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At least 541 records · Page 30

3D optical diagnostics for explosively driven deformation and fragmentation

High-speed, optical imaging diagnostics are presented for three-dimensional (3D) quantification of explosively driven metal fragmentation. At early times after detonation, Digital Image Correlation (DIC) provides non-contact measures of 3D case velocities, strains, and strain rates, while a proposed stereo imaging configuration quantifies in-flight fragment masses and velocities at later times. Experiments are performed using commercially obtained RP-80 detonators from Teledyne RISI, which are shown to create a reproducible fragment field at the benchtop scale. DIC measurements are compared with 3D simulations, which have been ‘leveled’ to match the spatial resolution of DIC. Overall, results demonstrate improved ability to identify predicted quantities-of-interest that fall outside of measurement uncertainty and shot-to-shot variability. Similarly, video measures of fragment trajectories and masses allow rapid experimental repetition and provide correlated fragment size-velocity measurements. Measured and simulated fragment mass distributions are shown to agree within confidence bounds, while some statistically meaningful differences are observed between the measured and predicted conditionally averaged fragment velocities. Together these techniques demonstrate new opportunities to improve future model validation.

42 ENGINEERING↗

BEYONDPLANCK VI. Noise characterization and modeling

We present a Bayesian method for estimating instrumental noise parameters and propagating noise uncertainties within the global BeyondPlanck Gibbs sampling framework, and apply this to Planck Low Frequency Instrument (LFI) time-ordered data. Following previous literature, we initially adopt a 1/ f model for the noise power spectral density (PSD), but find the need for an additional lognormal component in the noise model for the 30 and 44 GHz bands. We implement an optimal Wiener-filter (or constrained realization) gap-filling procedure to account for masked data. We then use this procedure to both estimate the gapless correlated noise in the time-domain, n corr , and to sample the noise PSD parameters, ξ n = {σ 0 , f knee , α, A p }. In contrast to previous Planck analyses, we assume piecewise stationary noise only within each pointing period (PID), not throughout the full mission, but we adopt the LFI Data Processing Center (DPC) results as priors on α and f knee . On average, we find best-fit correlated noise parameters that are mostly consistent with previous results, with a few notable exceptions. However, a detailed inspection of the time-dependent results reveals many important findings. First and foremost, we find strong evidence for statistically significant temporal variations in all noise PSD parameters, many of which are directly correlated with satellite housekeeping data. Second, while the simple 1/ f model appears to be an excellent fit for the LFI 70 GHz channel, there is evidence for additional correlated noise not described by a 1/ f model in the 30 and 44 GHz channels, including within the primary science frequency range of 0.1–1 Hz. In general, most 30 and 44 GHz channels exhibit deviations from 1/ f at the 2–3σ level in each one hour pointing period, motivating the addition of the lognormal noise component for these bands. For some periods of time, we also find evidence of strong common mode noise fluctuations across the entire focal plane. Overall, we conclude that a simple 1/ f profile is not adequate to fully characterize the Planck LFI noise, even when fitted hour-by-hour, and a more general model is required. These findings have important implications for large-scale CMB polarization reconstruction with the Planck LFI data, and the current work is a first attempt at understanding and mitigating these issues.

79 ASTRONOMY AND ASTROPHYSICS↗

Cosmic-Ray Extremely Distributed Observatory

The Cosmic-Ray Extremely Distributed Observatory (CREDO) is a newly formed, global collaboration dedicated to observing and studying cosmic rays (CR) and cosmic-ray ensembles (CRE): groups of at least two CR with a common primary interaction vertex or the same parent particle. The CREDO program embraces testing known CR and CRE scenarios, and preparing to observe unexpected physics, it is also suitable for multi-messenger and multi-mission applications. Perfectly matched to CREDO capabilities, CRE could be formed both within classical models (e.g., as products of photon–photon interactions), and exotic scenarios (e.g., as results of decay of Super-Heavy Dark Matter particles). Their fronts might be significantly extended in space and time, and they might include cosmic rays of energies spanning the whole cosmic-ray energy spectrum, with a footprint composed of at least two extensive air showers with correlated arrival directions and arrival times. As the CRE are predominantly expected to be spread over large areas and, due to the expected wide energy range of the contributing particles, such a CRE detection might only be feasible when using all available cosmic-ray infrastructure collectively, i.e., as a globally extended network of detectors. Thus, with this review article, the CREDO Collaboration invites the astroparticle physics community to actively join or to contribute to the research dedicated to CRE and, in particular, to pool together cosmic-ray data to support specific CRE detection strategies.

