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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

A NEW METHOD FOR DERIVING THE STELLAR BIRTH FUNCTION OF RESOLVED STELLAR POPULATIONS

We present a new method for deriving the stellar birth function (SBF) of resolved stellar populations. The SBF (stars born per unit mass, time, and metallicity) is the combination of the initial mass function (IMF), the star formation history (SFH), and the metallicity distribution function (MDF). The framework of our analysis is that of Poisson Point Processes (PPPs), a class of statistical models suitable when dealing with points (stars) in a multidimensional space (the measurement space of multiple photometric bands). The theory of PPPs easily accommodates the modeling of measurement errors as well as that of incompleteness. Our method avoids binning stars in the color–magnitude diagram and uses the whole likelihood function for each data point; combining the individual likelihoods allows the computation of the posterior probability for the population's SBF. Within the proposed framework it is possible to include nuisance parameters, such as distance and extinction, by specifying their prior distributions and marginalizing over them. The aim of this paper is to assess the validity of this new approach under a range of assumptions, using only simulated data. Forthcoming work will show applications to real data. Although it has a broad scope of possible applications, we have developed this method to study multi-band Hubble Space Telescope observations of the Milky Way Bulge. Therefore we will focus on simulations with characteristics similar to those of the Galactic Bulge.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

An all-sky sample of intermediate-mass star-forming regions

We present an all-sky sample of 984 candidate intermediate-mass Galactic star-forming regions that are color selected from the Infrared Astronomical Satellite (IRAS) Point Source Catalog and morphologically classify each object using mid-infrared Wide-field Infrared Survey Explorer (WISE) images. Of the 984 candidates, 616 are probable star-forming regions (62.6%), 128 are filamentary structures (13.0%), 39 are point-like objects of unknown nature (4.0%), and 201 are galaxies (20.4%). We conduct a study of four of these regions, IRAS 00259+5625, IRAS 00420+5530, IRAS 01080+5717, and IRAS 05380+2020, at Galactic latitudes |b| > 5° using optical spectroscopy from the Wyoming Infrared Observatory, along with near-infrared photometry from the Two-Micron All Sky Survey, to investigate their stellar content. New optical spectra, color-magnitude diagrams, and color-color diagrams reveal their extinctions, spectrophotometric distances, and the presence of small stellar clusters containing 20-78 M {sub ☉} of stars. These low-mass diffuse star clusters contain ∼65-250 stars for a typical initial mass function, including one or more mid-B stars as their most massive constituents. Using infrared spectral energy distributions we identify young stellar objects near each region and assign probable masses and evolutionary stages to the protostars. The total infrared luminosity lies in the range 190-960 L {sub ☉}, consistent with the sum of the luminosities of the individually identified young stellar objects.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

HHL algorithm with mapping function and enhanced sampling for model predictive control in microgrids

Here, this paper presents a refined quantum Harrow Hassidim Lloyd (HHL) algorithm for microgrid control. The first novelty of the developed method is that a mapping shift function enables the original HHL algorithm to handle general linear equations with non-singular and indefinite matrix. Second, a method of Matrix Extension for Amplifying Sampling Probabilities of Intended Solution (ME-ASPI) is proposed to design the reformulated linear algebraic equations, allowing for improved sampling efficiency of the quantum tomography in the refined HHL algorithm. Then, we applied the method to solve the model predictive control (MPC) problem in nonlinear dynamical microgrids. Specifically, with the ME-ASPI method, the refined HHL algorithm can effectively obtain the intended partial optimal control inputs for MPC. The optimization of quadratic programming problem in each time step of MPC is transformed into a linear system problem, which is addressed by the proposed quantum solver through using only partial information, with the time complexity improved from $\mathscr{O}(\mathscr{N}^{2.37286})$ classically to $\mathscr{O}(\mathscr{N}^{2} log \mathscr{N}$ x $p$ log $p)$ in quantum. Numerical examples have validated the effectiveness of the refined HHL algorithm with the proposed mapping function and the ME-ASPI method. By leveraging quantum properties, the proposed method provides a hybrid quantum–classical framework for microgrid control. This generic method can also potentially tackle many other challenges in analyzing and controlling general complex engineered systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2014

