Source Model Research Articles

EEG/MEG source imaging of deep brain activity within the maximum entropy on the mean framework: Simulations and validation in epilepsy.

Electro/Magneto-EncephaloGraphy (EEG/MEG) source imaging (EMSI) of epileptic activity from deep generators is often challenging due to the higher sensitivity of EEG/MEG to superficial regions and to the spatial configuration of subcortical structures. We previously demonstrated the ability of the coherent Maximum Entropy on the Mean (cMEM) method to accurately localize the superficial cortical generators and their spatial extent. Here, we propose a depth-weighted adaptation of cMEM to localize deep generators more accurately. These methods were evaluated using realistic MEG/high-density EEG (HD-EEG) simulations of epileptic activity and actual MEG/HD-EEG recordings from patients with focal epilepsy. We incorporated depth-weighting within the MEM framework to compensate for its preference for superficial generators. We also included a mesh of both hippocampi, as an additional deep structure in the source model. We generated 5400 realistic simulations of interictal epileptic discharges for MEG and HD-EEG involving a wide range of spatial extents and signal-to-noise ratio (SNR) levels, before investigating EMSI on clinical HD-EEG in 16 patients and MEG in 14 patients. Clinical interictal epileptic discharges were marked by visual inspection. We applied three EMSI methods: cMEM, depth-weighted cMEM and depth-weighted minimum norm estimate (MNE). The ground truth was defined as the true simulated generator or as a drawn region based on clinical information available for patients. For deep sources, depth-weighted cMEM improved the localization when compared to cMEM and depth-weighted MNE, whereas depth-weighted cMEM did not deteriorate localization accuracy for superficial regions. For patients' data, we observed improvement in localization for deep sources, especially for the patients with mesial temporal epilepsy, for which cMEM failed to reconstruct the initial generator in the hippocampus. Depth weighting was more crucial for MEG (gradiometers) than for HD-EEG. Similar findings were found when considering depth weighting for the wavelet extension of MEM. In conclusion, depth-weighted cMEM improved the localization of deep sources without or with minimal deterioration of the localization of the superficial sources. This was demonstrated using extensive simulations with MEG and HD-EEG and clinical MEG and HD-EEG for epilepsy patients.

A transient formulation of entropy and heat transfer coefficients of Newton's cooling law with the unifying entropy potential difference in compressible flows

The original Newton's law of cooling is considered an ideal convection model of a point source ignoring conduction, but its unknown convection conductance and inconsistent thermal potential difference make it difficult to further elucidate the transient heat transfer mechanism of convection because of the no-slip condition at the interface between a body and a fluid. For this purpose, both the convective entropy transfer theory and the hypothesis of the isothermal velocity sublayer are developed to recast Newton's law of cooling into a standard Ohm's law form via the unified entropy driving force and the unambiguous entropy transfer coefficient. An explicit expression for the transient heat transfer coefficient is presented theoretically and experimentally in compressible flows by virtue of the product of the free-stream velocity, the volumetric thermal capacity of the fluid, and the near-wall velocity constant. The unified thermal potential difference is established between the body temperature and the total temperature (reduced to the ambient temperature for incompressible fluids). The physical mechanism of convection mode in the original Newton's cooling law is reasonably explained by the entropy transfer theory and entropy transfer efficiency, and the formulae for the entropy flux vector driven by the standard entropy potential difference and the rate of entropy generation are obtained. The analytical heat transfer coefficients as well as the standard thermal driving forces are validated by comparison with the forced convection experiment with a maximum error of 4.6 % in incompressible flows and the previous Newton's benchmark cooling experiments with the maximum error of 6.7 % in compressible flows. The effects of radiation on the total heat transfer coefficient are also analyzed quantitatively.

Domain adaptation using AdaBN and AdaIN for high-resolution IVD mesh reconstruction from clinical MRI.

