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At least 37 records · Page 2

Probabilistic inversion of circular phase spectra: application to two-station phase-velocity dispersion estimation in western Canada

SUMMARY Periodic directional and temporal measurements are common in seismology, and necessitate specific statistical analyses that are appropriate for circular quantities. In this work, we explore the use of a von Mises distribution as a representation of errors on circular seismological observations. Specifically, we automate the estimation of surface-wave phase-velocity dispersion for the teleseismic two-station method, which generally suffers from a 2π phase ambiguity. The use of Bayesian inverse techniques, which aim to rigorously quantify model parameter uncertainty, have become widespread throughout seismology over the last decade. Here, we apply Bayesian inversion to measurements of surface-wave phase spectra in order to estimate 1-D, path-averaged Earth structure between station pairs. The dispersion curve and associated uncertainties are additional results of the inversion, which can then be used as input for subsequent analyses (e.g. tomography). We demonstrate this technique through application to surface-wave recordings from long-running seismic stations throughout western Canada. Our results for over 10 000 station pairs reveal first-order tectonic features consistent with previous studies, which provides confidence in our approach as well as an initial step towards resolving a full 3-D seismic velocity model for the region. This work also presents a foundation for the inversion of surface-wave phase spectra to estimate 3-D Earth structure directly. Finally, the ideas presented in this work are not limited to the inversion of surface-wave phase spectra, but can also be considered for Bayesian geophysical inversion of any circular quantities.

Gosselin, Jeremy M. (ORCID:0000000203754102)↗

Origin of light-induced metastability in ZrTe 5

Here we study the nonequilibrium electronic structure of a model Dirac semimetal ZrTe 5 by using time-and-angle resolved photoemission spectroscopy and density functional theory–based electron and phonon calculations. By measuring the electronic dispersion near the Γ point at time delays up to 10 picoseconds, we discovered that the band spectral weight does not recover during the measured temporal window, revealing the existence of a light-induced metastable state in the electronic structure of this material. Our calculations find that the photoexcited A 1⁢g phonon mode leads to a band renormalization that both supports our experimental observations at the zone center and predicts changes to the band structure outside of our experimental window, ultimately showing the evolution from a direct to an indirect gap semimetal; such band renormalization dramatically reduces the electron-hole recombination rate giving rise to the metastability in this system.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Topological controls on aluminosilicate glass dissolution: Complexities induced in hyperalkaline aqueous environments

Abstract Fly ash, an aluminosilicate composite consisting of disordered (major) and crystalline (minor) compounds, is a low‐carbon alternative that can partially replace ordinary portland cement (OPC) in the binder fraction of concrete. Therefore, understanding the reactivity of fly ash in the hyperalkaline conditions prevalent in concrete is critical to predicting concrete's performance; including setting and strength gain. Herein, temporal measurements of the solution composition (using inductively coupled plasma‐optical emission spectrometry: ICP‐OES) are used to assess the aqueous dissolution rate of monophasic synthetic aluminosilicate glasses analogous to those present in technical fly ashes, under hyperalkaline conditions (10 ≤ pH ≤ 13) across a range of temperatures (25°C ≤ T≤45°C). The dissolution rate is shown to depend on the average number of topological constraints per atom within the glass network (n c , unitless), but this dependence weakens with increasing pH (>10). This is postulated to be on account of: (a) time‐dependent changes in the glass’ surface structure, that is, the number of topological constraints; and/or (b) a change in the dissolution mechanism (eg from network hydrolysis to transport control). The results indicate that the topological description of glass dissolution is most rigorously valid only at very short reaction times (ie at high undersaturations), especially under conditions of hyperalkalinity. These findings provide an improved basis to understand the underlying factors that affect the initial and ongoing reactivity of aluminosilicate glasses such as fly ash in changing chemical environments, for example, when such materials are utilized in cementitious composites.

