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NASA NTRS2022

A Waveform Skewness Index for Measuring Time Series Nonlinearity and Its Applications to the ENSO-Indian Monsoon Relationship

Many geophysical time series possess nonlinear characteristics that reflect the underlying physics of the phenomena the time series describe. The nonlinear character of times series can change with time, so it is important to quantify time series nonlinearity without assuming stationarity. A common way of quantifying the time evolution of time series nonlinearity is to compute sliding skewness time series, but it is shown here that such an approach can be misleading when time series contain periodicities. To remedy this deficiency of skewness, a new waveform skewness index is proposed for quantifying local nonlinearities embedded in time series. A waveform skewness spectrum is proposed for determining the frequency components that are contributing to time series waveform skewness. The new methods are applied to the El Niño–Southern Oscillation (ENSO) and the Indian monsoon to test a recently proposed hypothesis that states that changes in the ENSO–Indian monsoon relationship are related to ENSO nonlinearity. We show that the ENSO–Indian rainfall relationship weakens during time periods of high ENSO waveform skewness. The results from two different analyses suggest that the breakdown of the ENSO–Indian monsoon relationship during time periods of high ENSO waveform skewness is related to the more frequent occurrence of strong central Pacific El Niño events, supporting arguments that changes in the ENSO–Indian rainfall relationship are not solely related to noise.

Justin Schulte↗
DOE OSTI2020

A space-time parallel algorithm with adaptive mesh refinement for computational fluid dynamics

This work describes a space-time parallel algorithm with space-time adaptive mesh refinement (AMR). AMR with subcycling is added to multigrid reduction-in-time (MGRIT) in order to provide solution efficient adaptive grids with a reduction in work performed on coarser grids. This algorithm is achieved by integrating two software libraries: XBraid (Parallel time integration with multigrid. https://computation.llnl.gov/projects/parallel-timeintegration-multigrid) and Chombo (Chombo software package for AMR applications—design document, 2014). The former is a parallel time integration library using multigrid and the latter is a massively parallel structured AMR library. Employing this adaptive space-time parallel algorithm is Chord (Comput Fluids 123:202–217, 2015), a computational fluid dynamics (CFD) application code for solving compressible fluid dynamics problems. For the same solution accuracy, speedups are demonstrated from the use of space-time parallelization over the time-sequential integration on Couette flow and Stokes’ second problem. On a transient Couette flow case, at least a 1.5× speedup is achieved, and with a time periodic problem, a speedup of up to 13.7× over the time-sequential case is obtained. In both cases, the speedup is achieved by adding processors and exploring additional parallelization in time. The numerical experiments show the algorithm is promising for CFD applications that can take advantage of the time parallelism. Future work will focus on improving the parallel performance and providing more tests with complex fluid dynamics to demonstrate the full potential of the algorithm.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Multi-time wave functions for quantum field theory

Multi-time wave functions such as ϕ(t{sub 1},x{sub 1},…,t{sub N},x{sub N}) have one time variable t{sub j} for each particle. This type of wave function arises as a relativistic generalization of the wave function ψ(t,x{sub 1},…,x{sub N}) of non-relativistic quantum mechanics. We show here how a quantum field theory can be formulated in terms of multi-time wave functions. We mainly consider a particular quantum field theory that features particle creation and annihilation. Starting from the particle–position representation of state vectors in Fock space, we introduce multi-time wave functions with a variable number of time variables, set up multi-time evolution equations, and show that they are consistent. Moreover, we discuss the relation of the multi-time wave function to two other representations, the Tomonaga–Schwinger representation and the Heisenberg picture in terms of operator-valued fields on space–time. In a certain sense and under natural assumptions, we find that all three representations are equivalent; yet, we point out that the multi-time formulation has several technical and conceptual advantages. -- Highlights: •Multi-time wave functions are manifestly Lorentz-covariant objects. •We develop consistent multi-time equations with interaction for quantum field theory. •We discuss in detail a particular model with particle creation and annihilation. •We show how multi-time wave functions are related to the Tomonaga–Schwinger approach. •We show that they have a simple representation in terms of operator valued fields.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Time Resolution Measurements of EJ-232Q With Single- and Dual-Sided Readouts