Low energy spectral index and E{sub p} evolution of quasi-thermal photosphere emission of gamma-ray bursts

Recent observations by the Fermi satellite suggest that a photosphere emission component is contributing to the observed spectrum of many gamma-ray bursts (GRBs). One important question is whether the photosphere component can interpret the typical 'Band' function of GRBs with a typical low energy photon spectral index α ∼ –1. We perform a detailed study of the photosphere emission spectrum by progressively introducing several physical ingredients previously not fully incorporated, including the probability distribution of the location of a dynamically evolving photosphere, superposition of emission from an equal arrival time 'volume' in a continuous wind, the evolution of optical depth of a wind with finite but evolving outer boundary, as well as the effect of different top-hat wind luminosity (L{sub w} ) profiles. By assuming a comoving blackbody spectrum emerging from the photosphere, we find that for an outflow with a constant or increasing L{sub w} , the low-energy spectrum below the peak energy (E{sub p} ), can be modified to F {sub ν} ∼ ν{sup 1.5} (α ∼ +0.5). A softer (–1 < α < +0.5) or flat (α = –1) spectrum can be obtained during the L{sub w} decreasing phase or high-latitude-emission-dominated phase. We also study the evolution of E{sub p} as a function of wind and photosphere luminosity in this photosphere model. An E{sub p} – L tracking pattern can be reproduced if a certain positive dependence between the dimensionless entropy η and L{sub w} is introduced. However, the hard-to-soft evolution pattern cannot be reproduced unless a contrived condition is invoked. In order to interpret the Band spectrum, a more complicated photosphere model or a different energy dissipation and radiation mechanism is needed.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

A Framework for Parametric and Predictive Uncertainty Quantification in the E3SM Land Model: Assessing Site and Observable Generalizability

Quantifying parametric uncertainty using observations from individual sites provides a critical foundation for Earth system modeling, serving as a necessary first step before scaling up to regional or global applications. This study introduces a novel computational framework designed to enhance model predictability by reducing parametric uncertainty and assessing site and observable generalizability using various observational constraints. The framework integrates five components: Model Simulation, Statistical Emulation, Global Sensitivity Analysis (GSA), Model Calibration, and Model Prediction. Using the E3SM land model, we simulated site-level land-atmosphere carbon and energy fluxes from 2003 to 2007 across five evergreen needleleaf FLUXNET sites, perturbing 26 vegetation-related model parameters. Gaussian process emulators were employed to expedite GSA and model calibration. Four critical parameters that strongly influence selected land-atmosphere fluxes were identified by GSA. Bayesian approaches were used to infer parameter probability distributions leveraging synthetic data and FLUXNET observations. The results reveal that posterior parameter distributions vary significantly across different sites and observables within the same plant functional type. Probabilistic predictions indicate that parameters calibrated at one site can enhance predictive accuracy at other sites, although site heterogeneity may sometimes outweigh parametric uncertainty. Additionally, the probabilistic predictions demonstrate that calibration for one variable can also improve predictability for other variables, thereby maximizing predictive capabilities with limited observations. This framework provides a powerful approach for reducing parametric uncertainty in Earth system models and deepening our understanding of carbon dynamics and energy cycles. Its adaptability makes it a valuable tool for broader applications in Earth system modeling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Effective field theory analysis of 3 He–α scattering data

We treat low-energy 3 He–α elastic scattering in an effective field theory (EFT) that exploits the separation of scales in this reaction. We compute the amplitude up to next-to-next-to-leading order, developing a hierarchy of the effective-range parameters (ERPs) that contribute at various orders. We use the resulting formalism to analyse data for recent measurements at center-of-mass energies of 0.38–3.12 MeV using the scattering of nuclei in inverse kinematics (SONIK) gas target at TRIUMF as well as older data in this energy regime. We employ a likelihood function that incorporates the theoretical uncertainty due to truncation of the EFT and use Markov chain Monte Carlo sampling to obtain the resulting posterior probability distribution. We find that the inclusion of a small amount of data on the analysing power A y is crucial to determine the sign of the p-wave splitting in such an analysis. Here, the combination of A y and SONIK data constrains all ERPs up to O(p 4 ) in both s- and p-waves quite well. The asymptotic normalisation coefficients and s-wave scattering length are consistent with a recent EFT analysis of the capture reaction 3 He(α, γ) 7 Be.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

