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Quantitative analysis of Raman spectral parameters for carbon fibers: practical considerations and connection to mechanical properties

Although the literature on the Raman spectra of carbon fibers is vast, no consistent, robust predictive relationship between mechanical properties of carbon fibers and spectral parameters exists. This shortcoming is due to the use of numerous fitting functions to evaluate Raman spectra of carbon fibers and the inconsistencies in establishing the best fitting models in a statistically robust fashion. To address this gap, we present a comprehensive work on the Raman spectra of carbon fibers that combines a vast library of experimental data with a robust numerical analysis and a statistical evaluation of a wide range of suggested fitting models. This manuscript begins with a brief review of the commonly applied fitting models. Then, the Raman spectra of 32 commercially available polyacrylonitrile-based carbon fibers collected at excitation wavelengths 532, 633, and 785 nm are presented and the best fit for all fibers is evaluated based on several statistical criteria in conjunction with numerical calculations and physical arguments. The results suggest that high-performance fibers must be fit with at least five peaks, whereas high-tensile modulus fibers are best fit with at least six distinct peaks. Finally, we employ simultaneous fitting of the Raman spectra of specific fibers and wavelengths and demonstrate that strong correlations exist between mechanical properties and the D1 peak position and shape across the range of evaluated mechanical properties. Finally, we suggest straightforward improvements in fitting analysis procedures that can be implemented to increase coherency in the understanding of the underlying carbon fiber microstructure intuited from Raman spectroscopy.

36 MATERIALS SCIENCE↗

Planck intermediate results: LI. Features in the cosmic microwave background temperature power spectrum and shifts in cosmological parameters

We present that the six parameters of the standard ΛCDM model have best-fit values derived from the Planck temperature power spectrum that are shifted somewhat from the best-fit values derived from WMAP data. These shifts are driven by features in Planck the Planck temperature power spectrum at angular scales that had never before been measured to cosmic-variance level precision. We have investigated these shifts to determine whether they are within the range of expectation and to understand their origin in the data. Taking our parameter set to be the optical depth of the reionized intergalactic medium Τ, the baryon density ω b , the matter density ω m , the angular size of the sound horizon θ&lowast; the spectral index of the primordial power spectrum, n s , and A s e -2τ (where A s is the amplitude of the primordial power spectrum), we have examined the change in best-fit values between a WMAP-like large angular-scale data set (with multipole moment < 800 in the Planck temperature power spectrum) and an all angular-scale data set (< 2500 Planck temperature power spectrum), each with a prior on τ of 0.07 ± 0.02. We find that the shifts, in units of the 1σ expected dispersion for each parameter, are { Δτ,ΔA s e - 2τ ,Δn s ,Δω m ,Δω b ,Δθ&lowast; } = { -1.7,-2.2,1.2,-2.0,1.1,0.9 }, with a χ2 value of 8.0. We find that this χ2 value is exceeded in 15% of our simulated data sets, and that a parameter deviates by more than 2.2σ in 9% of simulated data sets, meaning that the shifts are not unusually large. Comparing &ell; < 800 instead to &ell; > 800, or splitting at a different multipole, yields similar results. We examined the &ell; < 800 model residuals in the &ell; > 800 power spectrum data and find that the features there that drive these shifts are a set of oscillations across a broad range of angular scales. Although they partly appear similar to the effects of enhanced gravitational lensing, the shifts in ΛCDM parameters that arise in response to these features correspond to model spectrum changes that are predominantly due to non-lensing effects; the only exception is Τ, which, at fixed A s e -2τ , affects the &ell; > 800 temperature power spectrum solely through the associated change in A s and the impact of that on the lensing potential power spectrum. We also ask, "what is it about the power spectrum at &ell; < 800 that leads to somewhat different best-fit parameters than come from the full range?" We find that if we discard the data at &ell; < 30, where there is a roughly 2σ downward fluctuation in power relative to the model that best fits the full range, the &ell; < 800 best-fit parameters shift significantly towards the &ell; < 2500 best-fit parameters. In contrast, including &ell; < 30, this previously noted "low-deficit" drives n s up and impacts parameters correlated with n s , such as ω m and H 0 . As expected, the &ell; < 30 data have a much greater impact on the &ell; < 800 best fit than on the &ell; < 2500 best fit. So although the shifts are not very significant, we find that they can be understood through the combined effects of an oscillatory-like set of high-residuals and the deficit in low-power, excursions consistent with sample variance that happen to map onto changes in cosmological parameters. Finally, we examine agreement between PlanckTT data and two other CMB data sets, namely the Planck lensing reconstruction and the TT power spectrum measured by the South Pole Telescope, again finding a lack of convincing evidence of any significant deviations in parameters, suggesting that current CMB data sets give an internally consistent picture of the ΛCDM model.

