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DOE OSTI2022

Cloud Morphology Evolution in Arctic Cold‐Air Outbreak: Two Cases During COMBLE Period

Abstract Cloud feedbacks play an important role in Arctic warming. Cloud morphology, for example, cloud size and spatial distributions, is among key factors that directly impact their radiative effects. In this work, we use two cases observed during the Cold‐air Outbreak (CAO) in the Marine Boundary Layer Experiment (COMBLE) to study the evolution of cloud size distributions as an air mass is advected from the Arctic over a comparatively warm ocean and cloud mesoscale organization changes from rolls to cells. Cloud objects are identified from Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance images through an object segmentation procedure and roll breakup is identified by homogeneities in cloud water path (CWP). Roll breakup is found to be accompanied by a local minimum in wind shear and local maxima in cloud size and marine cold air outbreak index. The mean cloud horizontal aspect ratio has weak fetch dependency and is around 2 in roll, transition, and cell regimes. Regardless of distance from the ice edge, smaller clouds (<10 km 2 ) dominate the population number but not cloud cover. Cloud size distributions show bimodality in transition and cell regimes. For clouds with comparable sizes, mean nearest neighbor distances normalized by equivalent cloud radius converge to a single value for all regimes and for all but the smallest clouds, suggesting that clouds of comparable sizes in CAOs are separated by distance proportional to their sizes. The presented statistical results pave the way to evaluating model simulated cloud organizations during CAO events.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Combining Mass Spectrometry of Picoliter Samples with a Multicompartment Electrodynamic Trap for Probing the Chemistry of Droplet Arrays

Single droplet levitation provides contactless access to the microphysical and chemical properties of micrometer-sized samples. Most applications of droplet levitation to chemical and biological systems use nondestructive optical techniques to probe droplet properties. To provide improved chemical specificity, we coupled a multicompartment quadrupole electrodynamic trap (QET) with single droplet mass spectrometry. Our QET continuously traps a monodisperse droplet population (tens to hundreds of droplets) and allows for the simultaneous sizing of a single droplet using its Mie scattering pattern. Single droplets are subsequently ejected into the ionization region of an ambient pressure inlet mass spectrometer. We optimized two complementary soft ionization techniques for picoliter aqueous droplets: (1) paper spray (PS) ionization and (2) thermal desorption glow discharge (TDGD) ionization. Both techniques detect oxygenated organic acids in single droplets, with signal-to-noise ratios >100 and detection limits on the order of 10 pg. Sensitivity and reproducibility across single droplets are driven by the droplet deposition location and spray stability in PS-MS and the ionization region humidity and analyte evaporation rate in TDGD-MS. Importantly, the analyte evaporation rate can control the TDGD-MS quantitative capability because high evaporation rates result in significant ion suppression. Additionally, this effect is mitigated by optimizing the vaporization temperature, droplet size range, and analyte volatility. We demonstrate quantitative and reproducible measurements with a droplet internal standard (<10% RSD) and compare the sensitivity of PS-MS and TDGD-MS. Finally, we demonstrate the application of QET-MS to the study of heterogeneous chemical kinetics with the reaction of gas phase O 3 and aqueous maleic acid droplets.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Production and Persistence of Extreme Two-temperature Plasmas in Radiative Relativistic Turbulence

Turbulence is a predominant process for energizing electrons and ions in collisionless astrophysical plasmas, and thus is responsible for shaping their radiative signatures (luminosity, spectra, and variability). To better understand the kinetic properties of a collisionless radiative plasma subject to externally driven turbulence, we investigate particle-in-cell simulations of relativistic plasma turbulence with external inverse Compton cooling acting on the electrons. We find that ions continuously heat up while electrons gradually cool down (due to the net effect of radiation), and hence the ion-to-electron temperature ratio T i /T e grows in time. Furthermore, we show that Ti/Te is limited only by the size and duration of the simulations (reaching ${T}_{i}/{T}_{e}\sim {10}^{3}$), indicating that there are no efficient collisionless mechanisms of electron–ion thermal coupling. This result has implications for models of radiatively inefficient accretion flows, such as observed in the Galactic center and in M87, for which so-called two-temperature plasmas with ${T}_{i}/{T}_{e}\gg 1$ have been invoked to explain their low luminosity. Additionally, we find that electrons acquire a quasi-thermal distribution (dictated by the competition of turbulent particle energization and radiative cooling), while ions undergo efficient nonthermal acceleration (acquiring a harder distribution than in equivalent nonradiative simulations). There is a modest nonthermal population of high-energy electrons that are beamed intermittently in space, time, and direction; these beamed electrons may explain rapid flares in certain high-energy astrophysical systems (e.g., in the Galactic center). These numerical results demonstrate that extreme two-temperature plasmas can be produced and maintained by relativistic radiative turbulence.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2026