In view of its importance to applications in high energy physics, nuclear security, and time-of-flight PET, the time resolution of 0.5% benzophenone-quenched EJ-232Q plastic scintillators of various lengths was studied using a fast waveform digitizer and fast PMTs. The scintillator sizes were 5 mm × 5 mm × 10, 25, 50, 75, or 100 mm. First, the timing measurements were performed by using a single PMT reading out one end. The degradation in time resolution with increasing scintillator length was studied. The irradiation geometry was also observed to have a non-negligible impact on the time resolution due to the variation of depth-of-interaction positions, especially for the scintillators with a high aspect ratio. Second, two PMTs were employed for a dual-sided readout. This readout together with the mean time method was demonstrated to be an effective approach to improve the timing performance since the depth-of-interaction-related effect was considerably mitigated. A time resolution of 79 ± 1 ps (full-width at half-maximum) has been achieved for the 5 × 5 × 10 mm 3 scintillator. The 5 × 5 × 100 mm 3 scintillator can still provide a time resolution as good as 172 ± 1 ps. Here, the energy range used for each was between 340 keVee and 450 keVee. In addition, the time information from individual PMTs in a dual-sided readout was able to show a time resolution almost identical to that determined with the mean-time-based technique after correcting for the depth-of-interaction variation for the 100 mm long scintillator.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

Space–Time Least-Squares Petrov–Galerkin Projection for Nonlinear Model Reduction

This work proposes a space--time least-squares Petrov--Galerkin (ST-LSPG) projection method for model reduction of nonlinear dynamical systems. In contrast to typical nonlinear model-reduction methods that first apply (Petrov--)Galerkin projection in the spatial dimension and subsequently apply time integration to numerically resolve the resulting low-dimensional dynamical system, the proposed method applies projection in space and time simultaneously. To accomplish this, the method first introduces a low-dimensional space--time trial subspace, which can be obtained by computing tensor decompositions of state-snapshot data. The method then computes discrete-optimal approximations in this space--time trial subspace by minimizing the residual arising after time discretization over all space and time in a weighted $\ell^2$-norm. This norm can be defined to enable complexity reduction (i.e., hyper-reduction) in time, which leads to space--time collocation and space--time Gauss--Newton with Approximated Tensors (GNAT) variants of the ST-LSPG method. Advantages of the approach relative to typical spatial-projection-based nonlinear model reduction methods such as Galerkin projection and least-squares Petrov--Galerkin projection include a reduction of both the spatial and temporal dimensions of the dynamical system, and a priori error bounds that bound the solution error by the best space--time approximation error and whose stability constants exhibit slower growth in time. Numerical examples performed on model problems in fluid dynamics demonstrate the ability of the method to generate orders-of-magnitude computational savings relative to spatial-projection-based reduced-order models without sacrificing accuracy for a fixed spatio-temporal discretization.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

CAN LARGE TIME DELAYS OBSERVED IN LIGHT CURVES OF CORONAL LOOPS BE EXPLAINED IN IMPULSIVE HEATING?

The light curves of solar coronal loops often peak first in channels associated with higher temperatures and then in those associated with lower temperatures. The delay times between the different narrowband EUV channels have been measured for many individual loops and recently for every pixel of an active region observation. The time delays between channels for an active region exhibit a wide range of values. The maximum time delay in each channel pair can be quite large, i.e., >5000 s. These large time delays make-up 3%–26% (depending on the channel pair) of the pixels where a trustworthy, positive time delay is measured. It has been suggested that these time delays can be explained by simple impulsive heating, i.e., a short burst of energy that heats the plasma to a high temperature, after which the plasma is allowed to cool through radiation and conduction back to its original state. In this paper, we investigate whether the largest observed time delays can be explained by this hypothesis by simulating a series of coronal loops with different heating rates, loop lengths, abundances, and geometries to determine the range of expected time delays between a set of four EUV channels. We find that impulsive heating cannot address the largest time delays observed in two of the channel pairs and that the majority of the large time delays can only be explained by long, expanding loops with photospheric abundances. Additional observations may rule out these simulations as an explanation for the long time delays. We suggest that either the time delays found in this manner may not be representative of real loop evolution, or that the impulsive heating and cooling scenario may be too simple to explain the observations, and other potential heating scenarios must be explored.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRSDate not supplied