79 ASTRONOMY AND ASTROPHYSICS↗

Communication: A benchmark-quality, full-dimensional ab initio potential energy surface for Ar-HOCO

A full-dimensional, global ab initio potential energy surface (PES) for the Ar-HOCO system is presented. The PES consists of a previous intramolecular ab initio PES for HOCO [J. Li, C. Xie, J. Ma, Y. Wang, R. Dawes, D. Xie, J. M. Bowman, and H. Guo, J. Phys. Chem. A 116, 5057 (2012)], plus a new permutationally invariant interaction potential based on fitting 12 432 UCCSD(T)-F12a/aVDZ counterpoise-corrected energies. The latter has a total rms fitting error of about 25 cm{sup −1} for fitted interaction energies up to roughly 12 000 cm{sup −1}. Two additional fits are presented. One is a novel very compact permutational invariant representation, which contains terms only involving the Ar-atom distances. The rms fitting error for this fit is 193 cm{sup −1}. The other fit is the widely used pairwise one. The pairwise fit to the entire data set has an rms fitting error of 427 cm{sup −1}. All of these potentials are used in preliminary classical trajectory calculations of energy transfer with a focus on comparisons with the results using the benchmark potential.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Generating mock galaxy catalogues for flux-limited samples like the DESI Bright Galaxy Survey

ABSTRACT Accurate mock galaxy catalogues are crucial to validate analysis pipelines used to constrain dark energy models. We present a fast HOD-fitting method which we apply to the AbacusSummit simulations to create a set of mock catalogues for the DESI Bright Galaxy Survey, which contain r-band magnitudes and $(g-r)$ colours. The halo tabulation method fits HODs for different absolute magnitude threshold samples simultaneously, preventing unphysical HOD crossing between samples. We validate the HOD fitting procedure by fitting to real-space clustering measurements and galaxy number densities from the MXXL BGS mock, which was tuned to the SDSS and GAMA surveys. The best-fitting clustering measurements and number densities are mostly within the assumed errors, but the clustering for the faint samples is low on large scales. The best-fitting HOD parameters are robust when fitting to simulations with different realizations of the initial conditions. When varying the cosmology, trends are seen as a function of each cosmological parameter. We use the best-fitting HOD parameters to create cubic box and cut sky mocks from the AbacusSummit simulations, in a range of cosmologies. As an illustration, we compare the ${}^{0.1}M_r\lt -20$ sample of galaxies in the mock with BGS measurements from the DESI one-percent survey. We find good agreement in the number densities, and the projected correlation function is reasonable, with differences that can be improved in the future by fitting directly to BGS clustering measurements. The cubic box and cut-sky mocks in different cosmologies are made publicly available.