Oey, Tandré↗

A GPU-based 2D shallow water quality model

In this paper, a 2D shallow water flow solver integrated with a water quality model is presented. The interaction between the main water quality constituents included is based on the Water Quality Analysis Simulation Program. Efficiency is achieved by computing with a combination of a Central Processing Unit (CPU) and a Graphics Processing Unit (GPU) device. This technique is intended to provide robust and accurate simulations with high computation speedups with respect to a single-core CPU in real events. The proposed numerical model is evaluated in cases that include the transport and reaction of water quality components over irregular bed topography and dry–wet fronts, verifying that the numerical solution in these situations conserves the required properties (C-property and positivity). The model can operate in any steady or unsteady form allowing an efficient assessment of the environmental impact of water flows. The field data from an unsteady river reach test case are used to show that the model is capable of predicting the measured temporal distribution of dissolved oxygen and water temperature, proving the robustness and computational efficiency of the model, even in the presence of noisy signals such as wind speed.

54 ENVIRONMENTAL SCIENCES↗

Rapid Memory Footprint Access Diagnostics

Footprint and reuse distance measure temporal locality and therefore do not capture the significance of access patterns (spacial locality). A strided access pattern has the largest possible footprint but usually has the best performance. To highlight exposed memory latency, we separate footprint into strided (prefetchable) and irregular (non-prefetchable) access components and calculate the growth rate of each. To rapidly compute these footprint access diagnostics, we present two methods, whole-program and precise. Current footprint analyses can cause 200× or more slowdown with realistic inputs and are therefore impractical. Our whole-program method reduces the overhead to 10% by computing upper bounds, but still yields inter-procedural insight through a call path profile. Our precise method uses additional static analysis and profiling to refine the upper bounds for intra-procedural loop nests. We evaluate our approaches using benchmarks that vary access patterns (strided \vs unpredictable), sparsity (all words in a cache line \vs some), and reuse (varying and repeated accesses per element). Notably, for loop nests with unpredictable accesses, the precise method's accuracy is within 10% of ideal. The whole-program method has sufficient accuracy to diagnose bottlenecks.

data locality, memory footprint, footprint access ↗

Development of spatially and temporally resolved electron density measurements for the assessment of radiation hydrodynamics simulations of laboratory X-ray photoionized plasmas

The photoionized plasma gas cell experiment is an established platform we use to make at-parameter (ξ > > 1 ergs cm s –1 ) measurements of plasma properties with application to high-energy astrophysical systems. We model the experiments with 1D radiation hydrodynamics simulations using the HELIOS-CR code to inform our understanding and assist in the interpretation of results. The simulations predict that the bulk of the plasma is in a quasi-uniform and hydrodynamically unperturbed state throughout the duration of the experiment. To evaluate this prediction, we introduced a photonic Doppler velocimetry (PDV) diagnostic to measure spatially and temporally resolved plasma electron density. The initial measurements were successful but had limitations that made model-data comparisons challenging. To address this, we re-designed the gas cell PDV diagnostic and doubled the number of measurement locations to sample across two thirds of the depth of the cell. We also present a comparison of the results from the upgraded PDV diagnostic to the HELIOS-CR simulations for the first time. As a result, the experimental data confirms the prediction of an unperturbed region in the bulk of the plasma but reveals discrepancies in the time evolution and spatial distribution of the simulated electron density.

79 ASTRONOMY AND ASTROPHYSICS↗

A multi-channel x-ray temporal diagnostic for measurement of time-resolved electron temperature in cryogenic deuterium–tritium implosions at OMEGA

Electron-temperature (T e ) measurements in implosions provide valuable diagnostic information, as Te is unaffected by residual flows and other non-thermal effects unlike ion temperature inferred from a fusion product spectrum. In OMEGA cryogenic implosions, measurement of T e (t) can be used to investigate effects related to time-resolved hot-spot energy balance. The proposed diagnostic utilizes five fast-rise (~15 ps) scintillator channels with distinct x-ray filtering. Furthermore, titanium and stepped aluminum filtering were chosen to maximize detector sensitivity in the 10 keV–20 keV range, as it has been shown that these x rays have similar density and temperature weighting to the emitted deuterium–tritium fusion neutrons. Initial data collected using a prototype nosecone on the existing neutron temporal diagnostic demonstrate the validity of this diagnostic technique. The proposed system will be capable of measuring spatially integrated T e (t) with 20 ps time resolution and <10% uncertainty at peak emission in cryogenic DT implosions.

