role of the extended cluster environment in quenching galaxies by depleting their cold gas reservoirs well before they enter the dense cluster core.

Cheng, Cheng [Chinese Academy of Sciences South Am

From 2D to 4D: a containerized workflow and browser to explore dynamic chromatin architecture

Background Characterizing the physical organization of the genome is essential for understanding long-range gene regulation, chromatin compartmentalization, and epigenetic accessibility. Hi-C experiments generate two-dimensional (2D) genome-wide contact maps of chromatin interactions by capturing the spatial proximity between genomic loci, which reveal interaction frequencies but lack the spatial resolution needed to interpret the three-dimensional (3D) genome structure(s). Emerging evidence suggests that epigenetic regulation is closely linked to 3D genome architecture, and that structural changes over time (4D) drive key biological processes in development, disease, and environmental response. Thus, integrating 3D structure with functional data is critical for a more complete understanding of genome regulation. Previous work, most notably the 4DHiC chromosome modeling framework, has shown that physical multi-dimensional modeling approaches rooted in polymer physics and molecular dynamics can resolve these structures at biologically meaningful resolutions by integrating temporal Hi-C data with physical constraints to uncover dynamic chromosome reorganization. Thus, molecular dynamics simulations, constrained by Hi-C contact matrices, can resolve fine-scale structural changes and reveal functionally significant transitions in chromatin conformation. Results Herein, we present the 4D Genome Browser Workflow (4DGBWorkflow) and the 4D Genome Browser (4DGB). The algorithm is based on the 4DHiC method, and the containerized tool is an end-to-end workflow that can transform, filter, and view 4D epigenomics and chromatin datasets, allowing non-specialists to apply three-dimensional modeling principles to diverse datasets and experimental conditions. The software executes on a laptop running macOS, Linux or Windows. From input Hi-C files (.hic), the 4DGBWorkflow produces 3D reconstructions of chromosomes, integrates the reconstruction with track data (e.g., epigenetic marks, transcriptome profiles), and provides comparative visualization of the results in a single workflow. Conclusions The 4DGBWorkflow and 4D Genome Browser are open-source tools for comparative analysis and visualization of 4D chromosome datasets, including chromatin architecture and epigenomic signals. Automatic integration of Hi-C data with molecular dynamics democratizes the construction of time resolved 3D genome structures, simplifying complex simulations and data integration schemes.

3D Genome Browser

The Heterogeneous Integration of Electronic Components

Heterogeneous integration (HI) of electronics components is broadly recognized as a powerful and crucial enabler for the continued growth of computing and communication. From 2010 onwards, the value of HI is increasingly visible in the advanced packaging used in artificial intelligence, high-performance computing, smartphones and communications product implementations. In this Perspective, we argue that HI is crucial to semiconductors and more broadly to the continued evolution of computing and communications. We use leading-edge advanced packaging examples to represent the value, advancements and opportunities for HI. To succeed, it is critical to develop comprehensive HI roadmaps that inform collaborations across the design, manufacturing and reliability spectrum between systems architects, packaging and semiconductor technologists to common goals. Although this article does not provide a full roadmap, we instead detail additional parameters for artificial intelligence, smartphone and other cellular communication devices, and their constituent building blocks including interconnects, power electronics, photonics, thermal management, reliability, modelling and co-design, to foster greater collaboration opportunities among academia, research laboratories and industry.

42 ENGINEERING

Structural basis of differential gene expression at eQTLs loci from high-resolution ensemble models of 3D single-cell chromatin conformations

Abstract Motivation Techniques such as high-throughput chromosome conformation capture (Hi-C) have provided a wealth of information on nucleus organization and genome important for understanding gene expression regulation. Genome-Wide Association Studies have identified numerous loci associated with complex traits. Expression quantitative trait loci (eQTL) studies have further linked the genetic variants to alteration in expression levels of associated target genes across individuals. However, the functional roles of many eQTLs in noncoding regions remain unclear. Current joint analyses of Hi-C and eQTLs data lack advanced computational tools, limiting what can be learned from these data. Results We developed a computational method for simultaneous analysis of Hi-C and eQTL data, capable of identifying a small set of nonrandom interactions from all Hi-C interactions. Using these nonrandom interactions, we reconstructed large ensembles (×105) of high-resolution single-cell 3D chromatin conformations with thorough sampling, accurately replicating Hi-C measurements. Our results revealed many-body interactions in chromatin conformation at the single-cell level within eQTL loci, providing a detailed view of how 3D chromatin structures form the physical foundation for gene regulation, including how genetic variants of eQTLs affect the expression of associated eGenes. Furthermore, our method can deconvolve chromatin heterogeneity and investigate the spatial associations of eQTLs and eGenes at subpopulation level, revealing their regulatory impacts on gene expression. Together, ensemble modeling of thoroughly sampled single-cell chromatin conformations combined with eQTL data, helps decipher how 3D chromatin structures provide the physical basis for gene regulation, expression control, and aid in understanding the overall structure-function relationships of genome organization. Availability and implementation It is available at https://github.com/uic-liang-lab/3DChromFolding-eQTL-Loci.