79 ASTRONOMY AND ASTROPHYSICS↗

SU-F-BRD-16: Relative Biological Effectiveness of Double-Strand Break Induction for Modeling Cell Survival in Pristine Proton Beams of Different Dose-Averaged Linear Energy Transfers

Purpose: High throughput in vitro experiments assessing cell survival following proton radiation indicate that both the alpha and the beta parameters of the linear quadratic model increase with increasing proton linear energy transfer (LET). We investigated the relative biological effectiveness (RBE) of double-strand break (DSB) induction as a means of explaining the experimental results. Methods: Experiments were performed with two lung cancer cell lines and a range of proton LET values (0.94 – 19.4 keV/µm) using an experimental apparatus designed to irradiate cells in a 96 well plate such that each column encounters protons of different dose-averaged LET (LETd). Traditional linear quadratic survival curve fitting was performed, and alpha, beta, and RBE values obtained. Survival curves were also fit with a model incorporating RBE of DSB induction as the sole fit parameter. Fitted values of the RBE of DSB induction were then compared to values obtained using Monte Carlo Damage Simulation (MCDS) software and energy spectra calculated with Geant4. Other parameters including alpha, beta, and number of DSBs were compared to those obtained from traditional fitting. Results: Survival curve fitting with RBE of DSB induction yielded alpha and beta parameters that increase with proton LETd, which follows from the standard method of fitting; however, relying on a single fit parameter provided more consistent trends. The fitted values of RBE of DSB induction increased beyond what is predicted from MCDS data above proton LETd of approximately 10 keV/µm. Conclusion: In order to accurately model in vitro proton irradiation experiments performed with high throughput methods, the RBE of DSB induction must increase more rapidly than predicted by MCDS above LETd of 10 keV/µm. This can be explained by considering the increased complexity of DSBs or the nature of intra-track pairwise DSB interactions in this range of LETd values. NIH Grant 2U19CA021239-35.

60 APPLIED LIFE SCIENCES↗

Simulations of deep galaxy fields. 1: Monte Carlo simulations of optical and near-infrared counts

Monte Carlo simulations of three-dimensional galaxy distributions are performed, following the 1988 prescription of Chokshi & Wright, to study the photometric properties of evolving galaxy populations in the optical and near-infrared bands to high redshifts. In this paper, the first of a series, we present our baseline model in which galaxy numbers are conserved, and in which no explicit 'starburst' population is included. We use the model in an attempt to simultaneously fit published blue and near-infrared photometric and spectroscopic observations of deep fields. We find that our baseline models, with a formation redshift, z(sub f), of 1000, and H(sub 0) = 50, are able to reproduce the blue counts to b(sub j) = 22, independent of the value of Omega(sub 0), and also to provide a satisfactory fit to the observed blue-band redshift distributions, but for no value of Omega(sub 0) do we achieve an acceptable fit to the fainter blue counts. In the K band, we fit the number counts to the limit of the present-day surveys only for an Omega(sub 0) = 0 cosmology. We investigate the effect on the model fits of varying the cosmological parameters H(sub 0), the formation red-shift z(sub f), and the local luminosity function. Changing H(sub 0) does not improve the fits to the observations. However, reducing the epoch of a galaxy formation used in our simulations has a substantial effect. In particular, a model with z(sub f) approximately equal to 5 in a low Omega(sub 0) universe improves the fit to the faintest photometric blue data without any need to invoke a new population of galaxies, substantial merging, or a significant starburst galaxy population. For an Omega(sub 0) = 1 universe, however, reducing z(sub f) is less successful at fitting the blue-band counts and has little effect at all at K. Varying the parameters of the local luminosity function can also have a significant effect. In particular the steep low end slope of the local luminosity function of Franceschini et al. allows an acceptable fit to the b(sub j) less than or equal to 25 counts for Omega(sub 0) = 1, but is incompatible with Omega(sub 0) = 0.

