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At least 1,783 records · Page 99

Nb/Al-Al2O3/Nb junctions with inductive tuning elements for a very low noise 205-250 GHz heterodyne receiver

The superconductor-insulator-superconductor (SIS) junction is the most sensitive nonlinear element for millimeter-wave heterodyne detection. An Nb/Al-Al203/Nb junction fabrication process has been developed which allows the use of planar tuning circuits integrated with the junctions. These tuning elements permit the use of junctions with relatively large areas and small current densities with excellent results. Recent measurements have yielded a double sideband receiver noise temperature less than 50 K from 205 to 240 GHz and 44 K at 230 GHz. This Nb/Al-Al203/Nb trilayer technology is also being extended to the fabrication of sub-square-micron area planar junctions for submillimeter-wavelengths.

Lichtenberger, Arthur W.↗

Applications of data compression techniques in modal analysis for on-orbit system identification

Data compression techniques have been investigated for use with modal analysis applications. A redundancy-reduction algorithm was used to compress frequency response functions (FRFs) in order to reduce the amount of disk space necessary to store the data and/or save time in processing it. Tests were performed for both single- and multiple-degree-of-freedom (SDOF and MDOF, respectively) systems, with varying amounts of noise. Analysis was done on both the compressed and uncompressed FRFs using an SDOF Nyquist curve fit as well as the Eigensystem Realization Algorithm. Significant savings were realized with minimal errors incurred by the compression process.

Carlin, Robert A.↗

Psychoacoustic Analysis of Synthesized Jet Noise

An aircraft noise synthesis capability is being developed so the annoyance caused by proposed aircraft can be assessed during the design stage. To make synthesized signals as realistic as possible, high fidelity simulation is required for source (e.g., engine noise, airframe noise), propagation and receiver effects. This psychoacoustic study tests whether the jet noise component of synthesized aircraft engine noise can be made more realistic using a low frequency oscillator (LFO) technique to simulate fluctuations in level observed in recordings. Jet noise predictions are commonly made in the frequency domain based on models of time-averaged empirical data. The synthesis process involves conversion of the frequency domain prediction into an audible pressure time history. However, because the predictions are time-invariant, the synthesized sound lacks fluctuations observed in recordings. Such fluctuations are hypothesized to be perceptually important. To introduce time-varying characteristics into jet noise synthesis, a method has been developed that modulates measured or predicted 1/3-octave band levels with a (<20Hz) LFO. The LFO characteristics are determined through analysis of laboratory jet noise recordings. For the aft emission angle, results indicate that signals synthesized using a generic LFO are perceived as more similar to recordings than those using no LFO, and signals synthesized with an angle-specific LFO are more similar to recordings than those synthesized with a generic LFO.

Okcu, Selen↗

SU-E-I-01: Iterative CBCT Reconstruction with a Feature-Preserving Penalty

Purpose: Low-dose CBCT is desired in various clinical applications. Iterative image reconstruction algorithms have shown advantages in suppressing noise in low-dose CBCT. However, due to the smoothness constraint enforced during the reconstruction process, edges may be blurred and image features may lose in the reconstructed image. In this work, we proposed a new penalty design to preserve image features in the image reconstructed by iterative algorithms. Methods: Low-dose CBCT is reconstructed by minimizing the penalized weighted least-squares (PWLS) objective function. Binary Robust Independent Elementary Features (BRIEF) of the image were integrated into the penalty of PWLS. BRIEF is a general purpose point descriptor that can be used to identify important features of an image. In this work, BRIEF distance of two neighboring pixels was used to weigh the smoothing parameter in PWLS. For pixels of large BRIEF distance, weaker smooth constraint will be enforced. Image features will be better preserved through such a design. The performance of the PWLS algorithm with BRIEF penalty was evaluated by a CatPhan 600 phantom. Results: The image quality reconstructed by the proposed PWLS-BRIEF algorithm is superior to that by the conventional PWLS method and the standard FDK method. At matched noise level, edges in PWLS-BRIEF reconstructed image are better preserved. Conclusion: This study demonstrated that the proposed PWLS-BRIEF algorithm has great potential on preserving image features in low-dose CBCT.