Du, Lin (ORCID:0009000289869812)

Data-driven high-dimensional statistical inference with generative models

Crucial to many measurements at the LHC is the use of correlated multi-dimensional information to distinguish rare processes from large backgrounds, which is complicated by the poor modeling of many of the crucial backgrounds in Monte Carlo simulations. In this work, we introduce HI-SIGMA, a method to perform unbinned high-dimensional statistical inference with data-driven background distributions. In contradistinction to many applications of Simulation Based Inference in High Energy Physics, HI-SIGMA relies on generative ML models, rather than classifiers, to learn the signal and background distributions in the high-dimensional space. These ML models allow for interpretable inference while also incorporating model errors and other sources of systematic uncertainties. We showcase this methodology on a simplified version of a di-Higgs measurement in the bbγγ final state, where the di-photon resonance allows for background interpolation from sidebands into the signal region. We demonstrate that HI-SIGMA provides improved sensitivity as compared to standard classifier-based methods, and that systematic uncertainties can be straightforwardly incorporated by extending methods which have been used for histogram based analyses.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS

Quenching of single-particle strength inferred from nucleon-removal transfer reactions on 15 C

The difference in the proton and neutron separation energies (ΔS) of the weakly bound 15 C ground state is -19.86 MeV, an extreme value. Data from intermediate-energy heavy-ion induced (HI-induced) knockout reactions on nuclei spanning -20 ≲ ΔS ≲ +20 MeV, suggest that the degree to which single-particle strength is quenched, R s , has a negative correlation with ΔS, decreasing from unity around -20 MeV to around 0.2 at +20 MeV. For the 15 C ground state (R s = 0.96 (4) in HI-induced knockout), contrasting results have recently been obtained via the neutron-adding transfer reaction, which reveal a value of R s = 0.64 (15), similar to the value observed at modest and more extreme values of ΔS with reaction probes other than HI knockout. In order to explore the any potential differences between adding and removing processes in transfer reactions at extreme ΔS, single-neutron removal transfer reactions on 15 C were performed at 7.1 MeV/u in inverse kinematics. The removal of a valence neutron in 2s 1/2 orbit using both (p, d) and (d, t) reactions shows consistent quenching factors and agrees with those from the neutron-adding reaction. The present results, which can be compared with neutron knockout reaction, suggest that correlations, represented by the quenching factor, show limited dependence on neutron-proton asymmetry under the most extreme asymmetry conditions so far achieved in transfer reactions.

quenching factor

Investigating the Role π -Rich Solvents Play in the Growth of Cesium Lead Bromide Nanocrystals

In this report, the role that a high-boiling-point solvent type plays on the nucleation and growth, morphology, and crystal-phase transformation of cesium lead bromide nanocrystals (CsPbBr 3 ) is studied. The CsPbBr 3 products were compared between a one-pot growth mechanism at room temperature (RT) versus a hot-injection mechanism (HI) control using dibenzyl ether (DBE), diphenyl ether (DPE), dioctyl ether (DOE), or 1- octadecene (ODE). The coordination between these solvents and the PbBr 2 salt precursors resulted in different plumbate [PbSBr n ] 2−n precursors being formed. The S-to-Pb 2+ coordination within [PbSBr n ] 2−n was probed by UV−vis and solvent-phase 207 Pb NMR, both of which showed considerable coordination between [PbSBr n ] 2−n and the π-rich DBE and DPE, whose reactivity affected CsPbBr 3 growth. The effect was more pronounced for CsPbBr 3 prepared via RT, where the morphology was tunable, with π-rich solvents producing thin rod-like CsPbB r3 with a blue emission, compared to the green-emitting thicker platelets formed via HI. While XRD showed crystalline products for both RT and HI, with orthorhombic and cubic forms, respectively, the RT products had considerable surface defects, as was indicated by lower quantum yields, and to understand this the photoluminescent lifetimes were measured by time-correlated single photon counting.

207Pb NMR

Integrating chromosome conformation and DNA repair in a computational framework to assess cell radiosensitivity

Objective. The arrangement of chromosomes in the cell nucleus has implications for cell radiosensitivity. The development of new tools to utilize Hi-C chromosome conformation data in nanoscale radiation track structure simulations allows for in silico investigation of this phenomenon. We have developed a framework employing Hi-C-based cell nucleus models in Monte Carlo radiation simulations, in conjunction with mechanistic models of DNA repair, to predict not only the initial radiation-induced DNA damage, but also the repair outcomes resulting from this damage, allowing us to investigate the role chromosome conformation plays in the biological outcome of radiation exposure. Approach. In this study, we used this framework to generate cell nucleus models based on Hi-C data from fibroblast and lymphoblastoid cells and explore the effects of cell type-specific chromosome structure on radiation response. The models were used to simulate external beam irradiation including DNA damage and subsequent DNA repair. The kinetics of the simulated DNA repair were compared with previous results. Main results. We found that the fibroblast models resulted in a higher rate of inter-chromosome misrepair than the lymphoblastoid model, despite having similar amounts of initial DNA damage and total misrepairs for each irradiation scenario. Significance. This framework represents a step forward in radiobiological modeling and simulation allowing for more realistic investigation of radiosensitivity in different types of cells.

