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At least 1,117 records · Page 62

Ammonia generation in Ns pulse and Ns pulse/RF discharges over a catalytic surface

Plasma-catalytic ammonia synthesis in a ns pulse discharge and a 'hybrid' ns pulse/RF discharge in plane-to-plane geometry is studied by Fourier Transform infrared absorption spectroscopy. The data are taken in a preheated H 2 –N 2 mixture, with and without Ni/γ-Al 2 O 3 or Co/γ-Al 2 O 3 catalyst placed in the discharge section. The measurement results are taken using two different approaches. The first is a 'single-stage' process, where a ns pulse discharge in the H 2 –N 2 mixture is sustained continuously. In this case, the ammonia yield increases slowly, over a period of tens of minutes. The second is a 'two-stage' process, where the catalyst is first activated by the ns pulse discharge sustained in pure nitrogen, and then the activated catalyst is exposed to the H 2 –N 2 flow, with or without the discharge. In this case, a strong overshoot of the NH 3 number density at the reactor exit is detected, by over a factor of two compared to the single-stage process. After the initial overshoot, the ammonia yield gradually decreases to the 'single stage' value (with the discharge on), or to near zero (with the discharge off). The results demonstrate that the ammonia yield in the plasma-catalytic reactor is controlled by the N atom accumulation on the catalyst surface, which reacts with H atoms thermally dissociated on the catalyst or generated in the plasma. The results also show that the plasma-catalytic ammonia yield is significantly higher compared to that in the ns pulse discharge without the catalyst. The accumulation of H atoms on the catalyst, with their subsequent reactions with N atoms generated in the plasma, is of relatively minor importance at the present conditions. An additional series of measurements was made with a sub-breakdown RF waveform overlapped with the ns pulse discharge train, to enhance the vibrational excitation of nitrogen. The ammonia yield measured with the RF waveform added is approximately 20% higher compared to that at the baseline ns pulse discharge conditions, both with and without the catalyst. This effect is weaker compared to that of the catalyst activation by N atoms. Additional data are necessary to isolate the possible effect of the vibrationally excited N 2 molecules on the ammonia synthesis in the plasma catalytic reactions.

surface reactions↗

Developing new analysis tools for near surface radio-based neutrino detectors

The ARIANNA experiment is an Askaryan radio detector designed to measure high-energy neutrino induced cascades within the Antarctic ice. Ultra-high-energy neutrinos above 10 16 eV have an extremely low flux, so experimental data captured at trigger level need to be classified correctly to retain as much neutrino signal as possible. We first describe two new physics-based neutrino selection methods, or "cuts", (the updown and dipole cut) that extend the previously published analysis to a specialized ARIANNA station with 8 antenna channels, which is double the number used in the prior analysis. For a standard trigger with a threshold signal to noise ratio at 4.4, the new cuts produce a neutrino efficiency of > 95% per station-year of operation, while rejecting 99.93% of the background (corresponding to 53 remaining experimental background events). When the new cuts are combined with a previously developed cut using neutrino waveform templates, all background is removed at no change of efficiency. In addition, the neutrino efficiency is extrapolated to 1,000 station-years of operation, obtaining 91%. This work then introduces a new selection method (the deep learning cut) to augment the identification of neutrino events by using deep learning methods and compares the efficiency to the physics-based analysis. The deep learning cut gives 99% signal efficiency per station-year of operation while rejecting 99.997% of the background (corresponding to 2 remaining experimental background events), which are subsequently removed by the waveform template cut at no significant change in efficiency. Here the results of the deep learning cut were verified using measured cosmic rays which shows that the simulations do not introduce artifacts with respect to experimental data. The paper demonstrates that the background rejection and signal efficiency of near surface antennas meets the requirements of a large scale future array, as considered in baseline design of the radio component of IceCube-Gen2.