Interpretable machine learning study of the many-body localization transition in disordered quantum Ising spin chains

We apply support vector machine (SVM) to study the phase transition between many-body localized and thermal phases in a disordered quantum Ising chain in a transverse external field. The many-body eigenstate energy E is bounded by a bandwidth W = E max – E min . The transition takes place on a phase diagram spanned by the energy density ε = 2(E – E min )/W and the disorder strength δJ of the spin interaction uniformly distributed within [ – δJ, δJ], formally parallel to the mobility edge in Anderson localization. In our paper, we use the labeled probability density of eigenstate wave functions belonging to the deeply localized and thermal regimes at two different energy densities (ε's) as the training set, i.e., providing labeled data at four corners of the phase diagram. Then we employ the trained SVM to predict the whole phase diagram. The obtained phase boundary qualitatively agrees with previous work using entanglement entropy to characterize these two phases. We further analyze the decision function of the SVM to interpret its physical meaning and find that it is analogous to the inverse participation ratio in configuration space. Our findings demonstrate the ability of the SVM to capture potential quantities that may characterize the many-body localization phase transition.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2014

Power dependence of electron density at various pressures in inductively coupled plasmas

Experimental observation of the electron density variation in inductively coupled plasmas with the electron energy probability function (EEPFs) was performed at various gas pressures at two RF powers (25 W and 200 W). The measured EEPFs at high power discharges (200 W) showed a Maxwellian distribution, while evolution of the EEPFs from a bi-Maxwellian distribution to a Druyvesteyn-like distribution was observed at low RF powers (25 W) with increasing pressure. A discrepancy of the electron density variation between the two RF powers was observed. This difference is explained by the modified collisional loss and the Bohm velocity from the EEPF of the bi-Maxwellian distribution and the Druyvesteyn–like distribution.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Formal Experimentation and Analysis of Handheld RFID Readers as a Tool for Nuclear Material Accounting

Commercial, off-the-shelf Radio Frequency Identification (RFID) systems have been successfully deployed for inventory tracking in numerous industries, but their viability in the tracking of complex environments containing nuclear material is less understood. Of primary interest in this setting is a RFID tracking system for nuclear material accounting which can reliably identify as many tags as possible with high accuracy, while also reducing an operator’s exposure to radiation. In this work, we develop a formal statistical approach to identify relevant handheld RFID reader settings which optimize tagging performance. To achieve this goal, we design a full factorial split-plot experiment for a static shelf configuration scene with 50 randomly placed nuclear material containers affixed with RFID tags. We use Bayesian inference to fit a second-order response surface model which expresses the probability of a successful match for each container as a function of the experimental factors. Such effects are allowed to vary across individual containers and the containers’ population in its entirety to estimate overall effects. Uncertainties of estimates and predictions are quantified via their corresponding posterior distributions. Following extensive model checking and validation, the fitted model is used to identify experimental factors which maximize matching probabilities at both the container-level and for the full shelf configuration scene. We also analyze sensitivity of performance to relevant factors.

25 ENERGY STORAGE↗
DOE OSTI2019

Partial relay selection in mixed RF/FSO dual-hop system over unified M-distributed fading channel with non-zero boresight pointing errors

In this paper, the performance of a partial relay selection-based amplify-and-forward mixed radio frequency/free space optical (RF/FSO) system with a direct RF link and outdated channel state information (CSI) is presented. The source-to-relay and source-to-destination RF links are subjected to Rayleigh distributions while the relay-to-destination FSO link experiences Malaga (M)-distribution with generalized non-zero boresight pointing errors. It is also assumed that selection combining diversity with heterodyne detection is considered for the signal reception at the destination. Moreover, the cumulative distribution functions of the end-to-end signal-to-noise under the influence of with/or without a direct link are then derived for the concerned system. Through this, the closed-form expressions for the system outage probability and average bit error rate are obtained. Thus, the influence of atmospheric turbulence, outdated CSI and relay selection are evaluated for the system under zero boresight and non-zero boresight displacement pointing errors scenarios. The results illustrated that the mixed RF/FSO system with a direct link offers better performance than the one without a direct link. The accuracy of the presented results is validated by Monte-Carlo simulation.

