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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

The shape of protein–polymer conjugates in dilute solution

ABSTRACT Protein–polymer conjugation can significantly affect many different aspects of protein behavior, ranging from their solution properties to their ability to form solution and bulk nanostructured materials. An underlying fundamental question is how the molecular design affects the shape of the conjugate and, consequently, its properties. This work measures the molecular configuration of model protein–polymer conjugates in dilute solution using small‐angle neutron scattering (SANS) and uses quantitative model fitting to understand the shape of the molecules. Form factor measurements of four model bioconjugates of the red fluorescent protein mCherry and the polymers poly( N ‐isopropylacrylamide), poly(hydroxypropyl acrylate), poly(oligoethylene glycol acrylate), and poly(ethylene glycol) show that these protein–polymer conjugates are well described by a recently developed scattering function for colloid–polymer conjugates that explicitly incorporates excluded volume interactions in the polymer configuration. In the regime where the protein does not exhibit strong interactions with the polymer, modeling the protein–polymer interactions using a purely repulsive Weeks–Chandler–Andersen potential also leads to a coarse‐grained depiction of the conjugate that agrees well with its scattering behavior. The coarse‐grained model can additionally be used for systems with varying protein–polymer interactions, ranging from purely repulsive to strongly attractive, which may be useful for conjugates with strong electrostatic or hydrophobic attractive interactions. © 2015 Wiley Periodicals, Inc. J. Polym. Sci., Part A: Polym. Chem. 2016, 54, 292–302

Lam, Christopher N.↗
DOE OSTI2016

Nonlinear threshold effect in the Z-scan method of characterizing limiters for high-intensity laser light

A threshold model is described which permits one to determine the properties of limiters for high-powered laser light. It takes into account the threshold characteristics of the nonlinear optical interaction between the laser beam and the limiter working material. The traditional non-threshold model is a particular case of the threshold model when the limiting threshold is zero. The nonlinear characteristics of carbon nanotubes in liquid and solid media are obtained from experimental Z-scan data. Specifically, the nonlinear threshold effect was observed for aqueous dispersions of nanotubes, but not for nanotubes in solid polymethylmethacrylate. The threshold model fits the experimental Z-scan data better than the non-threshold model. Output characteristics were obtained that integrally describe the nonlinear properties of the optical limiters.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

EVOLUTIONARY TRACKS FOR BETELGEUSE

We have constructed a series of nonrotating quasi-hydrostatic evolutionary models for the M2 Iab supergiant Betelgeuse (α Orionis). Our models are constrained by multiple observed values for the temperature, luminosity, surface composition, and mass loss for this star, along with the parallax distance and high-resolution imagery that determines its radius. We have then applied our best-fit models to analyze the observed variations in surface luminosity and the size of detected surface bright spots as the result of up-flowing convective material from regions of high temperature in the surface convective zone. We also attempt to explain the intermittently observed periodic variability in a simple radial linear adiabatic pulsation model. Based on the best fit to all observed data, we suggest a best progenitor mass estimate of 20{sub −3}{sup +5} M{sub ⊙} and a current age from the start of the zero-age main sequence of 8.0–8.5 Myr based on the observed ejected mass while on the giant branch.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Investigating the differential emission measure and energetics of microflares with combined SDO/AIA and RHESSI observations

An important question in solar physics is whether solar microflares, the smallest currently observable flare events in X-rays, possess the same energetic properties as large flares. Recent surveys have suggested that microflares may be less efficient particle accelerators than large flares, and hence contribute less non-thermal energy, which may have implications for coronal heating mechanisms. We therefore explore the energetic properties of microflares by combining EUV and X-ray measurements. We present forward-fitting differential emission measure (DEM) analysis of 10 microflares. The fitting is constrained by combining, for the first time, high-temperature Reuven Ramaty High Energy Solar Spectroscopic Imager (RHESSI) observations and flux data from the Solar Dynamics Observatory (SDO) Atmospheric Imaging Assembly (AIA). Two fitting models are tested for the DEM; a Gaussian distribution and a uniform DEM profile. A Gaussian fit proved unable to explain the observations for any of the studied microflares. However, 8 of 10 events studied were reasonably fit by a uniform DEM profile. Hence microflare plasma can be considered to be significantly multi-thermal, and may not be significantly peaked or contain resolvable fine structure, within the uncertainties of the observational instruments. The thermal and non-thermal energy is estimated for each microflare, comparing the energy budget with an isothermal plasma assumption. From the multi-thermal fits the minimum non-thermal energy content was found to average approximately 30% of the estimated thermal energy. By comparison, under an isothermal model the non-thermal and thermal energy estimates were generally comparable. Hence, multi-thermal plasma is an important consideration for solar microflares that substantially alters their thermal and non-thermal energy content.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Estimation of Fission Product Transport Parameters for Cesium in the AGR-3/4 TRISO Fuel Experiment

