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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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At least 91 records · Page 5
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DOE OSTI2022

Measuring differential flow angle fluctuations in relativistic nuclear collisions

Recently studies of the differential nature of the flow angle fluctuations, known as event plane angular decorrelation, indicated that measurements that assume a common symmetry plane may need to consider the flow angle fluctuations effect. Using the HIJING and AMPT models, it is shown that the flow angle fluctuations measurements, obtained with the two- and three-subevents correlation method, could have significant nonflow effects associated with long- and short-range nonflow correlations. The current study demonstrates the four-subevents cumulant methods' ability to reduce the nonflow effects. Finally, it is further argued that the measurements using the four-subevents correlation method can be used to provide accurate quantification of the differential flow angle fluctuations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

3D structure of anisotropic flow in small collision systems at energies available at the BNL Relativistic Heavy Ion Collider

Here, we present (3 + 1)-dimensional [(3 + 1)D] dynamical simulations of asymmetric nuclear collisions at the BNL Relativistic Heavy Ion Collider (RHIC). Employing a dynamical initial state model coupled to (3 + 1)D viscous relativistic hydrodynamics, we explore the rapidity dependence of anisotropic flow in the RHIC small system scan at 200 GeV center-of-mass energy. We calibrate parameters to describe central 3 He + Au collisions and make extrapolations to d + Au and p + Au collisions. Our calculations demonstrate that approximately 50% of the v 3 (p T ) difference between the measurements by the STAR and PHENIX Collaborations can be explained by the use of reference flow vectors from different rapidity regions. This emphasizes the importance of longitudinal flow decorrelation for anisotropic flow measurements in asymmetric nuclear collisions, and the need for (3 + 1)D simulations. We also present results for the beam energy dependence of particle spectra and anisotropic flow in d + Au collisions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Measurement of directed flow in Au + Au collisions at $\sqrt{s{NN}}$ = 19.6 and 27 GeV with the STAR event plane detector

In heavy-ion collision experiments, the global collectivity of final-state particles can be quantified by anisotropic flow coefficients (𝑣 𝑛 ) . The first-order flow coefficient, also referred to as the directed flow (𝑣 1 ), describes the collective sideward motion of produced particles and nuclear fragments in heavy-ion collisions. It carries information on the very early stage of the collision, especially at large pseudorapidity (𝜂), where it is believed to be generated during the nuclear passage time. Directed flow therefore probes the onset of bulk collective dynamics during thermalization, providing valuable experimental guidance to models of the pre-equilibrium stage. In 2018, the Event Plane Detector (EPD) was installed in STAR and used for the Beam Energy Scan phase-II (BES-II) data taking. The combination of EPD (2.1 < |𝜂| < 5.1) and high-statistics BES-II data enables us to extend the 𝑣 1 measurement to the forward and backward 𝜂 regions. In this paper, we present the measurement of 𝑣 1 over a wide 𝜂 range in Au + Au collisions at $\sqrt{s_{NN}}$ = 19.6 and 27 GeV using the STAR EPD. The results of the analysis at $\sqrt{s_{NN}}$ = 19.6 GeV exhibit excellent consistency with the previous PHOBOS measurement, while elevating the precision of the overall measurement. The increased precision of the measurement also revealed finer structures in heavy-ion collisions, including a potential observation of the first-order event-plane decorrelation. Multiple physics models were compared to the experimental results. Only a transport model and a three-fluid hybrid model can reproduce a sizable 𝑣 1 at large 𝜂 as was observed experimentally. The model comparison also indicates 𝑣 1 at large 𝜂 might be sensitive to the QGP phase transition.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Online-compatible unsupervised nonresonant anomaly detection

There is a growing need for anomaly detection methods that can broaden the search for new particles in a model-agnostic manner. Most proposals for new methods focus exclusively on signal sensitivity. However, it is not enough to select anomalous events—there must also be a strategy to provide context to the selected events. In this work, we propose the first complete strategy for unsupervised detection of nonresonant anomalies that includes both signal sensitivity and a data-driven method for background estimation. Our technique is built out of two simultaneously trained autoencoders that are forced to be decorrelated from each other. This method can be deployed off-line for nonresonant anomaly detection and is also the first complete on-line-compatible anomaly detection strategy. We show that our method achieves excellent performance on a variety of signals prepared for the ADC2021 data challenge.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Paradigm for global gyrokinetic turbulence