Deep learning has firmly established its dominance in medical imaging applications. However, careful consideration must be exercised when transitioning a trained source model to adapt to an entirely distinct environment that deviates significantly from the training set. The majority of the efforts to mitigate this issue have predominantly focused on classification and segmentation tasks. In this work, we perform a domain adaptation of a trained source model to reconstruct high-resolution intervertebral disc meshes from low-resolution MRI. To address the outlined challenges, we use MRI2Mesh as the shape reconstruction network. It incorporates three major modules: image encoder, mesh deformation, and cross-level feature fusion. This feature fusion module is used to encapsulate local and global disc features. We evaluate two major domain adaptation techniques: adaptive batch normalization (AdaBN) and adaptive instance normalization (AdaIN) for the task of shape reconstruction. Experiments conducted on distinct datasets, including data from different populations, machines, and test sites demonstrate the effectiveness of MRI2Mesh for domain adaptation. MRI2Mesh achieved up to a 14% decrease in Hausdorff distance (HD) and a 19% decrease in the point-to-surface (P2S) metric for both AdaBN and AdaIN experiments, indicating improved performance. MRI2Mesh has demonstrated consistent superiority to the state-of-the-art Voxel2Mesh network across a diverse range of datasets, populations, and scanning protocols, highlighting its versatility. Additionally, AdaBN has emerged as a robust method compared to the AdaIN technique. Further experiments show that MRI2Mesh, when combined with AdaBN, holds immense promise for enhancing the precision of anatomical shape reconstruction in domain adaptation.

Double closed loop PI control with full compensation arc elimination based on zero sequence voltage of neutral point

Aiming at the problem of zero sequence voltage generated by unbalance parameters of line to ground, which affects arc suppression effect of grounding fault of controllable voltage source. By analyzing the influence of ground unbalance parameters on the arc suppression effect of controllable voltage source under different grounding modes, the mechanism of full compensation arc suppression based on zero sequence voltage of neutral point is revealed, and on this basis, a fully compensated arc suppression model of controllable voltage source controlled by double closed loop PI is established, and the deviation control is carried out by using the neutral voltage of distribution network and the voltage of fault phase supply. The residual voltage ring adopts the ground fault phase residual voltage for closed loop control. The simulation results show that the dual-closed-loop PI control algorithm can continuously stabilize the output waveform of the controllable voltage source. When the transition resistance is 0.1 ~ 10 kΩ, the residual voltage stabilization time of the independent controllable voltage source grounding method is 43 ms ~ 2.4 s, and the parallel arc suppression coil grounding method is 43 ms ~ 4.7 s. The proposed dual closed-loop PI control method for neutral point voltage deviation and fault residual voltage can stabilize the residual voltage of the grounded fault phase to below 10 V, forcing reliable arc extinction at the grounded fault point, exhibiting good stability. Low-voltage simulation tests have also proved the feasibility of the algorithm.

Compounding impacts of the earthquake and submarine landslide on the Toyama Bay tsunami during the January 2024 Noto Peninsula event

The January 2024 Noto Peninsula earthquake (Mw 7.6) generated a destructive tsunami in the Sea of Japan region. Locally, inside Toyama Bay, the tsunami arrived at the Toyama wave and tide gauges within 2–3 min of the earthquake. Such an early tsunami arrival is inconsistent with the epicentral distance of ∼60 km. The travel time of the earthquake-induced tsunami is anticipated to be around 20 min, which is confirmed through tsunami simulations. Based on spectral and wavelet analyses of the Toyama tide and wave gauge records, we found 5 min, 14 min, and 32 min dominant wave periods. The shorter wave periods of 5 and 14 min are likely associated with a submarine landslide due to their early arrivals, as evidenced in our wavelet analysis. We then identified a potential submarine landslide location using the tsunami back-propagated travel time technique and visual inspection of the bathymetric profile. Conducting several simulations and comparing simulated and observed waveforms, we identified a seafloor landslide length of approximately 3000 m located ∼4 km offshore Toyama City. Our combined earthquake-landslide source model better reproduces the tsunami observations, indicating the contribution of the submarine landslide to the January 2024 Noto Peninsula tsunami.