A one-dimensional (1D) finite-element model of fission product transport in the AGR-3/4 experiment has been developed using the Multiphysics Object Oriented Simulation Environment (MOOSE) framework and implemented in the fuel performance code, BISON. The model resolves capsule-specific geometries, materials, and temperature histories and simulates radial migration of fission products from the fuel compact through the inner ring, outer ring, and into the sink ring. Model parameters governing diffusion and sorption were estimated for key fission products – cesium (Cs), and europium (Eu) – by simultaneously fitting modeled isotopic concentration profiles and total ring inventories to a post-irradiation experimental measurement. These data include gamma scanning, liquid scintillation for Sr-90, radial deconsolidation leach-burn-leach analysis, tomographic reconstructions, and destructive physical sampling. A mortar-based interfacial sorption framework was implemented to enforce physically consistent mass transfer and flux conservation across gas gaps. Two classes of parameter sets were derived: a least-squares best-fit, and a safety-oriented conservative-fit, what applies strong penalties for underprediction of sink inventories. Across all twelve capsules, the model successfully reproduces the dominant radial transport trends for Cs, Sr, with decreasing concentrations from the compact outward through successive rings. Cs behavior is captured most consistently, while strontium predictions reveal systematic trade-offs between compact accuracy and conservative sink-ring bounding. The results demonstrate that sink ring weighted calibration provides conservative, safety relevant bounds on low temperature fission product transport, but at the cost of underpredicting compact inventories for Sr isotopes. These discrepancies highlight the need for additional physics, including fast-slow diffusion model, incorporating trapping mechanism in the transport behavior. Overall, this work establishes a robust, capsule-specific modeling framework for AGR-3/4 fission product transport and provides a defensible basis for parameter selection in source-term and fuel performance analyses for high temperature gas-cooled reactors.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Machine learning for impurity charge-state transition levels in semiconductors from elemental properties using multi-fidelity datasets

Quantifying charge-state transition energy levels of impurities in semiconductors is critical to understanding and engineering their optoelectronic properties for applications ranging from solar photovoltaics to infrared lasers. While these transition levels can be measured and calculated accurately, such efforts are time-consuming and more rapid prediction methods would be beneficial. Here, we significantly reduce the time typically required to predict impurity transition levels using multi-fidelity datasets and a machine learning approach employing features based on elemental properties and impurity positions. We use transition levels obtained from low-fidelity (i.e., local-density approximation or generalized gradient approximation) density functional theory (DFT) calculations, corrected using a recently proposed modified band alignment scheme, which well-approximates transition levels from high-fidelity DFT (i.e., hybrid HSE06). Further, the model fit to the large multi-fidelity database shows improved accuracy compared to the models trained on the more limited high-fidelity values. Crucially, in our approach, when using the multi-fidelity data, high-fidelity values are not required for model training, significantly reducing the computational cost required for training the model. Our machine learning model of transition levels has a root mean squared (mean absolute) error of 0.36 (0.27) eV vs high-fidelity hybrid functional values when averaged over 14 semiconductor systems from the II–VI and III–V families. As a guide for use on other systems, we assessed the model on simulated data to show the expected accuracy level as a function of bandgap for new materials of interest. Finally, we use the model to predict a complete space of impurity charge-state transition levels in all zinc blende III–V and II–VI systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

WHEN DID ROUND DISK GALAXIES FORM?