Using a novel wave-number-advection algorithm, we describe a method to add global profile curvature terms to the local gyrokinetic equations. This approach enables a high-precision global simulation capability without sacrificing the efficiency and spectral accuracy of local simulations. Preliminary numerical results suggest that there are two distinct types of global correction to the local result: (1) a trivial shift of the local result in radius, (2) a non-trivial decorrelation that is roughly equivalent to the well-known E×B shear effect. This interpretation provides a new, intuitive framework for understanding global gyrokinetic simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Collectivity in Ultraperipheral Pb+Pb Collisions at the Large Hadron Collider

In this work, we present the first full (3+1)D dynamical simulations of ultraperipheral Pb+Pb collisions at the Large Hadron Collider. Extrapolating from p + Pb collisions, we explore whether a quasireal photon γ* interacting with the lead nucleus in an ultraperipheral collision can create a many-body system exhibiting fluid behavior. Assuming strong final-state interactions, we provide model results for charged hadron multiplicity, identified particle mean transverse momenta, and charged hadron anisotropic flow coefficients, and compare them with experimental data from the ALICE and ATLAS Collaborations. The elliptic flow hierarchy between p + Pb and γ*+Pb collisions is dominated by the difference in longitudinal flow decorrelations and reproduces the experimental data well. We have demonstrated that our theoretical framework provides a quantitative tool to study particle production and collectivity for all system sizes, ranging from central heavy-ion collisions to small asymmetric collision systems at the Relativistic Heavy-Ion Collider and the Large Hadron Collider and even at the future Electron-Ion Collider.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Direct measurement of Stokes–Einstein diffusion of Cowpea mosaic virus with 19 µs-resolved XPCS

Brownian motion of Cowpea mosaic virus (CPMV) in water was measured using small-angle X-ray photon correlation spectroscopy (SA-XPCS) at 19.2 µs time resolution. It was found that the decorrelation time τ(Q) = 1/DQ 2 up to Q = 0.091 nm -1 . The hydrodynamic radius R H determined from XPCS using Stokes–Einstein diffusion D = kT/(6πηR H ) is 43% larger than the geometric radius R 0 determined from SAXS in the 0.007 M K 3 PO 4 buffer solution, whereas it is 80% larger for CPMV in 0.5 M NaCl and 104% larger in 0.5 M (NH 4 ) 2 SO 4 , a possible effect of aggregation as well as slight variation of the structures of the capsid resulting from the salt–protein interactions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Time series methods for the analysis of soundscapes and other cyclical ecological data

Biodiversity monitoring has entered an era of ‘big data’, exemplified by a near-continuous collection of sounds, images, chemical and other signals from organisms in diverse ecosystems. Such data streams have the potential to help identify new threats, assess the effectiveness of conservation interventions, as well as generate new ecological insights. However, appropriate analytical methods are often still missing, particularly with respect to characterizing cyclical temporal patterns. Here, we present a framework for characterizing and analysing ecological responses that represent nonstationary, complex temporal patterns and demonstrate the value of using Fourier transforms to decorrelate continuous data points. In our example, we use a framework based on three approaches (spectral analysis, magnitude squared coherence, and principal component analysis) to characterize differences in tropical forest soundscapes within and across sites and seasons in Gabon. By reconstructing the underlying, cyclic behaviour of the soundscape for each site, we show how one can identify circadian patterns in acoustic activity. Soundscapes in the dry season had a complex diel cycle, requiring multiple harmonics to represent daily variation, while in the wet season there was less variance attributable to the daily cyclic patterns. Our framework can be applied to most continuous, or near-continuous ecological data collected at a fine temporal resolution, allowing ecologists to explore patterns of temporal autocorrelation at multiple levels for biologically meaningful trends. Such methods will become indispensable as biological big data are used to understand the impact of anthropogenic pressures on biodiversity and to inform efforts to mitigate them.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Evaluating the Lagrangian Evolution of Subtropical Low Clouds in GCMs Using Observations: Mean Evolution, Time Scales, and Responses to Predictors

