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Results for “Observational methods”
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A complex systems analysis of stick-slip dynamics of a laboratory fault
We study the stick-slip behavior of a granular bed of photoelastic disks sheared by a rough slider pulled along the surface. Time series of a proxy for granular friction are examined using complex systems methods to characterize the observed stick-slip dynamics of this laboratory fault. Nonlinear surrogate time series methods show that the stick-slip behavior appears more complex than a periodic dynamics description. Phase space embedding methods show that the dynamics can be locally captured within a four to six dimensional subspace. These slider time series also provide an experimental test for recent complex network methods. Phase space networks, constructed by connecting nearby phase space points, proved useful in capturing the key features of the dynamics. In particular, network communities could be associated to slip events and the ranking of small network subgraphs exhibited a heretofore unreported ordering.
Temporal Stability of Surface Roughness Effects on Radar Based Soil Moisture Retrieval During the Corn Growth Cycle
A representative soil surface roughness parameterization needed for the retrieval of soil moisture from active microwave satellite observation is difficult to obtain through either in-situ measurements or remote sensing-based inversion techniques. Typically, for the retrieval of soil moisture, temporal variations in surface roughness are assumed to be negligible. Although previous investigations have suggested that this assumption might be reasonable for natural vegetation covers (Moran et al. 2002, Thoma et al. 2006), insitu measurements over plowed agricultural fields (Callens et al. 2006) have shown that the soil surface roughness can change considerably over time. This paper reports on the temporal stability of surface roughness effects on radar observations and soil moisture retrieved from these radar observations collected once a week during a corn growth cycle (May 10th - October 2002). The data set employed was collected during the Optimizing Production Inputs for Economic and Environmental Enhancement (OPE3) field campaign covering this 2002 corn growth cycle and consists of dual-polarized (HH and VV) L-band (1.6 GHz) acquired at view angles of 15, 35, and 55 degrees. Cross-polarized L baud radar data were also collected as part of this experiment, but are not used in the analysis reported on here. After accounting for vegetation effects on radar observations, time-invariant optimum roughness parameters were determined using the Integral Equation Method (IEM) and radar observations acquired over bare soil and cropped conditions (the complete radar data set includes entire corn growth cycle). The optimum roughness parameters, soil moisture retrieval uncertainty, temporal distribution of retrieval errors and its relationship with the weather conditions (e.g. rainfall and wind speed) have been analyzed. It is shown that over the corn growth cycle, temporal roughness variations due to weathering by rain are responsible for almost 50% of soil moisture retrieval uncertainty depending on the sensing configuration. The effects of surface roughness variations are found to be smallest for observations acquired at a view angle of 55 degrees and HH polarization. A possible explanation for this result is that at 55 degrees and HH polarization the effect of vertical surface height changes on the observed radar response are limited because the microwaves travel parallel to the incident plane and as a result will not interact directly with vertically oriented soil structures.
Assimilating partial observation to enhance feedback control of stochastic dynamical systems
Here, in this paper, we present a novel methodology to tackle feedback optimal control problems in scenarios where the exact state of the controlled process is unknown. It integrates data assimilation techniques and optimal control solvers to manage partial observation of the state process, a common occurrence in practical scenarios. Traditional stochastic optimal control methods assume full state observation, which is often not feasible in real-world fluid dynamics control problems. Our approach underscores the significance of utilizing observational data to inform control policy design. Specifically, we introduce a kernel learning backward stochastic differential equation (SDE) filter to enhance data assimilation efficiency and propose a sample-wise stochastic optimization method within the stochastic maximum principle framework. We demonstrate the efficacy and accuracy of our method in the control of advection-diffusion-reaction flow problem and the Dubins airplane maneuvering problem with model uncertainty.