When and how galaxy morphology, such as the disk and bulge seen in the present-day universe, emerged is still not clear. In the universe at z ≳ 2, galaxies with various morphologies are seen, and star-forming galaxies at z ∼ 2 show the intrinsic shape of bar-like structures. Then, when did the round disk structure form? Here we take a simple and straightforward approach to see the epoch when a round disk galaxy population emerged by constraining the intrinsic shape statistically based on the apparent axial ratio distribution of galaxies. We derived the distributions of the apparent axial ratios in the rest-frame optical light (∼5000 Å) of star-forming main-sequence galaxies at 2.5 > z > 1.4, 1.4 > z > 0.85, and 0.85 > z > 0.5, and found that their apparent axial ratios show peaky distributions at z ≳ 0.85, while a rather flat distribution at the lower redshift. By using a tri-axial model (A > B > C) for the intrinsic shape, we found that the best-fit models give the peaks of the B/A distribution of 0.81 ± 0.04, 0.84 ± 0.04, and 0.92 ± 0.05 at 2.5 > z > 1.4, 1.4 > z > 0.85, and 0.85 > z > 0.5, respectively. The last value is close to the local value of 0.95. Thickness (C/A) is ∼0.25 at all the redshifts and is close to the local value (0.21). The results indicate that the shape of the star-forming galaxies in the main sequence changes gradually, and that the round disk is established at around z ∼ 0.9. The establishment of the round disk may be due to the cessation of a violent interaction between galaxies or the growth of a bulge and/or a supermassive black hole residing at the center of a galaxy that dissolves the bar structure.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Electronic Structure and Optical Properties of Cu 2 ZnGeSe 4 . First-Principles Calculations and Vacuum-Ultraviolet Spectroscopic Ellipsometric Studies

Cu 2 ZnGeSe 4 is of interest for the development of next-generation thin-film photovoltaic technologies. To understand its electronic structure and related fundamental optical properties, we perform first-principles calculations for three structural variations: kesterite, stannite, and primitive-mixed CuAu phases. The calculated data are compared with the room-temperature dielectric functionϵ=ϵ1+iϵ2 spectrum of polycrystalline Cu 2 ZnGeSe 4 determined by vacuum-ultraviolet spectroscopic ellipsometry in the photon-energy range of 0.7 to 9.0 eV. Ellipsometric data are modeled with the sum of eight Tauc-Lorentz oscillators, and the best-fit model yields the band-gap and Tauc-gap energies of 1.25 and 1.19 eV, respectively. A comparison of overall peak shapes and relative intensities between experimental spectra and the calculated ϵ data for three structural variations suggests that the sample may not have a pure (ordered) kesterite phase. We found that the complex refractive index N=n+ik, normal-incidence reflectivity R, and absorption coefficients α are calculated from the modeled ϵ spectrum, which are also compared with those of Cu 2 ZnSnSe 4 . The spectral features for Cu 2 ZnGeSe 4 appear to be weaker and broader than those for Cu 2 ZnSnSe 4 , which is possibly due to more structural imperfections presented in Cu 2 ZnGeSe 4 than Cu 2 ZnSnSe 4 .

14 SOLAR ENERGY↗
DOE OSTI2020

Measurement of atom resolvability in cryo-EM maps with Q-scores

Cryogenic electron microscopy (cryo-EM) maps are now at the point where resolvability of individual atoms can be achieved. However, resolvability is not necessarily uniform throughout the map. We introduce a quantitative parameter to characterize the resolvability of individual atoms in cryo-EM maps, the map Q-score. Q-scores can be calculated for atoms in proteins, nucleic acids, water, ligands and other solvent atoms, using models fitted to or derived from cryo-EM maps. Q-scores can also be averaged to represent larger features such as entire residues and nucleotides. Averaged over entire models, Q-scores correlate very well with the estimated resolution of cryo-EM maps for both protein and RNA. Here, assuming the models they are calculated from are well fitted to the map, Q-scores can be used as a measure of resolvability in cryo-EM maps at various scales, from entire macromolecules down to individual atoms. Q-score analysis of multiple cryo-EM maps of the same proteins derived from different laboratories confirms the reproducibility of structural features from side chains down to water and ion atoms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Deep Learning and Likelihood Approaches for Viral Phylogeography Converge on the Same Answers Whether the Inference Model Is Right or Wrong