79 ASTRONOMY AND ASTROPHYSICS↗

Superposition principle and nonlinear response in spin glasses

The extended principle of superposition has been a touchstone of spin-glass dynamics for almost 30 years. Here the Uppsala group has demonstrated its validity for the metallic spin glass, CuMn, for magnetic fields H up to 10 Oe at the reduced temperature T r = T/T g = 0.95, where T g is the spin-glass condensation temperature. For H > 10 Oe, they observe a departure from linear response which they ascribe to the development of nonlinear dynamics. The thrust of this paper is to develop a microscopic origin for this behavior by focusing on the time development of the spin-glass correlation length, ξ(t, t w ; H). Here, t is the time after H changes, and t w is the time from the quench for T > T g to the working temperature T until H changes. We connect the growth of ξ(t, t w ; H) to the barrier heights Δ(t w ) that set the dynamics. The effect of H on the magnitude of Δ (t w ) is responsible for affecting differently the two dynamical protocols associated with turning H off (TRM, or thermoremanent magnetization) or on (ZFC, or zero-field-cooled magnetization). This difference is a consequence of nonlinearity based on the effect of H on Δ (t w ). Superposition is preserved if Δ(t w ) is linear in the Hamming distance Hd (proportional to the difference between the self-overlap q EA and the overlap q[Δ(t w )]). However, superposition is violated if Δ(t w ) increases faster than linear in Hd. We have previously shown, through experiment and simulation, that the barriers Δ(t w ) do increase more rapidly than linearly with Hd through the observation that the growth of ξ(t,t w ;H) slows down as ξ(t,t w ; H) increases. In this paper, we display the difference between the zero-field-cooled ξ ZFC (t, t w ; H) and the thermoremanent magnetization ξ TRM (t, t w ; H) correlation lengths as H increases, both experimentally and through numerical simulations, corresponding to the violation of the extended principle of superposition in line with the finding of the Uppsala Group.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

3DBFSVBF (3D BatFinder Smart Video BioFilter and Multi-class BatFinder Smart Video BioFilter) [SWR-22-88]

Bats are notoriously difficult to study, therefore, identifying specific behavioral trends and the precise environmental conditions at the time of collision requires a monitoring solution that can reliably collect relevant data. To date, thermal infrared video surveillance has been extensively applied to study bats and has proven to be a powerful yet cumbersome tool. Current analytical approaches are time consuming because data processing data has not been fully automated. In the past, steps have been taken to record avian and bat activity in conjunction with complicated image processing techniques that separate species from other moving objects within the field of view (i.e. clouds and portions of the wind turbine). Once the videos are collected, the post-processing does not allow real time monitoring and identification, leading to a delay in both studying the behavior of these species and determining the effectiveness of any impact reduction strategy being studied. Moreover, object identification capability is lacking, thus limiting the usefulness of video data. To resolve these issues, we are using open source 3D computer vision and machine learning techniques allowing for automatic detection of objects in real-time with the ability to correlate these objects with environmental variables and recording the flight paths of each object. The machine learning has been trained on 3D data and allows for automated real-time data collection, identification and tracking, thereby eliminating the need for long and tedious post-analysis processing of the videos. This machine learning model is an added feature to the previous BatFinder Smart Video BioFilter and increases the accuracy of that systems classification by increasing the accuracy of identifying bats (90% accuracy) and insects (69% accuracy) to a 97% accuracy. There are two object classifier machine learning models, Binary and multi-classification. Binary object classifier labeled BatFinder_Smart_Video_BioFilter.h5 distinguishes between biological objects and non-biological objects. The main goal of this object classifier is to ignore the turbine blades while detecting biological object flying withing the rotor swept area of the turbine. Non-biological objects have a probability of 0 and biological objects have a probability of 1. Multi-classifier labeled Multiclass_BatFinder_Smart_Video_BioFilter.h5 distinguishes between bats, birds, insects and non-biological.