Probing cosmic velocities with the pairwise kinematic Sunyaev-Zel’dovich signal in DESI Bright Galaxy Sample DR1 and ACT DR6

We present a measurement of the pairwise kinematic Sunyaev-Zel’dovich (kSZ) signal using the Dark Energy Spectroscopic Instrument (DESI) Bright Galaxy Sample (BGS) Data Release 1 (DR1) galaxy sample overlapping with the Atacama Cosmology Telescope (ACT) CMB temperature map. Our analysis makes use of 1.6 million galaxies with stellar masses log⁡ 𝑀 ⋆ /𝑀 ⊙ >10, and we explore measurements across a range of aperture sizes (2.1′ <𝜃 ap <3.5′) and stellar mass selections. This statistic directly probes the velocity field of the large-scale structure, a unique observable of cosmic dynamics and modified gravity. In particular, at low redshifts, this quantity is especially interesting, as deviations from General Relativity are expected to be largest. Notably, our result represents the highest-significance low-redshift (𝑧 ∼ 0.3) detection of the kSZ pairwise effect yet. In our most optimal configuration (𝜃 ap =3.3′, log⁡ 𝑀 ⋆ >11), we achieve a 5⁢𝜎 detection. Assuming that an estimate of the optical depth and galaxy bias of the sample exists via e.g., external observables, this measurement constrains the fundamental cosmological combination 𝐻 0 ⁡𝑓⁡𝜎$^2_8$. A key challenge is the degeneracy with the galaxy optical depth. We address this by combining CMB lensing, which allows us to infer the halo mass and galaxy population properties, with hydrodynamical simulation estimates of the mean optical depth, $\bar{𝜏}$ . We stress that this is a proof-of-concept analysis; with BGS DR2 data we expect to improve the statistical precision by roughly a factor of two, paving the way toward robust tests of modified gravity with kSZ-informed velocity-field measurements at low redshift.

Hadzhiyska, Boryana [Institute of Astronomy; Kavli↗

DOE OSTI2024

Adoption of Plug-in Electric Vehicles: Local Fuel Use and Greenhouse Gas Emissions Reductions Across the U.S.

The dependence on gasoline-powered light-duty automobiles has made U.S. households vulnerable to the burden of fuel costs. Tailpipe emissions from these vehicles constitute 58% of greenhouse gas (GHG) emissions in the U.S., which are damaging to the environment (EPA, 2023). The adoption of plug-in electric vehicles (PEVs) has been shown to effectively reduce fuel costs and GHG emissions. However, local effects on these benefits are not well understood by American consumers, potentially limiting adoption and therefore the realization of PEV benefits at scale (MacInnis & Krosnick, 2020; EY Americas, 2023). To fill this research gap, this study estimates the fuel cost savings and GHG emission reductions at the state and ZIP code levels by considering local fuel prices, vehicle class preference, average vehicle model year, fuel efficiencies, and driving intensities. The study's findings reveal that the adoption of PEVs can yield substantial benefits in terms of fuel cost savings and GHG emission reductions nationwide. Specifically, driving a battery electric vehicle (BEV) is estimated to result in annual savings of up to $\$2,200$, while driving a plug-in hybrid electric vehicle (PHEV) can lead to savings up to $\$1,500$, when compared to an internal combustion engine vehicle (ICEV) of equivalent size. Moreover, using population-weighted averages by ZIP code, BEVs and PHEVs show the potential to save 400 and 200 grams of carbon dioxide equivalent per mile, respectively, compared to a representative ICEV of the same class. The magnitude of fuel cost savings and emissions reduction vary by region due to various factors. Generally, regions with high gasoline prices, low electricity prices, preferences for larger vehicles, and high driving intensities tend to see relatively large fuel savings. The emissions reductions are more pronounced in areas with clean grids where consumer preferences lie with large vehicles. This regional variability underscores the importance of considering local contextual factors when assessing the potential benefits of PEV adoption. In more than 99% of U.S. ZIP codes, PEVs result in overall savings in fuel use (and subsequent costs) and GHG emissions. While not a central focus of this analysis, reductions in GHG tailpipe emissions from PEV adoption would also come with reductions in criteria pollutant emissions, contributing to improved local air quality depending on the PEV penetration, population density, and electricity generation infrastructure in the locality.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2022