42 ENGINEERING↗
DOE OSTI2018

Convergence and Efficiency of Adaptive Importance Sampling Techniques with Partial Biasing

We propose a new Monte Carlo method to efficiently sample a multimodal distribution (known up to a normalization constant). We consider a generalization of the discrete-time Self Healing Umbrella Sampling method, which can also be seen as a generalization of well-tempered metadynamics. The dynamics is based on an adaptive importance technique. The importance function relies on the weights (namely the relative probabilities) of disjoint sets which form a partition of the space. These weights are unknown but are learnt on the fly yielding an adaptive algorithm. In the context of computational statistical physics, the logarithm of these weights is, up to an additive constant, the free-energy, and the discrete valued function defining the partition is called the collective variable. The algorithm falls into the general class of Wang–Landau type methods, and is a generalization of the original Self Healing Umbrella Sampling method in two ways: (i) the updating strategy leads to a larger penalization strength of already visited sets in order to escape more quickly from metastable states, and (ii) the target distribution is biased using only a fraction of the free-energy, in order to increase the effective sample size and reduce the variance of importance sampling estimators. We prove the convergence of the algorithm and analyze numerically its efficiency on a toy example.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2011

PRE-MAIN-SEQUENCE STELLAR POPULATIONS ACROSS SHAPLEY CONSTELLATION III. I. PHOTOMETRIC ANALYSIS AND IDENTIFICATION ,

We present our investigation of pre-main-sequence (PMS) stellar populations in the Large Magellanic Cloud (LMC) from imaging with Hubble Space Telescope Wide-Field Planetary Camera 2. Our targets of interest are four star-forming regions located at the periphery of the super-giant shell LMC 4 (Shapley Constellation III). The PMS stellar content of the regions is revealed through the differential Hess diagrams and the observed color-magnitude diagrams (CMDs). Further statistical analysis of stellar distributions along cross sections of the faint part of the CMDs allowed the quantitative assessment of the PMS stars census, and the isolation of faint PMS stars as the true low-mass stellar members of the regions. These distributions are found to be well represented by a double-Gaussian function, the first component of which represents the main-sequence field stars and the second the native PMS stars of each region. Based on this result, a cluster membership probability was assigned to each PMS star according to its CMD position. The higher extinction in the region LH 88 did not allow the unambiguous identification of its native stellar population. The CMD distributions of the PMS stars with the highest membership probability in the regions LH 60, LH 63, and LH 72 exhibit an extraordinary similarity among the regions, suggesting that these stars share common characteristics, as well as common recent star formation history. Considering that the regions are located at different areas of the edge of LMC 4, this finding suggests that star formation along the super-giant shell may have occurred almost simultaneously.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

The Robust Dynamical Contribution to Precipitation Extremes in Idealized Warming Simulations across Model Resolutions

The impact of the circulation shift under climate warming on the distribution of precipitation extremes and the associated sensitivity to model resolution are investigated using the aquaplanet Community Atmosphere Model CAM3. The response of the probability density function of the precipitation to a uniform SST warming can be interpreted as superimposition of a dynamically induced poleward shift and a thermodynamically induced upward shift toward higher intensities, which give rise to manyfold increase in the frequency of the most extreme categories of the precipitation events at the poleward side of the midlatitude storm track. Meanwhile, the thermodynamic contribution to the intensification of the precipitation extremes is substantially less than expected from the Clausius-Clapeyron relation, implicative of significant change in the vertical structure of the precipitation processes. While coarser resolutions underestimate the dynamical contribution to the increase of precipitation extremes, a modest increase of the equator-to-pole SST warming gradient can have a significant opposite effect.