Incorporating Noncovalent Interactions in Transfer Learning Gaussian Process Regression Models for Molecular Simulations.

FFLUX is a quantum chemical topology-based multipolar force field that uses Gaussian process regression machine learning models to predict atomic energies and multipole moments on the fly for fast and accurate molecular dynamics simulations. These models have previously been trained on monomers, meaning that many-body effects, for example, intermolecular charge transfer, are missed in simulations. Moreover, dispersion and repulsion have been modeled using Lennard-Jones potentials, necessitating careful parametrization. In this work, we take an important step toward addressing these shortcomings and show that models trained on clusters, in this case, a dimer, can be used in FFLUX simulations by preparing and benchmarking a formamide dimer model. To mitigate the computational costs associated with training higher-dimensional models, we rely on the transfer of hyperparameters from a smaller source model to a larger target model, enabling an order of magnitude faster training than with a direct learning approach. The dimer model allows for simulations that account for two-body effects, including intermolecular polarization and charge penetration, and that do not require nonbonded potentials. We show that addressing these limitations allows for simulations that are closer to quantum mechanics than previously possible with the monomeric models.

Petroleum system assessment of the Beni Suef Basin, Western Desert, Egypt

Within the northwestern Desert of Egypt, the Beni Suef Basin is one of the most significant hydrocarbon basins. After over 50 years of exploration and production, the main challenge today is to locate new areas that are prolific to oil and gas production. The study aims to identify potential drilling locations by integrating geochemical methods, 1D and 2D basin modelling, well log analysis, seismic interpretation, and hydrocarbon migration pathways. Results show that the Lower Kharita shale contain both oil and gas generating kerogen with generating potential that ranges from fair to very good. The source rocks within the Lower Kharita are mature (main oil window) and have a transformation ratio of up to 60% based on 1D basin modeling. The modelled 2D vitrinite reflectance map showed that hydrocarbon generation occurred at depths greater than 10850 ft (3306 m) with vitrinite reflectance values greater than 0.65% in both the northern and southern parts of the Beni Suef Field. Two main reservoirs were studied. The lower Bahariya and upper Kharita reservoirs are composed of well to moderately sorted sandstone. The subsurface structural maps, reservoirs, source, and charge modeling maps have been constructed to show the migration pathways and accumulation areas. There are three accumulation areas identified. The first accumulation area is located in the high structure up-dip section of the major normal fault, and migration direction is from northwest. The second and third accumulation areas are located in the low structure and down-dip from the normal fault, with migration of hydrocarbons from southeast. The latter two areas should be tested by drilling in the future.

Benchmarking Physical Model Experiments with Numerical Simulations for the Wangjiashan Landslide-Induced Surge Waves in the Baihetan Reservoir Area

The Baihetan Hydropower Station reservoir area began impoundment in 2021, triggering the reactivation of ancient landslides and the formation of new ones. This not only caused direct landslide disasters but also significantly increased the likelihood of secondary surge wave disasters. This study takes the Wangjiashan (WJS) landslide in the Baihetan reservoir area as an example and conducts large-scale three-dimensional physical model experiments. Based on the results of the physical model experiments, numerical simulation is used as a comparative verification tool. The results show that the numerical simulation method effectively reproduces the formation and propagation process of the WJS landslide-induced surge waves observed in the physical experiments. At the impoundment water level of 825 m, the surge waves generated by the WJS landslide pose potential threats to the Xiangbiling (XBL) residential area. In this study, the numerical simulation based on computational fluid dynamics confirmed the actual propagation forms of the surge waves, aligning well with the results of the physical experiments at a microscopic scale. However, at a macroscopic scale, there is some discrepancy between the numerical simulation results and the physical experiment outcomes, with a maximum error of 25%, primarily stemming from the three-dimensional numerical source model. This study emphasizes the critical role of physical model experiments in understanding and mitigating surge wave disasters in China. Furthermore, physical experiments remain crucial for accurate disaster prediction and mitigation strategies. The theories and methods used in this study will provide important references for future research related to landslide disasters in reservoir areas.

