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Technical Note: On the analytical proton dose evaluation in compounds and mixtures

Purpose: By combining the physical processes occurring due to the interaction of protons with matter, analytical theories published so far have provided acceptable models for calculating depth-dose distributions in homogeneous media. As a well-defined and comprehensive theory, the formula derived by Bortfeld models the dose transferred to the target in terms of the parabolic cylinder function. The model also includes three parameters with values specified for an initial proton energy and for the target material. These parameters are obtainable through the data gathered in nuclear data tables. The analytical studies using this interesting model are therefore restricted to those materials for which the data have been provided in these tables. This study aims to find general solutions for calculation of these parameters for a compound or mixture composed of an arbitrary choice of constituent elements. Methods: Inspired by formulas dedicated for calculating the range and the probability of undergoing nonelastic nuclear interactions for protons in desired compounds, the analytical methods for finding the three mentioned parameters are investigated. The accuracy of the methods suggested is examined through comparison of the results with those which are calculated using the data taken from nuclear data tables. By employing the calculated parameters using the derived formulas in the Bortfeld model, the dose distribution at depth in a chosen target is calculated. Results: For an arbitrary selection of compounds, the predictions of the analytical depth-dose model using these parameters have been found to closely match the results employing the parameters calculated using the data reported in nuclear data tables. Conclusions: The formulas presented are general, mathematically easy to handle, and valid for almost every compound or mixture including materials of interest for proton radiotherapy purposes, making the Bortfeld model more practical and advantageous.

61 RADIATION PROTECTION AND DOSIMETRY↗

Fission fragment decay simulations with the CGMF code

The CGMF code implements the Hauser-Feshbach statistical nuclear reaction model to follow the de-excitation of fission fragments by successive emissions of prompt neutrons and γ rays. The Monte Carlo technique is used to facilitate the analysis of complex distributions and correlations among the prompt fission observables. Starting from initial configurations for the fission fragments in mass, charge, kinetic energy, excitation energy, spin, and parity, Y(A,Z,KE,U,J,π), CGMF samples neutron and γ-ray probability distributions at each stage of the decay process, conserving energy, spin and parity. Nuclear structure and reaction input data from the RIPL3 library are used to describe fission fragment properties and decay probabilities. Characteristics of prompt fission neutrons, prompt fission γ rays, and independent fission yields can be studied consistently. Correlations in energy, angle and multiplicity among the emitted neutrons and γ rays can be easily analyzed as a function of the emitting fragments. Finally, in its current version, CGMF is limited to certain spontaneous fission reactions on Pu and Cf isotopes, as well as neutron-induced fission reactions up to 20 MeV on U, Np, and Pu isotopes.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

WAS THE SUN BORN IN A MASSIVE CLUSTER?

A number of authors have argued that the Sun must have been born in a cluster of no more than several thousand stars, on the basis that, in a larger cluster, close encounters between the Sun and other stars would have truncated the outer solar system or excited the outer planets into eccentric orbits. However, this dynamical limit is in tension with meteoritic evidence that the solar system was exposed to a nearby supernova during or shortly after its formation; a several-thousand-star cluster is much too small to produce a massive star whose lifetime is short enough to have provided the enrichment. In this paper, we revisit the dynamical limit in the light of improved observations of the properties of young clusters. We use a series of scattering simulations to measure the velocity-dependent cross-section for disruption of the outer solar system by stellar encounters, and use this cross-section to compute the probability of a disruptive encounter as a function of birth cluster properties. We find that, contrary to prior work, the probability of disruption is small regardless of the cluster mass, and that it actually decreases rather than increases with cluster mass. Our results differ from prior work for three main reasons: (1) unlike in most previous work, we compute a velocity-dependent cross-section and properly integrate over the cluster mass-dependent velocity distribution of incoming stars; (2) we recognize that {approx}90% of clusters have lifetimes of a few crossing times, rather than the 10-100 Myr adopted in many earlier models; and (3) following recent observations, we adopt a mass-independent surface density for embedded clusters, rather than a mass-independent radius as assumed many earlier papers. Our results remove the tension between the dynamical limit and the meteoritic evidence, and suggest that the Sun was born in a massive cluster. A corollary to this result is that close encounters in the Sun's birth cluster are highly unlikely to truncate the Kuiper Belt unless the Sun was born in one of the unusual clusters that survived for tens of Myr. However, we find that encounters could plausibly produce highly eccentric Kuiper Belt objects such as Sedna.