Chokshi, Arati↗

Model Evaluation of Methods for Estimating Surface Emissions and Chemical Lifetimes from Satellite Data

Column densities from satellite retrievals can provide valuable information for estimating emissions and chemical lifetimes objectively across the globe. To better understand the uncertainties associated with these estimates, we test four methods using simulated column densities from a point source: a box model approach, a 2D Gaussian fit, an Inverse Radius fit and an Exponentially-Modified Gaussian fit. The model results were simulated using the WRF and CAMx models for the year 2005, for a single point source outside Atlanta in Georgia, USA with specified emissions and three chemical scenarios: no chemical reactions, 12 h chemical lifetime and 1 h chemical lifetime. No other sources were included in the simulations. We find that the box model provides reliable estimates irrespective of plume speed and plume direction, if the plume speed and the chemical lifetime are known accurately. The 2D Gaussian fit was found to be sensitive to plume speed and direction, and requires omnidirectional dispersion in order to have a decent fit. However, the 2D Gaussian fit is only an approximate fit to the data, and the discrepancies mean that the results are dependent on the geographical domain used for the optimization. An Inverse Radius fit is introduced to correct this issue, which is found to provide improved emissions and lifetime estimates. The Exponentially-Modified Gaussian fit also gave improved estimates. It is however dependent on accurate plume rotation such that reported chemical lifetimes with this method could be significantly underestimated.

Emission inventory↗

Modelling the Impact of Fractionation on Late Urinary Toxicity After Postprostatectomy Radiation Therapy

Purpose: To fit urinary toxicity data of patients treated with postprostatectomy radiation therapy with the linear quadratic (LQ) model with/without introducing a time factor. Methods and Materials: Between 1993 and 2010, 1176 patients were treated with conventional fractionation (1.8 Gy per fraction, median 70.2 Gy, n=929) or hypofractionation (2.35-2.90 Gy per fraction, n=247). Data referred to 2004-2010 (when all schemes were in use, n=563; conventional fractionation: 316; hypofractionation: 247) were fitted as a logit function of biological equivalent dose (BED), according to the LQ model with/without including a time factor γ (fixing α/β = 5 Gy). The 3-year risks of severe urethral stenosis, incontinence, and hematuria were considered as endpoints. Best-fit parameters were derived, and the resulting BEDs were taken in multivariable backward logistic models, including relevant clinical variables, considering the whole population. Results: The 3-year incidences of severe stenosis, incontinence, and hematuria were, respectively, 6.6%, 4.8%, and 3.3% in the group treated in 2004-2010. The best-fitted α/β values were 0.81 Gy and 0.74 Gy for incontinence and hematuria, respectively, with the classic LQ formula. When fixing α/β = 5 Gy, best-fit values for γ were, respectively, 0.66 Gy/d and 0.85 Gy/d. Sensitivity analyses showed reasonable values for γ (0.6-1.0 Gy/d), with comparable goodness of fit for α/β values between 3.5 and 6.5 Gy. Likelihood ratio tests showed that the fits with/without including γ were equivalent. The resulting multivariable backward logistic models in the whole population included BED, pT4, and use of antihypertensives (area under the curve [AUC] = 0.72) for incontinence and BED, pT4, and year of surgery (AUC = 0.80) for hematuria. Stenosis data could not be fitted: a 4-variable model including only clinical factors (acute urinary toxicity, pT4, year of surgery, and use of antihypertensives) was suggested (AUC = 0.73). Conclusions: The unexpected impact of moderate hypofractionation on severe incontinence and hematuria after postprostatectomy radiation therapy may be explained by a bladder α/β value <1 Gy or, radiobiologically more plausible, by introducing a time factor likely to represent a previously hypothesized consequential component of late effect.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Pressure effects on the relaxation of an excited nitromethane molecule in an argon bath