In this work, a Lagrangian framework is developed to show the daily-scale time evolution of low clouds over the eastern subtropical oceans. An identical framework is applied to two general circulation models (GCMs): the CAM5 and UKMET and a set of satellite observations. This approach follows thousands of parcels as they advect downwind in the subtropical trade winds, comparing cloud evolution in time and space. This study tracks cloud cover, in-cloud liquid water path (CLWP), droplet concentration $N_d$, planetary boundary layer (PBL) depth, and rain rate as clouds transition from regions with predominately stratiform clouds to regions containing mostly trade cumulus. The two models generate fewer clouds with greater $N_d$ relative to observations. Models show stronger Lagrangian cloud cover decline and greater PBL deepening when compared with observations. In comparing frequency distributions of cloud variables over time, it is seen that models generate increasing frequencies of nearly clear conditions at the expense of overcast conditions, whereas observations show transitions from overcast to cloud amounts between 50% and 90%. Lagrangian decorrelation time scales ($\mathcal{e}$-folding time $\tau$) of cloud cover and CLWP are between 11 and 19 h for models and observations, although they are a bit shorter for models. A Lagrangian framework applied here resolves and compares the time evolution of cloud systems as they adjust to environmental perturbations in models and observations. Increasing subsidence in the overlying troposphere leads to declining cloud cover, CLWP, PBL depth, and rain rates in models and observations. Modeled cloud responses to other meteorological variables are less consistent with observations, suggesting a need for continuing mechanical improvements in GCMs.

58 GEOSCIENCES↗
DOE OSTI2023

Influences of cloud vertical overlapping on the calculated cloud albedo and their validation with satellite observations

Cloud albedo is expected to influence cloud radiative forcing in addition to cloud fraction, and inadequate description of the cloud overlapping effects on the cloud fraction may influence the simulated cloud fraction, and thus the relative cloud radiative forcing (RCRF) and cloud albedo. In this study, we first present a new formula by extending that presented previously in Liu et al. (2011) to consider multilayer clouds directly in the relationship between cloud albedo, cloud fraction and RCRF, and then quantitatively evaluate the effects of different cloud vertical overlapping structures, represented by the decorrelation length scales (L cf ), on the simulated cloud albedos. We use the BCC_AGCM2.0_CUACE/Aero model with simultaneous validation by observations from the Clouds and the Earth's Radiation Energy System (CERES) satellite. When L cf < 4 km (i.e., the cloud overlap is closer to the random overlap), the simulated cloud albedos are generally in good agreement with the satellite-based albedos for December– February and June–August; when L cf ≥ 4 km (i.e., the cloud vertical overlap is closer to the maximum overlap), the difference between simulated and observed cloud albedos became larger, due mainly to significant differences in cloud fractions and RCRF. Further quantitative analysis shows that the relative Euclidean distance, which represents the degree of overall model–observation disagreement, increases with the L cf for all three variables (cloud albedo, cloud fraction and RCRF), indicating the importance of cloud vertical overlapping in determining the accuracy of the calculated cloud albedo for multilayer clouds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Constraints on Neutrino Oscillation Parameters from Neutrinos and Antineutrinos with Machine Learning

NOvA is a two detector, long baseline neutrino oscillation experiment measuring the oscillations of muon neutrinos from the \numi neutrino beam over a baseline of \SI{810}{km}. The experiment uses four oscillation channels, $\numu \rightarrow \numu$, $\numubar \rightarrow \numubar$, $\numu \rightarrow \nue$, and $\numubar \rightarrow \nuebar$, with a peak neutrino energy of \SI{1.8}{GeV}. This dissertation describes the analysis of these channels using a dataset of $13.6\times10^{20}$ protons on target neutrino beam mode and $12.5\times10^{20}$ protons on target antineutrino beam mode. The analysis makes use of improvements in the treatment of systematic uncertainties and machine learning techniques to reconstruct neutrino interactions. A technique for decorrelating systematic errors using principle component analysis was utilized to reduce and optimize neutrino cross section and beam related uncertainties. The improved machine learning algorithms make use of convolutional ne ural net works for neutrino event classification, particle classification, and instance segmentation. The selection of neutrino signal events utilizing the neutrino event classifier shows an efficiency of 63\% for the selection of electron neutrinos in neutrino beam mode and 75\% for electron antineutrinos in antineutrino beam mode. Using this algorithm, 82 appearing electron neutrino candidates and 33 appearing electron antineutrino candidates were observed with expected backgrounds of 26.8 and 14.0 respectively. In addition, 211 surviving muon neutrino candidates and 105 muon antineutrino candidates were identified with a purity of more than 96\% using the same neutrino event classifier. Fitting these data to the three flavor neutrino oscillation model, using constraints on \thetaonetwo, \thetaonethree, and \dmsqonetwo from solar and reactor neutrino experiments, the oscillation parameters are measured to be $\sintwothree = 0.57^{+0.04}_{-0.03}$, $\dmsqthreetwo = \SI[parse-numbers= false]{+ 2.41\pm0.07 \times 10^{-3}}{eV^2}$, and $\dcp=0.82^{+0.27}_{-0.87}\pi$ with a preference for the normal neutrino mass hierarchy. Leading systematic uncertainties for these measurements come from detector calibration and neutrino interaction models.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Computational Imaging for Intelligence in Highly Scattering Aerosols (Final Report)

