Gaussian Width Research Articles

Calculation of in-situ steady-state heat flux on EAST lower divertor

Heat flux is a key issue in tokamak devices. The non-uniform high heat flux on Plasma-Facing Components (PFCs) has led to local severe damage, including cracks and melting, in current tokamaks such as EAST and WEST. To characterize the non-uniform heat flux loading on the divertor surfaces, the parallel incident heat flux q‖, the decay length λq along the radial direction and the Gaussian spreading width S are used. The q‖ can lead to a very high peak heat flux loading on the divertor surfaces, which may cause critical heat flux problems. Additionally, the decay length is a key consideration for future tokamak designs like ITER. Every effort on the present tokamak devices contributes to updating the scaling of the heat flux. In EAST, a calculation method based on a high spatial resolution IR camera is employed to obtain the heat flux and decay length. The main process involves comparing the surface temperature distribution calculated by Fluent simulation with that measured by an infrared camera. Taking a high heating source discharge (#123059 ∼ 10 MW heating source) as an example, the heat flux is as follows: q‖=216-14+19 MW/m2, with λq=6.2-1.1+1 mm, and S=1.2±0.4 mm; it is in line with Langmuir probe data. The infrared-based heat flux calculation method can calculate the peak incident heat flux and the decay length simultaneously, its result can help to update the scaling model of heat flux, thus not only helping to improve the present device but also offering important reference for future tokamaks

Fault Diagnosis Method for Vacuum Contactor Based on Time-Frequency Graph Optimization Technique and ShuffleNetV2.

This paper presents a fault diagnosis method for a vacuum contactor using the generalized Stockwell transform (GST) of vibration signals. The objective is to solve the problem of low diagnostic performance efficiency caused by the inadequate feature extraction capability and the redundant pixels in the graph background. The proposed method is based on the time-frequency graph optimization technique and ShuffleNetV2 network. Firstly, vibration signals in different states are collected and converted into GST time-frequency graphs. Secondly, multi-resolution GST time-frequency graphs are generated to cover signal characteristics in all frequency bands by adjusting the GST Gaussian window width factor λ. The OTSU algorithm is then combined to crop the energy concentration area, and the size of these time-frequency graphs is optimized by 68.86%. Finally, considering the advantages of the channel split and channel shuffle methods, the ShuffleNetV2 network is adopted to improve the feature learning ability and identify fault categories. In this paper, the CKJ5-400/1140 vacuum contactor is taken as the test object. The fault recognition accuracy reaches 99.74%, and the single iteration time of model training is reduced by 19.42%.

FAUST. XVIII. Evidence of annular substructure in a very young Class 0 disk

Planets form in the disks surrounding young stars. The time at which the planet formation process begins is still an open question. Annular substructures such as rings and gaps in disks are intertwined with planet formation, and thus their presence or absence is commonly used to investigate the onset of this process. Current observations show that a limited number of disks surrounding protostars exhibit annular substructures, all of them in the Class I stage. The lack of observed features in most of these sources may indicate a late emergence of substructures, but it could also be an artifact of these disks being optically thick. To mitigate the problem of optical depth, we investigated substructures within a very young Class 0 disk characterized by low inclination using observations at longer wavelengths. We used 3 mm ALMA observations tracing dust emission at a resolution of 7 au to search for evidence of annular substructures in the disk around the deeply embedded Class 0 protostar Oph A SM1. The observations reveal a nearly face-on disk (inclinationsim 16$^ circ $) extending up to 40 au. The radial intensity profile shows a clear deviation from a smooth profile near 30 au, which we interpret as the presence of either a gap at 28 au or a ring at 34 au with Gaussian widths of $ $ au and $ $ au, respectively. Crucially, the 3 mm emission at the location of the possible gap or ring is determined to be optically thin, precluding the possibility that this feature in the intensity profile is due to the emission being optically thick. Annular substructures resembling those in the more evolved Class I and II disks could indeed be present in the Class 0 stage, which is earlier than suggested by previous observations. Similar observations of embedded disks in which the high-optical-depth problem can be mitigated are clearly needed to better constrain the onset of substructures in the embedded stages.