Classical molecular dynamics simulations were performed to study the relaxation of nitromethane in an Ar bath (of 1000 atoms) at 300 K and pressures 10, 50, 75, 100, 125, 150, 300, and 400 atm. The molecule was instantaneously excited by statistically distributing 50 kcal/mol among the internal degrees of freedom. At each pressure, 1000 trajectories were integrated for 1000 ps, except for 10 atm, for which the integration time was 5000 ps. The computed ensemble-averaged rotational energy decay is ∼100 times faster than the vibrational energy decay. Both rotational and vibrational decay curves can be satisfactorily fit with the Lendvay-Schatz function, which involves two parameters: one for the initial rate and one for the curvature of the decay curve. The decay curves for all pressures exhibit positive curvature implying the rate slows as the molecule loses energy. The initial rotational relaxation rate is directly proportional to density over the interval of simulated densities, but the initial vibrational relaxation rate decreases with increasing density relative to the extrapolation of the limiting low-pressure proportionality to density. The initial vibrational relaxation rate and curvature are fit as functions of density. For the initial vibrational relaxation rate, the functional form of the fit arises from a combinatorial model for the frequency of nitromethane “simultaneously” colliding with multiple Ar atoms. Roll-off of the initial rate from its low-density extrapolation occurs because the cross section for collision events with L Ar atoms increases with L more slowly than L times the cross section for collision events with one Ar atom. The resulting density-dependent functions of the initial rate and curvature represent, reasonably well, all the vibrational decay curves except at the lowest density for which the functions overestimate the rate of decay. The decay over all gas phase densities is predicted by extrapolating the fits to condensed-phase densities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Consistent and reproducible computation of the glass transition temperature from molecular dynamics simulations

In many fields, from semiconductors for opto-electronic applications to ionic liquids (ILs) for separations, the glass transition temperature (Tg) of a material is a useful gauge for its potential use in practical settings. As a result, there is a great deal of interest in predicting Tg using molecular simulations. However, the uncertainty and variation in the trend shift method, a common approach in simulations to predict Tg, can be high. This is due to the need for human intervention in defining a fitting range for linear fits of density with temperature assumed for the liquid and glass phases across the simulated cooling. The definition of such fitting ranges then defines the estimate for the Tg as the intersection of linear fits. We eliminate this need for human intervention by leveraging the Shapiro–Wilk normality test and proposing an algorithm to define the fitting ranges and, consequently, Tg. Through this integration, we incorporate into our automated methodology that residuals must be normally distributed around zero for any fit, a requirement that must be met for any regression problem. Consequently, fitting ranges for realizing linear fits for each phase are statistically defined rather than visually inferred, obtaining an estimate for Tg without any human intervention. The method is also capable of finding multiple linear regimes across density vs temperature curves. We compare the predictions of our proposed method across multiple IL and semiconductor molecular dynamics simulation results from the literature and compare other proposed methods for automatically detecting Tg from density–temperature data. We believe that our proposed method would allow for more consistent predictions of Tg. We make this methodology available and open source through GitHub.

Chemistry↗

Bayesian investigation of isochrone consistency using the old open cluster NGC 188

This paper provides a detailed comparison of the differences in parameters derived for a star cluster from its color–magnitude diagrams (CMDs) depending on the filters and models used. We examine the consistency and reliability of fitting three widely used stellar evolution models to 15 combinations of optical and near-IR photometry for the old open cluster NGC 188. The optical filter response curves match those of theoretical systems and are thus not the source of fit inconsistencies. NGC 188 is ideally suited to this study thanks to a wide variety of high-quality photometry and available proper motions and radial velocities that enable us to remove non-cluster members and many binaries. Our Bayesian fitting technique yields inferred values of age, metallicity, distance modulus, and absorption as a function of the photometric band combinations and stellar models. We show that the historically favored three-band combinations of UBV and VRI can be meaningfully inconsistent with each other and with longer baseline data sets such as UBVRIJHK{sub S}. Differences among model sets can also be substantial. For instance, fitting Yi et al. (2001) and Dotter et al. (2008) models to UBVRIJHK{sub S} photometry for NGC 188 yields the following cluster parameters: age = (5.78 ± 0.03, 6.45 ± 0.04) Gyr, [Fe/H] = (+0.125 ± 0.003, −0.077 ± 0.003) dex, (m−M){sub V} = (11.441 ± 0.007, 11.525 ± 0.005) mag, and A{sub V} = (0.162 ± 0.003, 0.236 ± 0.003) mag, respectively. Within the formal fitting errors, these two fits are substantially and statistically different. Such differences among fits using different filters and models are a cautionary tale regarding our current ability to fit star cluster CMDs. Additional modeling of this kind, with more models and star clusters, and future Gaia parallaxes are critical for isolating and quantifying the most relevant uncertainties in stellar evolutionary models.