Natural and man-made degraded visual environments pose major threats to national security. The random scattering and absorption of light by tiny particles suspended in the air reduces situational awareness and causes unacceptable down-time for critical systems and operations. To improve the situation, we have developed several approaches to interpret the information contained within scattered light to enhance sensing and imaging in scattering media. These approaches were tested at the Sandia National Laboratory Fog Chamber facility and with tabletop fog chambers. Computationally efficient light transport models were developed and leveraged for computational sensing. The models are based on a weak angular dependence approximation to the Boltzmann or radiative transfer equation that appears to be applicable in both the moderate and highly scattering regimes. After the new model was experimentally validated, statistical approaches for detection, localization, and imaging of objects hidden in fog were developed and demonstrated. A binary hypothesis test and the Neyman-Pearson lemma provided the highest theoretically possible probability of detection for a specified false alarm rate and signal-to-noise ratio. Maximum likelihood estimation allowed estimation of the fog optical properties as well as the position, size, and reflection coefficient of an object in fog. A computational dehazing approach was implemented to reduce the effects of scatter on images, making object features more readily discernible. We have developed, characterized, and deployed a new Tabletop Fog Chamber capable of repeatably generating multiple unique fog-analogues for optical testing in degraded visual environments. We characterized this chamber using both optical and microphysical techniques. In doing so we have explored the ability of droplet nucleation theory to describe the aerosols generated within the chamber, as well as Mie scattering theory to describe the attenuation of light by said aerosols, and correlated the aerosol microphysics to optical properties such as transmission and meteorological optical range (MOR). This chamber has proved highly valuable and has supported multiple efforts inclusive to and exclusive of this LDRD project to test optics in degraded visual environments. Circularly polarized light has been found to maintain its polarization state better than linearly polarized light when propagating through fog. This was demonstrated experimentally in both the visible and short-wave infrared (SWIR) by imaging targets made of different commercially available retroreflective films. It was found that active circularly polarized imaging can increase contrast and range compared to linearly polarized imaging. We have completed an initial investigation of the capability for machine learning methods to reduce the effects of light scattering when imaging through fog. Previously acquired experimental long-wave images were used to train an autoencoder denoising architecture. Overfitting was found to be a problem because of lack of variability in the object type in this data set. The lessons learned were used to collect a well labeled dataset with much more variability using the Tabletop Fog Chamber that will be available for future studies. We have developed several new sensing methods using speckle intensity correlations. First, the ability to image moving objects in fog was shown, establishing that our unique speckle imaging method can be implemented in dynamic scattering media. Second, the speckle decorrelation over time was found to be sensitive to fog composition, implying extensions to fog characterization. Third, the ability to distinguish macroscopically identical objects on a far-subwavelength scale was demonstrated, suggesting numerous applications ranging from nanoscale defect detection to security. Fourth, we have shown the capability to simultaneously image and localize hidden objects, allowing the speckle imaging method to be effective without prior object positional information. Finally, an interferometric effect was presented that illustrates a new approach for analyzing speckle intensity correlations that may lead to more effective ways to localize and image moving objects. All of these results represent significant developments that challenge the limits of the application of speckle imaging and open important application spaces. A theory was developed and simulations were performed to assess the potential transverse resolution benefit of relative motion in structured illumination for radar systems. Results for a simplified radar system model indicate that significant resolution benefits are possible using data from scanning a structured beam over the target, with the use of appropriate signal processing.