Novel light field imaging device with enhanced light collection for cold atom clouds

We present a light field imaging system that captures multiple views of an object with a single shot. The system is designed to maximize the total light collection by accepting a larger solid angle of light than a conventional lens with equivalent depth of field. This is achieved by populating a plane of virtual objects using mirrors and fully utilizing the available field of view and depth of field. Simulation results demonstrate that this design is capable of single-shot tomography of objects of size $\mathcal{O}$(1 mm 3 ), reconstructing the 3-dimensional (3D) distribution and features not accessible from any single view angle in isolation. In particular, for atom clouds used in atom interferometry experiments, the system can reconstruct 3D fringe patterns with size $\mathcal{O}$(100 μm). We also demonstrate this system with a 3D-printed prototype. The prototype is used to take images of $\mathcal{O}$(1 mm 3 ) sized objects, and 3D reconstruction algorithms running on a single-shot image successfully reconstruct $\mathcal{O}$(100 μm) internal features. The prototype also shows that the system can be built with 3D printing technology and hence can be deployed quickly and cost-effectively in experiments with needs for enhanced light collection or 3D reconstruction. Imaging of cold atom clouds in atom interferometry is a key application of this new type of imaging device where enhanced light collection, high depth of field, and 3D tomographic reconstruction can provide new handles to characterize the atom clouds.

47 OTHER INSTRUMENTATION↗

DOE OSTI2024

Mapping of flumioxazin tolerance in a snap bean diversity panel leads to the discovery of a master genomic region controlling multiple stress resistance genes

Effective weed management tools are crucial for maintaining the profitable production of snap bean (Phaseolus vulgaris L.). Preemergence herbicides help the crop to gain a size advantage over the weeds, but the few preemergence herbicides registered in snap bean have poor waterhemp (Amaranthus tuberculatus) control, a major pest in snap bean production. Waterhemp and other difficult-to-control weeds can be managed by flumioxazin, an herbicide that inhibits protoporphyrinogen oxidase (PPO). However, there is limited knowledge about crop tolerance to this herbicide. We aimed to quantify the degree of snap bean tolerance to flumioxazin and explore the underlying mechanisms. We investigated the genetic basis of herbicide tolerance using genome-wide association mapping approach utilizing field-collected data from a snap bean diversity panel, combined with gene expression data of cultivars with contrasting response. The response to a preemergence application of flumioxazin was measured by assessing plant population density and shoot biomass variables. Snap bean tolerance to flumioxazin is associated with a single genomic location in chromosome 02. Tolerance is influenced by several factors, including those that are indirectly affected by seed size/weight and those that directly impact the herbicide's metabolism and protect the cell from reactive oxygen species-induced damage. Transcriptional profiling and co-expression network analysis identified biological pathways likely involved in flumioxazin tolerance, including oxidoreductase processes and programmed cell death. Transcriptional regulation of genes involved in those processes is possibly orchestrated by a transcription factor located in the region identified in the GWAS analysis. Several entries belonging to the Romano class, including Bush Romano 350, Roma II, and Romano Purpiat presented high levels of tolerance in this study. The alleles identified in the diversity panel that condition snap bean tolerance to flumioxazin shed light on a novel mechanism of herbicide tolerance and can be used in crop improvement.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2023

Optimizing invader suppression to restore native species: Leveraging species traits to overcome collateral damage

