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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Clustering earthquake signals and background noises in continuous seismic data with unsupervised deep learning

The continuously growing amount of seismic data collected worldwide is outpacing our abilities for analysis, since to date, such datasets have been analyzed in a human-expert intensive, supervised fashion. Moreover, analyses that are conducted can be strongly biased by the standard models employed by seismologists. In response to both of these challenges, we develop a new unsupervised machine learning framework for detecting and clustering seismic signals in continuous seismic records. Our approach combines a deep scattering network and a Gaussian mixture model to cluster seismic signal segments and detect novel structures. To illustrate the power of the framework, we analyze seismic data acquired during the June 2017 Nuugaatsiaq, Greenland landslide. We demonstrate the blind detection and recovery of the repeating precursory seismicity that was recorded before the main landslide rupture, which suggests that our approach could lead to more informative forecasting of the seismic activity in seismogenic areas.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Dark Energy Survey Year 3 Results: Cosmological Constraints from Cluster Abundances, Weak Lensing, and Galaxy Clustering

Galaxy clusters provide a unique probe of the late-time cosmic structure and serve as a powerful independent test of the $\Lambda$CDM model. This work presents the first set of cosmological constraints derived with ~16,000 optically selected redMaPPer clusters across nearly 5,000 $\rm{deg}^2$ using DES Year 3 data sets. Our analysis leverages a consistent modeling framework for galaxy cluster cosmology and DES-Y3 joint analyses of galaxy clustering and weak lensing (3x2pt), ensuring direct comparability with the DES-Y3 3x2pt analysis. We obtain constraints of $S_8 = 0.864 \pm 0.035$ and $\Omega_{\rm{m}} = 0.265^{+0.019}_{-0.031}$ from the cluster-based data vector. We find that cluster constraints and 3x2pt constraints are consistent under the $\Lambda$CDM model with a Posterior Predictive Distribution (PPD) value of $0.53$. The consistency between clusters and 3x2pt provides a stringent test of $\Lambda$CDM across different mass and spatial scales. Jointly analyzing clusters with 3x2pt further improves cosmological constraints, yielding $S_8 = 0.811^{+0.022}_{-0.020}$ and $\Omega_{\rm{m}} = 0.294^{+0.022}_{-0.033}$, a $24\%$ improvement in the $\Omega_{\rm{m}}-S_8$ figure-of-merit over 3x2pt alone. Moreover, we find no significant deviation from the Planck CMB constraints with a probability to exceed (PTE) value of $0.6$, significantly reducing previous $S_8$ tension claims. Finally, combining DES 3x2pt, DES clusters, and Planck CMB places an upper limit on the sum of neutrino masses of $\sum m_\nu < 0.26$ eV at 95% confidence under the $\Lambda$CDM model. These results establish optically selected clusters as a key cosmological probe and pave the way for cluster-based analyses in upcoming Stage-IV surveys such as LSST, Euclid, and Roman.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1994

Assessment of the SFC database for analysis and modeling

SFC is one of the four clusters that make up the Integrated Work Control System (IWCS), which will integrate the shuttle processing databases at Kennedy Space Center (KSC). The IWCS framework will enable communication among the four clusters and add new data collection protocols. The Shop Floor Control (SFC) module has been operational for two and a half years; however, at this stage, automatic links to the other 3 modules have not been implemented yet, except for a partial link to IOS (CASPR). SFC revolves around a DB/2 database with PFORMS acting as the database management system (DBMS). PFORMS is an off-the-shelf DB/2 application that provides a set of data entry screens and query forms. The main dynamic entity in the SFC and IOS database is a task; thus, the physical storage location and update privileges are driven by the status of the WAD. As we explored the SFC values, we realized that there was much to do before actually engaging in continuous analysis of the SFC data. Half way into this effort, it was realized that full scale analysis would have to be a future third phase of this effort. So, we concentrated on getting to know the contents of the database, and in establishing an initial set of tools to start the continuous analysis process. Specifically, we set out to: (1) provide specific procedures for statistical models, so as to enhance the TP-OAO office analysis and modeling capabilities; (2) design a data exchange interface; (3) prototype the interface to provide inputs to SCRAM; and (4) design a modeling database. These objectives were set with the expectation that, if met, they would provide former TP-OAO engineers with tools that would help them demonstrate the importance of process-based analyses. The latter, in return, will help them obtain the cooperation of various organizations in charting out their individual processes.