Abstract Analysis of phylogenetic trees has become an essential tool in epidemiology. Likelihood-based methods fit models to phylogenies to draw inferences about the phylodynamics and history of viral transmission. However, these methods are often computationally expensive, which limits the complexity and realism of phylodynamic models and makes them ill-suited for informing policy decisions in real-time during rapidly developing outbreaks. Likelihood-free methods using deep learning are pushing the boundaries of inference beyond these constraints. In this paper, we extend, compare, and contrast a recently developed deep learning method for likelihood-free inference from trees. We trained multiple deep neural networks using phylogenies from simulated outbreaks that spread among 5 locations and found they achieve close to the same levels of accuracy as Bayesian inference under the true simulation model. We compared robustness to model misspecification of a trained neural network to that of a Bayesian method. We found that both models had comparable performance, converging on similar biases. We also implemented a method of uncertainty quantification called conformalized quantile regression that we demonstrate has similar patterns of sensitivity to model misspecification as Bayesian highest posterior density (HPD) and greatly overlap with HPDs, but have lower precision (more conservative). Finally, we trained and tested a neural network against phylogeographic data from a recent study of the SARS-Cov-2 pandemic in Europe and obtained similar estimates of region-specific epidemiological parameters and the location of the common ancestor in Europe. Along with being as accurate and robust as likelihood-based methods, our trained neural networks are on average over 3 orders of magnitude faster after training. Our results support the notion that neural networks can be trained with simulated data to accurately mimic the good and bad statistical properties of the likelihood functions of generative phylogenetic models.

Evolutionary Biology↗
DOE OSTI2020

Combined Neyman–Pearson chi-square: An improved approximation to the Poisson-likelihood chi-square

We describe an approximation to the widely-used Poisson-likelihood chi-square using a linear combination of Neyman’s and Pearson’s chi-squares, namely “combined Neyman–Pearson chi-square” ($X^2_{CNP}$). Through analytical derivations and toy model simulations, we show that leads to a significantly smaller bias on the best-fit model parameters compared to those using either Neyman’s or Pearson’s chi-square. When the computational cost of using the Poisson-likelihood chi-square is high, $X^2_{CNP}$ provides a good alternative given its natural connection to the covariance matrix formalism.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

Cosmological implications of baryon acoustic oscillation measurements

Here, we derive constraints on cosmological parameters and tests of dark energy models from the combination of baryon acoustic oscillation (BAO) measurements with cosmic microwave background (CMB) data and a recent reanalysis of Type Ia supernova (SN) data. Particularly, we take advantage of high-precision BAO measurements from galaxy clustering and the Lyman-α forest (LyaF) in the SDSS-III Baryon Oscillation Spectroscopic Survey (BOSS). Treating the BAO scale as an uncalibrated standard ruler, BAO data alone yield a high confidence detection of dark energy; in combination with the CMB angular acoustic scale they further imply a nearly flat universe. Adding the CMB-calibrated physical scale of the sound horizon, the combination of BAO and SN data into an “inverse distance ladder” yields a measurement of H 0 =67.3±1.1 km s -1 Mpc -1 , with 1.7% precision. This measurement assumes standard prerecombination physics but is insensitive to assumptions about dark energy or space curvature, so agreement with CMB-based estimates that assume a flat ΛCDM cosmology is an important corroboration of this minimal cosmological model. For constant dark energy (Λ), our BAO+SN+CMB combination yields matter density Ω m =0.301±0.008 and curvature Ω k =-0.003±0.003. When we allow more general forms of evolving dark energy, the BAO+SN+CMB parameter constraints are always consistent with flat ΛCDM values at ≈1σ. And while the overall χ 2 of model fits is satisfactory, the LyaF BAO measurements are in moderate (2–2.5σ) tension with model predictions. Models with early dark energy that tracks the dominant energy component at high redshift remain consistent with our expansion history constraints, and they yield a higher H 0 and lower matter clustering amplitude, improving agreement with some low redshift observations. Expansion history alone yields an upper limit on the summed mass of neutrino species, Σm ν <0.56 eV (95% confidence), improving to Σm ν <0.25 eV if we include the lensing signal in the Planck CMB power spectrum. In a flat ΛCDM model that allows extra relativistic species, our data combination yields N eff =3.43±0.26; while the LyaF BAO data prefer higher Neff when excluding galaxy BAO, the galaxy BAO alone favor N eff ≈3. Finally, when structure growth is extrapolated forward from the CMB to low redshift, standard dark energy models constrained by our data predict a level of matter clustering that is high compared to most, but not all, observational estimates.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Monte Carlo Study of Imaging Plate Response to Laser-Driven Aluminum Ion Beams