Benchmarking Physical Model Experiments with Numerical Simulations for the Wangjiashan Landslide-Induced Surge Waves in the Baihetan Reservoir Area

The Baihetan Hydropower Station reservoir area began impoundment in 2021, triggering the reactivation of ancient landslides and the formation of new ones. This not only caused direct landslide disasters but also significantly increased the likelihood of secondary surge wave disasters. This study takes the Wangjiashan (WJS) landslide in the Baihetan reservoir area as an example and conducts large-scale three-dimensional physical model experiments. Based on the results of the physical model experiments, numerical simulation is used as a comparative verification tool. The results show that the numerical simulation method effectively reproduces the formation and propagation process of the WJS landslide-induced surge waves observed in the physical experiments. At the impoundment water level of 825 m, the surge waves generated by the WJS landslide pose potential threats to the Xiangbiling (XBL) residential area. In this study, the numerical simulation based on computational fluid dynamics confirmed the actual propagation forms of the surge waves, aligning well with the results of the physical experiments at a microscopic scale. However, at a macroscopic scale, there is some discrepancy between the numerical simulation results and the physical experiment outcomes, with a maximum error of 25%, primarily stemming from the three-dimensional numerical source model. This study emphasizes the critical role of physical model experiments in understanding and mitigating surge wave disasters in China. Furthermore, physical experiments remain crucial for accurate disaster prediction and mitigation strategies. The theories and methods used in this study will provide important references for future research related to landslide disasters in reservoir areas.

Development of a DNN model using calibrated simulation for the optimal control of HVAC systems

Acquiring actual data for developing data-based prediction models for the optimization of control setpoints (hereinafter referred to as optimal control (OC)) in heating, ventilation, and air conditioning (HVAC) systems is challenging, especially when changing control setpoints while considering all possible boundary conditions. Thus, considering the scalability of OC, it is a promising solution to generate sufficient learning data according to the control settings using a highly accurate simulation model, build a source model, and expand the learning model based on the actual data of the target system. This is the first study to improve the scalability of OC aiming to develop a deep neural network (DNN) model to predict the power consumption of a heat source system. First, this study will construct a calibrated heat source system simulation model and then use the generated learning data to train a DNN model. The actual operation conditions of the target building and heating system located in Vietnam were analyzed using operation data. A physics-based simulation model of the target heat source system was developed and calibrated using actual operation data to improve accuracy. By using the calibrated simulation, sufficient learning data was generated for all control settings allowing for the development of a learning model based on DNN that predicted the power consumption of the heat source system. In addition, a highly accurate prediction model through hyperparameter optimization was secured.

Estimating crop coefficients and water use of a full-bearing mango orchard in north-eastern South Africa using the fraction of vegetation cover and a dual source evapotranspiration model