Centeno, Martha A.↗
NASA NTRS2003

Cluster electric current density measurements within a magnetic flux rope in the plasma sheet

On August 22, 2001 all 4 Cluster spacecraft nearly simultaneously penetrated a magnetic flux rope in the tail. The flux rope encounter took place in the central plasma sheet, Beta(sub i) approx. 1-2, near the leading edge of a bursty bulk flow. The "time-of-flight" of the flux rope across the 4 spacecraft yielded V(sub x) approx. 700 km/s and a diameter of approx.1 R(sub e). The speed at which the flux rope moved over the spacecraft is in close agreement with the Cluster plasma measurements. The magnetic field profiles measured at each spacecraft were first modeled separately using the Lepping-Burlaga force-free flux rope model. The results indicated that the center of the flux rope passed northward (above) s/c 3, but southward (below) of s/c 1, 2 and 4. The peak electric currents along the central axis of the flux rope predicted by these single-s/c models were approx.15-19 nA/sq m. The 4-spacecraft Cluster magnetic field measurements provide a second means to determine the electric current density without any assumption regarding flux rope structure. The current profile determined using the curlometer technique was qualitatively similar to those determined by modeling the individual spacecraft magnetic field observations and yielded a peak current density of 17 nA/m2 near the central axis of the rope. However, the curlometer results also showed that the flux rope was not force-free with the component of the current density perpendicular to the magnetic field exceeding the parallel component over the forward half of the rope, perhaps due to the pressure gradients generated by the collision of the BBF with the inner magnetosphere. Hence, while the single-spacecraft models are very successful in fitting flux rope magnetic field and current variations, they do not provide a stringent test of the force-free condition.

Slavin, J. A.↗
DOE OSTI2014

Weighing 'El Gordo' with a precision scale: Hubble space telescope weak-lensing analysis of the merging galaxy cluster ACT-CL J0102–4915 at z = 0.87

We present a Hubble Space Telescope weak-lensing study of the merging galaxy cluster 'El Gordo' (ACT-CL J0102–4915) at z = 0.87 discovered by the Atacama Cosmology Telescope (ACT) collaboration as the strongest Sunyaev-Zel'dovich decrement in its ∼1000 deg{sup 2} survey. Our weak-lensing analysis confirms that ACT-CL J0102–4915 is indeed an extreme system consisting of two massive (≳ 10{sup 15} M {sub ☉} each) subclusters with a projected separation of ∼0.7 h{sub 70}{sup −1} Mpc. This binary mass structure revealed by our lensing study is consistent with the cluster galaxy distribution and the dynamical study carried out with 89 spectroscopic members. We estimate the mass of ACT-CL J0102–4915 by simultaneously fitting two axisymmetric Navarro-Frenk-White (NFW) profiles allowing their centers to vary. We use only a single parameter for the NFW mass profile by enforcing the mass-concentration relation from numerical simulations. Our Markov-Chain-Monte-Carlo analysis shows that the masses of the northwestern (NW) and the southeastern (SE) components are M{sub 200c}=(1.38±0.22)×10{sup 15} h{sub 70}{sup −1} M{sub ⊙} and (0.78±0.20)×10{sup 15} h{sub 70}{sup −1} M{sub ⊙}, respectively, where the quoted errors include only 1σ statistical uncertainties determined by the finite number of source galaxies. These mass estimates are subject to additional uncertainties (20%-30%) due to the possible presence of triaxiality, correlated/uncorrelated large scale structure, and departure of the cluster profile from the NFW model. The lensing-based velocity dispersions are 1133{sub −61}{sup +58} km s{sup −1} and 1064{sub −66}{sup +62} km s{sup −1} for the NW and SE components, respectively, which are consistent with their spectroscopic measurements (1290 ± 134 km s{sup –1} and 1089 ± 200 km s{sup –1}, respectively). The centroids of both components are tightly constrained (∼4'') and close to the optical luminosity centers. The X-ray and mass peaks are spatially offset by ∼8'' (∼62 h{sub 70}{sup −1} kpc), which is significant at the ∼2σ confidence level. The mass peak, however, does not lead the gas peak in the direction expected if we are viewing the cluster soon after first core passage during a high speed merger. Under the assumption that the merger is happening in the plane of the sky, extrapolation of the two NFW halos to a radius r{sub 200a}=2.4 h{sub 70}{sup −1} Mpc yields a combined mass of M{sub 200a}=(3.13±0.56)×10{sup 15} h{sub 70}{sup −1} M{sub ⊙}. This extrapolated total mass is consistent with our two-component-based dynamical analysis and previous X-ray measurements, projecting ACT-CL J0102–4915 to be the most massive cluster at z > 0.6 known to date.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Coupled Cluster and Density Functional Studies of Atomic Fluorine Chemisorption on Coronene as Model Systems for Graphene Fluorination