59 BASIC BIOLOGICAL SCIENCES

Measurements of the thermal and ionization state of the intergalactic medium during the cosmic afternoon

We perform the first measurement of the thermal and ionization state of the intergalactic medium (IGM) across 0.9 < z < 1.5 using 301 Ly α absorption lines fitted from 12 archival Hubble Space Telescope Space Telescope Imaging Spectrograph quasar spectra. We employ the machine-learning-based inference method that uses joint Doppler parameter–column density (⁠b-N HI ⁠) distributions obtained from Ly α forest decomposition. Our results show that the Γ HI photoionization rates, ⁠, agree with recent ultraviolet background synthesis models, with log(Γ HI /s -1 ) = $-11.79^{+0.18}_{-0.15}$, $-11.98^{+0.09}_{-0.09}$⁠, and $-12.32^{+0.10}_{-0.12}$⁠, at z = 1.4, 1.2, and 1, respectively. We obtain the IGM temperature at the mean density, T 0 ⁠, and the adiabatic index, γ⁠, as [log(T 0 /K), γ] = $[4.13^{+0.12}_{-0.10}, 1.34^{+0.10}_{-0.15}]$, $[3.79^{+0.11}_{-0.11}, 1.70^{+0.09}_{-0.09}]$, and $[4.12^{+0.15}_{-0.25}, 1.34^{+0.21}_{-0.26}]$ at z = 1.4⁠, 1.2, and 1. Our measurements of T 0 at z = 1.4 and 1.2 are consistent with the trend predicted from previous z < 3 temperature measurements and theoretical expectations, where the IGM cools down after $He\tiny{II}$ reionization in the absence of any non-standard heating. However, our T 0 measurement at z = 1 unexpectedly high IGM temperature. Given the relatively large uncertainty in these measurements, where σ T$_0$ ~ 5000 K, mostly emanating from the limited size of our data set, we cannot conclude whether the IGM cools down as expected. Lastly, we generate mock data sets to test the constraining power of future measurement with larger data sets. The results demonstrate that, with redshift path-length Δz ~ 2 for each redshift bin, three times the current data set, we can constrain the T 0 of IGM within 1500 K, which would be sufficient to constrain the IGM thermal history at z < 1.5 conclusively.

79 ASTRONOMY AND ASTROPHYSICS

Chromatin structures from integrated AI and polymer physics model

The physical organization of the genome in three-dimensional space regulates many biological processes, including gene expression and cell differentiation. Three-dimensional characterization of genome structure is critical to understanding these biological processes. Direct experimental measurements of genome structure are challenging; computational models of chromatin structure are therefore necessary. We develop an approach that combines a particle-based chromatin polymer model, molecular simulation, and machine learning to efficiently and accurately estimate chromatin structure fromindirectmeasures of genome structure. More specifically, we introduce a new approach where the interaction parameters of the polymer model are extracted from experimental Hi-C data using a graph neural network (GNN). We train the GNN on simulated data from the underlying polymer model, avoiding the need for large quantities of experimental data. The resulting approach accurately estimates chromatin structures across all chromosomes and across several experimental cell lines despite being trained almost exclusively on simulated data. The proposed approach can be viewed as a general framework for combining physical modeling with machine learning, and it could be extended to integrate additional biological data modalities. Ultimately, we achieve accurate and high-throughput estimations of chromatin structure from Hi-C data, which will be necessary as experimental methodologies, such as single-cell Hi-C, improve.

Biochemistry & Molecular Biology

SIREN: Scaling Ion-Traps by REquiring iNnovative Heterogenous Integration

The SIREN (Scaling Ion Traps by Requiring iNnovative heterogenous integration) project explores the feasibility of heterogeneous integration (HI) as a transformative approach to scaling ion traps, a critical technology for advancing quantum computers and atomic clocks. Traditional ion trap architectures face significant challenges in scalability due to limitations in optical access, fabrication techniques, and material constraints. SIREN addresses these challenges by leveraging HI, which combines different materials and fabrication processes to create more complex and efficient ion trap structures. HI integrated structures can be manufactured without compromising the process to maintain compatibility to ion traps. This project focuses on integrating a separately fabricated waveguide with a fully functional ion trap. The respective alignment between the pieces needs to be accurate to less than 2 µm to ensure that the light from the waveguide can overlap with the trapping region. The fine alignment must also be maintained through an ultra-high vacuum bake, a critical step in preparing an ion trap experiment. The project's outcomes suggest that heterogeneous integration is a promising pathway for overcoming current scalability barriers, paving the way for the next generation of quantum technologies. SIREN's findings contribute significantly to the field, offering a scalable solution that could accelerate the development of practical quantum computers and highly accurate atomic clocks.

42 ENGINEERING