Optical Time Transfer for Bistatic SAR Spacecraft

A spacecraft-to-spacecraft optical time-transfer simulation has been developed as a tool for informing NASA’s Surface Deformation and Change (SDC) mission architecture. The SDC mission will combine radar images from multiple spacecraft to improve understanding of the Earth’s sea-level and landscape changes. Spacecraft must be precisely synchronized in order to create sharp radar images. Simulation of multiple spacecraft time-synchronizing via laser communication can inform technology choices of a mission by providing a picosecond-precision level estimate of clock error. This timing and ranging simulation has been combined with a radar system performance analysis pipeline. The simulated timing errors are used to predict performance of bistatic SAR systems in the presence of oscillator noise and time synchronization in accuracy. This analysis includes both analytic approximation equations from existing literature, and a numerical radar simulation to extract key system performance parameters like phase error and signal-to-noise ratio (SNR)degradation. Precision time-transfer techniques facilitate the accurate synchronization of clocks between any combination of terminals. Most time-transfer technology for comparing two clocks at different terminals use radio frequencies (RF) to measure the time delay between the sending and receiving of signals. Laser technology offers the capability to transmit high data rates with systems that are of smaller size and lower power than comparable RF systems. The clocks on independent spacecraft will have some phase and frequency errors between them that result in clock drift. The two clock models that are included in this bi-directional MATLAB simulation are a cesium-based Chip-Scale Atomic Clock (CSAC) and a rubidium-based Miniature Atomic Clock (MAC). The CSAC has flown as hardware for small satellite missions such as the University of Florida’s CHOMPTT mission. A study of example orbits, including that of NASA NASA-ISRO Synthetic Aperture Radar Mission (NISAR) mission, and lasing rates demonstrate the impact of flight configuration parameters on the synchronization error between two spacecraft. The MATLAB timing simulation uses a Runge-Kutta 4th-order method to propagate spacecraft orbits and computes the light-travel time estimate between them. The simulation outputs the estimated range and estimated clock error based on a user-defined spacecraft cluster configuration. The radar simulation and analytic approximations are applied to evaluate a potential future NASA bistatic SAR constellation architecture. In the proposed architecture, satellites follow each other in the same orbit at 800 km altitude, with a 210 km baseline. We also baseline the CSAC as an ultra stable oscillator, and use NASA’s NISAR for baseline radar system parameters to compute a clock-system introduced phase error of 5.6 degrees without synchronization by frequent time transfer. We build on this base case with a sensitivity analysis of radar performance over a proposed range of constellation and radar system parameters. With this analysis pipeline, we comment on which radar parameters should or should not be changed to minimize synchronization requirements. This analysis technique could be extended or modified to evaluate the timing requirements of other geometries for other future multistatic SAR missions, or other interferometric satellite missions.

Surface Deformation and Change↗
DOE OSTI2014

A stabilized Runge–Kutta–Legendre method for explicit super-time-stepping of parabolic and mixed equations