97 MATHEMATICS AND COMPUTING↗

The electronics and data acquisition system for the DarkSide-50 veto detectors

DarkSide-50 is a detector for dark matter candidates in the form of weakly interacting massive particles. It utilizes a liquid argon time projection chamber for the inner main detector, surrounded by a liquid scintillator veto (LSV) and a water Cherenkov veto detector (WCV). The LSV and WCV act as the neutron and cosmogenic muon veto detectors for DarkSide-50. This paper describes the electronics and data acquisition system used for these two detectors. The system is made of a custom built front end electronics and commercial National Instruments high speed digitizers. The front end electronics, the DAQ, and the trigger system have been used to acquire data in the form of zero-suppressed waveform samples from the 110 PMTs of the LSV and the 80 PMTs of the WCV. The veto DAQ system has proven its performance and reliability. This electronics and DAQ system can be scaled and used as it is for the veto of the next generation DarkSide-20k detector.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

The electronics, trigger and data acquisition system for the liquid argon time projection chamber of the DarkSide-50 search for dark matter

The DarkSide-50 experiment at the Laboratori Nazionali del Gran Sasso is a search for dark matter using a dual phase time projection chamber with 50 kg of low radioactivity argon as target. Light signals from interactions in the argon are detected by a system of 38 photo-multiplier tubes (PMTs), 19 above and 19 below the TPC volume inside the argon cryostat. We describe the electronics which processes the signals from the photo-multipliers, the trigger system which identifies events of interest, and the data-acquisition system which records the data for further analysis. The electronics include resistive voltage dividers on the PMTs, custom pre-amplifiers mounted directly on the PMT voltage dividers in the liquid argon, and custom amplifier/discriminators (at room temperature). After amplification, the PMT signals are digitized in CAEN waveform digitizers, and CAEN logic modules are used to construct the trigger, the data acquisition system for the TPC is based on the Fermilab "artdaq" software. The system has been in operation since early 2014.

Agnes, P.↗

Deep neural networks for energy and position reconstruction in EXO-200

Here, we apply deep neural networks (DNN) to data from the EXO-200 experiment. In the studied cases, the DNN is able to reconstruct the relevant parameters—total energy and position—directly from raw digitized waveforms, with minimal exceptions. For the first time, the developed algorithms are evaluated on real detector calibration data. The accuracy of reconstruction either reaches or exceeds what was achieved by the conventional approaches developed by EXO-200 over the course of the experiment. Most existing DNN approaches to event reconstruction and classification in particle physics are trained on Monte Carlo simulated events. Such algorithms are inherently limited by the accuracy of the simulation. We describe a unique approach that, in an experiment such as EXO-200, allows to successfully perform certain reconstruction and analysis tasks by training the network on waveforms from experimental data, either reducing or eliminating the reliance on the Monte Carlo.

97 MATHEMATICS AND COMPUTING↗

Multi-channel front-end ASIC for a 3D position-sensitive detector

Arrays of 3D position-sensitive detectors (3DPSD), operating at room temperature and using cadmium zinc telluride (CZT) and thallium bromide (TIBr) sensors, are suitable for gamma-ray spectrometry in many applications. One detector configuration, the 3D position-sensitive Virtual Frisch-Grid detector (VFG), is particularly advantageous for integrating into large area arrays. The signals generated inside each detector of the array are captured with the anode, cathode and four pads that enable the reconstruction of the position and energy of the ionizing interaction by measurements of amplitude and timing of the signals. For these applications, a low-noise front-end ASIC has been developed, capable of processing bipolar signals (needed because of AC-coupling of certain electrodes). The ASIC can be coupled to an ADC in order to form a compound “waveform digitizer” capable of post-processing the analog signals and determining amplitude and timing information. This paper describes a 32-channel front-end ASIC that is suitable for reading out a 3 × 3 or 4 × 4 element matrix in the VFG configuration. Each channel is composed of a low-noise charge amplifier with an adaptive continuous reset feedback circuit suitable for both positive and negative charge, a first order shaper and a single-to-differential converter output stage. Voltage and current references are all internally generated by 10-bit DACs and the chip is fully controllable with the I 2 C communication protocol. The readout channel response has been verified using the implemented injection circuit. Linear behavior up to ~75 ke ± with the gain of ~80 mV/fC, and up to ~200 ke ± with the gain of ~30 mV/fC was demonstrated. In conclusion, the first test result waveforms using a 137 Cs radioactive source on a 5 × 5 × 12 mm 3 TIBr crystal are reported.