79 ASTRONOMY AND ASTROPHYSICS↗

Wavelet flow for extragalactic foreground simulations

Extragalactic foregrounds in cosmic microwave background (CMB) observations are both a source of cosmological and astrophysical information and a nuisance to the CMB. Effective field-level modeling that captures their non-Gaussian statistical distributions is increasingly important for optimal information extraction, particularly given the low-noise observations from current and upcoming experiments. Here, we explore the use of Wavelet Flow (WF) models to tackle the novel task of modeling the field-level probability distributions of multi-component CMB secondaries and foregrounds. Specifically, we jointly train correlated CMB lensing convergence (κ) and cosmic infrared background (CIB) maps with a WF model and obtain a network that statistically recovers the input to high accuracy — the trained network generates samples of κ and CIB fields whose average power spectra are within a few percent of the inputs across all scales, and whose Minkowski functionals are similarly accurate compared to the inputs. Leveraging the multiscale architecture of these models, we fine-tune both the model parameters and the priors at each scale independently, optimizing performance across different resolutions. These results demonstrate that WF models can accurately simulate correlated components of CMB secondaries, supporting improved analysis of cosmological data. Our code and trained models can be found on this GitHub repo.

cosmological simulations↗

Bayesian Inference for the Seismic Moment Tensor Using Regional Waveforms and Teleseismic- P Polarities with a Data-Derived Distribution of Velocity Models and Source Locations

The largest source of uncertainty in any source inversion is the velocity model used in the transfer function that relates observed ground motion to the seismic moment tensor. However, standard inverse procedure often does not quantify uncertainty in the seismic moment tensor due to error in the Green’s functions from uncertain event location and Earth structure. Here, we incorporate this uncertainty into an estimation of the seismic moment tensor using a data-derived distribution of velocity models based on complementary geophysical data sets, including thickness constraints, velocity profiles, gravity data, surface-wave group velocities, and regional body-wave travel times. The data-derived distribution of velocity models is then used as a prior distribution of Green’s functions for use in Bayesian inference of an unknown seismic moment tensor using regional and teleseismic-P waveforms. The use of multiple data sets is important for gaining resolution to different components of the moment tensor. The combined likelihood is estimated using data-specific error models and the posterior of the seismic moment tensor is estimated and interpreted in terms of the most probable source type.

58 GEOSCIENCES↗

Mesh-Sequenced Realizations for Evaluation of Subgrid-Scale Models for Turbulent Combustion

This paper develops a new approach for analysis of subgrid closures for turbulent combustion as modeled using direct quadrature (finite-rate chemistry) techniques. The approach, termed multiresolution analysis through mesh-sequenced realizations (MRA-MSR), conducts simultaneous, constrained large-eddy simulations on a set of hierarchically coarsened meshes. Furthermore, the availability of underlying fine-mesh (subgrid) data corresponding to coarse-mesh locations allows a clearer assessment of the effects of unresolved fluctuations on apparent reactivity. A key to MRA-MSR is the correlation of eddy structures at coarser mesh levels, which is facilitated by the transfer of filtered fine-mesh velocity information. A seven-mesh MRA-MSR hierarchy using three resolution levels is applied to one of the Sydney bluff-body stabilized methane–hydrogen flames. Analysis of the simultaneously evolved data at different resolution levels reveals several interesting trends. First, at high Damköhler numbers, there is clear evidence of attenuation of apparent reactivity due to the effects of unresolved fluctuations. Secondly, single-point, single-time filtered density functions of a normalized subgrid Damköhler number show a characteristic beta probability density function (PDF) form and display evidence of scale similarity. Interrogation of the MRA-MSR database also shows that the recently-proposed least-squares minimization (LSM) turbulence–chemistry interaction model can account for the observed diminishment in reactivity at high Damköhler numbers but cannot reduce scatter significantly. A new form of the LSM model, which makes use of the normalized subgrid Damköhler number beta PDF distribution, performs slightly better than the original model, illustrating the potential of MRA-MSR both in assessing existing closure concepts and in developing new ones.