60 APPLIED LIFE SCIENCES↗

Online Rapid Analysis of Laser Heterodyne Radiometer (LHR) Data Using the Planetary Spectrum Generator (PSG)

One of the biggest challenges in developing scientific instruments is not just the build and testing of an instrument, but the method for processing the data and producing a consistent, well characterized data product that can be confidently used by the public and scientific community. Raw data products are frequently an array of numbers that are a read-out of voltages. The challenge is to convert these arrays into meaningful information as well as remove noise and interferences. Because this can be a tedious and time-consuming, the goal is to automate the process so that data ca be processed rapidly and be available in real-time for event monitoring. Here we present a rapid analysis method for Laser Heterodyne Radiometer (LHR) data that can be used to analyze data taken from a range of LHR observation modes (column, limb, etc.). This online tool uses the versatile Planetary Spectrum Generator (PSG) and allows LHR users to quickly analyze their own data using a NASA Goddard Space Flight Center (GSFC) monitored capability to ensure quality and reproducibility in the data products. Background: Development of a miniaturized LHR (mini-LHR) as a ground instrument for measuring carbon dioxide (CO 2 ) and methane (CH 4 ) in the atmospheric column started in 2009 with the commercial availability of distributive feedback lasers (DFB) in wavelengths that could measure absorption of gases in the near-IR. As new DFB lasers, detectors and hardware emerged at different wavelengths, additional gases were added to the capability. The mini-LHR was adapted into an occultation-viewing CubeSat with Lawrence Livermore National Laboratory (LLNL) for observing CO 2 , CH 4 , and H 2 O in the limb and was launched in 2019. Other versions of the LHR technology have been designed for observation of water vapor in the lunar exosphere as well as observations of trace gases in planetary atmospheres and plumes from icy moons. The PSG is an online tool developed at GSFC that can be used for synthesizing Earth and planetary spectra (atmospheres and surfaces) over a broad range of wavelengths (0.1 μm to 100 mm) for any observatory, orbiter or lander. Spectra are simulated by combining several state-of-the-art radiative transfer models, spectroscopic databases, planetary databases, as well as modern-era retrospective analysis for research and applications, version 2 (MERRA-2) data set which provides meteorological inputs such as modeled surface pressure for calculating dry-air columns.

Emily Wilson↗

Simultaneous X-ray diffraction and phase-contrast imaging for investigating material deformation mechanisms during high-rate loading

Using a high-speed camera and an intensified charge-coupled device (ICCD), a simultaneous X-ray imaging and diffraction technique has been developed for studying dynamic material behaviors during high-rate tensile loading. A Kolsky tension bar has been used to pull samples at 1000 s -1 and 5000 s -1 strain-rates for super-elastic equiatomic NiTi and 1100-O series aluminium, respectively. By altering the ICCD gating time, temporal resolutions of 100 ps and 3.37 µs have been achieved in capturing the diffraction patterns of interest, thus equating to single-pulse and 22-pulse X-ray exposure. Furthermore, the sample through-thickness deformation process has been simultaneously imaged via phase-contrast imaging. It is also shown that adequate signal-to-noise ratios are achieved for the detected white-beam diffraction patterns, thereby allowing sufficient information to perform quantitative data analysis diffraction via in-house software ( WBXRD_GUI ). Of current interest is the ability to evaluate crystal d -spacing, texture evolution and material phase transitions, all of which will be established from experiments performed at the aforementioned elevated strain-rates.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Connecting the dots: Semi-analytical and random walk numerical solutions of the diffusion–reaction equation with stochastic initial conditions

We study a system with bimolecular irreversible kinetic reaction A+B→∅ where the underlying transport of reactants is governed by diffusion, and the local reaction term is given by the law of mass action. We consider the case where the initial concentrations are given in terms of an average and a white noise perturbation. Our goal is to solve the diffusion–reaction equation which governs the system, and we tackle it with both analytical and numerical approaches. To obtain an analytical solution, we develop the equations of moments and solve them approximately. To obtain a numerical solution, we develop a grid-less Monte Carlo particle tracking approach, where diffusion is modeled by a random walk of the particles, and reaction is modeled by annihilation of particles. The probability of annihilation is derived analytically from the particles' co-location probability. We rigorously derive the relationship between the initial number of particles in the system and the amplitude of white noise represented by that number. This enables us to compare the particle simulations and the approximate analytical solution and offer an explanation of the late time discrepancies. - Graphical abstract:.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Stochastic symplectic and multi-symplectic methods for nonlinear Schrödinger equation with white noise dispersion

We indicate that the nonlinear Schrödinger equation with white noise dispersion possesses stochastic symplectic and multi-symplectic structures. Based on these structures, we propose the stochastic symplectic and multi-symplectic methods, which preserve the continuous and discrete charge conservation laws, respectively. Moreover, we show that the proposed methods are convergent with temporal order one in probability. Numerical experiments are presented to verify our theoretical results.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Electrochemical techniques and mechanisms for the corrosion of metals and alloys in sub- and supercritical aqueous systems