Strategies to control ongoing biological invasions are often developed by modelling the invasive species' population and aiming to reduce its abundance. However, if the ultimate objective is to protect and restore native species, focussing solely on the invader may not be optimal because it does not account for (i) species interactions that can cause the invader's impacts to depend nonlinearly on its abundance, (ii) collateral damages to native species incurred due to nonspecific removal methods or (iii) native-invader trait differences. Here, to identify an invader suppression strategy that maximizes average native population size, we applied optimal control theory to a two-species model of a native species threatened by an invasive competitor. We examined trade-offs between iterative physical removals that selectively target invaders and intensifiable chemical control that is nonselective but has higher efficacy. We found that while iterative removals were capable of supporting large native populations when applied continuously, cost could be prohibitively high. In contrast, when favourable native-invader trait differences enabled native species to re-establish more quickly than invaders, intensifiable methods could achieve substantial restoration benefits at lower cost by focussing removal effort into periodic, high-efficacy events. In a metapopulation, removals that rotated among spatial patches were optimal when the native species had higher dispersal, whereas synchronous removals were preferred when native recovery was initiated locally and the invader could disperse. For a case study in Hawaiian streams, we compared how effective two alternative methods of removing invasive live-bearing fishes (poeciliids) might be at restoring the endemic freshwater goby Sicyopterus stimpsoni. We found that rotenone (a piscicidal chemical) offered superior benefits when the control budget was small and efficacy was high, but that electrofishing (use of electricity to manually collect target fish) was better with larger budgets and in many lower-efficacy scenarios. Synthesis and applications. Our findings demonstrate that, by accounting for species interactions and collateral damage, invasive species control strategies can be optimized in light of species traits. Choices about the timing, locations and types of removal events present opportunities to increase the efficiency with which invasive species suppression benefits native species.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

The half-mass radius of MaNGA galaxies: effect of IMF gradients

Gradients in the stellar populations (SP) of galaxies – e.g. in age, metallicity, stellar initial mass function (IMF) – can result in gradients in the stellar-mass-to-light ratio, M * / L . Such gradients imply that the distribution of the stellar mass and light is different. For old SPs, e.g. in early-type galaxies at z ∼ 0, the M * / L gradients are weak if driven by variations in age and metallicity, but significantly larger if driven by the IMF. A gradient which has larger M * / L in the centre increases the estimated total stellar mass ( M * ) and reduces the scale which contains half this mass ( R e,* ), compared to when the gradient is ignored. For the IMF gradients inferred from fitting MILES simple SP models to the H β, 〈Fe〉, [MgFe], and TiO 2SDSS absorption lines measured in spatially resolved spectra of early-type galaxies in the MaNGA survey, the fractional change in R e,* can be significantly larger than that in M * , especially when the light is more centrally concentrated. The R e,* – M * correlation which results from accounting for IMF gradients is offset to smaller sizes by 0.3 dex compared to when these gradients are ignored. Comparisons with ‘quiescent’ galaxies at higher z must account for evolution in SP gradients (especially age and IMF) and in the light profile before drawing conclusions about how R e,* and M * evolve. Here, the implied merging between higher z and the present is less contrived if R e,* / R e at z ∼ 0 is closer to our IMF-driven gradient calibration than to unity.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

Prognostic simulations of mixed-phase clouds with model AC-1D v1.0: the impact of aerosol types and freezing parameterizations on ice crystal budgets

Mixed-phase clouds at high latitudes contribute to the uncertainty in predicting cloud feedbacks and climate sensitivity, mainly due to the complexity of microphysical processes that influence the partitioning between the supercooled liquid and ice phases, and hence, cloud radiative effects on regional scales. Particularly in Arctic mixed-phase clouds, the activation of ice-nucleating particles (INPs) from various aerosol populations remains a leading source of uncertainty. We developed an aerosol-cloud one-dimensional (AC-1D) model, which provides a novel framework to prognostically treat INP and ice crystal budgets while explicitly accounting for polydisperse and multicomponent aerosol that activate INPs following different freezing parameterizations. The AC-1D model is informed by large-eddy simulations to probe the impact of INP representation on predicted ice crystal number concentrations (N i ) and ice crystal budgets in mixed-phase Arctic stratus. We apply three immersion freezing (IMF) parameterizations, two time-independent (singular) and one time-dependent (classical nucleation theory), to predict the evolution of the INP reservoir and resulting ice crystal budget from polydisperse mineral dust, organic (humic-like substances), and sea spray aerosol particle size distributions. Our analysis focuses on how variations in aerosol number concentration and cloud system parameters such as cloud cooling rate, cloud-top entrainment rate, and ice crystal fall speed influence the INP reservoir and ice crystal budgets. Furthermore, this study investigates the competitive ice nucleation dynamics in mixed aerosol environments and provides a process-level quantification of the INP budget terms, which directly controls ice crystal budgets. For all studied case scenarios, the aerosol types and associated particle size distributions significantly impact INP and N i , and the choice between a time-dependent and a singular freezing description yields orders-of-magnitude differences in the predicted INP and N i over the 10 h simulation time, reflecting typical cloud lifetimes. Our results show that the influence of cloud cooling, INP entrainment, and sedimentation varies significantly depending on the chosen freezing parameterization. These findings underscore the critical need for robust IMF parameterizations and precise cloud system observations to enhance the accuracy of models in predicting mixed-phase cloud structure and evolution.