In semi-arid countries like South Africa, commercially produced mango (Mangifera Indica L.) are grown entirely under irrigation. However, there is little accurate quantitative information on the water use of mango orchards, and few accurate water use models currently exist. In this study, we evaluated the performance of the FAO 56 method of estimating crop evapotranspiration (ETc) and a dual source water use model against measurements of actual consumptive water use of a commercial mango orchard. The FAO approach calculates ETc as the product of a crop coefficient (Kc) and the reference evapotranspiration (ETo). We derived Kc for well-watered orchards from readily available data including the fraction of vegetation cover, average tree height, and a stomatal control coefficient. The dual-source model calculated orchard evapotranspiration as the sum of tree transpiration and orchard floor evaporation derived from the modified Shuttleworth and Wallace model. Actual evapotranspiration was measured using an open path eddy covariance system, while tree transpiration was measured using the heat ratio method of monitoring sap flow. Data were collected in a mature ‘Tommy Atkins’ mango orchard grown with micro-sprinkler irrigation in north-eastern South Africa. Results show that the reference evapotranspiration explained most of the variation in orchard transpiration (R2 ∼ 0.78) compared to the solar radiation (R2 ∼ 0.66) and the vapour pressure deficit of the air (R2 ∼ 0.66). Compared with field measured water use data, the FAO method gave relatively accurate estimates of transpiration (R2 = 0.74, NRMSE = ±18.00 %, NMAE = ±15.00 %, NSE = 0.70) and evapotranspiration (R2 = 0.58, NRMSE = ±19.00 %, NMAE = ±16.00 %, NSE = 0.55). NSE is the Nash-Sutcliffe Efficiency. The dual-source model yielded slightly less accurate estimates of transpiration (R2 = 0.61, NRMSE = ±22.00 %, NMAE = ±20.00 %, NSE = 0.39) and evapotranspiration (R2 = 0.52, NRMSE = ±23.00 %, NMAE = ±25.00 %, NSE = 0.51). The basal crop coefficient (Kcb) showed small seasonal fluctuations, varying between 0.40 and 0.60 throughout the year. In contrast, Kc showed clear seasonality varying between 0.59–0.64 at flowering and fruit set and rising to 0.81–0.90 during the fruit growing phase. Estimates of the annual total transpiration (686 mm) from the FAO method were within 5 % of the actual measured values (677 mm) while the dual source model estimated 612 mm of transpiration, which was almost 10 % lower than the measured values. The results highlight that even though the FAO method requires fewer input parameters, it is potentially more accurate in estimating water use in mango orchards than the dual-source model.

Flow-field characteristics of the thermal plume above an elliptical high-temperature heat source surface

The thermal plume formed by the high-temperature elliptical heat source surface during the smelting process is often captured and removed by the local exhaust system. Accurately mastering the flow-field characteristics of such high-temperature elliptical heat plumes is helpful for efficient design of local exhaust systems. In this paper, the effects of the ratio of long and short axes (5/4 ≤ ξ ≤ 5/1) and the intensity of heat source (80 ≤ F ≤ 160 W) on the axial and radial velocity distribution of thermal plume in an elliptical heat source are investigated by numerical simulation combined with experimental validation. The results show that in the range of ξ ≤ 5/1, the axial dimensionless velocity distribution of the elliptical plume field and the spreading range of the plume field are mainly affected by ξ instead of F. For 5/4 ≤ ξ ≤ 5/1, the maximum axial velocity Um appears at 1.7 to 2.7 times Z/L (plume height to heat source long axis ratio). For ξ ≤ 5/2, the height at which the cross-sectional velocity field transitions to a circular distribution aligns with the height of Um. It is found that the plume velocity field is characterized by applying the point source model for ξ ≤ 5/3, and vice versa for the linear source model. The plume flow rate formulation obtained by modifying the linear source model for ξ > 5/3 has a better predictive ability in the Z/L ≤ 5 region. This study provides a reference for the design of ventilation systems for elliptical surface heat sources.

Two Monte Carlo-based simulators for imaging-system modeling and projection simulation of flat-panel X-ray source

Two Monte Carlo-based simulators for imaging-system modeling and projection simulation of flat-panel X-ray source