Spectroscopic Observations of Low Lying Gas Clouds: Sensitivity of Detection by Method of Covariance Matrix
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Generic inference of inflation models by non-Gaussianity and primordial power spectrum reconstruction
We present a generic inference method for inflation models from observational data by the usage of higher-order statistics of the curvature perturbation on uniform density hypersurfaces. This method is based on the calculation of the posterior for the primordial non-Gaussianity parameters f{sub NL} and g{sub NL}, which in general depend on specific parameters of inflation and reheating models, and enables to discriminate among the still viable inflation models. To keep analyticity as far as possible to dispense with numerically expensive sampling techniques a saddle-point approximation is introduced, whose precision is validated for a numerical toy example. The mathematical formulation is done in a generic way so that the approach remains applicable to cosmic microwave background data as well as to large scale structure data. Additionally, we review a few currently interesting inflation models and present numerical toy examples thereof in two and three dimensions to demonstrate the efficiency of the higher-order statistics method. A second quantity of interest is the primordial power spectrum. Here, we present two Bayesian methods to infer it from observational data, the so called critical filter and an extension thereof with smoothness prior, both allowing for a non-parametric spectrum reconstruction. These methods are able to reconstruct the spectra of the observed perturbations and the primordial ones of curvature perturbation even in case of non-Gaussianity and partial sky coverage. We argue that observables like T- and B-modes permit to measure both spectra. This also allows to infer the level of non-Gaussianity generated since inflation.
Maps and navigation methods
Different maps and scales are discussed with particular emphasis on their use in aviation. The author makes the observation that current navigation methods are slow and dangerous and should be replaced by scientific methods of navigation based on loxodromy and the use of the compass.
One millimeter continuum observations of extragalactic thermal sources
The results of 1 mm observations of extragalactic thermal sources are reported. The methods of making 1 mm observations are described. The instrumentation used to make the observation is described.
Methods for Estimating 2D Cloud Size Distributions from 1D Observations
Abstract The two-dimensional (2D) size distribution of clouds in the horizontal plane plays a central role in the calculation of cloud cover, cloud radiative forcing, convective entrainment rates, and the likelihood of precipitation. Here, a simple method is proposed for calculating the area-weighted mean cloud size and for approximating the 2D size distribution from the 1D cloud-chord lengths measured by aircraft and vertically pointing lidar and radar. This simple method (which is exact for square clouds) compares favorably against the inverse Abel transform (which is exact for circular clouds) in the context of theoretical size distributions. Both methods also perform well when used to predict the size distribution of real clouds from a Landsat scene. When applied to a large number of Landsat scenes, the simple method is able to accurately estimate the mean cloud size. As a demonstration, the methods are applied to aircraft measurements of shallow cumuli during the Routine ARM Aerial Facility (AAF) Clouds with Low Optical Water Depths (CLOWD) Optical Radiative Observations (RACORO) campaign, which then allow for an estimate of the true area-weighted mean cloud size.
Precise Timing Based on Pulsar Observation for Grid Synchronization
While Global Positioning System signals are widely used as the synchronized timing Sources for wide-area measurement systems for power grid monitoring and control, they are vulnerable to failures and malicious attacks. To address this Problem, an alternative kind of timing sources, the millisecond pulsars, were proposed to serve the power grid as they are more precise and physically indestructible. Millisecond pulsars are a kind of neutron stars that emit radio pulse signals that have extremely stable periods of milliseconds. However, the observed pulse Signals from pulsars cannot be directly used for timing because of their low signal-to-noise ratio and the dispersion effects of interstellar medium. In this paper, the precise timing method based on pulsar observation data is proposed to interpret the pulsar observation data and therefrom to generate precise timing signal for the power grid synchronization. In our proposed method,. incoherent de-dispersion is used on the observation data to mitigate the effect of interstellar medium. dispersion. Then spectrum analysis and segment folding are used to precisely estimate the local pulsar period. Finally the standard pulse per second signal is generated from. the estimated pulsar period and its precision. is analyzed. Experiments with the observation data of the pulsar based timing signal can be more accurate compared to GPS timing signals.