Arctic clouds↗

DOE OSTI2022

Influence of Entrainment on Centimeter-Scale Cloud Microphysics in Marine Stratocumulus Clouds Observed during CSET

Abstract Cloud microphysical relationships observed during the Cloud System Evolution in the Trades (CSET) campaign held between Northern California and Hawaii were analyzed to study the effects of entrainment and subsequent mixing of free-tropospheric and cloudy air on cloud microphysical properties of marine stratocumulus clouds. The data measured by Holographic Detector for Clouds (HOLODEC) were extensively used because they could provide the 3D positions and sizes of droplets within sample volume on the centimeter scale, making it possible to explore the 3D spatial distribution of droplets, which has not been possible for conventional cloud probes. This study focused on analyzing the 3D spatial distribution of droplets and visual traits of inhomogeneous mixing and on quantifying the relationship between 3D spatial distributions and traits of inhomogeneous mixing. Two types of spatial distributions are compared. The first is measured droplet spatial distribution and the second type is generated randomly distributed droplets using the Monte Carlo approach, that is, to analyze whether or not clustering is strong enough to classify as a clustered distribution for a hologram. The difference between the two types of spatial distributions depends on whether they are affected by entrainment and mixing. The holograms observed near the cloud top, where the effects of entrainment and mixing would be immediate, showed relatively high confidence in the significance test for spatially clustered populations of droplets. Moreover, spatially clustered holograms appeared to exhibit stronger visual traits of inhomogeneous mixing than perfectly randomly distributed holograms only when observed near the cloud top. On the other hand, these characteristics did not appear for holograms observed deeper into the cloud where the effects of entrainment and mixing would be reduced. Such 3D structural characteristics of droplet distributions seem to be consistent with vertical circulation mixing.

Meteorology & Atmospheric Sciences↗

DOE OSTI2024

Implications of increased spatial and trophic overlap between juvenile Pacific salmon and Sablefish in the northern California Current

Abstract Objective The study was designed to assess long-term variability in the distribution of juvenile Pacific salmon Oncorhynchus spp. and Sablefish Anoplopoma fimbria. The study also evaluated whether Sablefish and Pacific salmon shared food resources and looked to characterize Sablefish during an understudied period of their life cycle. Methods To meet the objectives, the study used data from 26 years of surface trawls conducted in Oregon and Washington coastal waters (1998–2023). Spatial–temporal models were used to measure changes in abundance and distribution of Pacific salmon and Sablefish along with covariates of ocean temperature. The study evaluated trophic characteristics of Pacific salmon and Sablefish from 2020 for differences. The temporal variation in size and diets of Sablefish were also analyzed, along with energy density of fish caught in 2020. Result The spatial–temporal model demonstrated that there has been a nearshore expansion of juvenile Sablefish over the past 26 years that was correlated with increased ocean temperature. The nearshore expansion of Sablefish resulted in increased spatial and trophic overlap with juvenile Pacific salmon. While feeding in nearshore waters, juvenile Sablefish demonstrated competitive feeding advantages over juvenile Pacific salmon during a critical phase of salmonid early marine life history. Juvenile Sablefish exhibited significant ontogenetic diet and energetic shifts, and even the smallest (68–80 mm fork length) were piscivorous. Conclusions If juvenile Sablefish numbers continue to increase relative to Pacific salmon, they could exert more competitive pressure, especially if food resources become limited. Pacific salmon may experience adverse effects from competition, regardless of whether or not juvenile Sablefish, which have recently expanded into nearshore waters, successfully recruit to the adult population.

Daly, Elizabeth A. (ORCID:0000000195334457)↗

DOE OSTI2026

DELVE Milky Way Satellite Galaxy Census. I. Satellite Population and Survey Selection Function in DES, DELVE, and Pan-STARRS