Petroleum System Assessment of the Beni Suef Basin, Western Desert, Egypt

Within the northwestern Desert of Egypt, the Beni Suef Basin is one of the most significant hydrocarbon basins. After over 50 years of exploration and production, the main challenge today is to locate new areas that are prolific to oil and gas production. The study aims to identify potential drilling locations by integrating geochemical methods, 1D and 2D basin modelling, well log analysis, seismic interpretation, and hydrocarbon migration pathways. Results show that the Lower Kharita shale contain both oil and gas generating kerogen with generating potential that ranges from fair to very good. The source rocks within the Lower Kharita are mature (main oil window) and have a transformation ratio of up to 60% based on 1D basin modeling. The modeled 2D vitrinite reflectance map showed that hydrocarbon generation occurred at depths greater than 10850 ft (3306 m) with vitrinite reflectance values greater than 0.65% in both the northern and southern parts of the Beni Suef Field. Two main reservoirs were studied. The lower Bahariya and upper Kharita reservoirs are composed of well to moderately sorted sandstone. The subsurface structural maps, reservoirs, source, and charge modeling maps have been constructed to show the migration pathways and accumulation areas. There are three accumulation areas identified. The first accumulation area is located in the high structure up-dip section of the major normal fault, and migration direction is from northwest. The second and third accumulation areas are located in the low structure and down-dip from the normal fault, with migration of hydrocarbons from southeast. The latter two areas should be tested by drilling in the future.

Advancements in multi-wavelength data analysis: The ThreeML framework for high-energy astronomy

The Multi-Mission Maximum Likelihood framework (ThreeML) is a Python-based software package designed for multi-wavelength data analysis in high-energy astronomy. Integrating X-ray and gamma-ray data from various instruments, along with measurements at lower wavelengths, is essential for unlocking the full potential of observational data. However, the lack of standardization and unique challenges posed by each instrument often complicate the process of combining data from multiple sources. ThreeML addresses these challenges with its flexible, plugin-based structure, allowing for the seamless inclusion of data from diverse observatories in their native formats. Leveraging astromodels, a versatile modeling framework, ThreeML enables separate handling of source modeling and data access from likelihood optimization, facilitating a flexible combination of both aspects. Moreover, in addition to frequentist maximum likelihood analysis, ThreeML supports Bayesian analysis through posterior distribution sampling.

Regional soundscape modeling of the Atlantic Outer Continental Shelfa).

The ocean soundscape is a complex superposition of sound from natural and anthropogenic sources. Recent advances in acoustic remote sensing and marine bioacoustics have highlighted how animals use their soundscape and how the background sound levels are influenced by human activities. In this paper, developments in computational ocean acoustics, remote sensing, and oceanographic modeling are combined to generate modelled sound fields at multiple scales in time and space. Source mechanisms include surface shipping, surface wind, and wave fields. A basin scale model is presented and applied to the United States Atlantic Outer Continental Shelf (OCS). For model-data comparison at a single hydrophone location, the model is run for a single receiver position. Environmental and source model uncertainty is included in the site-specific modeling of the soundscape. An inversion of the local sediment type is made for a set of sites in the OCS. After performing this inversion, the qualitative comparison of the modelled sound pressure level (SPL) time series and observed SPL is excellent. The quantitative differences in the mean root mean square error between the model and data is less than 3 dB for most sites and frequencies above 90 Hz.

Effects of fault roughness on estimating critical slip-weakening distance from fault slip history: A laboratory study

Earthquakes are the dynamic rupture of faults governed by fault weakening processes. Critical slip-weakening distance (Dc) is a crucial source parameter of earthquakes, and the determination of Dc is of great concern to semiologists. However, determining Dc for natural earthquakes is challenging due to the trade-off in inversed source models. To solve this problem, Fukuyama and his coworkers proposed a simple method (denoted as the F&M method) to estimate Dc directly from slip-velocity functions. According to the F&M method, the fault slip at the peak slip velocity (Dc') can be used as an approximation of Dc. However, the feasibility of this method has not been completely resolved. Here, we performed laboratory earthquake rupture experiments to examine the validity of the F&M method. Experiments were conducted on faults with different roughness and stress level. We studied the effect of fault roughness on the validity of the F&M method. Our results show that the increase in fault roughness could complicate the fault weakening process, producing repeated weakening and strengthening phase, which leads to a prominent deviation between Dc' and Dc. Furthermore, we also observed a correlation between the critical slip-weakening distance Dc and the final fault slip D. Such correlation implies the scale-dependent nature of Dc, which is consistent with seismic observations in the field.