We measured the response of BAS-TR imaging plate (IP) to energetic aluminum ions up to 222 MeV, and compared it with predictions from a Monte Carlo simulation code using two different IP response models. Energetic aluminum ions were produced with an intense laser pulse, and the response was evaluated from cross-calibration between CR-39 track detector and IP energy spectrometer. For the first time, we obtained the response function of the BAS-TR IP for aluminum ions with a kinetic energy as high as 222 MeV. On close examination of the two IP response models, we confirm that the exponential model fits our experimental data better. Moreover, we find that the IP sensitivity in the exponential model is nearly constant in this energy range, suggesting that the response function can be determined even with little experimental data.

Won, Junho↗
DOE OSTI2016

ESTIMATING THE RADIUS OF THE CONVECTIVE CORE OF MAIN-SEQUENCE STARS FROM OBSERVED OSCILLATION FREQUENCIES

The determination of the size of the convective core of main-sequence stars is usually dependent on the construction of models of stars. Here we introduce a method to estimate the radius of the convective core of main-sequence stars with masses between about 1.1 and 1.5 M {sub ⊙} from observed frequencies of low-degree p -modes. A formula is proposed to achieve the estimation. The values of the radius of the convective core of four known stars are successfully estimated by the formula. The radius of the convective core of KIC 9812850 estimated by the formula is 0.140 ± 0.028 R {sub ⊙}. In order to confirm this prediction, a grid of evolutionary models was computed. The value of the convective-core radius of the best-fit model of KIC 9812850 is 0.149 R {sub ⊙}, which is in good agreement with that estimated by the formula from observed frequencies. The formula aids in understanding the interior structure of stars directly from observed frequencies. The understanding is not dependent on the construction of models.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

SUPERMASSIVE BLACK HOLES AND THEIR HOST SPHEROIDS. I. DISASSEMBLING GALAXIES

Several recent studies have performed galaxy decompositions to investigate correlations between the black hole mass and various properties of the host spheroid, but they have not converged on the same conclusions. This is because their models for the same galaxy were often significantly different and not consistent with each other in terms of fitted components. Using 3.6 μm Spitzer imagery, which is a superb tracer of the stellar mass (superior to the K band), we have performed state-of-the-art multicomponent decompositions for 66 galaxies with directly measured black hole masses. Our sample is the largest to date and, unlike previous studies, contains a large number (17) of spiral galaxies with low black hole masses. We paid careful attention to the image mosaicking, sky subtraction, and masking of contaminating sources. After a scrupulous inspection of the galaxy photometry (through isophotal analysis and unsharp masking) and—for the first time—2D kinematics, we were able to account for spheroids; large-scale, intermediate-scale, and nuclear disks; bars; rings; spiral arms; halos; extended or unresolved nuclear sources; and partially depleted cores. For each individual galaxy, we compared our best-fit model with previous studies, explained the discrepancies, and identified the optimal decomposition. Moreover, we have independently performed one-dimensional (1D) and two-dimensional (2D) decompositions and concluded that, at least when modeling large, nearby galaxies, 1D techniques have more advantages than 2D techniques. Finally, we developed a prescription to estimate the uncertainties on the 1D best-fit parameters for the 66 spheroids that takes into account systematic errors, unlike popular 2D codes that only consider statistical errors.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Implementation of Stochastic Gradient Descent in an Automated Glow Peak Identification Software for Multiple Thermoluminescent Dosimeter Types

A glow-curve analysis code was previously developed in C++ to analyze thermoluminescent dosimeter glow curves using automated peak detection while applying a first-order kinetics model. A newer version of this code was implemented to improve the automated peak detection and curve fitting models. The Stochastic Gradient Descent Algorithm was introduced to replace the prior approach of taking first and second-order derivatives for peak detection. Additionally, early stopping mechanisms were invoked to improve the previously used Levenberg-Marquardt Algorithm employed for curve fitting. The two software versions were compared through glow curve analysis of different thermoluminescent dosimeter materials and calculation of the corresponding figures of merit. Altogether improvements were shown, namely an increase in the number of peaks detected and a reduction of the mean figure of merit by approximately 46%.