Parabolic partial differential equations appear in several physical problems, including problems that have a dominant hyperbolic part coupled to a sub-dominant parabolic component. Explicit methods for their solution are easy to implement but have very restrictive time step constraints. Implicit solution methods can be unconditionally stable but have the disadvantage of being computationally costly or difficult to implement. Super-time-stepping methods for treating parabolic terms in mixed type partial differential equations occupy an intermediate position. In such methods each superstep takes “s” explicit Runge–Kutta-like time-steps to advance the parabolic terms by a time-step that is s{sup 2} times larger than a single explicit time-step. The expanded stability is usually obtained by mapping the short recursion relation of the explicit Runge–Kutta scheme to the recursion relation of some well-known, stable polynomial. Prior work has built temporally first- and second-order accurate super-time-stepping methods around the recursion relation associated with Chebyshev polynomials. Since their stability is based on the boundedness of the Chebyshev polynomials, these methods have been called RKC1 and RKC2. In this work we build temporally first- and second-order accurate super-time-stepping methods around the recursion relation associated with Legendre polynomials. We call these methods RKL1 and RKL2. The RKL1 method is first-order accurate in time; the RKL2 method is second-order accurate in time. We verify that the newly-designed RKL1 and RKL2 schemes have a very desirable monotonicity preserving property for one-dimensional problems – a solution that is monotone at the beginning of a time step retains that property at the end of that time step. It is shown that RKL1 and RKL2 methods are stable for all values of the diffusion coefficient up to the maximum value. We call this a convex monotonicity preserving property and show by examples that it is very useful in parabolic problems with variable diffusion coefficients. This includes variable coefficient parabolic equations that might give rise to skew symmetric terms. The RKC1 and RKC2 schemes do not share this convex monotonicity preserving property. One-dimensional and two-dimensional von Neumann stability analyses of RKC1, RKC2, RKL1 and RKL2 are also presented, showing that the latter two have some advantages. The paper includes several details to facilitate implementation. A detailed accuracy analysis is presented to show that the methods reach their design accuracies. A stringent set of test problems is also presented. To demonstrate the robustness and versatility of our methods, we show their successful operation on problems involving linear and non-linear heat conduction and viscosity, resistive magnetohydrodynamics, ambipolar diffusion dominated magnetohydrodynamics, level set methods and flux limited radiation diffusion. In a prior paper (Meyer, Balsara and Aslam 2012 [36]) we have also presented an extensive test-suite showing that the RKL2 method works robustly in the presence of shocks in an anisotropically conducting, magnetized plasma.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Characterizing Performance of Freshwater Wetland Methane Models Across Time Scales at FLUXNET-CH 4 Sites Using Wavelet Analyses

Process-based land surface models are important tools for estimating global wetland methane (CH 4 ) emissions and projecting their behavior across space and time. So far there are no performance assessments of model responses to drivers at multiple time scales. In this study, we apply wavelet analysis to identify the dominant time scales contributing to model uncertainty in the frequency domain. We evaluate seven wetland models at 23 eddy covariance tower sites. Our study first characterizes site-level patterns of freshwater wetland CH 4 fluxes (FCH 4 ) at different time scales. A Monte Carlo approach was developed to incorporate flux observation error to avoid misidentification of the time scales that dominate model error. Our results suggest that (a) significant model-observation disagreements are mainly at multi-day time scales (<15 days); (b) most of the models can capture the CH 4 variability at monthly and seasonal time scales (>32 days) for the boreal and Arctic tundra wetland sites but have significant bias in variability at seasonal time scales for temperate and tropical/subtropical sites; (c) model errors exhibit increasing power spectrum as time scale increases, indicating that biases at time scales <5 days could contribute to persistent systematic biases on longer time scales; and (d) differences in error pattern are related to model structure (e.g., proxy of CH 4 production). Our evaluation suggests the need to accurately replicate FCH 4 variability, especially at short time scales, in future wetland CH 4 model developments.

58 GEOSCIENCES↗
DOE OSTI2017

On the importance of minimizing “coast-time” in x-ray driven inertially confined fusion implosions

By the time an inertially confined fusion (ICF) implosion has converged a factor of 20, its surface area has shrunk 400×, making it an inefficient x-ray energy absorber. So, ICF implosions are traditionally designed to have the laser drive shut off at a time, toff, well before bang-time, tBT, for a coast-time of tcoast=tBT−toff>1 ns. High-foot implosions on NIF showed a strong dependence of many key ICF performance quantities on reduced coast-time (by extending the duration of laser power after the peak power is first reached), most notably stagnation pressure and fusion yield. Herein we show that the ablation pressure, pabl, which drives high-foot implosions, is essentially triangular in temporal shape, and that reducing tcoast boosts pabl by as much as ∼2× prior to stagnation thus increasing fuel and hot-spot compression and implosion speed. One-dimensional simulations are used to track hydrodynamic characteristics for implosions with various coast-times and various assumed rates of hohlraum cooling after toff to illustrate how the late-time conditions exterior to the implosion can impact the fusion performance. A simple rocket model-like analytic theory demonstrates that reducing coast-time can lead to a ∼15% higher implosion velocity because the reduction in x-ray absorption efficiency at late-time is somewhat compensated by small (∼5%−10%) ablator mass remaining. Together with the increased ablation pressure, the additional implosion speed for short coast-time implosions can boost the stagnation pressure by ∼2× as compared to a longer coast-time version of the same implosion. Four key dimensionless parameters are identified and we find that reducing coast-time to as little as 500 ps still provides some benefit. Finally, we show how the high-foot implosion data is consistent with the above mentioned picture.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Absolute timing calibration of the Resolve microcalorimeter spectrometer on the X-ray Imaging and Spectroscopy Mission