42 ENGINEERING↗

Predicting responses to climate change using a joint species, spatially dependent physiologically guided abundance model

Abstract Predicting the effects of warming temperatures on the abundance and distribution of organisms under future climate scenarios often requires extrapolating species–environment correlations to climatic conditions not currently experienced by a species, which can result in unrealistic predictions. For poikilotherms, incorporating species' thermal physiology to inform extrapolations under novel thermal conditions can result in more realistic predictions. Furthermore, models that incorporate species and spatial dependencies may improve predictions by capturing correlations present in ecological data that are not accounted for by predictor variables. Here, we present a joint species, spatially dependent physiologically guided abundance (jsPGA) model for predicting multispecies responses to climate warming. The jsPGA model uses a basis function approach to capture both species and spatial dependencies. We apply the jsPGA model to predict the response of eight fish species to projected climate warming in thousands of lakes in Minnesota, USA. By the end of the century, the cold‐adapted species was predicted to have high probabilities of extirpation across its current range—with 10% of lakes currently inhabited by this species having an extirpation probability >0.90. The remaining species had varying levels of predicted changes in abundance, reflecting differences in their thermal physiology. Though the model did not identify many strong species dependencies, the variation in estimated spatial dependence across species suggested that accounting for both dependencies was important for predicting the abundance of these fishes. The jsPGA model provides a new tool for predicting changes in the abundance, distribution, and extirpation probability of poikilotherms under novel thermal conditions.

54 ENVIRONMENTAL SCIENCES↗

Multiplicity dependence of charged-particle intra-jet properties in pp collisions at $\sqrt{s}$ = 13 TeV

The first measurement of the multiplicity dependence of intra-jet properties of leading charged-particle jets in proton–proton (pp) collisions is reported. The mean charged particle multiplicity and jet fragmentation distributions are measured in minimum-bias and high-multiplicity pp collisions at center-of-mass energy $\sqrt{s}$ = 13 TeV using the ALICE detector. Jets are reconstructed from charged particles produced in the midrapidity region (|η| < 0.9) using the sequential recombination anti-k T algorithm with jet resolution parameters R = 0.2, 0.3, and 0.4 for the trans verse momentum (p T ) interval 5–110 GeV/c. The high multiplicity events are selected by the forward V0 scintilla tor detectors. The mean charged-particle multiplicity inside the leading jet cone rises monotonically with increasing jet p T in qualitative agreement with previous measurements at lower energies. The distributions of jet fragmentation function variables z ch and ξ ch are measured for different jet-p T intervals. Jet-p T independent fragmentation of leading jets is observed for wider jets except at high- and low-z ch values. The observed “hump-backed plateau” structure in the ξ ch distribution indicates suppression of low-p T particles. In high-multiplicity events, an enhancement of the fragmen tation probability of low-z ch particles accompanied by a suppression of high-zch particles is observed compared to minimum-bias events. This behavior becomes more promi nent for low-p T jets with larger jet radius. The results are compared with predictions of QCD-inspired event generators, PYTHIA 8 with Monash 2013 tune and EPOS LHC. It is found that PYTHIA 8 qualitatively reproduces the jet modification in high-multiplicity events except at high jet p T . These measurements provide important constraints to models of jet fragmentation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A Spatially Explicit Individual-Based Modeling Approach to Evaluate the Cumulative Effects of Wind Energy Development on the Greater Sage-Grouse: Sensitivity Analysis and Validation of Key Parameters