dynamical↗
DOE OSTI2017

Crystal chemical characterization of mullite-type aluminum borate compounds

Al-rich aluminum borates were prepared by different synthesis routes using various Al/B ratios, characterized by diffraction methods, spectroscopy and prompt gamma activation analysis. The {sup 11}B NMR data show a small amount of BO{sub 4} species in all samples. The chemical analysis indicates a trend in the Al/B ratio instead of a fixed composition. Both methods indicate a solid solution Al{sub 5−x}B{sub 1+x}O{sub 9} where Al is substituted by B in the range of 1–3%. The structure of B-rich Al{sub 4}B{sub 2}O{sub 9} (C2/m, a=1488 pm, b=553 pm, c=1502 pm, ß=90.6°), was re-investigated by electron diffraction methods, showing that structural details vary within a crystallite. In most of the domains the atoms are orderly distributed, showing no signal for the postulated channel oxygen atom O5. The absence of O5 is supported by density functional theory calculations. Other domains show a probable disordered configuration of O5 and O10, indicated by diffuse scattering along the b direction. - Graphical abstract: Projections of three-dimensional electron diffraction space of Al{sub 4}B{sub 2}O{sub 9} along the main directions. - Highlights: • The crystal structure of Al{sub 4}B{sub 2}O{sub 9} was re-evaluated. • Structural details vary among different crystals and inside Al{sub 4}B{sub 2}O{sub 9} crystallites. • Diffuse scattering indicate a probable disordered configuration of O5 and O10. • A solid solution series for Al{sub 5−x}B{sub x}O{sub 9} is indicated by PGAA and NMR spectroscopy. • The presence of BO{sub 4} groups is confirmed by {sup 11}B MAS NMR spectroscopy for Al{sub 5−x}B{sub 1+x}O{sub 9}.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

PRIMUS: AN OBSERVATIONALLY MOTIVATED MODEL TO CONNECT THE EVOLUTION OF THE ACTIVE GALACTIC NUCLEUS AND GALAXY POPULATIONS OUT TO z ∼ 1

We present an observationally motivated model to connect the active galactic nucleus (AGN) and galaxy populations at 0.2 < z < 1.0 and predict the AGN X-ray luminosity function (XLF). We start with measurements of the stellar mass function of galaxies (from the Prism Multi-object Survey) and populate galaxies with AGNs using models for the probability of a galaxy hosting an AGN as a function of specific accretion rate. Our model is based on measurements indicating that the specific accretion rate distribution is a universal function across a wide range of host stellar masses with slope γ{sub 1} ≈ –0.65 and an overall normalization that evolves with redshift. We test several simple assumptions to extend this model to high specific accretion rates (beyond the measurements) and compare the predictions for the XLF with the observed data. We find good agreement with a model that allows for a break in the specific accretion rate distribution at a point corresponding to the Eddington limit, a steep power-law tail to super-Eddington ratios with slope γ{sub 2}=-2.1{sup +0.3}{sub -0.5}, and a scatter of 0.38 dex in the scaling between black hole and host stellar mass. Our results show that samples of low luminosity AGNs are dominated by moderately massive galaxies (M{sub *} ∼ 10{sup 10}-10{sup 11} M{sub ☉}) growing with a wide range of accretion rates due to the shape of the galaxy stellar mass function rather than a preference for AGN activity at a particular stellar mass. Luminous AGNs may be a severely skewed population with elevated black hole masses relative to their host galaxies and in rare phases of rapid accretion.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Distributionally Robust Partially Observable Markov Decision Process with Moment-Based Ambiguity

In this paper, we consider a distributionally robust partially observable Markov decision process (DR-POMDP), where the distribution of the transition-observation probabilities is unknown at the beginning of each decision period, but their realizations can be inferred using side information at the end of each period after an action being taken. We build an ambiguity set of the joint distribution using bounded moments via conic constraints and seek an optimal policy to maximize the worst-case (minimum) reward for any distribution in the set. We show that the value function of DR-POMDP is piecewise linear convex with respect to the belief state and propose a heuristic search value iteration method for obtaining lower and upper bounds of the value function. We conduct numerical studies and demonstrate the computational performance of our approach via testing instances of a dynamic epidemic control problem. Our results show that DR-POMDP can produce more robust policies under misspecified distributions of transition-observation probabilities as compared to POMDP but has less costly solutions than robust POMDP. The DR-POMDP policies are also insensitive to varying parameter in the ambiguity set and to noise added to the true transition-observation probability values obtained at the end of each decision period.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Statistical properties of Charney-Hasegawa-Mima zonal flows