Yarbrough, John↗

Periodic Narrowband Radio Wave Emissions and Inward Plasma Transport at Saturn's Magnetosphere

The abrupt brightening of an Energetic Neutral Atom (ENA) blob or cloud has been interpreted as plasma injection in the Kronian magnetosphere (termed ENA injection herein). Morphologically, there appears to be two types of abrupt ENA cloud brightening: (1) the brightening of a large cloud usually seen at distances >10–12 R {sub s} (R {sub s} ∼ 60,268 km) in the midnight or postmidnight region; (2) the brightening of a smaller cloud usually seen at distances <10–12 R {sub s} around 21–03 magnetic local time. Among many radio waves observed at Saturn, type 2 ENA injections correlate best with the 5 kHz narrowband (NB) waves. Using Cassini Ion and Neutral Camera (INCA) and Radio and Plasma Wave Science (RPWS) data, we examine the periodicities of the type 2 ENA injections and the 5 kHz NB emissions as well as their cross-correlations, which have been previously used to measure the lag times or phase differences. Because correlational analysis can only establish linear relationships, we also use mutual information to establish linear and nonlinear relationships. On average, the peak of the 5 kHz NB emission lags those of the type 2 ENA injection by about a few minutes to 2 hr. The injection of hot plasma to the inner magnetosphere can lead to temperature anisotropy, which can generate electrostatic upper hybrid waves, which upon encountering the high-density gradient at the outer edge of the Enceladus density torus, can mode convert to Z mode and then to O mode. The 5 kHz NB waves commonly propagate in the O mode.

79 ASTRONOMY AND ASTROPHYSICS↗

System, algorithm, and method using short pulse interrogation with neutrons to detect and identify matter

A system, method, and algorithm for detecting and identifying special nuclear material (SNM) (including fissionable material), explosives, or drugs is disclosed. This material detection system relies on active interrogation of material using a short, intense neutron pulse, and characterization of the resulting prompt gamma response in two short time windows, the first concurrent with and the second immediately following the end of the neutron pulse, optionally subject to a total transit delay time of the neutrons from the neutron source to the target and from the target to the gamma detector. A high data rate analysis system implements data stream analysis and statistical correlations of the two short time window gamma responses to rapidly detect or identify SNM, explosives, or drugs. The duration of the neutron pulse is so short that minimal dose results. Various shields help to minimize the background signal falling on the gamma detector to improve sensitivity.

Derzon, Mark S.↗

A three-point velocity estimation method for two-dimensional coarse-grained imaging data

Time delay and velocity estimation methods have been widely studied subjects in the context of signal processing, with applications in many different fields of physics. The velocity of waves or coherent fluctuation structures is commonly estimated as the distance between two measurement points divided by the time lag that maximizes the cross correlation function between the measured signals, but this is demonstrated to result in erroneous estimates for two spatial dimensions. We present an improved method to accurately estimate both components of the velocity vector, relying on three non-aligned measurement points. We introduce a stochastic process describing the fluctuations as a superposition of uncorrelated pulses moving in two dimensions. Using this model, we show that the three-point velocity estimation method, using time delays calculated through cross correlations, yields the exact velocity components when all pulses have the same velocity. The two- and three-point methods are tested on synthetic data generated from realizations of such processes for which the underlying velocity components are known. The results reveal the superiority of the three-point technique. Finally, we demonstrate the applicability of the velocity estimation on gas puff imaging data of strongly intermittent plasma fluctuations due to the radial motion of coherent, blob-like structures at the boundary of the Alcator C-Mod tokamak.