The Resolve microcalorimeter spectrometer on the X-ray Imaging and Spectroscopy Mission (XRISM) is designed to have a good timing capability with the mission-level requirement of 1 ms as the absolute time tagging accuracy to suffice the needs for observatory science. In the ground calibration campaign, the absolute and relative timing offsets were measured using pulsed X-rays from the modulated X-ray sources. These offsets were used to determine calibration parameters, the Resolve timing coefficients, which are used in the offline correction of event times. In the orbit, reevaluation of the timing coefficients was carried out using the Crab pulsar, which was observed in two periods, one in the performance verification phase and the other in the guest observation phase. We report the absolute timing calibration of XRISM/Resolve using the ground and in-orbit data. Although the requirement is likely satisfied with the ground parameters, the timing coefficients have been refined using the in-orbit calibration to improve the timing accuracy. In addition, for the first time, we present the interpretation of the absolute timing offset originating from the analog and digital processing of X-ray events unique to a microcalorimeter spectrometer and present a complete view of the timing error of the Resolve instrument.

Astronomy and AstroPhysics↗
DOE OSTI2014

Optimizing mini-ridge filter thickness to reduce proton treatment times in a spot-scanning synchrotron system

Purpose: Study the contributors to treatment time as a function of Mini-Ridge Filter (MRF) thickness to determine the optimal choice for breath-hold treatment of lung tumors in a synchrotron-based spot-scanning proton machine. Methods: Five different spot-scanning nozzles were simulated in TOPAS: four with MRFs of varying maximal thicknesses (6.15–24.6 mm) and one with no MRF. The MRFs were designed with ridges aligned along orthogonal directions transverse to the beam, with the number of ridges (4–16) increasing with MRF thickness. The material thickness given by these ridges approximately followed a Gaussian distribution. Using these simulations, Monte Carlo data were generated for treatment planning commissioning. For each nozzle, standard and stereotactic (SR) lung phantom treatment plans were created and assessed for delivery time and plan quality. Results: Use of a MRF resulted in a reduction of the number of energy layers needed in treatment plans, decreasing the number of synchrotron spills needed and hence the treatment time. For standard plans, the treatment time per field without a MRF was 67.0 ± 0.1 s, whereas three of the four MRF plans had treatment times of less than 20 s per field; considered sufficiently low for a single breath-hold. For SR plans, the shortest treatment time achieved was 57.7 ± 1.9 s per field, compared to 95.5 ± 0.5 s without a MRF. There were diminishing gains in time reduction as the MRF thickness increased. Dose uniformity of the PTV was comparable across all plans; however, when the plans were normalized to have the same coverage, dose conformality decreased with MRF thickness, as measured by the lung V20%. Conclusions: Single breath-hold treatment times for plans with standard fractionation can be achieved through the use of a MRF, making this a viable option for motion mitigation in lung tumors. For stereotactic plans, while a MRF can reduce treatment times, multiple breath-holds would still be necessary due to the limit imposed by the proton extraction time. To balance treatment time and normal tissue dose, the ideal MRF choice was shown to be the thinnest option that is able to achieve the desired breath-hold timing.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

An Evaluation of Bang-Time Measurements from a Multichannel, Triaxial, nTOF Diagnostic for MagLIF Experiments at the Z facility

