Photon Tracking Research Articles

Modeling the Thermal Infrared Emissivity of Snow and Ice Using Photon Tracking

Modeling the Thermal Infrared Emissivity of Snow and Ice Using Photon Tracking

Approximate global illumination using photon mapping: A review

This paper introduces the two-step process of the standard photon mapping algorithm and a variety of other global biased illumination algorithms using photon mapping that have been proposed in recent years. Since there are many global biased illumination algorithms based on photon mapping, this review is a combination of these algorithms for the convenience of the reader, and the two-step process of standard PM will also be presented in this review to accommodate readers who are not familiar with the field. We will first introduce the specific implementation process and principles based on the two steps of PM, photon tracking and rendering, and then introduce a variety of polarized illumination techniques using photon maps, compare these methods and discuss the advantages, disadvantages, and applicability of each method in detail, and finally give a specific implementation of each method to give readers a clearer understanding of these methods. The final implementation of each method is shown to give the reader a clearer understanding of these methods.

Stellar Neutrino Emission across the Mass–Metallicity Plane

We explore neutrino emission from nonrotating, single-star models across six initial metallicities and 70 initial masses from the zero-age main sequence to the final fate. Overall, across the mass spectrum, we find metal-poor stellar models tend to have denser, hotter, and more massive cores with lower envelope opacities, larger surface luminosities, and larger effective temperatures than their metal-rich counterparts. Across the mass–metallicity plane we identify the sequence (initial CNO → 14N → 22Ne → 25Mg → 26Al → 26Mg → 30P → 30Si) as making primary contributions to the neutrino luminosity at different phases of evolution. For the low-mass models we find neutrino emission from the nitrogen flash and thermal pulse phases of evolution depend strongly on the initial metallicity. For the high-mass models, neutrino emission at He-core ignition and He-shell burning depends strongly on the initial metallicity. Antineutrino emission during C, Ne, and O burning shows a strong metallicity dependence with 22Ne(α, n)25Mg providing much of the neutron excess available for inverse-β decays. We integrate the stellar tracks over an initial mass function and time to investigate the neutrino emission from a simple stellar population. We find average neutrino emission from simple stellar populations to be 0.5–1.2 MeV electron neutrinos. Lower metallicity stellar populations produce slightly larger neutrino luminosities and average β decay energies. This study can provide targets for neutrino detectors from individual stars and stellar populations. We provide convenient fitting formulae and open access to the photon and neutrino tracks for more sophisticated population synthesis models.

Adding the X‐ray Bragg reflection physical process in crystal to the Geant4 Monte Carlo simulation toolkit, part I: reflection from a crystal slab

AbstractX‐ray diffraction from a solid crystal shows the wave nature of photons. It is an important electromagnetic (EM) physics process when X‐ray photons interact with a crystal. Bragg diffraction, often called Bragg reflection, is a special case of the general form of X‐ray diffraction, known as Laue diffraction. When the Bragg's law is met, the incident photon beam is reflected from the crystal plane behaving as a specular reflection at the Bragg angle. However, the Bragg reflection physical process has not been integrated into the general‐purpose Monte Carlo simulation toolkit Geant4 for particle physics. In the current study, we developed a new EM physical process class “G4CrystalBraggReflection” and a new EM physical model class “G4DarwinDynamicalModel” for modeling the Bragg reflection physical process within a crystal. We added the Bragg reflection physical process to the EM physics category of Geant4. The preliminary results of photon tracking in a silicon crystal slab have shown the feasibility of simulating the Bragg reflection process in addition to the standard EM processes in the framework of Geant4.

Parathyroid Hormone Reduces Persistent Proton Induced DNA Double-Strand Breaks in Osteocytes