To address the need for an approach to evaluate cumulative ecological impacts of wind energy development, particularly those on critical wildlife habitats and species, the authors developed a proof-of-concept, landscape-based, spatially explicit individual-based modeling (IBM) framework for populations of the greater sage-grouse (Centrocercus urophasianus) in Albany County, Wyoming, based on published and other available information on the life history of the species. This sage-grouse IBM estimates the spatial and temporal movements of sage-grouse based on modeled effects of habitat characteristics and developments on sage-grouse condition, survivorship, and reproduction. After completing the initial version of the model, we conducted a series of sensitivity analyses of key model parameters and validation of lek occurrences and spatial distributions to better understand performance of the model relative to observed values of important life history characteristics. The parameter sensitivity analysis was conducted as a series of one-factor-at-a-time tests in which the values of selected parameters were individually varied to evaluate the corresponding effects on model output. We examined the model’s response to changes in parameter values to gain insight into the overall robustness of the model, identify key driver parameters, and initiate qualitative validation. Five functions selected for sensitivity analyses were (1) the rate of change in body condition in relationship to habitat suitability index (HSI) of occupied habitat (condition change rate), (2) the effect of competition between individuals with overlapping home ranges expressed as a percentage reduction in HSI (competition factor), (3) value of condition at which survivorship probability is equal to zero (zero survivorship condition), (4) the relationship between female body condition and clutch size, and (5) the relationship between female body condition and nest success. We varied the parameter values to be tested for the sensitivity analysis around the original value used in the model (i.e., tested values were higher and lower than the model’s original value) to examine the effect of this variation on the predicted output of the model. Model outputs evaluated in the sensitivity analysis included (1) predicted age-class distribution (as measured by the percentage of immature individuals within the population); (2) predicted sex ratio; (3) predicted age-sex class distribution (percent of population in each of six age-sex classes, i.e., male and female juveniles, yearlings, and adults); (4) lifespan; (5) population size; and (6) spatial distribution. Of the five parameters analyzed, condition change rate, survivorship, clutch size, and nest success did not substantially affect any of the evaluated model outputs. For the predicted age-class distribution, the percentage of immature individuals predicted by the model for these four parameters ranged from 61.9% to 65.0%, which was reasonable with respect to the reference values of 51.4 to 57.8% in published studies. The ratio of females to males ranged from 1.09 to 1.14, which was comparable to the reference values of 1.2 to 3.0 presented in an existing study. The predicted mean lifespan ranged from 1.62 to 1.74 years, which appears to be reasonable with respect to the reference values of 0.9 to 1.1 years for sharp-tail grouse and greater prairie chickens presented by published studies. The predicted population size ranged from 1,877 to 3,140. This prediction would be reasonable with respect to our estimate of 5,000 yearlings and adults, which was based on the USFWS estimate for the state of Wyoming scaled to the number of leks in the county. The predicted spatial distribution was not substantially affected by the parameter values examined. In our sensitivity analyses, the only tested parameter that had a noticeable effect on model output was competition factor. Over the range of values tested for this parameter, predicted population size exhibited the largest range (from 1,833 to 4,737) of all parameters tested. As the competition factor increased, the predicted population size decreased. This reflects the effect competition had on the number of individuals that could co occur in high-quality habitat patches. Despite this apparently significant effect, the range of values appears to be reasonable with respect to our estimate of 5,000 yearlings and adults, which was based on the USFWS estimate for the state of Wyoming scaled to the number of leks in the county.

