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At least 397 records · Page 22

Phase Transitions in Planning Problems: Design and Analysis of Parameterized Families of Hard Planning Problems

There are two common ways to evaluate algorithms: performance on benchmark problems derived from real applications and analysis of performance on parametrized families of problems. The two approaches complement each other, each having its advantages and disadvantages. The planning community has concentrated on the first approach, with few ways of generating parametrized families of hard problems known prior to this work. Our group's main interest is in comparing approaches to solving planning problems using a novel type of computational device - a quantum annealer - to existing state-of-the-art planning algorithms. Because only small-scale quantum annealers are available, we must compare on small problem sizes. Small problems are primarily useful for comparison only if they are instances of parametrized families of problems for which scaling analysis can be done. In this technical report, we discuss our approach to the generation of hard planning problems from classes of well-studied NP-complete problems that map naturally to planning problems or to aspects of planning problems that many practical planning problems share. These problem classes exhibit a phase transition between easy-to-solve and easy-to-show-unsolvable planning problems. The parametrized families of hard planning problems lie at the phase transition. The exponential scaling of hardness with problem size is apparent in these families even at very small problem sizes, thus enabling us to characterize even very small problems as hard. The families we developed will prove generally useful to the planning community in analyzing the performance of planning algorithms, providing a complementary approach to existing evaluation methods. We illustrate the hardness of these problems and their scaling with results on four state-of-the-art planners, observing significant differences between these planners on these problem families. Finally, we describe two general, and quite different, mappings of planning problems to QUBOs, the form of input required for a quantum annealing machine such as the D-Wave II.

Problems↗

Constraints on Cumulus Parameterization from Simulations of Observed MJO Events

Two recent activities offer an opportunity to test general circulation model (GCM) convection and its interaction with large-scale dynamics for observed Madden-Julian oscillation (MJO) events. This study evaluates the sensitivity of the Goddard Institute for Space Studies (GISS) GCM to entrainment, rain evaporation, downdrafts, and cold pools. Single Column Model versions that restrict weakly entraining convection produce the most realistic dependence of convection depth on column water vapor (CWV) during the Atmospheric Radiation Measurement MJO Investigation Experiment at Gan Island. Differences among models are primarily at intermediate CWV where the transition from shallow to deeper convection occurs. GCM 20-day hindcasts during the Year of Tropical Convection that best capture the shallow–deep transition also produce strong MJOs, with significant predictability compared to Tropical Rainfall Measuring Mission data. The dry anomaly east of the disturbance on hindcast day 1 is a good predictor of MJO onset and evolution. Initial CWV there is near the shallow–deep transition point, implicating premature onset of deep convection as a predictor of a poor MJO simulation. Convection weakly moistens the dry region in good MJO simulations in the first week; weakening of large-scale subsidence over this time may also affect MJO onset. Longwave radiation anomalies are weakest in the worst model version, consistent with previous analyses of cloud/moisture greenhouse enhancement as the primary MJO energy source. The authors’ results suggest that both cloud-/moisture-radiative interactions and convection–moisture sensitivity are required to produce a successful MJO simulation.

Madden-Julian Oscillation↗

Implementation of a Parameterized Interacting Multiple Model Filter on an FPGA for Satellite Communications

In a communications channel, the space environment between a spacecraft and an Earth ground station can potentially cause the loss of a data link or at least degrade its performance due to atmospheric effects, shadowing, multipath, or other impairments. In adaptive and coded modulation, the signal power level at the receiver can be used in order to choose a modulation-coding technique that maximizes throughput while meeting bit error rate (BER) and other performance requirements. It is the goal of this research to implement a generalized interacting multiple model (IMM) filter based on Kalman filters for improved received power estimation on software-dened radio (SDR) technology for satellite communications applications. The IMM filter has been implemented in Verilog consisting of a customizable bank of Kalman filters for choosing between performance and resource utilization. Each Kalman filter can be implemented using either solely a Schur complement module (for high area efficiency) or with Schur complement, matrix multiplication, and matrix addition modules (for high performance). These modules were simulated and synthesized for the Virtex II platform on the JPL Radio Experimenter Development System (EDS) at NASA Glenn Research Center. The results for simulation, synthesis, and hardware testing are presented.