A theoretical interpretation of numerically generated probability density functions (PDFs) of intermittent plasma transport events in unforced zonal flows is provided within the Charney-Hasegawa-Mima (CHM) model. The governing equation is solved numerically with various prescribed density gradients that are designed to produce different configurations of parallel and anti-parallel streams. Long-lasting vortices form whose flow is governed by the zonal streams. It is found that the numerically generated PDFs can be matched with analytical predictions of PDFs based on the instanton method by removing the autocorrelations from the time series. In many instances, the statistics generated by the CHM dynamics relaxes to Gaussian distributions for both the electrostatic and vorticity perturbations, whereas in areas with strong nonlinear interactions it is found that the PDFs are exponentially distributed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2013

ESTIMATING THE PROPERTIES OF HARD X-RAY SOLAR FLARES BY CONSTRAINING MODEL PARAMETERS

We wish to better constrain the properties of solar flares by exploring how parameterized models of solar flares interact with uncertainty estimation methods. We compare four different methods of calculating uncertainty estimates in fitting parameterized models to Ramaty High Energy Solar Spectroscopic Imager X-ray spectra, considering only statistical sources of error. Three of the four methods are based on estimating the scale-size of the minimum in a hypersurface formed by the weighted sum of the squares of the differences between the model fit and the data as a function of the fit parameters, and are implemented as commonly practiced. The fourth method is also based on the difference between the data and the model, but instead uses Bayesian data analysis and Markov chain Monte Carlo (MCMC) techniques to calculate an uncertainty estimate. Two flare spectra are modeled: one from the Geostationary Operational Environmental Satellite X1.3 class flare of 2005 January 19, and the other from the X4.8 flare of 2002 July 23. We find that the four methods give approximately the same uncertainty estimates for the 2005 January 19 spectral fit parameters, but lead to very different uncertainty estimates for the 2002 July 23 spectral fit. This is because each method implements different analyses of the hypersurface, yielding method-dependent results that can differ greatly depending on the shape of the hypersurface. The hypersurface arising from the 2005 January 19 analysis is consistent with a normal distribution; therefore, the assumptions behind the three non-Bayesian uncertainty estimation methods are satisfied and similar estimates are found. The 2002 July 23 analysis shows that the hypersurface is not consistent with a normal distribution, indicating that the assumptions behind the three non-Bayesian uncertainty estimation methods are not satisfied, leading to differing estimates of the uncertainty. We find that the shape of the hypersurface is crucial in understanding the output from each uncertainty estimation technique, and that a crucial factor determining the shape of hypersurface is the location of the low-energy cutoff relative to energies where the thermal emission dominates. The Bayesian/MCMC approach also allows us to provide detailed information on probable values of the low-energy cutoff, E{sub c} , a crucial parameter in defining the energy content of the flare-accelerated electrons. We show that for the 2002 July 23 flare data, there is a 95% probability that E{sub c} lies below approximately 40 keV, and a 68% probability that it lies in the range 7-36 keV. Further, the low-energy cutoff is more likely to be in the range 25-35 keV than in any other 10 keV wide energy range. The low-energy cutoff for the 2005 January 19 flare is more tightly constrained to 107 {+-} 4 keV with 68% probability. Using the Bayesian/MCMC approach, we also estimate for the first time probability density functions for the total number of flare-accelerated electrons and the energy they carry for each flare studied. For the 2002 July 23 event, these probability density functions are asymmetric with long tails orders of magnitude higher than the most probable value, caused by the poorly constrained value of the low-energy cutoff. The most probable electron power is estimated at 10{sup 28.1} erg s{sup -1}, with a 68% credible interval estimated at 10{sup 28.1}-10{sup 29.0} erg s{sup -1}, and a 95% credible interval estimated at 10{sup 28.0}-10{sup 30.2} erg s{sup -1}. For the 2005 January 19 flare spectrum, the probability density functions for the total number of flare-accelerated electrons and their energy are much more symmetric and narrow: the most probable electron power is estimated at 10{sup 27.66{+-}0.01} erg s{sup -1} (68% credible intervals). However, in this case the uncertainty due to systematic sources of error is estimated to dominate the uncertainty due to statistical sources of error.

79 ASTRONOMY AND ASTROPHYSICS↗