17 WIND ENERGY↗

Evolution of the Kdo2-lipid A Biosynthesis in Bacteria

BACKGROUND: Lipid A is the highly immunoreactive endotoxic center of lipopolysaccharide (LPS). It anchors the LPS into the outer membrane of most Gram-negative bacteria. Lipid A can be recognized by animal cells, triggers defense-related responses, and causes Gram-negative sepsis. The biosynthesis of Kdo2-lipid A, the LPS substructure, involves with nine enzymatic steps. RESULTS: In order to elucidate the evolutionary pathway of Kdo2-lipid A biosynthesis, we examined the distribution of genes encoding the nine enzymes across bacteria. We found that not all Gram-negative bacteria have all nine enzymes. Some Gram-negative bacteria have no genes encoding these enzymes and others have genes only for the first four enzymes (LpxA, LpxC, LpxD, and LpxB). Among the nine enzymes, five appeared to have arisen from three independent gene duplication events. Two of such events happened within the Proteobacteria lineage, followed by functional specialization of the duplicated genes and pathway optimization in these bacteria. CONCLUSIONS: The nine-enzyme pathway, which was established based on the studies mainly in Escherichia coli K12, appears to be the most derived and optimized form. It is found only in E. coli and related Proteobacteria. Simpler and probably less efficient pathways are found in other bacterial groups, with Kdo2-lipid A variants as the likely end products. The Kdo2-lipid A biosynthetic pathway exemplifies extremely plastic evolution of bacterial genomes, especially those of Proteobacteria, and how these mainly pathogenic bacteria have adapted to their environment.

59 BASIC BIOLOGICAL SCIENCES↗

Statistical analysis of non-Maxwellian electron distribution functions measured with angularly resolved Thomson scattering

Angularly resolved Thomson scattering is a novel extension of Thomson scattering, enabling the measurement of the electron velocity distribution function over many orders of magnitude. Here, details of the theoretical basis of the technique and the instrument designed for this measurement are described. Angularly resolved Thomson-scattering data from several experiments are shown with descriptions of the corresponding distribution functions. A reduced model describing the distribution function is given and used to perform a Monte Carlo analysis of the uncertainty in the measurements. The electron density and temperature were determined to a precision of 12% and 21%, respectively, on average, while all other parameters defining the distribution function were generally determined to better than 20%. It was found that these uncertainties were primarily due to limited signal to noise and instrumental effects. Furthermore, measurements with this level of precision were sufficient to distinguish between Maxwellian and non-Maxwellian distribution functions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

High-gradient performance of a prototype accelerator cavity for a 3 GeV proton radiography booster

This paper reports the design, fabrication, and results of the high-gradient conditioning and testing for a two-cell, π -mode, standing wave normal-conducting prototype booster cavity for the proposed 3 GeV proton linac upgrade at Los Alamos Neutron Science Center. Increasing the energy of proton beam from the existing 800 MeV to 3 GeV will improve resolution of the proton radiography by up to 10 times. The proposed energy boost can be achieved with a compact normal-conducting high-gradient radio-frequency (rf) linac section. The C-band section of the booster linac was designed with optimized-shaped copper accelerator cavities with distributed rf coupling. A short two-cell test prototype structure was designed for the frequency of 5.712 GHz, fabricated, and tested at the C-band Engineering Research Test Facility in New Mexico (CERF-NM) at Los Alamos National Laboratory. The maximum klystron power coupled into the test structure was 8.3 MW with 1 μ s pulse length and 100 Hz repetition rate. The breakdown probabilities were recorded as functions of the accelerating gradient and peak surface fields. Operation of the test cavity at accelerating gradients of up to 100 MV / m was demonstrated. Published by the American Physical Society 2024

43 PARTICLE ACCELERATORS↗

Selecting Critical Scenarios of DER Adoption in Distribution Grids Using Bayesian Optimization

We develop a new methodology to select scenarios of DER adoption most critical for distribution grids. Anticipating risks of future voltage and line flow violations due to additional PV adopters is central for utility investment planning but continues to rely on deterministic or ad hoc scenario selection. We propose a highly efficient search framework based on multi-objective Bayesian Optimization. We treat underlying grid stress metrics as computationally expensive black-box functions, approximated via Gaussian Process surrogates and design an acquisition function based on probability of scenarios being Pareto-critical across a collection of line- and bus-based violation objectives. Our approach provides a statistical guarantee and offers an order of magnitude speed-up relative to a conservative exhaustive search. Case studies on realistic feeders with 200-400 buses demonstrate the effectiveness and accuracy of our approach.