cognitive radio↗

Parameterizations of Chromospheric Condensations in dG and dMe Model Flare Atmospheres

The origin of the near-ultraviolet and optical continuum radiation in flares is critical for understanding particle acceleration and impulsive heating in stellar atmospheres. Radiative-hydrodynamic (RHD) simulations in 1D have shown that high energy deposition rates from electron beams produce two flaring layers at T approximately 10 (exp 4) K that develop in the chromosphere: a cooling condensation (downflowing compression) and heated non-moving (stationary) flare layers just below the condensation. These atmospheres reproduce several observed phenomena in flare spectra, such as the red-wing asymmetry of the emission lines in solar flares and a small Balmer jump ratio in M dwarf flares. The high beam flux simulations are computationally expensive in 1D, and the (human) timescales for completing NLTE models with adaptive grids in 3D will likely be unwieldy for some time to come. We have developed a prescription for predicting the approximate evolved states, continuum optical depth, and emergent continuum flux spectra of RHD model flare atmospheres. These approximate prescriptions are based on an important atmospheric parameter: the column mass (m(sub ref)) at which hydrogen becomes nearly completely ionized at the depths that are approximately in steady state with the electron beam heating. Using this new modeling approach, we find that high energy flux density (>F11) electron beams are needed to reproduce the brightest observed continuum intensity in IRIS data of the 2014 March 29 X1 solar flare, and that variation in m(sub ref) from 0.001 to 0.02 g cm (exp -2) reproduces most of the observed range of the optical continuum flux ratios at the peak of M dwarf flares.

Kowalski, Adam F.↗

Dressing the Coronal Magnetic Extrapolations of Active Regions with a Parameterized Thermal Structure

The study of time-dependent solar active region (AR) morphology and its relation to eruptive events requires analysis of imaging data obtained in multiple wavelength domains with differing spatial and time resolution, ideally in combination with 3D physical models. To facilitate this goal, we have undertaken a major enhancement of our IDL-based simulation tool, GX_Simulator, previously developed for modeling microwave and X-ray emission from flaring loops, to allow it to simulate quiescent emission from solar ARs. The framework includes new tools for building the atmospheric model and enhanced routines for calculating emission that include new wavelengths. In this paper, we use our upgraded tool to model and analyze an AR and compare the synthetic emission maps with observations. We conclude that the modeled magneto-thermal structure is a reasonably good approximation of the real one.

Nita, Gelu M.↗

Quantifying the Relative Impact of Model Microphysics Parameterizations and Scattering Models in Simulating Synthetic Radar and Microwave Radiometer Observations

Output from numerical weather models is often used to simulate observations from remote sensing instruments, for purposes ranging from data assimilation, synthetic retrievals of geophysical quantities, and optimization of observing systems. However, when hydrometeors are present, the level of detail provided by the weather model is generally insufficient to fully constrain the input to the radiative transfer model (RTM), and further assumptions must be made by the RTM user in order to produce synthetic observations. Using a hierarchy of models including cloud-resolving, double-moment, bin microphysical, and ice-habit predicting models, along with scattering properties from the OpenSSP, Atmospheric Radiative Transfer Simulator (ARTS) databases, as well as relatively simple geometries (e.g., cylindrical plates and columns), we demonstrate the spread in synthetic observation output and the extent to which it is reduced when microphysics is more strongly constrained by the model. As an intermediate step, an error budget for the RTM simulations was derived and from that we developed and will describe best practices for observation simulation (e.g., optimal number of hydrometeor size bins, truncation of the particle size distribution, angular resolution of scattering phase function). Some statistical comparisons with observations will also be presented.