<h3>Purpose/Objective(s)</h3> Healthy bone is commonly irradiated during radiotherapy for many cancers, and bone fractures can be a late complication. A recent study revealed a higher incidence of rib fractures after breast irradiation with protons (7%) compared to photons (1%) at the same dose, but the underlying biological mechanisms are unknown. Here we used <i>in vitro</i> experiments, supported by Monte Carlo track structure simulations, to investigate differences in bone cell responses to proton and photon radiation, and to identify potential therapeutic interventions. <h3>Materials/Methods</h3> We used TOPAS-nBio, a radiobiology simulation toolkit, to simulate a segment of bone using geometric models of bone cells (osteoblasts, osteoclasts, and osteocytes). Photon and proton tracks were simulated through bone matrix to investigate energy distributions received by each cell. For <i>in vitro</i> experiments, we utilized the murine osteocytic cell line Ocy454. Cells were irradiated with different doses of protons or photons. Surviving fraction as a function of dose was determined using colony formation assays. DNA double-strand breaks were assessed by 53BP1 foci assay. For PTH treatments, cells were treated with 10 nM human PTH(1-34) for 24 hours prior to irradiation. All experiments were repeated independently three or more times. Statistical analysis was performed by unpaired t-test with Bonferroni correction. <h3>Results</h3> Monte Carlo track simulations showed osteocytes are the bone cell most likely to receive radiation damage, particularly with protons. In the case of large multi-nucleated osteoclasts, both photons and protons spared some of the nuclei, suggesting functional sparing of osteoclasts from radiation damage. We therefore focused our <i>in vitro</i> experiments on Ocy454 osteocytes. Interestingly, the surviving fraction of osteocytes was significantly lower after protons compared to photons for all investigated doses of 1 to 8 Gy. The dose for 10% surviving fraction was 5.38 Gy for protons and 7.46 Gy for photons (Relative Biological Effect 1.39). Although protons and photons induced similar numbers of 53BP1 foci at 1 hour (79% vs. 72% cells with foci), a significantly higher number of foci was observed at 24 hours after protons compared to photons (22% vs. 6.5%, p=0.0078), suggestive of persistent DNA damage after protons. Remarkably, we found that pre-treatment with parathyroid hormone (PTH) decreased 53BP1 foci at 24 hours in proton-irradiated cells to levels comparable to that of non-irradiated cells (22% without PTH vs. 6.3% with PTH, p=0.014). <h3>Conclusion</h3> Surviving fraction of osteocytes was lower after proton compared to photon irradiation, suggesting a greater sensitivity of osteocytes to protons. Protons result in greater DNA damage in osteocytes, but this damage may be mitigated with the addition of PTH. Further study is needed to investigate the potential of PTH to reduce bone damage induced by proton irradiation.

Sensitivity of modeled snow grain size retrievals to solar geometry, snow particle asphericity, and snowpack impurities

Abstract. Snow grain size is an important metric to determine snow age and metamorphism, but it is difficult to measure. The effective grain size can be derived from spaceborne and airborne radiance measurements due to strong attenuation of near-infrared energy by ice. Consequently, a snow grain size inversion technique that uses hyperspectral radiances and exploits variations in the 1.03 µm ice absorption feature was previously developed for use with airborne imaging spectroscopy. Previous studies have since demonstrated the effectiveness of the technique, though there has yet to be a quantitative assessment of the retrieval sensitivity to snowpack impurities, ice particle shape, or solar geometry. In this study, we use the Snow, Ice, and Aerosol Radiative (SNICAR) model and a Monte Carlo photon tracking model to examine the sensitivity of snow grain size retrievals to changes in dust and black carbon content, anisotropic reflectance, changes in solar illumination angle (θ0), and scattering asymmetry parameter (g) associated with different particle shapes. Our results show that changes in these variables can produce large grain size errors, especially when the effective grain size exceeds 500 µm. Dust content of 1000 ppm induces errors exceeding 800 µm, with the highest biases associated with small particles. Aspherical ice particles and perturbed solar zenith angles produce maximum biases of ∼540 µm and ∼400 µm, respectively, when spherical snow grains and θ0=60∘ are assumed in the generation of the retrieval calibration curve. Retrievals become highly sensitive to viewing angle when reflectance is anisotropic, with biases exceeding 1000 µm in extreme cases. Overall, we show that a more detailed understanding of snowpack state and solar geometry improves the precision when determining snow grain size through hyperspectral remote sensing.

Generation of primary photons through inverse Compton scattering using a Monte Carlo simulation code

Photon sources based on inverse Compton scattering, namely, the interaction between relativistic electrons and laser photons, are emerging as quasimonochromatic energy-tunable sources either as compact alternatives to synchrotron facilities for the production of low-energy (10--100 keV) x rays or to reach the 1--100 MeV photon energy range, which is inaccessible at synchrotrons. Different interaction layouts are possible for electron and laser beams, and several applications are being studied, ranging from fundamental research in nuclear physics to advanced x-ray imaging in the biomedical field, depending on the radiation energy range, intensity, and bandwidth. Regardless of the specific application, a reliable tool for the simulation of the radiation produced is essential for the design, the commissioning, and, subsequently, the study and optimization of this kind of source. Different computational tools have been developed for this task, based on both a purely analytical treatment and Monte Carlo simulation codes. Each of these tools has strengths and weaknesses. Here, we present a novel Monte Carlo code based on geant4 for the simulation of inverse Compton scattering in the linear regime. The code produces results in agreement with cain, one of the most used Monte Carlo tools, for a wide range of interaction conditions at a computational time reduced by 2 orders of magnitude. Furthermore, the developed tool can be easily embedded in a geant4 user application for the tracking of photons generated through inverse Compton scattering in a given experimental setup.