Mulkin, Olivier↗

Neutron Star Mergers Might Not Be the Only Source of r -process Elements in the Milky Way

Probing the origin of r -process elements in the universe represents a multidisciplinary challenge. We review the observational evidence that probes the properties of r -process sites, and address them using galactic chemical evolution simulations, binary population synthesis models, and nucleosynthesis calculations. Our motivation is to define which astrophysical sites have significantly contributed to the total mass of r -process elements present in our Galaxy. We found discrepancies with the neutron star (NS–NS) merger scenario. When we assume that they are the only site, the decreasing trend of [Eu/Fe] at [Fe/H] > -1 in the disk of the Milky Way cannot be reproduced while accounting for the delay-time distribution (DTD) of coalescence times ( ∝t -1 ) derived from short gamma-ray bursts (GRBs) and population synthesis models. Steeper DTD functions ( ∝t -1.5 ) or power laws combined with a strong burst of mergers before the onset of supernovae (SNe) Ia can reproduce the [Eu/Fe] trend, but this scenario is inconsistent with the similar fraction of short GRBs and SNe Ia occurring in early-type galaxies, and it reduces the probability of detecting GW170817 in an early-type galaxy. One solution is to assume an additional production site of Eu that would be active in the early universe, but would fade away with increasing metallicity. If this is correct, this additional site could be responsible for roughly 50% of the Eu production in the early universe before the onset of SNe Ia. Rare classes of supernovae could be this additional r -process source, but hydrodynamic simulations still need to ensure the conditions for a robust r -process pattern.

79 ASTRONOMY AND ASTROPHYSICS↗

Radiation Transport in Random Media With Large Fluctuations

Strongly heterogeneous media arise in several applications that include radiation shields, nuclear fuel, BWR moderators, clouds, planetary and stellar atmospheres, turbulent gases and plasmas. Neutral and charged particle transport computations in such media have relied heavily on formulating transport equations with spatially random coefficients (physical data) and developing solution methods to deal with the additional stochastic dimensions. Attempts at developing approximate closures that yield only low order statistical information (e.g., mean and variance of the flux) have proved to be highly restrictive under real physics conditions or rely on techniques that require fluctuation amplitudes to be small for robustness. Recently, stochastic spectral methods such as polynomial chaos and stochastic collocation have been developed for aleatoric uncertainty quantification and sensitivity analysis, and successfully applied in radiation transport work. Advances in UQ techniques have tended to focus on efficiently handling large numbers of uncertain variables but the rigorous stochastic basis of the approach also promotes its use in situations where stochasticity is due to spatial heterogeneity and the associated uncertainty is large. Here we apply these techniques to radiation transport in media with spatially randomly varying cross sections without restriction on fluctuation amplitudes. Specifically, we represent the cross sections as a lognormal spatial random process with specified mean, variance and covariance function and use a Karhunen-Loeve (KL) decomposition to generate cross section realizations that are strictly positive. Woodcock Monte Carlo (WMC) is then used to simulate transport using random sampling of cross sections and deterministic sampling based on a stochastic collocation technique. Numerical results for the mean and variance in the scalar flux and leakage currents are obtained for weak and strong random variations. We focus in this work on demonstrating the approach and defer application to specific problems to a future investigation. We have demonstrated that a combination of stochastic spectral representation and Woodcock Monte Carlo simulation allows efficient computation of radiation transport in strongly random media. The use of a lognormal distribution to represent the fluctuations in medium properties facilitates enforcement of strict positivity of cross section realizations, a condition that has challenged standard approaches that assume Gaussian fluctuations. The fact that the lognormal random process is a memoryless nonlinear transformation of a Gaussian process further enables efficient and accurate reconstruction of the random cross section realizations using a Karhunen-Loeve representation of the cross section. Finally, the robustness of this model enables fluctuations of arbitrarily large amplitude to be studied, using both random sampling Monte Carlo and more efficient stochastic collocation techniques. The present work is being extended to allow reconstruction of probability density functions of output variables using polynomial chaos representation, and to accommodate general cross section covariance functions. Also, techniques are being explored to more judiciously select ceiling cross sections to enhance the efficiency of Woodcock Monte Carlo for transport in random media. (authors)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