Materials Science↗

SMBH binary candidate PKS J2134−0153: possible multi-band periodic variability and inter-band time lags

ABSTRACT Studying the periodic flux-variation behaviour of blazars is vital for probing supermassive black hole binaries and the kinematics of relativistic jets. In this work, we report the detection of multi-band possible periodic variations of the blazar PKS J2134−0153, including infrared ($1.6(\pm 0.4)\times 10^3$ day) and optical ($1.8(\pm 1)\times 10^3$ day) wavelengths. The periods in the infrared and optical bands are statistically consistent with the period in the radio band ($P_{\mathrm{Radio}} = 1760\pm 33$ days, obtained from our previous work). Moreover, flux variations in different bands are correlated with evident inter-band time delays, and the time lags of infrared and optical emission with respect to radio emission are $(3.3\pm 2.3)\times 10^{2}$ days and $(3.0\pm 2.3)\times 10^{2}$ days, respectively. The cross-correlations indicate a common origin of radio, infrared, and optical emission. The relative positions between emission regions of infrared and optical emission and radio emission are estimated according to the time lags, i.e. $0.37\pm 0.26$ and $0.33\pm 0.26$ pc. The relative distances seem to be quantitatively consistent with the theoretical prediction.

Ren, Guo-Wei (ORCID:0000000214978371)↗

AI-NERD: Elucidation of relaxation dynamics beyond equilibrium through AI-informed X-ray photon correlation spectroscopy

Abstract Understanding and interpreting dynamics of functional materials in situ is a grand challenge in physics and materials science due to the difficulty of experimentally probing materials at varied length and time scales. X-ray photon correlation spectroscopy (XPCS) is uniquely well-suited for characterizing materials dynamics over wide-ranging time scales. However, spatial and temporal heterogeneity in material behavior can make interpretation of experimental XPCS data difficult. In this work, we have developed an unsupervised deep learning (DL) framework for automated classification of relaxation dynamics from experimental data without requiring any prior physical knowledge of the system. We demonstrate how this method can be used to accelerate exploration of large datasets to identify samples of interest, and we apply this approach to directly correlate microscopic dynamics with macroscopic properties of a model system. Importantly, this DL framework is material and process agnostic, marking a concrete step towards autonomous materials discovery.

36 MATERIALS SCIENCE↗

BFSVBF (BatFinder Smart Video BioFilter) [SWR-22-87] and Multi-class BatFinder Smart Video BioFilter Keras

Bats are notoriously difficult to study, therefore, identifying specific behavioral trends and the precise environmental conditions at the time of collision requires a monitoring solution that can reliably collect relevant data. To date, thermal infrared video surveillance has been extensively applied to study bats and has proven to be a powerful yet cumbersome tool. Current analytical approaches are time consuming because data processing data has not been fully automated. In the past, steps have been taken to record avian and bat activity in conjunction with complicated image processing techniques that separate species from other moving objects within the field of view (i.e. clouds and portions of the wind turbine). Once the videos are collected, the post-processing does not allow real time monitoring and identification, leading to a delay in both studying the behavior of these species and determining the effectiveness of any impact reduction strategy being studied. Moreover, object identification capability is lacking, thus limiting the usefulness of video data. To resolve these issues, we are using open source computer vision and machine learning techniques allowing for automatic detection of objects in real-time with the ability to correlate these objects with environmental variables and recording the flight paths of each object. The code has gone through five rounds of development with images used to train the models. This advancement allows for automated real-time data collection, identification, and tracking, thereby eliminating the need for long and tedious post-analysis processing of the videos. We will discuss the two open source and publicly available machine learning models developed within this scope of this work: 1) a binary model with a 97.5% accuracy in identifying the difference between an object and an empty scene, including wind turbine and clouds; and 2) a multiple classification model with the capability of identifying the type of object detected: bats (90% accuracy), birds (83% accuracy), insects (69% accuracy) and non-biological (99% accuracy).