47 OTHER INSTRUMENTATION↗

Temporal X-ray Reconstruction using Temporal and Spectral Measurements at LCLS

Transverse deflecting structures (TDSs) are widely used in accelerator physics to measure the longitudinal density of particle bunches. When used in combination with a dispersive section, the whole longitudinal phase space density can be imaged. At the Linac Coherent Light Source (LCLS), the installation of such a device downstream of the undulators enables the reconstruction of the X-ray temporal intensity profile by comparing longitudinal phase space distributions with lasing on and lasing off. However, the resolution of this TDS is limited to around 1 fs rms (root mean square), and therefore, it is not possible to resolve single self-amplified spontaneous emission (SASE) spikes within an X-ray photon pulse. By combining the power spectrum from a high resolution photon spectrometer and the temporal structure from the TDS, the overall resolution is enhanced, thus allowing the observation of temporal, single SASE spikes. The combined data from the spectrometer and the TDS is analysed using an iterative algorithm to obtain the actual intensity profile. In this paper, we present some improvements to the reconstruction algorithm as well as real data taken at LCLS.

47 OTHER INSTRUMENTATION↗

Forecasting high-dimensional spatio-temporal systems from sparse measurements

This paper introduces a new neural network architecture designed to forecast high-dimensional spatio-temporal data using only sparse measurements. The architecture uses a two-stage end-to-end framework that combines neural ordinary differential equations (NODEs) with vision transformers. Initially, our approach models the underlying dynamics of complex systems within a low-dimensional space; and then it reconstructs the corresponding high-dimensional spatial fields. Many traditional methods involve decoding high-dimensional spatial fields before modeling the dynamics, while some other methods use an encoder to transition from high-dimensional observations to a latent space for dynamic modeling. In contrast, our approach directly uses sparse measurements to model the dynamics, bypassing the need for an encoder. This direct approach simplifies the modeling process, reduces computational complexity, and enhances the efficiency and scalability of the method for large datasets. We demonstrate the effectiveness of our framework through applications to various spatio-temporal systems, including fluid flows and global weather patterns. Although sparse measurements have limitations, our experiments reveal that they are sufficient to forecast system dynamics accurately over long time horizons. Our results also indicate that the performance of our proposed method remains robust across different sensor placement strategies, with further improvements as the number of sensors increases. This robustness underscores the flexibility of our architecture, particularly in real-world scenarios where sensor data is often sparse and unevenly distributed.

97 MATHEMATICS AND COMPUTING↗

Detecting dark matter substructures on small scales with fast radio bursts

The matter power spectrum is only weakly constrained on subgalactic scales, while physics beyond the Standard Model can leave unique imprints, especially on sub-parsec scales. We propose measuring the arrival-time difference of fast radio bursts (FRBs) along two adjacent sightlines as a new probe to dark matter substructures on scales down to ∼ 1 AU . We discuss two observational scenarios in which it may be possible to place interesting constraints on such models through the monitoring of repeating FRB sources: (i) By sending radio receivers to space to form a baseline of tens of AU or more and measuring the temporal variation of the arrival-time difference between receivers. (ii) By measuring the temporal variation of the arrival-time difference between two lensed images of one strongly lensed repeater. In both scenarios, obtaining interesting constraints requires correlating the voltage time series to measure the radio signal arrival time to sub-nanosecond precision. We find that two radio dishes separated by 20 AU may be sensitive to the enhancement of small-scale structures at ∼ 10 - 8 M ⊙ masses in the QCD axion dark matter scenario, or from an early epoch of matter domination with a reheating temperature up to 60 MeV. Other dark matter models, such as those composed of ∼ 10 - 13 M ⊙ primordial black holes produced during inflation, would also be probed by this method. We further show that a strong lensing situation of multiple images provides an equivalent ∼ 2000 AU ( σ v / 10 3 km s - 1 ) ( δ t / 10 yr ) baseline, for a typical velocity of dark matter substructures σ v and an observational time span δ . This is much more sensitive, but with the uncertainty that intervening decoherence from the interstellar medium may degrade the timing precision, and that spatial variation in the FRB emission spot may result in confounding signals. We show that the lensing magnifications of Type Ia supernovae constrain a similar quantity to such FRB timing, with present limits being equivalent to ruling out the same parameter space that would be probed by a 0.14 AU baseline.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Real-Time Measurements of Gas-Phase Medium-Chain Chlorinated Paraffins Reveal Daily Changes in Gas-Particle Partitioning Controlled by Ambient Temperature