In-situ ellipsometric study of WO3–x dielectric permittivity during gasochromic colouration

The complex dielectric permittivity of tungsten oxide at all stages of its colouration in a hydrogen-rich atmosphere was retrieved from measured VIS-NIR ellipsometric spectra of WO3/Pd bilayer. The retrieval was done by fitting the spectra with the Cody-Lorentz dispersion model, and, for optical absorption features, two Gaussian functions were added. The band gap edge, the Gaussian center energies, amplitudes, spectral widths and integrals were traced as the redox reaction progressed. Analysis of obtained data provides insight into mechanism of surface and bulk oxygen vacancies formation. We discuss these peculiarities in detail and show how they do affect the optical constants of WO3–x and potential sensors’ response rates.

Magnetic Resonance Image Radiomic Reproducibility: The Impact of Preprocessing on Extracted Features from Gross and High-Risk Clinical Tumor Volumes in Cervical Cancer Patients before Brachytherapy.

Radiomic feature reproducibility assessment is critical in radiomics-based image biomarker discovery. This study aims to evaluate the impact of preprocessing parameters on the reproducibility of magnetic resonance image (MRI) radiomic features extracted from gross tumor volume (GTV) and high-risk clinical tumor volume (HR-CTV) in cervical cancer (CC) patients. This study included 99 patients with pathologically confirmed cervical cancer who underwent an MRI prior to receiving brachytherapy. The GTV and HR-CTV were delineated on T2-weighted MRI and inputted into 3D Slicer for radiomic analysis. Before feature extraction, all images were preprocessed to a combination of several parameters of Laplacian of Gaussian (1 and 2), resampling (0.5 and 1), and bin width (5, 10, 25, and 50). The reproducibility of radiomic features was analyzed using the intra-class correlation coefficient (ICC). Almost all shapes and first-order features had ICC values > 0.95. Most second-order texture features were not reproducible (ICC < 0.95) in GTV and HR-CTV. Furthermore, 20% of all neighboring gray-tone difference matrix texture features had ICC > 0.90 in both GTV and HR-CTV. The results presented here showed that MRI radiomic features are vulnerable to changes in preprocessing, and this issue must be understood and applied before any clinical decision-making. Features with ICC > 0.90 were considered the most reproducible features. Shape and first-order radiomic features were the most reproducible features in both GTV and HR-CTV. Our results also showed that GTV and HR-CTV radiomic features had similar changes against preprocessing sets.

Very-high-energy γ-Ray Emission from Young Massive Star Clusters in the Large Magellanic Cloud

The Tarantula Nebula in the Large Magellanic Cloud is known for its high star formation activity. At its center lies the young massive star cluster R136, providing a significant amount of the energy that makes the nebula shine so brightly at many wavelengths. Recently, young massive star clusters have been suggested to also efficiently produce very high-energy cosmic rays, potentially beyond PeV energies. Here, we report the detection of very-high-energy γ-ray emission from the direction of R136 with the High Energy Stereoscopic System, achieved through a multicomponent, likelihood-based modeling of the data. This supports the hypothesis that R136 is indeed a very powerful cosmic-ray accelerator. Moreover, from the same analysis, we provide an updated measurement of the γ-ray emission from 30 Dor C, the only superbubble detected at TeV energies presently. The γ-ray luminosity above 0.5 TeV of both sources is (2–3) × 1035 erg s−1. This exceeds by more than a factor of 2 the luminosity of HESS J1646−458, which is associated with the most massive young star cluster in the Milky Way, Westerlund 1. Furthermore, the γ-ray emission from each source is extended with a significance of >3σ and a Gaussian width of about 30 pc. For 30 Dor C, a connection between the γ-ray emission and the nonthermal X-ray emission appears likely. Different interpretations of the γ-ray signal from R136 are discussed.

Pressure broadening and narrowing due to oxygen and nitrogen gas mixtures at 1270 nm band: part III

Collisional effects on the absorption spectrum of oxygen and nitrogen gas mixtures at 1270 nm band appear as a broadening or narrowing at the component of Lorentzian width in the Voigt profile. The deconvolution method of spectral lines reveals two kinds of bands, the first centered at 1264 nm, and the second centered at 1268 nm. At high pressures, the Gaussian full width may be fixed, and Voigt's full width at half maximum (FWHM) nearly equals to Lorentzian full width. Partial pressures of each gas were between 1-10 bar at 298 K. New results highlight the effect of nitrogen as a collisional partner on the oxygen spectrum. PACS: 32.30. Bv; 33.20. Ea; 33.20.-t; 34.50.-s; 34.50. Ez; 51.30. +I; 87.64. km.