47 OTHER INSTRUMENTATION↗

GRAPH — an readout ASIC for large MCP based detectors

We present a programmable 16 channel, mixed signal, low power readout ASIC, having the project historically named Gigasample Recorder of Analog waveforms from a PHotodetector (GRAPH). It is designed to read large aperture single photon imaging detectors using micro channel plates for charge multiplication, and measuring the detector's response on crossed strips anodes to extrapolate the incoming photon position. Each channel consists of a fast, low power and low noise charge sensitive amplifier, which provides a myriad of coarse and fine programmable options for gain and shaping settings. Further, the amplified signal is recorded using, to our knowledge novel, the Hybrid Universal sampLing Architecture (HULA) ADC. A kind of mixed signal double buffer memory, that enables concurrent waveform recording, and selected event digitized data extraction. The sampling frequency is freely adjustable between few kHz up to 125 MHz, while the chip's internal digital memory holds a history 2048 samples for each channel, with a digital headroom of 12 bits. An optimized region of interest sample-read algorithm allows to extract the information just around the event pulse peak, while selecting the next event, thus substantially reducing the operational dead time. The chip is designed in 130 nm TSMC CMOS technology, and its power consumption is around 47 mW per channel.

47 OTHER INSTRUMENTATION↗

Discrete solitons and vortices in anisotropic hexagonal and honeycomb lattices

We consider the self-focusing discrete nonlinear Schrödinger equation on hexagonal and honeycomb lattice geometries. Our emphasis is on the study of the effects of anisotropy, motivated by the tunability afforded in recent optical and atomic physics experiments. We find that multi-soliton and discrete vortex states undergo destabilizing bifurcations as the relevant anisotropy control parameter is varied. Furthermore, we quantify these bifurcations by means of explicit analytical calculations of the solutions, as well as of their spectral linearization eigenvalues. Finally, we corroborate the relevant stability picture through direct numerical computations. In the latter, we observe the prototypical manifestation of these instabilities to be the spontaneous rearrangement of the solution, for larger values of the coupling, into localized waveforms typically centered over fewer sites than the original unstable structure. In weak coupling, the instability appears to result in a robust breathing of the relevant waveforms.

97 MATHEMATICS AND COMPUTING↗

A HYBRID MODE MODEL OF THE BLAZHKO EFFECT, SHOWN TO ACCURATELY FIT KEPLER DATA FOR RR Lyr

The waveform for Blazhko stars can be substantially different during the ascending and descending parts of the Blazhko cycle. A hybrid model, consisting of two component oscillators of the same frequency, is proposed as a means to fit the data over the entire cycle. One component exhibits a sawtooth-like velocity waveform while the other is nearly sinusoidal. One method of generating such a hybrid is presented: a nonlinear model is developed for the first overtone mode, which, if excited to large amplitude, is found to drop strongly in frequency and become highly non-sinusoidal. If the frequency drops sufficiently to become equal to the fundamental frequency, the two can become phase locked and form the desired hybrid. A relationship is assumed between the hybrid mode velocity and the observed light curve, which is approximated as a power series. An accurate fit of the hybrid model is made to actual Kepler data for RR Lyr. The sinusoidal component may tend to stabilize the period of the hybrid which is found in real Blazhko data to be extremely stable. It is proposed that the variations in amplitude and phase might result from a nonlinear interaction with a third mode, possibly a nonradial mode at 3/2 the fundamental frequency. The hybrid model also applies to non-Blazhko RRab stars and provides an explanation for the light curve bump. A method to estimate the surface gravity is also proposed.