Chlorinated paraffins (CPs) are synthetic polychlorinated n-alkanes produced as mixtures of a range of C x Cl y H 2x–y+2 formulas. CPs have numerous industrial applications but are toxic, long-lived, and environmentally ubiquitous with environmental releases occurring throughout their production, use, and disposal. Short-chain chlorinated paraffins (SCCPs, C 10–13 ) have been regulated by the United States Environmental Protection Agency since 2009 and by the Stockholm Convention since 2017. SCCP regulation is expected to cause increased production of medium-chain chlorinated paraffins (MCCPs; C 14–17 ), which are currently under consideration for Stockholm Convention regulations. Thus, there is a need to improve the understanding of MCCP environmental transport, distribution, and fate. Existing measurements are limited in their spatial and temporal coverage. Measurements of CP atmospheric loading are particularly scarce. Historically, these measurements have required long sampling times, obscuring the temporal behavior of atmospheric CPs. We report real-time in situ measurements of 18 gas-phase MCCPs. These measurements were made in the United States Southern Great Plains with nitrate ion chemical ionization mass spectrometry (NO 3 –CIMS). Here, the estimated average lower-limit concentration of MCCPs is on the order of single-digit ng/m 3 . MCCP diel behavior is partially explained by gas-particle partitioning with implications for MCCP transport and lifetimes.

54 ENVIRONMENTAL SCIENCES↗

Comparison of laser-produced plasma spatio-temporal electron density evolution measured using interferometry with simulation results

Due to the difficulties associated with experimental measurements of laser-produced plasma (LPP) properties during the earliest stages of plasma evolution, radiation hydrodynamic codes are often used. However, although these codes have been extensively validated in the higher intensity regimes, validation at low to moderate intensities has been limited. In this study, the spatio-temporal electron density evolution in an LPP generated at moderate laser intensities and at various laser wavelengths was validated against the FLASH code for times up to 20 ns. The LPP was generated by focusing the fundamental and various harmonics radiation (1064, 532, and 266 nm) from a 6 ns full width half maximum Nd:YAG laser, at a laser intensity of 10 GW cm -2 , onto a copper target. The spatio-temporal density evolution of the expanding plasma was analyzed using Nomarski interferometry. Experimental measurements were found to be consistent with FLASH simulations, and the dependence of electron densities on wavelength was found to be in agreement with analytical models, varying as n e ∝ λ -0.7 . However, slight differences were noted in the widths and shape functions of the experimental and simulated electron density profiles.

2D fast imaging↗

The phase-2 particle x-ray temporal diagnostic for simultaneous measurement of multiple x-ray and nuclear emission histories from OMEGA implosions (invited)

Electron-temperature (T e ) measurements in implosions provide valuable diagnostic information, as T e is negligibly affected by residual flows and other non-thermal effects unlike ion-temperature inferred from a fusion product spectrum. In OMEGA cryogenic implosions, measurement of T e (t) can be used to investigate effects related to time-resolved hot-spot energy balance. The newly implemented phase-2 Particle X-ray Temporal Diagnostic (PXTD) utilizes four fast-rise (~15 ps) scintillator-channels with distinct x-ray filtering. Titanium and stepped aluminum filtering were chosen to maximize detector sensitivity in the 10–20 keV range, as it has been shown that these x rays have similar density and temperature weighting to the emitted deuterium–tritium fusion neutrons (DTn) from OMEGA Cryo-DT implosions. High quality data have been collected from warm implosions at OMEGA. These data have been used to infer spatially integrated T e (t) with <10% uncertainty at peak emission. Nuclear and x-ray emission histories are measured with 10 ps relative timing uncertainty for x rays and DTn and 12 ps for x rays and deuterium- 3 He protons (D 3 Hep). A future upgrade to the system will enable spatially integrated T e (t) with 40 ps time-resolution from cryogenic DT implosions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Multiframe X-ray diffraction on the OMEGA EP laser