The properties of Milky Way satellite galaxies have important implications for galaxy formation, reionization, and the fundamental physics of dark matter. However, the population of Milky Way satellites includes the faintest known galaxies, and current observations are incomplete. To understand the impact of observational selection effects on the known satellite population, we perform rigorous, quantitative estimates of the Milky Way satellite galaxy detection efficiency in three wide-field survey datasets: the Dark Energy Survey Year 6, the DECam Local Volume Exploration Data Release 3, and the Pan-STARRS1 Data Release 1. Together, these surveys cover ∼13,600 deg 2 to g ∼ 24.0 and ∼27,700 deg 2 to g ∼ 22.5, spanning ∼91% of the high-Galactic-latitude sky (∣b∣ ≥ 15°). We apply multiple detection algorithms over the combined footprint and recover 49 known satellites above a strict census detection threshold. To characterize the sensitivity of our census, we run our detection algorithms on a large set of simulated galaxies injected into the survey data, which allows us to develop models that predict the detectability of satellites as a function of their properties. We then fit an empirical model to our data and infer the luminosity function, radial distribution, and size–luminosity relation of Milky Way satellite galaxies. Our empirical model predicts a total of $265^{+79}_{-47}$ satellite galaxies with −20 ≤ M V ≤ 0, half-light radii of 15 ≤ r 1/2 , (pc) ≤ 3000, and galactocentric distances of 10 ≤ D GC (kpc) ≤ 300. We also identify a mild anisotropy in the angular distribution of the observed galaxies, at a significance of ∼2σ, which can be attributed to the clustering of satellites associated with the LMC.

Tan, Chin Yi [Univ. of Chicago, IL (United States)↗

DOE OSTI2026

Role of Wadsley Defects and Cation Disorder to Enhance MoNb 12 O 33 Diffusion

Wadsley-Roth (WR) niobates have emerged as high-rate anode materials that can combine rapid ionic diffusion with good electronic conductivity. WR compounds have been defect-enhanced by limited annealing, however, such materials often contain multiple types of defects. In particular, both Wadsley defects (variable block size) and transition metal disorder have the potential to modify transport rates, however the corresponding effects are not well understood mechanistically. Here, MoNb 12 O 33 (MNO) was calcined at two different temperatures to compare a defect-rich condition (MNO-800) with a proximal order-rich condition (MNO-900) as assessed through XRD, XANES, EXAFS, and STEM characterizations. Galvanostatically cycled lithium half cells of MNO-800 exhibited additional capacity (307 mAhg −1 at 0.1C, 4.66% higher) and improved high-rate capacity of 200 mAhg −1 at 10C. ICI-based overpotential analysis identified solid state diffusion as the dominant rate limiting process where MNO-800 correspondingly exhibited ∼3X faster capacity-weighted diffusivity. A machine-learning interatomic potential was trained to density functional theory and then applied with molecular dynamics (MLIP-MD) to examine the possible roles of Wadsley defects and transition metal disorder. For both defect-types, Li was found to populate and activate fast diffusion paths from window sites at lower extents of lithiation as compared to the order-rich model.

defect↗

DOE OSTI2023

Impact of crowding on the diversity of expanding populations

Crowding effects critically impact the self-organization of densely packed cellular assemblies, such as biofilms, solid tumors, and developing tissues. When cells grow and divide, they push each other apart, remodeling the structure and extent of the population’s range. Recent work has shown that crowding has a strong impact on the strength of natural selection. However, the impact of crowding on neutral processes, which controls the fate of new variants as long as they are rare, remains unclear. Here, we quantify the genetic diversity of expanding microbial colonies and uncover signatures of crowding in the site frequency spectrum. By combining Luria–Delbrück fluctuation tests, lineage tracing in a novel microfluidic incubator, cell-based simulations, and theoretical modeling, we find that the majority of mutations arise behind the expanding frontier, giving rise to clones that are mechanically “pushed out” of the growing region by the proliferating cells in front. These excluded-volume interactions result in a clone-size distribution that solely depends on where the mutation first arose relative to the front and is characterized by a simple power law for low-frequency clones. Our model predicts that the distribution depends on a single parameter—the characteristic growth layer thickness—and hence allows estimation of the mutation rate in a variety of crowded cellular populations. Combined with previous studies on high-frequency mutations, our finding provides a unified picture of the genetic diversity in expanding populations over the whole frequency range and suggests a practical method to assess growth dynamics by sequencing populations across spatial scales.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Simulating large one-dimensional neutral-atom quantum systems