58 GEOSCIENCES↗
DOE OSTI2020

Development of Coarse-Grained Models for Poly(4-vinylphenol) and Poly(2-vinylpyridine): Polymer Chemistries with Hydrogen Bonding

In this paper, we identify the modifications needed in a recently developed generic coarse-grained (CG) model that captured directional interactions in polymers to specifically represent two exemplary hydrogen bonding polymer chemistries—poly(4-vinylphenol) and poly(2-vinylpyridine). We use atomistically observed monomer-level structures (e.g., bond, angle and torsion distribution) and chain structures (e.g., end-to-end distance distribution and persistence length) of poly(4-vinylphenol) and poly(2-vinylpyridine) in an explicitly represented good solvent (tetrahydrofuran) to identify the appropriate modifications in the generic CG model in implicit solvent. For both chemistries, the modified CG model is developed based on atomistic simulations of a single 24-mer chain. This modified CG model is then used to simulate longer (36-mer) and shorter (18-mer and 12-mer) chain lengths and compared against the corresponding atomistic simulation results. We find that with one to two simple modifications (e.g., incorporating intra-chain attraction, torsional constraint) to the generic CG model, we are able to reproduce atomistically observed bond, angle and torsion distributions, persistence length, and end-to-end distance distribution for chain lengths ranging from 12 to 36 monomers. We also show that this modified CG model, meant to reproduce atomistic structure, does not reproduce atomistically observed chain relaxation and hydrogen bond dynamics, as expected. Simulations with the modified CG model have significantly faster chain relaxation than atomistic simulations and slower decorrelation of formed hydrogen bonds than in atomistic simulations, with no apparent dependence on chain length.

36 MATERIALS SCIENCE↗
DOE OSTI2020

On the Accuracy of the ALMA Flux Calibration in the Time Domain and across Spectral Windows

A diverse array of science goals requires accurate flux calibration of observations with the Atacama Large Millimeter/submillimeter array (ALMA); however, this goal remains challenging due to the stochastic time-variability of the “grid” quasars ALMA uses for calibration. In this work, we use 343.5 GHz (Band 7) ALMA Atacama Compact Array observations of four bright and stable young stellar objects over seven epochs to independently assess the accuracy of the ALMA flux calibration and to refine the relative calibration across epochs. The use of these four extra calibrators allows us to achieve an unprecedented relative ALMA calibration accuracy of ~3%. On the other hand, when the observatory calibrator catalog is not up to date, the Band 7 data calibrated by the ALMA pipeline may have a flux calibration poorer than the nominal 10%, which can be exacerbated by weather-related phase decorrelation when self-calibration of the science target is either not possible or not attempted. We also uncover a relative flux calibration uncertainty between spectral windows of 0.8%, implying that measuring spectral indices within a single ALMA band is likely highly uncertain. We thus recommend various methods for science goals requiring high flux accuracy and robust calibration, in particular, the observation of additional calibrators combined with a relative calibration strategy, and observation of solar system objects for high absolute accuracy.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Physical Parameters of the Multiplanet Systems HD 106315 and GJ 9827

HD 106315 and GJ 9827 are two bright, nearby stars that host multiple super-Earths and sub-Neptunes discovered by K2 that are well suited for atmospheric characterization. We refined the planets’ ephemerides through Spitzer transits, enabling accurate transit prediction required for future atmospheric characterization through transmission spectroscopy. Through a multiyear high-cadence observing campaign with Keck/High Resolution Echelle Spectrometer and Magellan/Planet Finder Spectrograph, we improved the planets’ mass measurements in anticipation of Hubble Space Telescope transmission spectroscopy. For GJ 9827, we modeled activity-induced radial velocity signals with a Gaussian process informed by the Calcium II H&K lines in order to more accurately model the effect of stellar noise on our data. We measured planet masses of M {sub b} = 4.87 ± 0.37 M {sub ⊕}, M {sub c} = 1.92 ± 0.49 M {sub ⊕}, and M {sub d} = 3.42 ± 0.62 M {sub ⊕}. For HD 106315, we found that such activity radial velocity decorrelation was not effective due to the reduced presence of spots and speculate that this may extend to other hot stars as well (T {sub eff} > 6200 K). We measured planet masses of M {sub b} = 10.5 ± 3.1 M {sub ⊕} and M {sub c} = 12.0 ± 3.8 M {sub ⊕}. We investigated all of the planets’ compositions through comparison of their masses and radii to a range of interior models. GJ 9827 b and GJ 9827 c are both consistent with a 50/50 rock-iron composition, GJ 9827 d and HD 106315 b both require additional volatiles and are consistent with moderate amounts of water or hydrogen/helium, and HD 106315 c is consistent with a ∼10% hydrogen/helium envelope surrounding an Earth-like rock and iron core.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

BICEP/Keck. XVI. Characterizing Dust Polarization through Correlations with Neutral Hydrogen