79 ASTRONOMY AND ASTROPHYSICS↗

Physics-inspired spatiotemporal-graph AI ensemble for the detection of higher order wave mode signals of spinning binary black hole mergers

We present a new class of AI models for the detection of quasi-circular, spinning, non-precessing binary black hole mergers whose waveforms include the higher order gravitational wave modes ($\ell$, |m|) = {(2,2), (2,1), (3,3), (3,2), (4,4)}, and mode mixing effects in the $\ell$ = 3, |m| = 2 harmonics. These AI models combine hybrid dilated convolution neural networks to accurately model both short- and long-range temporal sequential information of gravitational waves; and graph neural networks to capture spatial correlations among gravitational wave observatories to consistently describe and identify the presence of a signal in a three detector network encompassing the Advanced LIGO and Virgo detectors. We first trained these spatiotemporal-graph AI models using synthetic noise, using 1.2 million modeled waveforms to densely sample this signal manifold, within 1.7 h using 256 NVIDIA A100 GPUs in the Polaris supercomputer at the Argonne Leadership Computing Facility. This distributed training approach exhibited optimal classification performance, and strong scaling up to 512 NVIDIA A100 GPUs. With these AI ensembles we processed data from a three detector network, and found that an ensemble of 4 AI models achieves state-of-the-art performance for signal detection, and reports two misclassifications for every decade of searched data. We distributed AI inference over 128 GPUs in the Polaris supercomputer and 128 nodes in the Theta supercomputer, and completed the processing of a decade of gravitational wave data from a three detector network within 3.5 h. Finally, we fine-tuned these AI ensembles to process the entire month of February 2020, which is part of the O3b LIGO/Virgo observation run, and found 6 gravitational waves, concurrently identified in Advanced LIGO and Advanced Virgo data, and zero false positives. This analysis was completed in one hour using one NVIDIA A100 GPU.

79 ASTRONOMY AND ASTROPHYSICS↗

Precise relative magnitude measurement improves fracture characterization during hydraulic fracturing

SUMMARY Microseismic monitoring is an important technique to obtain detailed knowledge of in-situ fracture size and orientation during stimulation to maximize fluid flow throughout the rock volume and optimize production. Furthermore, considering that the frequency of earthquake magnitudes empirically follows a power law (i.e. Gutenberg–Richter), the accuracy of microseismic event magnitude distributions is potentially crucial for seismic risk management. In this study, we analyse microseismicity observed during four hydraulic fracture treatments of the legacy Cotton Valley experiment in 1997 at the Carthage gas field of East Texas, where fractures were activated at the base of the sand-shale Upper Cotton Valley formation. We perform waveform cross-correlation to detect similar event clusters, measure relative amplitude from aligned waveform pairs with a principal component analysis, then measure precise relative magnitudes. The new magnitudes significantly reduce the deviations between magnitude differences and relative amplitudes of event pairs. This subsequently reduces the magnitude differences between clusters located at different depths. Reduction in magnitude differences between clusters suggests that some attenuation-related biases could be effectively mitigated with relative magnitude measurements. The maximum likelihood method is applied to understand the magnitude frequency distributions and quantify the seismogenic index of the clusters. Statistical analyses with new magnitudes suggest that fractures that are more favourably oriented for shear failure have lower b-value and higher seismogenic index, suggesting higher potential for relatively larger earthquakes, rather than fractures subparallel to maximum horizontal principal stress orientation.

58 GEOSCIENCES↗

MTUQ: a framework for estimating moment tensors, point forces, and their uncertainties