79 ASTRONOMY AND ASTROPHYSICS↗

NuSTAR unveils a Compton-thick type 2 quasar in MrK 34

We present Nuclear Spectroscopic Telescope Array (NuSTAR) 3-40 keV observations of the optically selected Type 2 quasar (QSO2) SDSS J1034+6001 or Mrk 34. The high-quality hard X-ray spectrum and archival XMM-Newton data can be fitted self-consistently with a reflection-dominated continuum and a strong Fe Kα fluorescence line with equivalent width >1 keV. Prior X-ray spectral fitting below 10 keV showed the source to be consistent with being obscured by Compton-thin column densities of gas along the line of sight, despite evidence for much higher columns from multiwavelength data. NuSTAR now enables a direct measurement of this column and shows that N {sub H} lies in the Compton-thick (CT) regime. The new data also show a high intrinsic 2-10 keV luminosity of L {sub 2-10} ∼ 10{sup 44} erg s{sup –1}, in contrast to previous low-energy X-ray measurements where L {sub 2-10} ≲ 10{sup 43} erg s{sup –1} (i.e., X-ray selection below 10 keV does not pick up this source as an intrinsically luminous obscured quasar). Both the obscuring column and the intrinsic power are about an order of magnitude (or more) larger than inferred from pre-NuSTAR X-ray spectral fitting. Mrk 34 is thus a 'gold standard' CT QSO2 and is the nearest non-merging system in this class, in contrast to the other local CT quasar NGC 6240, which is currently undergoing a major merger coupled with strong star formation. For typical X-ray bolometric correction factors, the accretion luminosity of Mrk 34 is high enough to potentially power the total infrared luminosity. X-ray spectral fitting also shows that thermal emission related to star formation is unlikely to drive the observed bright soft component below ∼3 keV, favoring photoionization instead.

79 ASTRONOMY AND ASTROPHYSICS↗

Testing MONDian dark matter with galactic rotation curves

MONDian dark matter (MDM) is a new form of dark matter quantum that naturally accounts for Milgrom's scaling, usually associated with modified Newtonian dynamics (MOND), and theoretically behaves like cold dark matter (CDM) at cluster and cosmic scales. In this paper, we provide the first observational test of MDM by fitting rotation curves to a sample of 30 local spiral galaxies (z ≈ 0.003). For comparison, we also fit the galactic rotation curves using MOND and CDM. We find that all three models fit the data well. The rotation curves predicted by MDM and MOND are virtually indistinguishable over the range of observed radii (∼1 to 30 kpc). The best-fit MDM and CDM density profiles are compared. We also compare with MDM the dark matter density profiles arising from MOND if Milgrom's formula is interpreted as Newtonian gravity with an extra source term instead of as a modification of inertia. We find that discrepancies between MDM and MOND will occur near the center of a typical spiral galaxy. In these regions, instead of continuing to rise sharply, the MDM mass density turns over and drops as we approach the center of the galaxy. Our results show that MDM, which restricts the nature of the dark matter quantum by accounting for Milgrom's scaling, accurately reproduces observed rotation curves.