Corrosion has become a decisive factor hindering supercritical water technologies' long-cycle, safe implementation. Electrochemical experiments performed in supercritical aqueous systems can capture essential, real-time information about the micro/nanoscale processes of corrosion and their kinetics. As a starting point, this paper first summarizes the critical chemical properties of supercritical aqueous systems and analyzes their role in determining the duality of corrosion mechanisms (whether electrochemical or chemical micro-processes predominate). Next, it reviews the available electrochemical techniques such as pH sensors, electrochemical noise measurements, and related applications for quantitatively elaborating the corrosion issues in supercritical aqueous systems. With thick and heavy colors, a series of mechanistic models, such as the mixed potential model and the coupled environment models were introduced from the fundamental theories to the related applications, which have been applied widely in ambient and subcritical aqueous systems and exhibit great values and potential to be employed in high-density supercritical water environments. The passivity, depassivation, and passivity breakdown of metals and alloys in terms of the Point Defect Model (PDM) were also successfully implemented and discussed. Further, the newly built SCW_PDM describes the film growth kinetics at the atomic level of metals and alloys in supercritical water and is being developed to quantitatively analyze and resolve a series of corrosion issues such as the passivity breakdown and the stress corrosion cracking that occur in supercritical aqueous systems. This review is helpful by promoting the development of the electrochemical corrosion theory in supercritical aqueous systems and by identifying corrosion prevention and control methods for the safe implementation of relevant supercritical water technologies.

36 MATERIALS SCIENCE↗

Sensitive response of a model of symbiotic ecosystem to seasonal periodic drive

A symbiotic ecosysytem (metapopulation) is studied by means of the stochastic Lotka-Volterra model with generalized Verhulst self-regulation. The effect of variable environment on the carrying capacities of populations is taken into account as an asymmetric dichotomous noise and as a deterministic periodic stimulus. In the framework of the mean-field theory an explicit self-consistency equation for the system in the long-time limit is presented. Also, expressions for the probability distribution and for the moments of the population size are found. In certain cases the mean population size exhibits large oscillations in time, even if the amplitude of the seasonal environmental drive is small. Particularly, it is shown that the occurrence of large oscillations of the mean population size can be controlled by noise parameters (such as amplitude and correlation time) and by the coupling strength of the symbiotic interaction between species.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Numerical analysis of randomly forced glycolitic oscillations

Randomly forced glycolytic oscillations in Higgins model are studied both numerically and analytically. Numerical analysis is based on the direct simulation of the solutions of stochastic system. Non-uniformity of the stochastic bundle along the deterministic cycle is shown. For the analytical investigation of the randomly forced Higgins model, the stochastic sensitivity function technique and confidence domains method are applied. Results of the influence of additive noise on the cycle of this model are given.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Understanding the distinctively skewed and heavy tailed character of atmospheric and oceanic probability distributions

The probability distributions of large-scale atmospheric and oceanic variables are generally skewed and heavy-tailed. We argue that their distinctive departures from Gaussianity arise fundamentally from the fact that in a quadratically nonlinear system with a quadratic invariant, the coupling coefficients between system components are not constant but depend linearly on the system state in a distinctive way. In particular, the skewness arises from a tendency of the system trajectory to linger near states of weak coupling. We show that the salient features of the observed non-Gaussianity can be captured in the simplest such nonlinear 2-component system. If the system is stochastically forced and linearly damped, with one component damped much more strongly than the other, then the strongly damped fast component becomes effectively decoupled from the weakly damped slow component, and its impact on the slow component can be approximated as a stochastic noise forcing plus an augmented nonlinear damping. In the limit of large time-scale separation, the nonlinear augmentation of the damping becomes small, and the noise forcing can be approximated as an additive noise plus a correlated additive and multiplicative noise (CAM noise) forcing. Much of the diversity of observed large-scale atmospheric and oceanic probability distributions can be interpreted in this minimal framework.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Tracking stochastic resonance curves using an assisted reference model

The optimal noise amplitude for Stochastic Resonance (SR) is located employing an Artificial Neural Network (ANN) reference model with a nonlinear predictive capability. A modified Kalman Filter (KF) was coupled to this reference model in order to compensate for semi-quantitative forecast errors. Three manifestations of stochastic resonance, namely, Periodic Stochastic Resonance (PSR), Aperiodic Stochastic Resonance (ASR), and finally Coherence Resonance (CR) were considered. Using noise amplitude as the control parameter, for the case of PSR and ASR, the cross-correlation curve between the sub-threshold input signal and the system response is tracked. However, using the same parameter the Normalized Variance curve is tracked for the case of CR. The goal of the present work is to track these curves and converge to their respective extremal points. The ANN reference model strategy captures and subsequently predicts the nonlinear features of the model system while the KF compensates for the perturbations inherent to the superimposed noise. This technique, implemented in the FitzHugh-Nagumo model, enabled us to track the resonance curves and eventually locate their optimal (extremal) values. This would yield the optimal value of noise for the three manifestations of the SR phenomena.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Deterministic and stochastic control of chimera states in delayed feedback oscillator