Nonadiabatic Dynamics with Exact Factorization: Implementation and Assessment.

In this work, we report our implementation of several independent-trajectory mixed-quantum-classical (ITMQC) nonadiabatic dynamics methods based on exact factorization (XF) in the Libra package for nonadiabatic and excited-state dynamics. Namely, the exact factorization surface hopping (SHXF), mixed quantum-classical dynamics (MQCXF), and mean-field (MFXF) are introduced. Performance of these methods is compared to that of several traditional surface hopping schemes, such as the fewest-switches surface hopping (FSSH), branching-corrected surface hopping (BCSH), and the simplified decay of mixing (SDM), as well as conventional Ehrenfest (mean-field, MF) method. Based on a comprehensive set of 1D model Hamiltonians, we find the ranking SHXF ≈ MQCXF > BCSH > SDM > FSSH ≫ MF, with the BCSH sometimes outperforming the XF methods in terms of describing coherences. Although the MFXF method can yield reasonable populations and coherences for some cases, it does not conserve the total energy and is therefore not recommended. We also find that the branching correction for auxiliary trajectories is important for the XF methods to yield accurate populations and coherences. However, the branching correction can worsen the quality of the energy conservation in the MQCXF. Finally, we find that using the time-dependent Gaussian width approximation used in the XF methods for computing decoherence correction can improve the quality of energy conservation in the MQCXF dynamics. The parameter-free scheme of Subotnik for computing the Gaussian widths is found to deliver the best performance in situations where such widths are not known a priori.

Development and application of a three-dimensional pseudo-Voigt function for muon spin relaxation analysis of weakly magnetic materials.

We present a three-dimensional pseudo-Voigt function to analyze muon spin relaxation (μSR) in weakly magnetic materials. Our approach approximates the Voigt function by superimposing Gaussian and Lorentzian functions using a one-dimensional method proposed by Di Rocco and Cruzado [Acta Phys. Pol., A 122, 666 (2012)]. We derive the peak of the Voigt function analytically and express the Half Width at Half Maximum (HWHM) of the Voigt function as a function of the HWHMs of the Gaussian and Lorentzian functions. We compare the pseudo-Voigt function to the exact Voigt function and find a maximum normalized discrepancy of ∼20% at the tail of the distribution function, depending on the ratio of Lorentzian to Gaussian HWHMs and internal magnetic field. We apply the derived three-dimensional pseudo-Voigt function to calculate μSR functions for zero- and longitudinal-field experiments and use them to fit μSR time spectra of La2-xSrxCuO4 with 2.4% Sr, employing a strong collision model with the static-based pseudo-Voigt muon spin relaxation function as the initial condition. Our results show that the Gaussian- and Lorentzian-fitted parameters and fluctuation rate are in good agreement with results from the exact Voigt function for a temperature range of 30-200K, with the deviation of Gaussian and Lorentzian width parameters reaching ∼0.15G below 30K.

Machine-learning descriptor search on the density of states profile of bimetallic alloy systems and comparison with the d-band center theory.

In this study, the electronic density of states (DOSs) calculated with density functional theory (DFT) were analyzed by the machine-learning techniques. More than 400 pure metal and bimetallic alloy systems were calculated with DFT, and obtained the surface DOSs and the CH3 adsorption energy (Ead). By fitting the Gaussian functions to the DOS, multiple descriptors, such as the Gaussian peak positions, heights, and widths were extracted. Several regression methods, such as the least absolute shrinkage of selection operator (LASSO), random-forest, gradient-boosting, and extra-tree were used to find the relationship between these descriptors and the Ead. The results show that the energy position of the peaks in the d-projected DOS is the most important descriptor, in agreement with the previously known d-band center theory. It was also shown that the peak position in d-projected DOS improves the regression model in addition to the d-band center, since it reduces the regression error.