Noise coupling reduction using temperature enhanced device for future integrated circuit integration applications

<p>Information technology-to-internet of things may have succeeded because of fast silicon chip capability expansion. Moore's law, which reduces device size, boosted integrated circuit (IC) performance. Delay rises with highdensity connection parasitic capacitance. Interconnect delays have surpassed transistor delays and slowed progress. An alternative is required now to reduce connection latency. The third dimension is used in popular 3D IC technology IC technology requires through silicon via (TSV) for signal integrity and heat mitigation. Noise coupling hinders electrical communication between signal-carrying TSVs (aggressive TSVs) and ground TSVs (victim TSVs), a 3D IC bottleneck. TSVs must be dielectrically insulated from Si substrates to avoid electrical signal interference. Additionally, first-order modelling will confirm the suggestions. This article proposes using the nanosheet field effect transistor (NSFET) to overcome 3D IC noise coupling and complementary metal oxide semiconductor (CMOS) technology nodes. After discussing the electronic industry and sub nm, several basic metrics and criteria for developing electronic components are presented. The first technique uses Perylene-N's exceptional noise-cancelling characteristics. Second technique uses electrical TSV (ETSV), thermal TSV (TTSV), and heat source models to measure noise coupling on numerous ICs. The third proposes many noise-reducing materials. The suggested structures outperform traditional approaches.</p>

Finite Element Modeling of Ring and Gaussian Dual Laser Heat Sources for Aluminum Butt Welding

Aluminum alloys have been used extensively for automotive industries for the structural applications with their high specific strength and corrosion resistance. In order to use aluminum alloys for automotive components, laser welding has been used due to the advantage of being capable to weld thick products due to its deep penetration depth. In this regard, a dual laser heat source combining an outer ring laser beam with a centrally focused Gaussian laser beam was proposed to compensate for insufficient melting caused by laser reflection of aluminum alloy. The purpose of this study is to develop a simulation model that can consider heat input from the dual laser beams individually, for analyzing melting and heat distribution behavior during the laser welding. Two different heat source models were proposed. One model used 3D Gaussian distribution of heat input for the centrally focused laser while the other model utilized Gaussian cylinder heat input. The proposed heat input models were implemented by finite element analyses, and the results were compared with aluminum butt welding experiments. It was shown that Gaussian cylinder heat input for the centrally focused laser beam reproduced much better the experimentally observed melting behavior in comparison to the 3D Gaussian distribution.

Unveiling lens light complexity with a novel multi-Gaussian expansion approach for strong gravitational lensing

ABSTRACT In a strong gravitational lensing system, the distorted light from a source is analysed to infer the properties of the lens. However, light emitted by the lens itself can contaminate the image of the source, introducing systematic errors in the analysis. We present a simple and efficient lens light model based on the well-tested multi-Gaussian expansion (MGE) method for representing galaxy surface brightness profiles, which we combine with a semi-linear inversion scheme for pixelized source modelling. Testing it against realistic mock lensing images, we show that our scheme can fit the lensed images to the noise level, with relative differences between the true input and best-fitting lens light model remaining below 5 per cent. We apply the MGE lens light model to 38 lenses from the HST SLACS sample. We find that the new scheme provides a good fit for the majority of the sample with only 3 exceptions – these show clear asymmetric residuals in the lens light. We examine the radial dependence of the ellipticity and position angles and confirm that it is common for a typical lens galaxy to exhibit twisting non-elliptical isophotes and boxy / disky isophotes. Our MGE lens light model will be a valuable tool for understanding the hidden complexity of the lens mass distribution.