Neutron bang times for a series of MagLIF (Magnetic Liner Inertial Fusion) experiments with D 2 -filled targets have been measured at the Z facility. The emitted neutrons were detected as current-mode pulses in a multichannel, neutron time-of-flight (nTOF) diagnostic with conventional, scintillator-photomultiplier-tube (PMT) detectors. In these experiments, the detectors were fielded at known, fixed distances L (690-2510 cm) from the target, and on three, non-coplanar (but convergent) lines-of-sight (LOS). The primary goal of this diagnostic was to estimate a fiducial time (bang time) relative to an externally generated time-base for synchronizing all the diagnostics in an experiment. Recorded arrival times (A7) of the pulses were characterized experimentally by three numerical methods: a first-moment estimate (centroid) and two nodal measures — Savitzky-Golay (SG) smoothing and a single point peak estimate of the raw data. These times were corrected for internal detector time delays (transit and impulse-response function) — an adjustment that linked the recorded ATs to the corresponding arrival of uncollided neutrons at each detector. The bang time was then estimated by linearly regressing the arrival times against the associated distances to the source; t bang (on the system timescale) was taken as the temporal intercept of the regression equation at distance L = 0. This article reports the analysis for a representative shot #2584 for which (a) the recorded ATs — even without detector corrections — agreed by method in each channel to within 1-2 ns; (b) internal corrections were each ~3 — 5 ns; and (c) a 95% uncertainty (confidence) interval for t bang in this shot was estimated at ±3 ns with 4 degrees of freedom. A secondary goal for this diagnostic was to check that the bang time measurements corresponded to neutrons emitted by the D(d,n) 3 He reaction in a thermalized DD plasma. According to the theoretical studies by Brysk, such neutrons should be emitted with an isotropic Gaussian distribution of mean kinetic energy $ \overline{E}$ of 2.449 MeV; this energy translates to a mean neutron speed $ \overline{u}$ of 2.160 cm/ns [D. H. Munro, Nuclear Fusion, 56(3) 036001 (2016)]. In the MagLIF series of shots there was no evidence of spatial asymmetry in the time-distance regressions, and it was possible to extract the mean neutron speed from the slope of these fits. In shot 2584 $ \overline{u}$ was estimated at 2.152 cm/ns ± 0.010 cm/ns [95 % confidence, 4 dof] and the mean kinetic energy $ \overline{E}$ (with relativistic corrections) was 2.431 MeV ± 0.022 MeV [95 % confidence, 4 dof] — results supporting the assumption that D-D neutrons were, in fact, measured.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Multigrid Reduction in Time for Chaotic and Hyperbolic Problems (Final Report)

The coming massive parallelism of exascale computing presents a pressing challenge for the many DOE simulations of time-dependent partial differential equations (PDEs), which typically use traditional sequential time stepping methods. Since this traditional approach is inherently serial, it presents a sequential bottleneck when moving to exascale computing, because future performance gains will come through greater concurrency, not faster clock speeds. Thus, the goal of this work is to research parallelism in time, i.e., methods that compute multiple time values simultaneously, not sequentially. The focus will be on hyperbolic and chaotic problems of interest to DOE, with the goal of enabling scalable simulations of time-dependent hyperbolic and chaotic problems on future architectures. The chosen methodology for solving these problems parallel-in-time is multigrid, because multigrid (when it works) is a powerful, optimal, and scalable solver for discretized PDEs. Multigrid is already commonly used in many DOE simulations for scalably and optimally solving space-only PDE problems. The areas of hyperbolic and chaotic problems are chosen because of their relevance to problems of programmatic interest to DOE. However, these problems are also well-known to be difficult for parallel-in-time methods, with the most common method, parareal, diverging in many cases. The current state of-the-art for parallel-in-time at LLNL is the multigrid reduction in time (MGRIT) XBraid package, which also struggles for such problems, while still showing some improvement over parareal. In summary, new methods are needed for an efficient parallel-in-time scheme for hyperbolic and chaotic problems, and this work shall research promising new multigrid methods in this area. In particular, this work shall continue researching the directions from the current collaboration with Dr. Falgout, which are laid out in the work Toward Parallel in Time for Chaotic Dynamical Systems and showed the first known results of a parallel-in-time speedup for a chaotic problem. This work outlines two key improvements to XBraid for chaotic problems, the so-called “theta” and “delta-correction” methods. Here, these two improvements will be further researched and improved (including with a new relaxation method inspired by on Least Squares Shadowing (LSS)) and explored for more complicated problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