SDSS-IV MaNGA: calibration of astrophysical line-widths in the Hα region using HexPak observations

ABSTRACT We have re-observed $\rm \sim$40 low-inclination, star-forming galaxies from the MaNGA survey (σ ∼ 65 km s−1) at ∼6.5 times higher spectral resolution (σ ∼ 10 km s−1) using the HexPak integral field unit on the WIYN 3.5-m telescope. The aim of these observations is to calibrate MaNGA’s instrumental resolution and to characterize turbulence in the warm interstellar medium and ionized galactic outflows. Here we report the results for the Hα region observations as they pertain to the calibration of MaNGA’s spectral resolution. Remarkably, we find that the previously reported MaNGA line-spread-function (LSF) Gaussian width is systematically underestimated by only 1 per cent. The LSF increase modestly reduces the characteristic dispersion of H ii regions-dominated spectra sampled at 1–2 kpc spatial scales from 23 to 20 km s−1 in our sample, or a 25 per cent decrease in the random-motion kinetic energy. This commensurately lowers the dispersion zeropoint in the relation between line-width and star-formation rate surface-density in galaxies sampled on the same spatial scale. This modest zero-point shift does not appear to alter the power-law slope in the relation between line-width and star-formation rate surface-density. We also show that adopting a scheme whereby corrected line-widths are computed as the square root of the median of the difference in the squared measured line width and the squared LSF Gaussian avoids biases and allows for lower signal-to-noise data to be used reliably.

Propagation of Lorentz-Gaussian elliptical multi-Gaussian correlated Schell-Model beam in uniaxial crystal

The evolution behavior of the intensity profile, beam spreading, and spectral degree of coherence of the Lorentz-Gaussian elliptical multi-Gaussian correlated Schell-Model beam propagating in uniaxial crystal are studied. The expression of the cross spectral density of the beam in uniaxial crystal is obtained based on Huygens-Fresnel integration, and the expressions of spectral coherence and root mean square (rms) beam width are derived. The beam spot is circular or elliptical while the ordinary and extraordinary refractive indices of the crystal are equal or unequal, respectively. The ellipticity of the light spot is affected by the Lorentz parameters. The larger the ratio of ordinary to extraordinary refractive index in uniaxial crystal is, the larger the spectral coherence of beam and rms beam waist width is. The spectral coherence increases with the increase of the Gaussian beam waist and the decrease of the Lorentz parameters. The rms beam width of the beam increases with the increase of the Gaussian beam width and Lorentz partial parameters. With the increase of the transmission distance, the influence of the light source parameters on the rms beam width gradually weakens. The total number of terms of multi-Gaussian correlated Schell-Model (MGSM) source and the spatial coherence lengths add additional degree of freedom for adjusting the spot pattern inside crystal.

Support vector clustering algorithm for cell formation in cellular manufacturing systems

Support Vector Clustering (SVC) algorithm is presented in this study to resolve the cell creation problem in Cellular Manufacturing Systems, even if prior approaches have been used to solve this problem as well. A Gaussian kernel is used in the SVC technique to translate data points from data space to Hilbert space. The method then performs in Hilbert space for the smallest sphere that contains the data images. When the minimal sphere is transferred back to data space, it breaks up into multiple parts, each of which encloses a different point cluster. The scale, at which cluster formation in the data is examined, is determined by the Gaussian kernel's width. Managing overlapping clusters and outliers is made easier by the soft margin constant. The performance of the SVC algorithm is conducted using a collection of two test problems from the literature of Cellular manufacturing systems. The encouraging results are obtained.

Broadening of He 1083nm, 388.8 nm, 501.6 nm, 587.5 nm, 667.8 nm, 706.5 nm, 728.1 nm lines and of H(α), H(β) and O 777 nm lines in atmospheric pressure helium

Helium atoms in electronically excited states are produced in atmospheric pressure parallel plate DBD helium plasma. Pressure broadening coefficients of several helium lines and of O(777 nm), H(β) and H(α) lines are deduced from the analysis of the spectral profiles of those lines. Absorption spectroscopy on He(3S) metastable atoms with a diode laser is used for 1083 nm He line. The influence of the laser power density on recorded absorption spectral profile is analyzed. For the other lines, emission from the plasma is analyzed with a very high resolution 2 m focal length spectrometer, working in the 2nd, 3rd or 4th diffraction order of the 1200 g/mm grating. Instrumental width ΔI ranges between 2.2 and 9.8 pm, depending on the spectral line. Knowing with high precision ΔI and the Doppler widths of the lines and the fact that the resulting Gaussian width of each line remains, at least, 4 times smaller than its Lorentzian width, permits to deduce the pressure broadening coefficients of helium 388.8, 501.6, 587.5, 667.8, 706.5, 728.1 and 1083 nm lines and of 777 O line with less than 3 % uncertainty for most of them. Observation of the forbidden 2p 1P1 –4f 1F3 component in the blue wing of the allowed 492.19 nm He(2p 1P1 –4d 1D2) line, indicates the presence of a static electric field E ≈ 5 ± 1 kV/cm during the 0.4 µs light collection time from the DBD. It is concluded that in pulsed plasmas, like DBD and plasma-jet, before deducing the plasma density from the homogeneous widths of H(β) or H(α) lines, one should ascertain that the static E-field in the gas is small enough during the light collection period for not inducing significant splitting of these lines. This would induce an extra broadening of the line, leading to an overestimated electron density.