Munchak, S. Joseph↗

Light Ion Double-Differential Cross Section Parameterization and Results from the SHIELD Transport Code

Light ions and neutrons have been shown to make large contributions to space radiation dose equivalent for realistic shielding scenarios. Efficient and accurate calculations of light ion double-differential cross sections are required for input into space radiation transport codes. A thermal proton cross section model is developed which includes proton production from the three sources of projectile, central fireball, and target. It is shown that this three-source model is able to explain the low momentum shoulder seen in proton spectra. Using the coalescence model, the thermal proton model is used to calculate light ion double-differential cross sections employed in space radiation transport codes. The three-source model is also seen to be essential to explain the light ion shoulders, which are even more pronounced than the proton shoulders. Comparisons are also made to the cross section models used in the SHIELD transport code.

Space radiation↗

The Relationship Of Size Distributions To Spectral (300 - 700 Nm) Extinction Parameterization Of Ambient In Situ Aerosols Measured During FIREX-AQ And The Influence Of Aerosol Composition

Hyperspectral (300 - 700 nm, 0.7 nm resolution) aerosol extinction spectra were measured at seven fires in six states in the western United States during the Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) field campaign in July and August 2019. Obtained using an in situ aerosol sampling method, these spectra are directly comparable to other in situ aerosol measurements such as size distribution and composition. A previous deployment of the in situ Spectral Aerosol Extinction (SpEx) instrument that measured fine mode aerosols (50% size cut of 1.3 µm particle diameter) around the Korean peninsula showed that over this spectral range 2nd order polynomials provided a better fit to the logarithmically transformed spectra than linear fits (representative of Ångström exponents). The two fit parameters (a1, a2) of the polynomials are related to the classic Ångström exponent but provide additional information via their two-dimensional parameter space. The previous work was limited by the lack of commensurate size distribution information. Here, using the FIREX-AQ spectra set it is possible to expand on the previous analysis in three specific ways: 1) size distribution information is available to further elucidate how size distribution maps into (a1, a2) space, 2) the sampled size distributions include larger particles than the Korean study, and 3) the FIREX-AQ data set exhibits smoke-related spectral features in the UV part of the spectrum that are not present in background air nor were they observed previously in the Korean study. The UV spectral features are particularly intriguing as they likely arise from the absorption component of the extinction measurement and therefore may be related to composition. The relationships between the ambient in situ aerosol size distributions, the extinction spectra, and composition will be presented.

Carolyn Jordan↗

Flux-Pinned Dynamics Model Parameterization and Sensitivity Study

Flux-pinned interfaces for spacecraft are an action-at-a-distance technology that can maintain a passively stable equilibrium between two spacecraft in close-proximity using the physics of magnetic flux pinning. Although flux pinning dynamics have been studied from a material-science perspective and at an interface level, there is a need to better understand the sensitivities and implications of system-level designs on the flux-pinned interface dynamics, especially in designs with multiple magnets and superconductors. These interfaces have highly nonlinear, coupled dynamics that are influenced by physical parameters including but not limited to strength of magnetic field sources, field-cooled position, and superconductor geometry. This paper addresses that gap by codifying parametric terms into an improved dynamics model, which can then be used to simulate the interaction of a multiple-superconductor-multiple-magnet interface. A standard starting point for modeling flux pinning dynamics is Kordyuk’s frozen image model, which defines a geometric mapping between magnetic field sources and their corresponding magnetic point source “images inside the volume of the superconductor.” The frozen image model successfully approximates the characteristics of flux pinning dynamics, but could provide more precise position and orientation predictions with the addition of various physical parameter refinements. The sensitivity of the general flux-pinned dynamics model is studied by varying the physical parameters and simulating the systems level dynamics. A predictive dynamics model is crucial to the maturation of this technology so it can be utilized in spacecraft systems, and this work represents a critical step in the development of that model.

Peck, Mason↗