The ETROC2 as the Final Version for CMS Endcap Timing Layer (ETL) Upgrade

The ETROC (Endcap Timing Readout Chip) is being developed for the LGAD-based CMS Endcap Timing Layer (ETL) at HL-LHC. The ETL on each side of the interaction region will be instrumented with a two-disk system of MIP-sensitive LGAD (Low Gain Avalanche Diodes) silicon devices, read out by ETROCs for precision timing measurement with down to ~30 ps timing resolution per track. The ETROC is designed to handle a 16 x 16 pixel cell matrix, with each pixel being 1.3 mm x 1.3 mm to match the LGAD sensor pixel size. The front-end design for preamplifier and discriminator has been specifically optimized for the reduced LGAD signals, with enough flexibilities to meet the ETL specific needs for time resolution, power budget and radiation profile. The ETROC chip is implemented in a commercial 65nm CMOS process. Each channel consists of a preamplifier, a discriminator, a TDC used for TOA (Time Of Arrival) and TOT (Time Over Threshold) measurements, and a memory for data storage and readout. An in-pixel auto threshold calibration is included, along with a self-testing pattern generator. The TOT is used for time-walk correction of the TOA measurement. The detailed hit information (TOA and TOT) from each cell will be read out from a local circular buffer after each Level-1 Accept (about 1 MHz). In addition, a charge injection circuit is implemented to allow for testing and calibration. For more detailed monitoring of the signal pulses, waveform sampling circuits are included for one pixel. The clock distribution is based on a 16x16 H-tree design with a shielding structure to alleviate potential interference. The global peripheral circuits include a PLL, a phase shifter, an I2C slave controller, a fast control block, a global readout, and a data driver along with an efuse and temperature sensor. The ETROC builds event data frames for each L1A selected event and is also capable of providing L1 trigger information for user-defined delayed hits. The main design challenge is how to extract precision timing information from the small LGAD signals in the presence of high irradiation fluence, while keeping the power consumption and digital activity low. The ETL design goal for the time resolution of 50 ps per hit is required to achieve a 35 ps arrival time measurement for a MIP particle, which has its track registered in two ETL disk layers. The LGAD contribution is known to be about 30 ps, this means that the jitter from the ETROC has to be kept below 40 ps. The ETROC2 is the first full size full functionality prototype design fully compatible with the final chip specifications for CMS ETL and now becomes the final version. The ETROC2 chips have been extensively tested. We will present here new testing results including the bump bonding yield improvement study, the time walk correction (TWC) generality study with one pixel TWC applying to all pixels, the final SEU testing using both heavy ion and proton beam, more beam test studies including different sensors, and readiness for the ETROC2 production for CMS ETL upgrade.

Liu, Tiehui [Fermilab] (ORCID:0009000765225605)↗
DOE OSTI2020

DEEP CELLULAR RECURRENT NEURAL ARCHITECTURE FOR EFFICIENT MULTIDIMENSIONAL TIME-SERIES DATA PROCESSING

Efficient processing of time series data is a fundamental yet challenging problem in pattern recognition. Though recent developments in machine learning and deep learning have enabled remarkable improvements in processing large scale datasets in many application domains, most are designed and regulated to handle inputs that are static in time. Many real-world data, such as in biomedical, surveillance and security, financial, manufacturing and engineering applications, are rarely static in time, and demand models able to recognize patterns in both space and time. Current machine learning (ML) and deep learning (DL) models adapted for time series processing tend to grow in complexity and size to accommodate the additional dimensionality of time. Specifically, the biologically inspired learning based models known as artificial neural networks that have shown extraordinary success in pattern recognition, tend to grow prohibitively large and cumbersome in the presence of large scale multi-dimensional time series biomedical data such as EEG. Consequently, this work aims to develop representative ML and DL models for robust and efficient large scale time series processing. First, we design a novel ML pipeline with efficient feature engineering to process a large scale multi-channel scalp EEG dataset for automated detection of epileptic seizures. With the use of a sophisticated yet computationally efficient time-frequency analysis technique known as harmonic wavelet packet transform and an efficient self-similarity computation based on fractal dimension, we achieve state-of-the-art performance for automated seizure detection in EEG data. Subsequently, we investigate the development of a novel efficient deep recurrent learning model for large scale time series processing. For this, we first study the functionality and training of a biologically inspired neural network architecture known as cellular simultaneous recurrent neural network (CSRN). We obtain a generalization of this network for multiple topological image processing tasks and investigate the learning efficacy of the complex cellular architecture using several state-of-the?art training methods. Finally, we develop a novel deep cellular recurrent neural network (CDRNN) architecture based on the biologically inspired distributed processing used in CSRN for processing time series data. The proposed DCRNN leverages the cellular recurrent architecture to promote extensive weight sharing and efficient, individualized, synchronous processing of multi-source time series data. Experiments on a large scale multi-channel scalp EEG, and a machine fault detection dataset show that the proposed DCRNN offers state-of-the-art recognition performance while using substantially fewer trainable recurrent units.