Statistical performance of quantile tensor regression with convex regularization

In this paper, we consider high-dimensional quantile tensor regression using a general convex decomposable regularizer and analyze the statistical performances of the estimator. The rates are stated in terms of the intrinsic dimension of the estimation problem, which is, roughly speaking, the dimension of the smallest subspace that contains the true coefficient. Previously, convex regularized tensor regression has been studied with a least squares loss, Gaussian tensorial predictors and Gaussian errors, with rates that depend on the Gaussian width of a convex set. Our results extend the previous work to nonsmooth quantile loss. To deal with the non-Gaussian setting, we use the concept of Rademacher complexity with appropriate concentration inequalities instead of the Gaussian width. For the multi-linear nuclear norm penalty, our Orlicz norm bound for the operator norm of a random matrix may be of independent interest. We validate the theoretical guarantees in numerical experiments. We also demonstrate advantage of quantile regression over mean regression, and compare the performance of convex regularization method and nonconvex decomposition method in solving quantile tensor regression problem in simulation studies.

Astrometry with PRAIA

PRAIA – Package for the Reduction of Astronomical Images Automatically – is a suite of astrometric and photometric tasks designed to cope with huge amounts of heterogeneous observations with fast processing, no human intervention, minimum parameterization and yet maximum possible accuracy and precision. It is the main tool used to analyse astronomical observations by an international collaboration involving Brazilian, French and Spanish researchers under the Lucky Star umbrella for Solar System studies. In this paper, we focus on the astrometric concepts underneath PRAIA, used in reference system works, natural satellite and NEA astrometry for dynamical and ephemeris studies, and lately for the precise prediction of stellar occultations by planetary satellites, dwarf-planets, TNOs, Centaurs and Trojan asteroids. We highlight novelties developed by us and never reported before in the literature, which significantly enhance astrometry precision and automation. Such as the robust object detection and aperture characterization (BOIA), which explains the long standing empirical photometry/astrometry axiom that recommends using apertures with 2 – 3 σ (Gaussian width) radius. We give examples showing the astrometry performance, discuss the advantages of PRAIA over other astrometry packages and comment about future planed astrometry implementations. PRAIA codes and input files are publicly available for the first time at: https://ov.ufrj.br/en/PRAIA/. PRAIA astrometry is useful for Solar System as well as astrophysical observations.

Propagation of hollow higher-order cosh-Gaussian beam in human upper dermis

Optical detection, measurement, and treatment methods are widely used in the medical industry nowadays. The evolution of radiated beams, received power and beam size play vital roles while developing devices. The propagation properties of hollow higher-order cosh-Gaussian beam (HHOCGB) while propagating in human upper dermis tissue are derived analytically and analyzed numerically. The impact of the hollowness parameter, beam order, operating wavelength, and Gaussian beam waists on the beam’s intensity profile is examined. Received power and beam size variations are analyzed considering operating wavelength and Gaussian waist width. According to the results, as the beam propagates, its profile rapidly evolves into a shape with a circular Gaussian peak in the center and petals at the corner. Dark hollow regions are observed among the petals. Furthermore, the received power by HHOCGBs with a higher Gaussian waist width is more than those received by beams with a lower Gaussian waist width. However, at far field, operating at a lower wavelength prevents the increase of the beam spread. Thus, the obtained results will be significant in the bio-optical disease detection and treatment technology development.