Potential energy curves (PECs) of atomic fluorine adsorption on coronene as a model for graphene or nanocarbon surfaces have been computed. The PECs were obtained by scanning the fluorine atom distance to one of the center carbon atoms of the coronene molecule as model system in a “top” position from 4.0 to1.0 Å in intervals of 0.1 Å using a variety of quantum chemical methods. Various density functional theory (DFT) functionals, such as B3LYP, PBE, PBE0, CAM-B3LYP, and LC-ωPBE; approximate DFT methods such as several levels of the density-functional tight-binding (DFTB) method, as well as ab initio wave function theory methods such as MP2, CCSD, CCSD(T), and G2MS extrapolations, were used to evaluate energies for B3LYP/cc-pVDZ PEC geometries. G2MS is an approximation to the highly accurate CCSD(T)/cc-pVTZ level of theory in our work. We found that fluorine is chemically adsorbed on coronene with a binding energy of 22.9 and 23.3 kcal/mol at the B3LYP/cc-pVDZ and G2MS levels of theory, respectively, and 18.3 and 19.3 kcal/mol after counterpoise correction. Here, we found that pure DFT functionals and their DFTB approximations fail to predict the correct dissociation limit due to the DFT-inherent self-interaction error and various limitations in the DFTB approximation itself.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Identifying COVID-19 cases and extracting patient reported symptoms from Reddit using natural language processing

We used social media data from “covid19positive” subreddit, from 03/2020 to 03/2022 to identify COVID-19 cases and extract their reported symptoms automatically using natural language processing (NLP). We trained a Bidirectional Encoder Representations from Transformers classification model with chunking to identify COVID-19 cases; also, we developed a novel QuadArm model, which incorporates Question-answering, dual-corpus expansion, Adaptive rotation clustering, and mapping, to extract symptoms. Our classification model achieved a 91.2% accuracy for the early period (03/2020-05/2020) and was applied to the Delta (07/2021–09/2021) and Omicron (12/2021–03/2022) periods for case identification. We identified 310, 8794, and 12,094 COVID-positive authors in the three periods, respectively. The top five common symptoms extracted in the early period were coughing (57%), fever (55%), loss of sense of smell (41%), headache (40%), and sore throat (40%). During the Delta period, these symptoms remained as the top five symptoms with percent authors reporting symptoms reduced to half or fewer than the early period. During the Omicron period, loss of sense of smell was reported less while sore throat was reported more. Our study demonstrated that NLP can be used to identify COVID-19 cases accurately and extracted symptoms efficiently.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2012