A method of measuring multiple temporally resolved powder x-ray diffraction measurements during a single dynamic compression laser experiment has been demonstrated on the OMEGA EP laser. Up to four time-gated snapshots of the x-ray diffraction pattern are collected on an ultrafast x-ray framing camera with a 2θ scattering angle coverage of 48°–65° and 400-ps temporal resolution with the potential for 10°–160° and 200-ps resolution. X-ray diffraction snapshots capture the transformation to a high-pressure β phase in ramp-compressed Zr, constraining the atomic structure and pressure–density equation-of-state in a single shot. Here, this platform will be used to constrain transition pressures, understand the role of kinetics, and verify the existence of hysteresis and metastability on phase transformations at the lattice level under single-shot dynamic compression.

47 OTHER INSTRUMENTATION↗

ITeM: Independent temporal motifs to summarize and compare temporal networks

We report networks are a fundamental and flexible way of representing various complex systems. Many domains such as communication, citation, procurement, biology, social media, and transportation can be modeled as a set of entities and their relationships. Temporal networks are a specialization of general networks where every relationship occurs at a discrete time. The temporal evolution of such networks is as important to understand as the structure of the entities and relationships. We present the Independent Temporal Motif (ITeM) to characterize temporal graphs from different domains. ITeMs can be used to model the structure and the evolution of the graph. In contrast to existing work, ITeMs are edge-disjoint directed motifs that measure the temporal evolution of ordered edges within the motif. For a given temporal graph, we produce a feature vector of ITeM frequencies and the time it takes to form the ITeM instances. We apply this distribution to measure the similarity of temporal graphs. We show that ITeM has higher accuracy than other motif frequency-based approaches. We define various ITeM-based metrics that reveal salient properties of a temporal network. We also present importance sampling as a method to efficiently estimate the ITeM counts. We present a distributed implementation of the ITeM discovery algorithm using Apache Spark and GraphFrame. We evaluate our approach on both synthetic and real temporal networks.

97 MATHEMATICS AND COMPUTING↗

Efficient Loads Surrogates for Waked Turbines in an Array

Accurately and efficiently predicting wind turbine structural loading is a crucial step in wind farm design. Without considering structural loading, wind farm optimization could negatively impact turbine fatigue and ultimate loads, especially for waked and partially waked turbines, which could result in higher maintenance costs and reduced turbine lifetime. However, predicting turbine loads throughout an array is a costly step, as these quantities require time-accurate results across long time histories, which is often intractable for large array optimization. Therefore, surrogate models that link array spacing to load outputs are often used, but the surrogates are then unique to the inflow conditions and array configurations in the training library. This work develops surrogate models for many wind turbine load outputs based solely on rotor plane velocity measurements, with no required input about array configuration or freestream inflow parameters. Surrogate models were constructed for many turbine quantities of interest (QoI), considering mean, standard deviation, ultimate, and fatigue loads. In general, most QoI statistics were accurately captured, as measured by predicted vs. actual correlation coefficient, confirming the suitability of the approach. Temporal mean values of the QoI required only temporal mean measurements of the rotor plane inflow velocity. However, accurate prediction of temporal standard deviation, ultimate, and fatigue values of QoI also required temporal standard deviations of the rotor plane velocity field. Poor surrogate performance was observed when too many correlated inputs were used, such as multiple velocity components. If the fewest inflow parameters are used to construct the surrogates, the average correlation coefficient value for all output QoI statistics is 0.89. Surrogates for standard deviations and damage equivalent loads (DELs) of turbine QoIs generally had lower accuracy and tower-base and shaft load channels posed the most difficult to capture accurately. The results suggest that these surrogates could be easily paired with analytic wake models, which are frequently used for pre-construction wind farm array optimization, to account for turbine loading in addition to power production. By including the optimal inflow conditions, the surrogate accuracy can improve to an average correlation coefficient value for all output QoI statistics of 0.92. This work has established the ability to build accurate surrogates for mean, standard deviation, ultimate load, and DEL turbine QoI values based on the rotor plane inflow velocity, and identified which inflow conditions lead to greater surrogate accuracy.

17 WIND ENERGY↗