137Cs↗
DOE OSTI2016

SU-D-204-05: Fitting Four NTCP Models to Treatment Outcome Data of Salivary Glands Recorded Six Months After Radiation Therapy for Head and Neck Tumors

Purpose: To estimate the radiobiological parameters of four popular NTCP models that describe the dose-response relations of salivary glands to the severity of patient reported dry mouth 6 months post chemo-radiotherapy. To identify the glands, which best correlate with the manifestation of those clinical endpoints. Finally, to evaluate the goodness-of-fit of the NTCP models. Methods: Forty-three patients were treated on a prospective multiinstitutional phase II study for oropharyngeal squamous cell carcinoma. All the patients received 60 Gy IMRT and they reported symptoms using the novel patient reported outcome version of the CTCAE. We derived the individual patient dosimetric data of the parotid and submandibular glands (SMG) as separate structures as well as combinations. The Lyman-Kutcher-Burman (LKB), Relative Seriality (RS), Logit and Relative Logit (RL) NTCP models were used to fit the patients data. The fitting of the different models was assessed through the area under the receiver operating characteristic curve (AUC) and the Odds Ratio methods. Results: The AUC values were highest for the contralateral parotid for Grade ≥ 2 (0.762 for the LKB, RS, Logit and 0.753 for the RL). For the salivary glands the AUC values were: 0.725 for the LKB, RS, Logit and 0.721 for the RL. For the contralateral SMG the AUC values were: 0.721 for LKB, 0.714 for Logit and 0.712 for RS and RL. The Odds Ratio for the contralateral parotid was 5.8 (1.3–25.5) for all the four NTCP models for the radiobiological dose threshold of 21Gy. Conclusion: It was shown that all the examined NTCP models could fit the clinical data well with very similar accuracy. The contralateral parotid gland appears to correlated best with the clinical endpoints of severe/very severe dry mouth. An EQD2Gy dose of 21Gy appears to be a safe threshold to be used as a constraint in treatment planning.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Planck 2015 results: XVIII. Background geometry and topology of the Universe

We report that maps of cosmic microwave background (CMB) temperature and polarization from the 2015 release of Planck data provide the highestquality full-sky view of the surface of last scattering available to date. This enables us to detect possible departures from a globally isotropic cosmology. We present the first searches using CMB polarization for correlations induced by a possible non-trivial topology with a fundamental domain that intersects, or nearly intersects, the last-scattering surface (at comoving distance χ rec ), both via a direct scan for matched circular patterns at the intersections and by an optimal likelihood calculation for specific topologies. We specialize to flat spaces with cubic toroidal (T3) and slab (T1) topologies, finding that explicit searches for the latter are sensitive to other topologies with antipodal symmetry. These searches yield no detection of a compact topology with a scale below the diameter of the last-scattering surface. The limits on the radius R i of the largest sphere inscribed in the fundamental domain (at log-likelihood ratio ΔlnL > -5 relative to a simply-connected flat Planck best-fit model) are: R i > 0.97 χ rec for the T3 cubic torus; and R i > 0.56 χ rec for the T1 slab. The limit for the T3 cubic torus from the matched-circles search is numerically equivalent, R i > 0.97 χ rec at 99% confidence level from polarization data alone. We also perform a Bayesian search for an anisotropic global Bianchi VII h geometry. In the non-physical setting, where the Bianchi cosmology is decoupled from the standard cosmology, Planck temperature data favour the inclusion of a Bianchi component with a Bayes factor of at least 2.3 units of log-evidence. However, the cosmological parameters that generate this pattern are in strong disagreement with those found from CMB anisotropy data alone. Fitting the induced polarization pattern for this model to the Planck data requires an amplitude of -0.10 ± 0.04 compared to the value of + 1 if the model were to be correct. In the physically motivated setting, where the Bianchi parameters are coupled and fitted simultaneously with the standard cosmological parameters, we find no evidence for a Bianchi VII h cosmology and constrain the vorticity of such models to (ω/H) 0 < 7.6 × 10 -10 (95% CL).

79 ASTRONOMY AND ASTROPHYSICS↗