SUMMARY We introduce MTUQ, an open-source Python package for seismic source estimation and uncertainty quantification, emphasizing flexibility and operational scalability. MTUQ provides MPI-parallelized grid search and global optimization capabilities, compatibility with 1-D and 3-D Green’s function database formats, customizable data processing, C-accelerated waveform and first-motion polarity misfit functions, and utilities for plotting seismic waveforms and visualizing misfit and likelihood surfaces. Applicability to a range of full- and constrained-moment tensor, point force, and centroid inversion problems is possible via a documented application programming interface, accompanied by example scripts and integration tests. We demonstrate the software using three different types of seismic events: (1) a 2009 intraslab earthquake near Anchorage, Alaska; (2) an episode of the 2021 Barry Arm landslide in Alaska; and (3) the 2017 Democratic People’s Republic of Korea underground nuclear test. With these events, we illustrate the well-known complementary character of body waves, surface waves, and polarities for constraining source parameters. We also convey the distinct misfit patterns that arise from each individual data type, the importance of uncertainty quantification for detecting multimodal or otherwise poorly constrained solutions, and the software’s flexible, modular design.

58 GEOSCIENCES↗

Modelling infrasound signal generation from two underground explosions at the Source Physics Experiment using the Rayleigh integral

For this study, we use the Rayleigh integral (RI) as an approximation to the Helmholtz–Kirchoff integral to model infrasound generation and propagation from underground chemical explosions at distances of 250 m out to 5 km as part of the Source Physics Experiment (SPE). Using a sparse network of surface accelerometers installed above ground zero, we are able to accurately create synthetic acoustic waveforms and compare them to the observed data. Although the underground explosive sources were designed to be symmetric, the resulting seismic wave at the surface shows an asymmetric propagation pattern that is stronger to the northeast of the borehole. This asymmetric bias may be attributed to the subsurface geology and faulting of the area and is observed in the acoustic waveforms. We compare observed and modelled results from two of the underground SPE tests with a sensitivity study to evaluate the asymmetry observed in the data. This work shows that it is possible to model infrasound signals from underground explosive sources using the RI and that asymmetries observed in the data can be modelled with this technique.

58 GEOSCIENCES↗

An Adaptable Seismic Data Format

We present ASDF, the Adaptable Seismic Data Format, a modern and practical data format for all branches of seismology and beyond. The growing volume of freely available data coupled with ever expanding computational power opens avenues to tackle larger and more complex problems. Current bottlenecks include inefficient resource usage and insufficient data organization. Properly scaling a problem requires the resolution of both these challenges, and existing data formats are no longer up to the task. ASDF stores any number of synthetic, processed or unaltered waveforms in a single file. A key improvement compared to existing formats is the inclusion of comprehensive meta information, such as event or station information, in the same file. Additionally, it is also usable for any non-waveform data, for example, cross-correlations, adjoint sources or receiver functions. Last but not least, full provenance information can be stored alongside each item of data, thereby enhancing reproducibility and accountability. Any data set in our proposed format is self-describing and can be readily exchanged with others, facilitating collaboration. The utilization of the HDF5 container format grants efficient and parallel I/O operations, integrated compression algorithms and check sums to guard against data corruption. To not reinvent the wheel and to build upon past developments, we use existing standards like QuakeML, StationXML, W3C PROV and HDF5 wherever feasible. Usability and tool support are crucial for any new format to gain acceptance. We developed mature C/Fortran and Python based APIs coupling ASDF to the widely used SPECFEM3D_GLOBE and ObsPy toolkits.

58 GEOSCIENCES↗

Internal structure of the San Jacinto fault zone at Blackburn Saddle from seismic data of a linear array

Local and teleseismic earthquake waveforms recorded by a 180-m-long linear array (BB) with seven seismometers crossing the Clark fault of the San Jacinto fault zone northwest of Anza are used to image a deep bimaterial interface and core damage structure of the fault. Delay times of P waves across the array indicate an increase in slowness from the southwest most (BB01) to the northeast most (BB07) station. Automatic algorithms combined with visual inspection and additional analyses are used to identify local events generating fault zone head and trapped waves. The observed fault zone head waves imply that the Clark fault in the area is a sharp bimaterial interface, with lower seismic velocity on the southwest side. The moveout between the head and direct P arrivals for events within ~40 km epicentral distance indicates an average velocity contrast across the fault over that section and the top 20 km of 3.2 per cent. A constant moveout for events beyond ~40 km to the southeast is due to off-fault locations of these events or because the imaged deep bimaterial interface is discontinuous or ends at that distance. The lack of head waves from events beyond ~20 km to the northwest is associated with structural complexity near the Hemet stepover. Events located in a broad region generate fault zone trapped waves at stations BB04–BB07. Waveform inversions indicate that the most likely parameters of the trapping structure are width of ~200 m, S velocity reduction of 30–40 per cent with respect to the bounding blocks, Q value of 10–20 and depth of ~3.5 km. The trapping structure and zone with largest slowness are on the northeast side of the fault. The observed sense of velocity contrast and asymmetric damage across the fault suggest preferred rupture direction of earthquakes to the northwest. This inference is consistent with results of other geological and seismological studies.