Yarbrough, John↗

Sensitivity of transverse momentum correlations to early-stage and thermal fluctuations

Transverse momentum correlations were recently measured by the ALICE collaboration at the LHC [Acharya et al (2020 Phys. Lett. B 804 135375)]. A long-range structure in terms of relative pseudorapidity of particle pairs is observed. This may imply some signal of the initial state owing to the sheer spread of the correlation. However, the fluctuations inside a thermally equilibrated medium have to be taken into account, serving as motivation for this paper. Using lattice Quantum Chromodynamics constraints, we predicted the development and spread of balancing correlations caused by energy-momentum conservation. At the same time, we propagated the Gaussian-shaped initial correlation using hydrodynamics to estimate its effects. Our findings suggest that the resulting correlation, known as ‘the ridge,’ is sensitive both to flucutations seeded in the pre-equilibrium stage and to those seeded in the equilibrated medium. This can provide important insight into the early stages of the collision.

ALICE↗

Connecting Global Modes of Variability to Climate in High Mountain Asia

Oscillations in global modes of variability (MoVs) form global teleconnections that affect regional climate variability and modify the potential for severe and damaging weather conditions. Understanding the link between certain MoVs and regional climate can improve the ability to more accurately predict environmental conditions that impact human life and health. In this study, we explore the connection between different MoVs, including the Arctic oscillation (AO), Eurasian teleconnection, Indian Ocean dipole (IOD), North Atlantic oscillation (NAO), and El Niño southern oscillation (Nino34), with winter and summer climates in the High Mountain Asia (HMA) region, including geopotential height at 250 hPa (z250), 2 m air temperature (T2M), total precipitation (PRECTOT), and fractional snow cover area (fSCA). Relationships are explored for the same monthly period between the MoVs and the climate variables, and a lagged correlation analysis is used to investigate whether any relationship exists at different time lags. We find that T2M has a negative correlation with the Eurasian teleconnection in the Inner Tibetan Plateau and central China in both winter and summer and a positive correlation in western China in summer. PRECTOT has a positive correlation with all MoVs in most regions in winter, especially with the IOD, and a negative correlation in summer, especially with the Eurasian teleconnection. Snow cover in winter is positively correlated with most indices throughout many regions in HMA, likely due to wintertime precipitation also being positively correlated with most indices. Generally, the AO and NAO show similar correlation patterns with all climate variables, especially in the winter, possibly due to their oscillations being so similar. Furthermore, the AO and NAO are shown to be less significant in explaining the variation in HMA climate compared to other MoVs such as the Eurasian teleconnection. Overall, our results identify different time windows and specific regions within HMA that exhibit high correlations between climate and MoVs, which might offer additional predictability of the MoVs as well as of climate and weather patterns in HMA and throughout the globe.

54 ENVIRONMENTAL SCIENCES↗

Collapse of the waiting time effect in a spin glass

Waiting time measurements are reported here for a bulk polycrystalline sample of the spin glass Cu 0.95 Mn 0.05 . We observe a suppression of aging as the glass temperature is approached from below. These results are interpreted in terms of a spin-glass correlation length approaching and reaching crystallite sizes. They provide a direct experimental connection between the correlation length scale and relaxation times in the spin-glass state. In particular, these measurements track the value of the dynamic critical exponent as the system transitions from the critical temperature regime to its low-temperature, quasistatic nonequilibrium phase.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

On the relation between active-region lifetimes and the autocorrelation function of light curves

ABSTRACT Rotational modulation of stellar light curves due to dark spots encloses information on spot properties and, thus, on magnetic activity. In particular, the decay of the autocorrelation function (ACF) of light curves is presumed to be linked to spot/active-region lifetimes, given that some coherence of the signal is expected throughout their lifetime. In the literature, an exponential decay has been adopted to describe the ACF. Here, we investigate the relation between the ACF and the active-region lifetimes. For this purpose, we produce artificial light curves of rotating spotted stars with different observation, stellar, and spot properties. We find that a linear decay and respective time-scale better represent the ACF than the exponential decay. We therefore adopt a linear decay. The spot/active-region time-scale inferred from the ACF is strongly restricted by the observation length of the light curves. For 1-yr light curves our results are consistent with no correlation between the inferred and the input time-scales. The ACF decay is also significantly affected by differential rotation and spot evolution: strong differential rotation and fast spot evolution contribute to a more severe underestimation of the active-region lifetimes. Nevertheless, in both circumstances the observed time-scale is still correlated with the input lifetimes. Therefore, our analysis suggests that the ACF decay can be used to obtain a lower limit of the active-region lifetimes for relatively long-term observations. However, strategies to avoid or flag targets with fast active-region evolution or displaying stable beating patterns associated with differential rotation should be employed.