Chimera states, characterized by the coexistence of regular and chaotic dynamics, are found in a nonlinear oscillator model with negative time-delayed feedback. The control of these chimera states by external periodic forcing is demonstrated by numerical simulations. Both deterministic and stochastic external periodic forcing are considered. It is shown that multi-cluster chimeras can be achieved by adjusting the external forcing frequency to appropriate resonance conditions. The constructive role of noise in the formation of a chimera states is shown.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Internal additive noise effects in stochastic resonance using organic field effect transistor

Stochastic resonance phenomenon was observed in organic field effect transistor using poly(3-hexylthiophene), which enhances performance of signal transmission with application of noise. The enhancement of correlation coefficient between the input and output signals was low, and the variation of correlation coefficient was not remarkable with respect to the intensity of external noise, which was due to the existence of internal additive noise following the nonlinear threshold response. In other words, internal additive noise plays a positive role on the capability of approximately constant signal transmission regardless of noise intensity, which can be said “homeostatic” behavior or “noise robustness” against external noise. Furthermore, internal additive noise causes emergence of the stochastic resonance effect even on the threshold unit without internal additive noise on which the correlation coefficient usually decreases monotonically.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Discovering causal structure with reproducing-kernel Hilbert space ε -machines

We merge computational mechanics’ definition of causal states (predictively equivalent histories) with reproducing-kernel Hilbert space (RKHS) representation inference. The result is a widely applicable method that infers causal structure directly from observations of a system’s behaviors whether they are over discrete or continuous events or time. A structural representation—a finite- or infinite-state kernel ϵ-machine—is extracted by a reduced-dimension transform that gives an efficient representation of causal states and their topology. In this way, the system dynamics are represented by a stochastic (ordinary or partial) differential equation that acts on causal states. We introduce an algorithm to estimate the associated evolution operator. Paralleling the Fokker–Planck equation, it efficiently evolves causal-state distributions and makes predictions in the original data space via an RKHS functional mapping. We demonstrate these techniques, together with their predictive abilities, on discrete-time, discrete-value infinite Markov-order processes generated by finite-state hidden Markov models with (i) finite or (ii) uncountably infinite causal states and (iii) continuous-time, continuous-value processes generated by thermally driven chaotic flows. The method robustly estimates causal structure in the presence of varying external and measurement noise levels and for very high-dimensional data.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Impact and mitigation of spectroscopic systematics on DESI DR1 clustering measurements

The large scale structure catalogs within DESI Data Release 1 (DR1) use nearly 6 million galaxies and quasars as tracers of the large-scale structure of the universe to measure the expansion history with baryon acoustic oscillations and the growth of structure with redshift-space distortions. In order to take advantage of DESI's unprecedented statistical power, we must ensure that the galaxy clustering measurements are unaffected by non-cosmological density fluctuations. One source of spurious fluctuations comes from variation in galaxy density with spectroscopic observing conditions, lowering the redshift efficiency (and thus galaxy density) in certain areas of the sky. We measure the uniformity of the redshift success rate for DESI luminous red galaxies (LRG), bright galaxies (BGS) and quasars (QSO), complementing the detailed discussion of emission line galaxy (ELG) systematics in a companion paper [1]. We find small but significant fluctuations of up to 3% in redshift success rate with the effective spectroscopic signal-to-noise, and create and describe weights that remove these fluctuations. We also describe the process to identify and remove data from certain poorly performing fibers from DESI DR1, and measure the stability of the redshift success rate with time. Finally, we find small but significant correlations of redshift success rate with position on the focal plane, survey speed, and number of exposures required, and show the impact of weights correcting these trends on the power spectrum multipoles and on cosmological parameters from BAO and RSD fits. These corrections change the best-fit parameters by <15% of their statistical errors, and thus contribute negligibly to the overall DESI error budget.

cosmological parameters from LSS↗

Nonreciprocal signal routing in an active quantum network

As superconductor quantum technologies are moving towards large-scale integrated circuits, a robust and flexible approach to routing photons at the quantum level becomes a critical problem. Active circuits, which contain parametrically driven elements selectively embedded in the circuit, offer a viable solution. In this work, we present a general strategy for routing nonreciprocally quantum signals between two sites of a given lattice of oscillators, implementable with existing superconducting circuit components. Our approach makes use of a dual lattice of overdamped oscillators linking the nodes of the main lattice. Solutions for spatially selective driving of the lattice elements can be found, which optimally balance coherent and dissipative hopping of microwave photons to nonreciprocally route signals between two given nodes. In certain lattices these optimal solutions are obtained at the exceptional point of the dynamical matrix of the network. We also demonstrate that signal and noise transmission characteristics can be separately optimized.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