COSMOLOGICAL CONSTRAINTS FROM GALAXY CLUSTERING AND THE MASS-TO-NUMBER RATIO OF GALAXY CLUSTERS

We place constraints on the average density ({Omega}{sub m}) and clustering amplitude ({sigma}{sub 8}) of matter using a combination of two measurements from the Sloan Digital Sky Survey: the galaxy two-point correlation function, w{sub p} (r{sub p} ), and the mass-to-galaxy-number ratio within galaxy clusters, M/N, analogous to cluster M/L ratios. Our w{sub p} (r{sub p} ) measurements are obtained from DR7 while the sample of clusters is the maxBCG sample, with cluster masses derived from weak gravitational lensing. We construct nonlinear galaxy bias models using the Halo Occupation Distribution (HOD) to fit both w{sub p} (r{sub p} ) and M/N for different cosmological parameters. HOD models that match the same two-point clustering predict different numbers of galaxies in massive halos when {Omega}{sub m} or {sigma}{sub 8} is varied, thereby breaking the degeneracy between cosmology and bias. We demonstrate that this technique yields constraints that are consistent and competitive with current results from cluster abundance studies, without the use of abundance information. Using w{sub p} (r{sub p} ) and M/N alone, we find {Omega}{sup 0.5}{sub m}{sigma}{sub 8} = 0.465 {+-} 0.026, with individual constraints of {Omega}{sub m} = 0.29 {+-} 0.03 and {sigma}{sub 8} = 0.85 {+-} 0.06. Combined with current cosmic microwave background data, these constraints are {Omega}{sub m} = 0.290 {+-} 0.016 and {sigma}{sub 8} = 0.826 {+-} 0.020. All errors are 1{sigma}. The systematic uncertainties that the M/N technique are most sensitive to are the amplitude of the bias function of dark matter halos and the possibility of redshift evolution between the SDSS Main sample and the maxBCG cluster sample. Our derived constraints are insensitive to the current level of uncertainties in the halo mass function and in the mass-richness relation of clusters and its scatter, making the M/N technique complementary to cluster abundances as a method for constraining cosmology with future galaxy surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Machine learning-powered data cleaning for LEGEND: a semi-supervised approach using affinity propagation and support vector machines

Neutrinoless double-beta decay ($0\nu\beta\beta$) is a rare nuclear process that, if observed, will provide insight into the nature of neutrinos and help explain the matter-antimatter asymmetry in the Universe. The large enriched germanium experiment for neutrinoless double-beta decay (LEGEND) will operate in two phases to search for $0\nu\beta\beta$. The first (second) stage will employ 200 (1000) kg of High-Purity Germanium (HPGe) enriched in 76 Ge to achieve a half-life sensitivity of 10 27 (10 28 ) years. In this study, we present a semi-supervised data-driven approach to remove non-physical events captured by HPGe detectors powered by a novel artificial intelligence model. We utilize affinity propagation to cluster waveform signals based on their shape and a support vector machine to classify them into different categories. We train, optimize, and test our model on data taken from a natural abundance HPGe detector installed in the Full Chain Test experimental stand at the University of North Carolina at Chapel Hill. We demonstrate that our model yields a maximum sacrifice of physics events of $0.024 ^{+0.004}_{-0.003} \%$ after data cleaning. Our model is being used to accelerate data cleaning development for LEGEND-200 and will serve to improve data cleaning procedures for LEGEND-1000.

artificial intelligence↗
DOE OSTI2012

Developing custom fire behavior fuel models from ecologically complex fuel structures for upper Atlantic Coastal Plain forests.

Currently geospatial fire behavior analyses are performed with an array of fire behavior modeling systems such as FARSITE, FlamMap, and the Large Fire Simulation System. These systems currently require standard or customized surface fire behavior fuel models as inputs that are often assigned through remote sensing information. The ability to handle hundreds or thousands of measured surface fuelbeds representing the fine scale variation in fire behavior on the landscape is constrained in terms of creating compatible custom fire behavior fuel models. In this study, we demonstrate an objective method for taking ecologically complex fuelbeds from inventory observations and converting those into a set of custom fuel models that can be mapped to the original landscape. We use an original set of 629 fuel inventory plots measured on an 80,000 ha contiguous landscape in the upper Atlantic Coastal Plain of the southeastern United States. From models linking stand conditions to component fuel loads, we impute fuelbeds for over 6000 stands. These imputed fuelbeds were then converted to fire behavior parameters under extreme fuel moisture and wind conditions (97th percentile) using the fuel characteristic classification system (FCCS) to estimate surface fire rate of spread, surface fire flame length, shrub layer reaction intensity (heat load), non-woody layer reaction intensity, woody layer reaction intensity, and litter-lichen-moss layer reaction intensity. We performed hierarchical cluster analysis of the stands based on the values of the fire behavior parameters. The resulting 7 clusters were the basis for the development of 7 custom fire behavior fuel models from the cluster centroids that were calibrated against the FCCS point data for wind and fuel moisture. The latter process resulted in calibration against flame length as it was difficult to obtain a simultaneous calibration against both rate of spread and flame length. The clusters based on FCCS fire behavior parameters represent reasonably identifiable stand conditions, being: (1) pine dominated stands with more litter and down woody debriscomponents than other stands, (2) hardwood and pine stands with no shrubs, (3) hardwood dominated stands with low shrub and high non-woody biomass and high down woody debris, (4) stands with high grass and forb (i.e., non-woody) biomass as well as substantial shrub biomass, (5) stands with both high shrub and litter biomass, (6) pine-mixed hardwood stands with moderate litter biomass and low shrub biomass, and (7) baldcypress-tupelo stands. Models representing these stand clusters generated flame lengths from 0.6 to 2.3 musing a 30 km h{sub 1} wind speed and fireline intensities of 100-1500 kW m{sub 1} that are typical within the range of experience on this landscape. The fuel models ranked 1 < 2 < 7 < 5 < 4 < 3 < 6 in terms of both flame length and fireline intensity. The method allows for ecologically complex data to be utilized in order to create a landscape representative of measured fuel conditions and to create models that interface with geospatial fire models.