We characterize Galactic dust filaments by correlating BICEP/Keck and Planck data with polarization templates based on neutral hydrogen (H i) observations. Dust polarization is important for both our understanding of astrophysical processes in the interstellar medium (ISM) and the search for primordial gravitational waves in the cosmic microwave background (CMB). In the diffuse ISM, H i is strongly correlated with the dust and partly organized into filaments that are aligned with the local magnetic field. We analyze the deep BICEP/Keck data at 95, 150, and 220 GHz, over the low-column-density region of sky where BICEP/Keck has set the best limits on primordial gravitational waves. We separate the H i emission into distinct velocity components and detect dust polarization correlated with the local Galactic H i but not with the H i associated with Magellanic Stream i. We present a robust, multifrequency detection of polarized dust emission correlated with the filamentary H i morphology template down to 95 GHz. For assessing its utility for foreground cleaning, we report that the Hi morphology template correlates in B modes at a ~10%–65% level over the multipole range 20 < ℓ < 200 with the BICEP/Keck maps, which contain contributions from dust, CMB, and noise components. We measure the spectral index of the filamentary dust component spectral energy distribution to be β = 1.54 ± 0.13. We find no evidence for decorrelation in this region between the filaments and the rest of the dust field or from the inclusion of dust associated with the intermediate velocity H i. Finally, we explore the morphological parameter space in the H i-based filamentary model.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Analysis of Polarized Dust Emission Using Data from the First Flight of SPIDER

Using data from the first flight of Spider and from the Planck High Frequency Instrument, we probe the properties of polarized emission from interstellar dust in the Spider observing region. Component-separation algorithms operating in both the spatial and harmonic domains are applied to probe their consistency and to quantify modeling errors associated with their assumptions. Analyses of diffuse Galactic dust emission spanning the full Spider region demonstrate (i) a spectral energy distribution that is broadly consistent with a modified-blackbody (MBB) model with a spectral index of β d = 1.45 ± 0.05 (1.47 ± 0.06) for E (B)-mode polarization, slightly lower than that reported by Planck for the full sky; (ii) an angular power spectrum broadly consistent with a power law; and (iii) no significant detection of line-of-sight polarization decorrelation. Tests of several modeling uncertainties find only a modest impact (~10% in σ r ) on Spider's sensitivity to the cosmological tensor-to-scalar ratio. The size of the Spider region further allows for a statistically meaningful analysis of the variation in foreground properties within it. Assuming a fixed dust temperature T d = 19.6 K, an analysis of two independent subregions of that field results in inferred values of β d = 1.52 ± 0.06 and β d = 1.09 ± 0.09, which are inconsistent at the 3.9σ level. Furthermore, a joint analysis of Spider and Planck 217 and 353 GHz data within one subregion is inconsistent with a simple MBB at more than 3σ, assuming a common morphology of polarized dust emission over the full range of frequencies. This evidence of variation may inform the component-separation approaches of future cosmic microwave background polarization experiments.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Millimeter Light Curves of Sagittarius A* Observed during the 2017 Event Horizon Telescope Campaign

The Event Horizon Telescope (EHT) observed the compact radio source, Sagittarius A* (Sgr A*), in the Galactic Center on 2017 April 5–11 in the 1.3 mm wavelength band. At the same time, interferometric array data from the Atacama Large Millimeter/submillimeter Array and the Submillimeter Array were collected, providing Sgr A* light curves simultaneous with the EHT observations. These data sets, complementing the EHT very long baseline interferometry, are characterized by a cadence and signal-to-noise ratio previously unattainable for Sgr A* at millimeter wavelengths, and they allow for the investigation of source variability on timescales as short as a minute. While most of the light curves correspond to a low variability state of Sgr A*, the April 11 observations follow an X-ray flare and exhibit strongly enhanced variability. All of the light curves are consistent with a red-noise process, with a power spectral density (PSD) slope measured to be between −2 and −3 on timescales between 1 minute and several hours. Our results indicate a steepening of the PSD slope for timescales shorter than 0.3 hr. The spectral energy distribution is flat at 220 GHz, and there are no time lags between the 213 and 229 GHz frequency bands, suggesting low optical depth for the event horizon scale source. We characterize Sgr A*’s variability, highlighting the different behavior observed just after the X-ray flare, and use Gaussian process modeling to extract a decorrelation timescale and a PSD slope. We also investigate the systematic calibration uncertainties by analyzing data from independent data reduction pipelines.

79 ASTRONOMY AND ASTROPHYSICS↗