79 ASTRONOMY AND ASTROPHYSICS↗

SIMULTANEOUS ESTIMATION OF PHOTOMETRIC REDSHIFTS AND SED PARAMETERS: IMPROVED TECHNIQUES AND A REALISTIC ERROR BUDGET

We seek to improve the accuracy of joint galaxy photometric redshift estimation and spectral energy distribution (SED) fitting. By simulating different sources of uncorrected systematic errors, we demonstrate that if the uncertainties in the photometric redshifts are estimated correctly, so are those on the other SED fitting parameters, such as stellar mass, stellar age, and dust reddening. Furthermore, we find that if the redshift uncertainties are over(under)-estimated, the uncertainties in SED parameters tend to be over(under)-estimated by similar amounts. These results hold even in the presence of severe systematics and provide, for the first time, a mechanism to validate the uncertainties on these parameters via comparison with spectroscopic redshifts. We propose a new technique (annealing) to re-calibrate the joint uncertainties in the photo-z and SED fitting parameters without compromising the performance of the SED fitting + photo-z estimation. This procedure provides a consistent estimation of the multi-dimensional probability distribution function in SED fitting + z parameter space, including all correlations. While the performance of joint SED fitting and photo-z estimation might be hindered by template incompleteness, we demonstrate that the latter is “flagged” by a large fraction of outliers in redshift, and that significant improvements can be achieved by using flexible stellar populations synthesis models and more realistic star formation histories. In all cases, we find that the median stellar age is better recovered than the time elapsed from the onset of star formation. Finally, we show that using a photometric redshift code such as EAZY to obtain redshift probability distributions that are then used as priors for SED fitting codes leads to only a modest bias in the SED fitting parameters and is thus a viable alternative to the simultaneous estimation of SED parameters and photometric redshifts.

79 ASTRONOMY AND ASTROPHYSICS↗

Measurements of E-mode polarization and temperature-E-MODE correlation in the cosmic microwave background from 100 square degrees of SPTPOL data

We present measurements of E-mode polarization and temperature-E-mode correlation in the cosmic microwave background using data from the first season of observations with SPTpol, the polarization-sensitive receiver currently installed on the South Pole Telescope (SPT). The observations used in this work cover 100 deg{sup 2} of sky with arcminute resolution at 150 GHz. We report the E-mode angular auto-power spectrum (EE) and the temperature-E-mode angular cross-power spectrum (TE) over the multipole range 500 < ℓ ≤ 5000. These power spectra improve on previous measurements in the high-ℓ (small-scale) regime. We fit the combination of the SPTpol power spectra, data from Planck, and previous SPT measurements with a six-parameter ΛCDM cosmological model. We find that the best-fit parameters are consistent with previous results. The improvement in high-ℓ sensitivity over previous measurements leads to a significant improvement in the limit on polarized point-source power: after masking sources brighter than 50 mJy in unpolarized flux at 150 GHz, we find a 95% confidence upper limit on unclustered point-source power in the EE spectrum of D{sub ℓ}=ℓ(ℓ+1)C{sub ℓ}/2π<0.40 μK{sup 2} at ℓ=3000, indicating that future EE measurements will not be limited by power from unclustered point sources in the multipole range ℓ<3600, and possibly much higher in ℓ.

79 ASTRONOMY AND ASTROPHYSICS↗

Dependency of EBT2 film calibration curve on postirradiation time

Purpose: The Ashland Inc. product EBT2 film model is a widely used quality assurance tool, especially for verification of 2-dimensional dose distributions. In general, the calibration film and the dose measurement film are irradiated, scanned, and calibrated at the same postirradiation time (PIT), 1-2 days after the films are irradiated. However, for a busy clinic or in some special situations, the PIT for the dose measurement film may be different from that of the calibration film. In this case, the measured dose will be incorrect. This paper proposed a film calibration method that includes the effect of PIT. Methods: The dose versus film optical density was fitted to a power function with three parameters. One of these parameters was PIT dependent, while the other two were found to be almost constant with a standard deviation of the mean less than 4%. The PIT-dependent parameter was fitted to another power function of PIT. The EBT2 film model was calibrated using the PDD method with 14 different PITs ranging from 1 h to 2 months. Ten of the fourteen PITs were used for finding the fitting parameters, and the other four were used for testing the model. Results: The verification test shows that the differences between the delivered doses and the film doses calculated with this modeling were mainly within 2% for delivered doses above 60 cGy, and the total uncertainties were generally under 5%. The errors and total uncertainties of film dose calculation were independent of the PIT using the proposed calibration procedure. However, the fitting uncertainty increased with decreasing dose or PIT, but stayed below 1.3% for this study. Conclusions: The EBT2 film dose can be modeled as a function of PIT. For the ease of routine calibration, five PITs were suggested to be used. It is recommended that two PITs be located in the fast developing period (1∼6 h), one in 1 ∼ 2 days, one around a week, and one around a month.