Vidyaratne, Lasitha S.↗
DOE OSTI2022

Capturing the interactions between ice sheets, sea level and the solid Earth on a range of timescales: a new “time window” algorithm

Retreat and advance of ice sheets perturb the gravitational field, solid surface and rotation of the Earth, leading to spatially variable sea-level changes over a range of timescales $\textit{O}$ (10 0–6 years), which in turn feed back onto ice-sheet dynamics. Coupled ice-sheet–sea-level models have been developed to capture the interactive processes between ice sheets, sea level and the solid Earth, but it is computationally challenging to capture short-term interactions $\textit{O}$ (10 0–2 years) precisely within longer $\textit{O}$ (10 3–6 years) simulations. The standard forward sea-level modelling algorithm assigns a uniform temporal resolution in the sea-level model, causing a quadratic increase in total CPU time with the total number of input ice history steps, which increases with either the length or temporal resolution of the simulation. In this study, we introduce a new “time window” algorithm for 1D pseudo-spectral sea-level models based on the normal mode method that enables users to define the temporal resolution at which the ice loading history is captured during different time intervals before the current simulation time. Utilizing the time window, we assign a fine temporal resolution $\textit{O}$ (10 0–2 years) for the period of ongoing and recent history of surface ice and ocean loading changes and a coarser temporal resolution $\textit{O}$ (10 3–6 years) for earlier periods in the simulation. This reduces the total CPU time and memory required per model time step while maintaining the precision of the model results. We explore the sensitivity of sea-level model results to the model temporal resolution and show how this sensitivity feeds back onto ice-sheet dynamics in coupled modelling. We apply the new algorithm to simulate sea-level changes in response to global ice-sheet evolution over two glacial cycles and the rapid collapse of marine sectors of the West Antarctic Ice Sheet in the coming centuries and provide appropriate time window profiles for each application. The time window algorithm reduces the total CPU time by ~ 50 % in each of these examples and changes the trend of the total CPU time increase from quadratic to linear. This improvement would increase with longer simulations than those considered here. Our algorithm also allows for coupling time intervals of annual temporal scale for coupled ice-sheet–sea-level modelling of regions such as West Antarctica that are characterized by rapid solid Earth response to ice changes due to the thin lithosphere and low mantle viscosities.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1990

Time and frequency measuring metrological equipment in the USSR

The complex of the means of providing time and frequency traceability in the USSR includes the system of time and frequency standards of the National Time and Frequency Calibration Service, time and frequency transfer facilities and local time and frequency standards. Control on measurement correctness is performed by the All-Union State Standard calibration service. The hardware of most of the above-mentioned systems is provided by the instruments developed by our institute. A common scientific and technological approach allowed us to create a unified system of time-frequency equipment composed of widely used serial instruments, sets, automated systems and complexes. Primary frequency standards of different classes, time and frequency references and instruments are based on the unified system. CH1-70 hydrogen frequency standard and its CH1-70A, CH1-80 modifications are used in the group time and frequency standards. Measuring time and data processing techniques, and also instrumentation specifications on the results of 10-year operation are given. The existing system provides time-frequency measurements with 2 times 10(exp -13) plus or minus 1 times 10(exp -14) accuracy.

Uljanov, Adolph A.↗