While abstract models of quantum computation assume a closed system of two-level states, practical quantum devices inevitably couple to the environment in some way, creating sources of noise. Understanding the tolerance to noise of specific quantum algorithms run on specific devices is important for determining the feasibility of quantum computing in the current noisy intermediate-scale quantum era. Of particular interest is understanding the noise sensitivity of these devices as more qubits are added to the system. Classical simulations are a useful tool to understand the effects of this noise, but direct classical simulations of open quantum systems are burdened by an exponentially growing cost in the number of qubits and a large local Hilbert space dimension. For onedimensional, shallow circuits, using tensor networks can replace this exponential cost with a linear one and simulate far wider systems than what would normally be available. In this paper, we describe a tensor network simulation of a neutral atom quantum system under the presence of noise, while introducing a purity-preserving truncation technique that compromises between the simplicity of the matrix product state and the positivity of the matrix product density operator. We apply this simulation to a near-optimized iteration of the quantum approximate optimization algorithm on a transverse field Ising model in order to investigate the influence of large system sizes on the performance of the algorithm. We find that while circuits with a large number of qubits fail more often under noise that depletes the qubit population, their outputs on a successful measurement are just as robust under Rydberg atom dissipation or qubit dephasing as smaller systems. However, such circuits might not perform as well under coherent multiqubit errors such as Rydberg atom crosstalk. We also find that the optimized parameters are especially robust to noise, suggesting that a noisier quantum system can be used to find the optimal parameters before switching to a cleaner system for measurements of observables.

Allen, James↗

DOE OSTI2023

Demographic and genetic consequences of a steelhead supplementation program

Abstract Objective Supplementation of naturally spawning populations by the addition of hatchery-spawned individuals is commonly conducted for recovery of threatened and endangered populations and to support harvest opportunities. Our objective was to evaluate whether the use of a juvenile captive broodstock and an integrated paradigm could increase returns of steelhead, the anadromous form of Rainbow Trout Oncorhynchus mykiss, while avoiding negative genetic impacts commonly associated with hatchery propagation. Methods We analyzed 291 genetic markers in adult steelhead returning to an integrated population in southwest Washington over the course of 15 years. Reproductive success (RS) of fish spawning in the natural environment was evaluated by origin (hatchery versus natural) and return year. Data were then pooled over years to maximize sample sizes for comparing RS estimates among groups (i.e., estimation of relative reproductive success [RRS]). Result We observed a weak relationship between RS and origin (male p = 0.347; female p = 0.066), but a significant relationship between RS and return year (male p < 0.001, η2 = 0.896; female p ⟨ 0.001, η2 = 0.867) (i.e., hatchery- and natural-origin fish did well or poorly together each year). Estimates of RRS for fish spawned in the hatchery ranged from 2.4 to 6.4, indicating that fish spawned in the hatchery produced more returning adult progeny than did fish allowed to spawn in the natural environment. Estimates of RRS were ⟨1.0 for hatchery-origin fish spawning in the natural environment, but the difference was nonsignificant for males and marginally significant for females. Hatchery-origin fish exhibited reduced genetic diversity as well as evidence of increased temporal population structure. Conclusion We conclude that the program was successful in achieving an increase in adult returns but not in avoiding negative genetic effects on the population and that any lasting impacts of supplementation remain to be determined.

Smith, Christian T. (ORCID:0000000240522669)↗

DOE OSTI2022

Subaru High-z Exploration of Low-Luminosity Quasars (SHELLQs) – XV. Constraining the cosmic reionization at 5.5 < z < 7

ABSTRACT Revealing the cosmic hydrogen reionization history is one of the main goals of the modern cosmology. z > 5 quasars (QSOs) have been used as back-lights to investigate the evolution of the intervening intergalactic medium (IGM) during the cosmic reionization since their first discovery. However, due to the small population of luminous QSOs (∼130 QSOs known to date), a tight constraint on the reionization history has not yet been placed. In this work, we aim to tighten the constraint using the 93 QSOs (5.5 < z < 7.1) recently discovered in the Subaru High-z Exploration of Low-Luminosity Quasars (SHELLQS) project. This is the largest QSO sample used to constrain the epoch of reionization. We measure the mean IGM Ly α transmission and the QSO near-zone size using the UV spectra of these QSOs. The mean IGM Ly α transmission rises above zero at z ≲ 6, indicating the end of the reionization. The near-zone sizes of the SHELLQs QSOs are consistent with sizes spanned by QSOs of lifetime tq ∼ 1–100 Myr in simulations. Due to the scatter created by the low signal-to-noise spectra and large Ly α redshift uncertainty, we cannot conclude whether the redshift evolution of the near-zone size is affected by the reionization effect.

Lu, Ting-Yi (ORCID:0000000249656524)↗