PRODUCTIVITY OF SOLAR FLARES AND MAGNETIC HELICITY INJECTION IN ACTIVE REGIONS

The main objective of this study is to better understand how magnetic helicity injection in an active region (AR) is related to the occurrence and intensity of solar flares. We therefore investigate the magnetic helicity injection rate and unsigned magnetic flux, as a reference. In total, 378 ARs are analyzed using SOHO/MDI magnetograms. The 24 hr averaged helicity injection rate and unsigned magnetic flux are compared with the flare index and the flare-productive probability in the next 24 hr following a measurement. In addition, we study the variation of helicity over a span of several days around the times of the 19 flares above M5.0 which occurred in selected strong flare-productive ARs. The major findings of this study are as follows: (1) for a sub-sample of 91 large ARs with unsigned magnetic fluxes in the range from (3-5) x 10{sup 22} Mx, there is a difference in the magnetic helicity injection rate between flaring ARs and non-flaring ARs by a factor of 2; (2) the GOES C-flare-productive probability as a function of helicity injection displays a sharp boundary between flare-productive ARs and flare-quiet ones; (3) the history of helicity injection before all the 19 major flares displayed a common characteristic: a significant helicity accumulation of (3-45) x 10{sup 42} Mx{sup 2} during a phase of monotonically increasing helicity over 0.5-2 days. Our results support the notion that helicity injection is important in flares, but it is not effective to use it alone for the purpose of flare forecast. It is necessary to find a way to better characterize the time history of helicity injection as well as its spatial distribution inside ARs.

79 ASTRONOMY AND ASTROPHYSICS↗

HIghMass-high H I mass, H I-rich galaxies at z ∼ 0 sample definition, optical and Hα imaging, and star formation properties

We present first results of the study of a set of exceptional H I sources identified in the 40% ALFALFA extragalactic H I survey catalog α.40 as both being H I massive (M{sub HI}>10{sup 10} M{sub ⊙}) and having high gas fractions for their stellar masses: the HIghMass galaxy sample. We analyze UV- and optical-broadband and Hα images to understand the nature of their relatively underluminous disks in optical and to test whether their high gas fractions can be tracked to higher dark matter halo spin parameters or late gas accretion. Estimates of their star formation rates (SFRs) based on spectral energy distribution fitting agree within uncertainties with the Hα luminosity inferred current massive SFRs. The H II region luminosity functions, parameterized as dN/dlog L∝L {sup α}, have standard slopes at the luminous end (α ∼ –1). The global SFRs demonstrate that the HIghMass galaxies exhibit active ongoing star formation (SF) with moderate SF efficiency but, relative to normal spirals, a lower integrated SFR in the past. Because the SF activity in these systems is spread throughout their extended disks, they have overall lower SFR surface densities and lower surface brightness in the optical bands. Relative to normal disk galaxies, the majority of HIghMass galaxies have higher Hα equivalent widths and are bluer in their outer disks, implying an inside-out disk growth scenario. Downbending double exponential disks are more frequent than upbending disks among the gas-rich galaxies, suggesting that SF thresholds exist in the downbending disks, probably as a result of concentrated gas distribution.

79 ASTRONOMY AND ASTROPHYSICS↗

Recovery time in quantum dynamics of wave packets

A wave packet formed by a linear superposition of bound states with an arbitrary energy spectrum returns arbitrarily close to the initial state after a quite long time. A method in which quantum recovery times are calculated exactly is developed. In particular, an exact analytic expression is derived for the recovery time in the limiting case of a two-level system. In the general case, the reciprocal recovery time is proportional to the Gauss distribution that depends on two parameters (mean value and variance of the return probability). The dependence of the recovery time on the mean excitation level of the system is established. The recovery time is the longest for the maximal excitation level.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