61 RADIATION PROTECTION AND DOSIMETRY↗

Auto-BLAST (AutoBLAST) [SWR-20-93]

Battery life modeling often involves a lot of manual parameter fitting and is not easy for users to adopt the model and use it. To reduce the difficulties for users to adopt battery lifetime models, an automatic battery lifetime modeling analysis and simulation tool suite, Auto-BLAST, has been developed. Auto-BLAST includes a lithium-loss-base life model, a battery electric model, and an algorithm which automatically fits all key parameters in the electric and life models using user provided data. The models and algorithm are packaged into two user-friendly GUIs, Auto-LifeMod, for easy battery life prognostic model fitting and Auto-LifeSim, for easy battery lifetime simulation. The lithium-loss-based life model adopts a similar model framework that models degradations using aging rate models, using battery cycling data to predict battery degradation and expected lifetime. The electric model is an equivalent circuit model which simulates battery voltage responses based on current/power demand profiles. The auto-fitting algorithm uses the user-input data to generate custom battery life model(s). Two GUIs, wrapping around the life model and the auto-fitting algorithm, provide friendly interfaces for users to generate a life model and use it for case study. One GUI requires summary data from accelerated battery life degradation tests as an input and produces battery life models predicting (a) capacity degradation, and (b) resistance growth of the battery. The GUI displays the electrical model response and the input experimental data against the life model predictions with fitted model parameters and fitting error. The GUI also generates an output file to save the fitted model parameters. The second GUI uses the life model from the first GUI and a user-defined battery cycling profile to predict battery lifetime degradation and expected lifetime. Predicted capacity and resistance vs. time are plotted in the GUI and saved to output file. There is a user guide for both GUIs

Mishra, Partha↗

Correcting Type Ia Supernova Distances for Selection Biases and Contamination in Photometrically Identified Samples

We present a new technique to create a bin-averaged Hubble diagram (HD) from photometrically identified SN Ia data. The resulting HD is corrected for selection biases and contamination from core-collapse (CC) SNe, and can be used to infer cosmological parameters. This method, called “BEAMS with Bias Corrections” (BBC), includes two fitting stages. The first BBC fitting stage uses a posterior distribution that includes multiple SN likelihoods, a Monte Carlo simulation to bias-correct the fitted SALT-II parameters, and CC probabilities determined from a machine-learning technique. The BBC fit determines (1) a bin-averaged HD (average distance versus redshift), and (2) the nuisance parameters α and β, which multiply the stretch and color (respectively) to standardize the SN brightness. In the second stage, the bin-averaged HD is fit to a cosmological model where priors can be imposed. We perform high-precision tests of the BBC method by simulating large (150,000 event) data samples corresponding to the Dark Energy Survey Supernova Program. Our tests include three models of intrinsic scatter, each with two different CC rates. In the BBC fit, the SALT-II nuisance parameters α and β are recovered to within 1% of their true values. In the cosmology fit, we determine the dark energy equation of state parameter w using a fixed value of Ω{sub M} as a prior: averaging over all six tests based on 6 × 150,000 = 900,000 SNe, there is a small w-bias of 0.006±0.002. Finally, the BBC fitting code is publicly available in the SNANA package.

79 ASTRONOMY AND ASTROPHYSICS↗