Atomic charges for modeling metal–organic frameworks: Why and how
Atomic partial charges are parameters of key importance in the simulation of Metal–Organic Frameworks (MOFs), since Coulombic interactions decrease with the distance more slowly than van der Waals interactions. But despite its relevance, there is no method to unambiguously assign charges to each atom, since atomic charges are not quantum observables. There are several methods that allow the calculation of atomic charges, most of them starting from the electronic wavefunction or the electronic density or the system, as obtained with quantum mechanics calculations. In this work, we describe the most common methods employed to calculate atomic charges in MOFs. In order to show the influence that even small variations of structure have on atomic charges, we present the results that we obtained for DMOF-1. We also discuss the effect that small variations of atomic charges have on the predicted structural properties of IRMOF-1. - Graphical abstract: We review the different method with which to calculate atomic partial charges that can be used in force field-based calculations. We also present two examples that illustrate the influence of the geometry on the calculated charges and the influence of the charges on structural properties. - Highlights: • The choice of atomic charges is crucial in modeling adsorption and diffusion in MOFs. • Methods for calculating atomic charges in MOFs are reviewed. • We discuss the influence of the framework geometry on the calculated charges. • We discuss the influence of the framework charges on structural the properties.
Time stretching of the GeV emission of GRBs: Fermi-LAT data versus geometrical model
It is known that the high-energy (>100 MeV) emission of gamma-ray bursts is delayed with respect to the low-energy emission. However, the dependence of light curves on energy has not been studied for the high-energy bands. In this paper, we consider the bursts observed by Fermi LAT from 2008 August 4 to 2011 August 1, for which at least 10 photons were observed with energy greater than 1 GeV. These include four bursts: GRB 080916C, GRB 090510, GRB 090902B, and GRB 090926A. We use the Kolmogorov–Smirnov test to compare the light curves in the two bands 100 MeV 1 GeV. For GRB 080916C and GRB 090510 the light curves in the two bands are statistically compatible. However, for GRB 090926A, the higher-energy light curve is stretched compared to the lower-energy one with a statistical significance of 3.3σ and, for GRB 090902B, on the contrary, the lower-energy curve is stretched with 2.3σ significance. We argue that the observed diversity of stretching factors may be explained using a simple geometrical model. The model assumes that the jet opening angle depends on the emission energy in a way that the most energetic photons are radiated near the axis of the jet. All of the bursts are considered equivalent in their rest frames, and the observed light curves differ only due to different redshifts and view directions. The model conforms to the total burst energy constraint and matches the Fermi-LAT observations of the fraction of GRBs visible in the 100 MeV<E<1 GeV band, which may be observed at higher energies. The model predicts the distribution of observable stretching factors, which may be tested in future data. Finally, we propose a method to estimate the observer's off-axis angle based on the stretching factor and the fraction of the high-energy photons. The code for modeling is open source and is publicly available on GitHub (https://github.com/maxitg/GammaRays).
Convergence and stability properties of minimal polynomial and reduced rank extrapolation algorithms
The minimal polynomial and reduced rank extrapolation algorithms are two acceleration of convergence methods for sequences of vectors. In a recent survey these methods were tested and compared with the scalar, vector, topological epsilon algorithms, and were observed to be more efficient than the latter. It was also observed that the two methods have similar convergence properties. The convergence and stability properties of these methods are analyzed and the performance of the acceleration methods when applied to a class of vector sequences that includes those sequences obtained from systems of linear equations by using matrix iterative methods is discussed.