GPU-based optical simulation of the DARWIN detector

Understanding propagation of scintillation light is critical for maximizing the discovery potential of next-generation liquid xenon detectors that use dual-phase time projection chamber technology. This work describes a detailed optical simulation of the DARWIN detector implemented using Chroma, a GPU-based photon tracking framework. To evaluate the framework and to explore ways of maximizing efficiency and minimizing the time of light collection, we simulate several variations of the conventional detector design. Results of these selected studies are presented. More generally, we conclude that the approach used in this work allows one to investigate alternative designs faster and in more detail than using conventional Geant4 optical simulations, making it an attractive tool to guide the development of the ultimate liquid xenon observatory.

Experimentally validated x-ray image simulations of 50 μm x-ray PIV tracer particles

We evaluate Beer–Lambert (BL) ray-tracing and Monte Carlo N-Particle (MCNP) photon tracking simulations for prediction and comparison of x-ray imaging system performance. These simulation tools can aid the methodical design of laboratory-scale x-ray particle image velocimetry (XPIV) experiments and tracer particles by predicting image quality. Particle image signal-to-noise ratio (SNR) is used as the metric of system performance. Simulated and experiment data of hollow, silver-coated, glass sphere tracer particles (AGSF-33) are compared. As predicted by the simulations, the AGSF-33 particles are visible with a SNR greater than unity in 100 ms exposure time images, demonstrating their potential as x-ray PIV or particle tracking velocimetry (XPTV) tracers. The BL approach predicts the image contrast, is computationally inexpensive, and enables the exploration of a vast parameter space for system design. MCNP simulations, on the other hand, predict experiment images slightly more accurately, but are more than an order of magnitude more computationally expensive than BL simulations. For most practical XPIV system design applications, the higher computational expense of MCNP is likely not justified by the modest accuracy improvement compared to BL.

Monte Carlo Simulations of a Non-Invasive Positron Detector to Measure the Arterial Input Function for Dynamic PET

This work presents Monte Carlo (MC) study of a novel non-invasive positron detector, hereinafter called NID, designed to measure the arterial input function (AIF) through the wrist of a patient for use with dynamic positron emission tomography (PET). The goal of the study was to optimize a previously developed NID prototype, to determine its efficiency and ability to distinguish between the arterial and venous portions of the signal escaping a wrist phantom. A user code based on the Geant4 MC toolkit was developed to model the NID and a wrist phantom. The scintillator based detectors were modelled as 64 polystyrene cylinders, 0.97 mm in diameter, 10 cm long and capped with cylindrical photomultiplier tubes. The scintillator fibers were arranged in a single band around a 64.13 mm polyethylene cylinder representing a model of the wrist. Two cylinders, 2.30 mm in diameter were placed 6 mm apart, 2 mm below the surface of the wrist phantom representing the radial artery and vein. Two simulations were performed by placing 100 million decay events of oxygen-15 (15O) or fluorine-18 (18F), randomly distributed between the artery and vein. Visible wavelength photon tracking was enabled, and Photomultiplier tubes were simulated to collect the visible photons. Deposited energy per event and location of energy deposition were calculated. A python algorithm was used to analyse the results. The arterial signal produced a 5.28 mm and 10.32 mm FWHM for 15O and 18F respectively. The algorithm could determine the correct location of interaction 98% of the time. The NID can resolve the arterial and venous signal and is thus suitable for determining the AIF for dynamic PET.

Inter-crystal scattering recovery of light-sharing PET detectors using convolutional neural networks

Inter-crystal scattering (ICS) is a type of Compton scattering of photons from one crystal to adjacent crystals and causes inaccurate assignment of the annihilation photon interaction position in positron emission tomography (PET). Because ICS frequently occurs in highly light-shared PET detectors, its recovery is crucial for the spatial resolution improvement. In this study, we propose two different convolutional neural networks (CNNs) for ICS recovery, exploiting the good pattern recognition ability of CNN techniques. Using the signal distribution of a photosensor array as input, one network estimates the energy deposition in each crystal (ICS-eNet) and another network chooses the first-interacted crystal (ICS-cNet). We performed GATE Monte Carlo simulations with optical photon tracking to test PET detectors comprising different crystal arrays (8 × 8 to 21 × 21) with lengths of 20 mm and the same photosensor array (3 mm 8 × 8 array) covering an area of 25.8 × 25.8 mm2. For each detector design, we trained ICS-eNet and ICS-cNet and evaluated their respective performance. ICS-eNet accurately identified whether the events were ICS (accuracy > 90%) and selected interacted crystals (accuracy > 60%) with appropriate energy estimation performance (R 2 > 0.7) in the 8 × 8, 12 × 12, and 16 × 16 arrays. ICS-cNet also exhibited satisfactory performance, which was less dependent on the crystal-to-sensor ratio, with an accuracy enhancement that exceeds 10% in selecting the first-interacted crystal and a reduction in error distances compared when no recovery was applied. Both ICS-eNet and ICS-cNet exhibited consistent performances under various optical property settings of the crystals. For spatial resolution measurements in PET rings, both networks achieved significant enhancements particularly for highly pixelated arrays. We also discuss approaches for training the networks in an actual experimental setup. This proof-of-concept study demonstrated the feasibility of CNNs for ICS recovery in various light-sharing designs to efficiently improve the spatial resolution of PET in various applications.