58 GEOSCIENCES↗

Balancing unevenly distributed data in seismic tomography: a global adjoint tomography example

SUMMARY The uneven distribution of earthquakes and stations in seismic tomography leads to slower convergence of nonlinear inversions and spatial bias in inversion results. Including dense regional arrays, such as USArray or Hi-Net, in global tomography causes severe convergence and spatial bias problems, against which conventional pre-conditioning schemes are ineffective. To save computational cost and reduce model bias, we propose a new strategy based on a geographical weighting of sources and receivers. Unlike approaches based on ray density or the Voronoi tessellation, this method scales to large full-waveform inversion problems and avoids instabilities at the edges of dense receiver or source clusters. We validate our strategy using a 2-D global waveform inversion test and show that the new weighting scheme leads to a nearly twofold reduction in model error and much faster convergence relative to a conventionally pre-conditioned inversion. We implement this geographical weighting strategy for global adjoint tomography.

Ruan, Youyi↗

Temporal changes of seismic velocities in the San Jacinto Fault zone associated with the 2016 M w 5.2 Borrego Springs earthquake

We study temporal changes of seismic velocities associated with the 10 June 2016 Mw 5.2 Borrego Springs earthquake in the San Jacinto fault zone, using nine component Green's function estimates reconstructed from daily cross correlations of ambient noise. The analysed data are recorded by stations in two dense linear arrays, at Dry Wash (DW) and Jackass Flat (JF), crossing the fault surface trace ~3 km northwest and southeast of the event epicentre. The two arrays have 9 and 12 stations each with instrument spacing of 25–100 m. Relative velocity changes (δv/v) are estimated from arrival time changes in the daily correlation coda waveforms compared to a reference stack. The obtained array-average δv/v time-series exhibit changes associated with the Borrego Springs event, superposed with seasonal variations. The earthquake-related changes are characterized by a rapid coseismic velocity drop followed by a gradual recovery. This is consistently observed at both arrays using time- and frequency-domain δv/v analyses with data from different components in various frequency bands. Larger changes at lower frequencies imply that the variations are not limited to the near surface material. A decreasing coseismic velocity reduction with coda wave lapse time indicates larger coseismic structural perturbations in the fault zone and near-fault environment compared to the surrounding rock. Observed larger changes at the DW array compared to the JF array possibly reflect the northwestward rupture directivity of the Borrego Springs earthquake.

Geochemistry & Geophysics↗

Superresolution without separation

Abstract This article provides a theoretical analysis of diffraction-limited superresolution, demonstrating that arbitrarily close point sources can be resolved in ideal situations. Precisely, we assume that the incoming signal is a linear combination of $M$ shifted copies of a known waveform with unknown shifts and amplitudes, and one only observes a finite collection of evaluations of this signal. We characterize properties of the base waveform such that the exact translations and amplitudes can be recovered from $2M+1$ observations. This recovery can be achieved by solving a weighted version of basis pursuit over a continuous dictionary. Our analysis shows that $\ell_1$-based methods enjoy the same separation-free recovery guarantees as polynomial root finding techniques, such as de Prony’s method or Vetterli’s method for signals of finite rate of innovation. Our proof techniques combine classical polynomial interpolation techniques with contemporary tools from compressed sensing.

Schiebinger, Geoffrey↗