Gradient complexity and non-stationary views of differentially private empirical risk minimization

In this paper, we study the Differentially Private Empirical Risk Minimization (DP-ERM) problem, considering both convex and non-convex loss functions. For cases where DP-ERM involves smooth (strongly) convex loss functions with or without non-smooth regularization, we propose several novel methods. These methods achieve (near) optimal expected excess risks (i.e., utility bounds) while reducing the gradient complexity compared to existing approaches. When dealing with DP-ERM and smooth convex loss functions in high dimensions, we introduce an algorithm that achieves a superior upper bound with lower gradient complexity than previous solutions.In the second part of the paper, for DP-ERM with non-convex loss functions, we explore both low and high dimensional spaces. In the low dimensional case with a non-smooth regularizer, we extend an existing approach by measuring the utility using the ℓ2 norm of the projected gradient. Furthermore, we introduce a novel error bound measurement, transitioning from empirical risk to population risk by employing the expected ℓ2 norm of the gradient. For the high dimensional case, we demonstrate that by measuring utility with the Frank-Wolfe gap, we can bound the utility using the Gaussian Width of the constraint set, instead of the dimensionality (p) of the underlying space. We also show that the advantages of this approach can be achieved by measuring the ℓ2 norm of the projected gradient. Finally, we reveal that the utility of certain special non-convex loss functions can be reduced to a level (depending only on log⁡p) similar to that of convex loss functions.

Comparison of Different Radial Basis Function Networks for the Electrical Impedance Tomography (EIT) Inverse Problem

This paper aims to determine whether regularization improves image reconstruction in electrical impedance tomography (EIT) using a radial basis network. The primary purpose is to investigate the effect of regularization to estimate the network parameters of the radial basis function network to solve the inverse problem in EIT. Our approach to studying the efficacy of the radial basis network with regularization is to compare the performance among several different regularizations, mainly Tikhonov, Lasso, and Elastic Net regularization. We vary the network parameters, including the fixed and variable widths for the Gaussian used for the network. We also perform a robustness study for comparison of the different regularizations used. Our results include (1) determining the optimal number of radial basis functions in the network to avoid overfitting; (2) comparison of fixed versus variable Gaussian width with or without regularization; (3) comparison of image reconstruction with or without regularization, in particular, no regularization, Tikhonov, Lasso, and Elastic Net; (4) comparison of both mean square and mean absolute error and the corresponding variance; and (5) comparison of robustness, in particular, the performance of the different methods concerning noise level. We conclude that by looking at the R2 score, one can determine the optimal number of radial basis functions. The fixed-width radial basis function network with regularization results in improved performance. The fixed-width Gaussian with Tikhonov regularization performs very well. The regularization helps reconstruct the images outside of the training data set. The regularization may cause the quality of the reconstruction to deteriorate; however, the stability is much improved. In terms of robustness, the RBF with Lasso and Elastic Net seem very robust compared to Tikhonov.

Gaussian and Faddeeva broadening of the Franz-Keldysh oscillations at three-dimensional critical-points

Faddeeva broadening (FB) couples the physical characteristics of Gaussian and Lorentzian broadening into a single profile shaping the spectral response of dielectric functions. The electric field induces Franz-Keldysh oscillations (FKOs) as deviations in the dielectric function of semiconductors. We investigated the impact of Gaussian and FB on FKOs at the isotropic M0 of three-dimensional critical points. The twenty-pole Martin–Donoso–Zamudio quadrature was applied to compute the FB of FKOs in differential reflectivity based on the electro-optic function, H(z), with the complex Airy function, Ai(z). H(z) was simplified into a compact product of to reduce the truncation error and determine its asymptotics. We derived a general asymptotic expansion of order N, accounting for Stokes’ phenomenon as the arg(z) crosses The computation of H(z) is detailed for twelve digits of accuracy. The effects of higher Gaussian and FB widths on the damping of FKOs are assessed using FKO peak-to-peak attenuations. For the low-field regime, this work H(z) smoothly evolves into Aspnes’ third derivative functional form (TDFF). Between low- to intermediate-field regimes, we investigated the boundaries for the relevant use of the TDFF by assessing parameters extracted from simulated lineshapes, and the average root mean-squared error. We fitted of the Faddeeva broadened single Airy model to published experimental photoreflectance (PR) lineshapes of InGaAsP. To model degenerate light-and heavy-holes transitions, we fitted of the Faddeeva broadened double Airy model to published experimental contactless electroreflectance (CER) lineshapes of GaAs. In addition to legacy mean-squared error () and coefficient of determination (), the goodness of fit was evaluated using the unbiased Akaike information criteria. The effectiveness of Faddeeva versus Lorentzian broadening in sample PR and CER spectra analysis was assessed using Airy function FKO models. Concludingly, the FB of the differential reflectivity model outperformed the Lorentzian broadening even with the empirical energy-dependent width.