Time-resolved characterization and energy balance analysis of implosion core in shock-ignition experiments at OMEGA
Time-resolved temperature and density conditions in the core of shock-ignition implosions have been determined for the first time. The diagnostic method relies on the observation, with a streaked crystal spectrometer, of the signature of an Ar tracer added to the deuterium gas fill. The data analysis confirms the importance of the shell attenuation effect previously noted on time-integrated spectroscopic measurements of thick-wall targets [R. Florido et al., Phys. Rev. E 83, 066408 (2011)]. This effect must be taken into account in order to obtain reliable results. The extracted temperature and density time-histories are representative of the state of the core during the implosion deceleration and burning phases. As a consequence of the ignitor shock launched by the sharp intensity spike at the end of the laser pulse, observed average core electron temperature and mass density reach T ~ 1100 eV and ρ ~ 2 g/cm 3 ; then temperature drops to T ~ 920 eV while density rises to ρ ~ 3.4 g/cm 3 about the time of peak compression. Compared to 1D hydrodynamic simulations, the experiment shows similar maximum temperatures and smaller densities. Simulations do not reproduce all observations. Differences are noted in the heating dynamics driven by the ignitor shock and the optical depth time-history of the compressed shell. Time-histories of core conditions extracted from spectroscopy show that the implosion can be interpreted as a two-stage polytropic process. Furthermore, an energy balance analysis of implosion core suggests an increase in total energy greater than what 1D hydrodynamic simulations predict. This new methodology can be implemented in other ICF experiments to look into implosion dynamics and help to understand the underlying physics.
Lunar occultation of Saturn. IV - Astrometric results from observations of the satellites
The method of determining local lunar limb slopes, and the consequent time scale needed for diameter studies, from accurate occultation timings at two nearby telescopes is described. Results for photoelectric observations made at Mauna Kea Observatory during the occultation of Saturn's satellites on March 30, 1974, are discussed. Analysis of all observations of occultations of Saturn's satellites during 1974 indicates possible errors in the ephemerides of Saturn and its satellites.
Realistic galaxy image simulation via score-based generative models
ABSTRACT We show that a denoising diffusion probabilistic model (DDPM), a class of score-based generative model, can be used to produce realistic mock images that mimic observations of galaxies. Our method is tested with Dark Energy Spectroscopic Instrument (DESI) grz imaging of galaxies from the Photometry and Rotation curve OBservations from Extragalactic Surveys (PROBES) sample and galaxies selected from the Sloan Digital Sky Survey. Subjectively, the generated galaxies are highly realistic when compared with samples from the real data set. We quantify the similarity by borrowing from the deep generative learning literature, using the ‘Fréchet inception distance’ to test for subjective and morphological similarity. We also introduce the ‘synthetic galaxy distance’ metric to compare the emergent physical properties (such as total magnitude, colour, and half-light radius) of a ground truth parent and synthesized child data set. We argue that the DDPM approach produces sharper and more realistic images than other generative methods such as adversarial networks (with the downside of more costly inference), and could be used to produce large samples of synthetic observations tailored to a specific imaging survey. We demonstrate two potential uses of the DDPM: (1) accurate inpainting of occluded data, such as satellite trails, and (2) domain transfer, where new input images can be processed to mimic the properties of the DDPM training set. Here we ‘DESI-fy’ cartoon images as a proof of concept for domain transfer. Finally, we suggest potential applications for score-based approaches that could motivate further research on this topic within the astronomical community.
Effects of the atmosphere on ERTS observations
Atmospheric radiation models and methods of computing radiation effects are reported that are important both in the meteorological and Earth Resources Satellite programs. Results of using them to compute the atmospheric effects on just the ERTS observations are presented.
Wind speed and aerosol optical thickness estimates from aircraft observations of sea glitter
A method is proposed whereby the optical characteristics of the bright glitter pattern of the sunlight reflected from water are used to determine wind speed and aerosol optical thickness in the troposphere. Radiances observed from an aircraft are used to derive the aerosol optical thickness and the surface wind speed. A scanning radiometer is used to measure the radiances in several spectral channels within 45 deg of the nadir and in a plane transverse to the aircraft motion. The observations are taken under nearly cloudless sky conditions over the Pacific Ocean (long. 130.4 deg, lat. 42.3 deg), and the aircraft height is 150 m above water with a 292-deg heading. It is shown that the derived wind speed depends strongly on the width of the glitter pattern, and that the width of the computed radiance pattern at the 150-m aircraft height diverges from the measured value, indicating overestimated wind speed.