09 BIOMASS FUELS↗
NASA NTRS1995

Large-scale motions in the universe: Using clusters of galaxies as tracers

Can clusters of galaxies be used to trace the large-scale peculiar velocity field of the universe? We answer this question by using large-scale cosmological simulations to compare the motions of rich clusters of galaxies with the motion of the underlying matter distribution. Three models are investigated: Omega = 1 and Omega = 0.3 cold dark matter (CDM), and Omega = 0.3 primeval baryonic isocurvature (PBI) models, all normalized to the Cosmic Background Explorer (COBE) background fluctuations. We compare the cluster and mass distribution of peculiar velocities, bulk motions, velocity dispersions, and Mach numbers as a function of scale for R greater than or = 50/h Mpc. We also present the large-scale velocity and potential maps of clusters and of the matter. We find that clusters of galaxies trace well the large-scale velocity field and can serve as an efficient tool to constrain cosmological models. The recently reported bulk motion of clusters 689 +/- 178 km/s on approximately 150/h Mpc scale (Lauer & Postman 1994) is larger than expected in any of the models studied (less than or = 190 +/- 78 km/s).

Gramann, Mirt↗
DOE OSTI2017

Discovery of a Lensed Ultrabright Submillimeter Galaxy at z = 2.0439

We report an ultrabright lensed submillimeter galaxy (SMG) at z = 2.0439, WISE J132934.18+224327.3, identified as a result of a full-sky cross-correlation of the AllWISE and Planck compact source catalogs aimed to search for bright analogs of the SMG SMM J2135, the Cosmic Eyelash. Inspection of archival SCUBA-2 observations of the candidates revealed a source with fluxes (S{sub 850μm}=130 mJy) consistent with the Planck measurements. The centroid of the SCUBA-2 source coincides within 1 arcsec with the position of the AllWISE mid-IR source, and, remarkably, with an arc-shaped lensed galaxy in HST images at visible wavelengths. Low-resolution rest-frame UV-optical spectroscopy of this lensed galaxy obtained with 10.4 m GTC reveals the typical absorption lines of a starburst galaxy. Gemini-N near-IR spectroscopy provided a clear detection of H{sub α} emission. The lensed source appears to be gravitationally magnified by a massive foreground galaxy cluster lens at z = 0.44; modeling with Lenstool indicates a lensing amplification factor of 11 ± 2. We determine an intrinsic rest-frame 8–1000 μm luminosity, L{sub IR}, of (1.3±0.1)×10{sup 13} L{sub ⊙}, and a likely star formation rate (SFR) of ∼500--2000 M{sub ⊙} yr{sup −1}. The SED shows a remarkable similarity with the Cosmic Eyelash from optical-mid/IR to submillimeter/radio, albeit at higher fluxes.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Constraints on the Optical Depth of Galaxy Groups and Clusters