Santos, A. R. G. (ORCID:0000000171956542)↗

Structural Dynamics in UV Curable Resins Resolved by In Situ 3D Printing X-ray Photon Correlation Spectroscopy

Additive manufacturing (AM) is a promising technique to rapidly produce polymeric materials into complex 3-dimensional (3D) geometries. While AM is widespread and relevant for a range of applications, implementation in industry has outpaced our fundamental understanding of polymer dynamics and structure development during the printing process. Characterization and quantification of such dynamics is necessary to optimize final material properties and design future materials and processes for 3D printing. Here, we utilize X-ray photon correlation spectroscopy (XPCS) to measure spatial and time-resolved, out-of-equilibrium dynamics during direct ink write (DIW) 3D printing. Specifically, we investigate the progression of structural dynamics in a dual cure (UV/thermal) nanocomposite during and directly after printing. As the filament is printed and cured in situ, the relaxation processes of the cross-linking network are measured through the dynamics of inorganic filler particles. The characteristic relaxation time of the dynamics is calculated through the intensity–intensity autocorrelation function g 2 and directly correlated to the printing process parameters, such as printhead velocity and UV light intensity. The time-resolved evolution of nanoscale dynamics follows a power-law dependence as the filament is cured. Additionally, bulk rheological characterizations reveal the macroscopic solidification of the resin, providing correlation of material properties across a wide range of length and time scales. Overall, the measurement of multiscale, out-of-equilibrium dynamics provides insight into the development of structure in polymer nanocomposite filaments during 3D printing and is used to further understand the influence of such parameters on the AM process.

36 MATERIALS SCIENCE↗

Evaluating the Potential for Tidal Phase Diversity to Produce Smoother Power Profiles

Although tidal energy conversion technologies are not yet commercially available or cost-competitive with other renewable energy technologies like wind turbines and solar panels, tides are a highly predictable resource. Tidal energy’s predictability indicates that the resource could introduce less volatility into balancing the electric grid when compared to other renewables, a fundamentally desirable attribute for the electric system. More specifically, tidal energy resources are unique in that they have the potential to produce relatively smoother power profiles over time through aggregation. In order to generate smooth power profiles from tidal resources, sufficient complexity within the timing of tides is necessary within electrical proximity. This study evaluates the concept of aggregating diverse tides for the purpose of reducing periods of no and low energy production and creating smoother power profiles in regions around Alaska and Washington by calculating cross-correlations of tidal current velocity time series. Ultimately, study results show limited potential to exploit the resources for this purpose and describe the institutional mechanisms necessary to realize the benefits in practice.

16 TIDAL AND WAVE POWER↗

Enhanced domain dynamics in alternating current poled rhombohedral Pb(Mg 1/3 Nb 2/3 )O 3 –PbTiO 3 single crystals

Abstract The understanding of domain dynamics in ferroelectric materials is crucial for optimizing their performance in piezoelectric and electro‐optic applications. Although previous studies have focused on static domain structures and macroscopic characteristics, the time‐resolved approach of domains remains largely unexplored. In this study, we compare the dynamic responses of direct current (DC) and alternating current (AC) poled [001]‐oriented rhombohedral Pb(Mg 1/3 Nb 2/3 )O 3 –PbTiO 3 (PMN–PT) single crystals using X‐ray photon correlation spectroscopy (XPCS) during the application of external electric fields. Our results demonstrate that the AC‐poled sample exhibit enhanced reconfiguration of domain variants in response to driving fields compared to the DC‐poled counterpart, as evidenced by accelerated correlation decay and faster relaxation time. This phenomenon is attributed to enhanced reversible domain wall motion achieved through AC poling, which facilitates field‐induced domain realignment. These findings provide insight into the relationship between dynamics and macroscopic properties in relaxor‐PT single crystals for high‐performance applications.

36 MATERIALS SCIENCE↗