Future data from galaxy redshift surveys, combined with high-resolutions maps of the cosmic microwave background, will enable measurements of the pairwise kinematic Sunyaev–Zel’dovich (kSZ) signal with unprecedented statistical significance. This signal probes the matter-velocity correlation function, scaled by the average optical depth (τ) of the galaxy groups and clusters in the sample, and is thus of fundamental importance for cosmology. However, in order to translate pairwise kSZ measurements into cosmological constraints, external constraints on τ are necessary. In this work, we present a new model for the intracluster medium, which takes into account star formation, feedback, non-thermal pressure, and gas cooling. Our semi-analytic model is computationally efficient and can reproduce results of recent hydrodynamical simulations of galaxy cluster formation. We calibrate the free parameters in the model using recent X-ray measurements of gas density profiles of clusters, and gas masses of groups and clusters. Our observationally calibrated model predicts the average τ{sub 500} (i.e., the integrated τ within a disk of size R {sub 500}) to better than 6% modeling uncertainty (at 95% confidence level). If the remaining uncertainties associated with other astrophysical uncertainties and X-ray selection effects can be better understood, our model for the optical depth should break the degeneracy between optical depth and cluster velocity in the analysis of future pairwise kSZ measurements and improve cosmological constraints with the combination of upcoming galaxy and CMB surveys, including the nature of dark energy, modified gravity, and neutrino mass.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Gravothermal collapse and the diversity of galactic rotation curves

The rotation curves of spiral galaxies exhibit a great diversity that challenges our understanding of galaxy formation and the nature of dark matter. Previous studies showed that in self-interacting dark matter (SIDM) models with a cross section per unit mass of σ/m ≈ $\mathscr{O}$(1) cm 2 /g, the predicted dark matter central densities are a good match to the observed densities in galaxies. Here, in this work, we explore a regime with a larger cross section of σ/m ≈ 20−40 cm 2 /g in dwarf galactic halos. We will show that such strong dark matter self-interactions can further amplify the diversity of halo densities inherited from their assembly history. High concentration halos can enter the gravothermal collapse phase within 10 Gyr, resulting in a high density, while low concentration ones remain in the expansion phase and have a low density. We fit the rotation curves of 14 representative low surface brightness galaxies and demonstrate how the large range of observed central densities is naturally accommodated in the strong SIDM regime of σ/m ≈ 20 – 40 cm 2 /g. Galaxies that are outliers in the previous studies, due to their high halo central densities, are no longer outliers in this SIDM regime as their halos would be in the collapse phase. For galaxies with a low density, the SIDM fits are robust to the variation of the cross section. Our findings open up a new window for testing gravothermal collapse, the unique signature of strong dark matter self-interactions, and exploring a broader SIDM model space. As an example, we illustrate how the larger cross sections favored by our fits, together with upper limits from strong lensing observations in clusters, pick out the preferred SIDM model space for a dark matter particle coupled to a light gauge boson in the Born regime.

dark matter↗
DOE OSTI2014

A tale of two anomalies: Depletion, dispersion, and the connection between the stellar lithium spread and inflated radii on the pre-main sequence

We investigate lithium depletion in standard stellar models (SSMs) and main sequence (MS) open clusters, and explore the origin of the Li dispersion in young, cool stars of equal mass, age, and composition. We first demonstrate that SSMs accurately predict the Li abundances of solar analogs at the zero-age main sequence (ZAMS) within theoretical uncertainties. We then measure the rate of MS Li depletion by removing the [Fe/H]-dependent ZAMS Li pattern from three well-studied clusters, and comparing the detrended data. MS depletion is found to be mass-dependent, in the sense of more depletion at low mass. A dispersion in Li abundance at fixed T{sub eff} is nearly universal, and sets in by ∼200 Myr. We discuss mass and age dispersion trends, and the pattern is mixed. We argue that metallicity impacts the ZAMS Li pattern, in agreement with theoretical expectations but contrary to the findings of some previous studies, and suggest Li as a test of cluster metallicity. Finally, we argue that a radius dispersion in stars of fixed mass and age, during the epoch of pre-MS Li destruction, is responsible for the spread in Li abundances and the correlation between rotation and Li in young cool stars, most well known in the Pleiades. We calculate stellar models, inflated to match observed radius anomalies in magnetically active systems, and the resulting range of Li abundances reproduces the observed patterns of young clusters. We discuss ramifications for pre-MS evolutionary tracks and age measurements of young clusters, and suggest an observational test.

79 ASTRONOMY AND ASTROPHYSICS↗