Technical Note: Standalone application to generate custom reflectance Look-Up Table for advanced optical Monte Carlo simulation in GATE/Geant4.

The need for high-fidelity modeling of radiation detectors to perform reliable detector performance optimization using Monte Carlo simulations requires to accurately simulate the light transport in the scintillator and the light collection by the photodetector. In this work, we implement our well-validated crystal reflectance model computed from three-dimensional (3D) crystal surface measurement in a standalone open-source application to allow researchers to generate fully customized crystal reflectance look-up-tables (LUTs) to be used in optical Monte Carlo simulation. The LUTDavisModel application can be installed in a few minutes on Windows, macOS, and Linux, using 26MB of space. MATLAB Runtime is required and is automatically installed with the application. The core algorithm has been previously validated experimentally and implemented in GATE v8.0. The standalone is divided into five panels, each of which performing a specific task: generate LUTs from a combination of surface type, scintillator, and coupling medium available in the database (such as LSO or BGO) or custom; compute LUTs with the reflectors available and custom coupling thickness; create a mixture of coupling media to account for possible defects in the optical coupling; plot precomputed LUTs for visual comparison. Tooltips and errors/warnings facilitate the navigation. The reported computational times were obtained with an Intel Core i7 MacBook Pro. LUTs can be generated with computational time ranging from a few minutes to several hours depending on the selected surface, sampling, and computational power. A longer time is needed when using rough surfaces and thick coupling media (hundreds of ) due to increased photon tracking. We developed a user-friendly standalone application to generate LUTs that can be used inside GATE Monte Carlo simulations. It can be easily downloaded, installed, and used. Future optimizations will expand the database, decrease the computational time through greater parallelization, and include the generation of LUTs to study Cerenkov photons transport.

Parallel, multi-purpose Monte Carlo code for simulation of light propagation in segmented tissues

We have developed a massive-parallel, multi-purpose Monte Carlo (MC) code for simulation of light propagation in complex structures modelled with e.g. magnetic resonance images. The code is designed to execute parallel threads on a Linux-based cluster of computers equipped with multiple graphical processing units (GPU) utilizing NVidia CUDA technology. We show steps one can take to implements such code itself. Furthermore, we provide methodology of building a MRI-based head model and populating it with realistic optical properties at excitation and fluorescence emission wavelengths during inflow of fluorescence agent (indocyanine green – ICG). The proposed code provides following original features: (i) Simulation of fluorescence light propagation in media with spatial distribution of multiple different fluorophores characterized by concentration, quantum yield and fluorescence lifetime. (ii) The fluorescence light tracking does not need extra photon tracking and works in parallel with tracking photons at the excitation wavelength, introducing execution time overhead of 0.02% only. (iii) Calculation of high-resolution spatial distributions of sensitivity factors mapping voxels absorption change to parameters measured on a model surface: statistical parameters (moments) of the distribution of time of flight of photons. (iv) Random number generators states are preserved between runs to greatly improve calculation time of the sensitivity factors. (v) Simulation of fluorescence lifetime wide field imaging in diffusively scattering media. The code is designed to handle big models, divided into e.g. 200 million voxels or more, which other methods struggle to handle. Simulations on a human head model with 0.3 mm voxel size require 2 GB of a GPU memory only. This is supported by developed non-standard floating-point data storage format. The proposed code is cross-validated with field-leading MC and finite element methods on the same hardware environment for varying model sizes and temporal resolutions. Tests revealed competitive execution time and high temporal resolution of boundary data for high spatial resolution of MRI-based head model.

Optimization of Beta Radioluminescent Batteries with Different Radioisotopes: A Theoretical Study

In this paper, a beta radioluminescent battery with different radioisotopes is studied, and different parameters of the proposed structure are optimized. These parameters include the luminescent layer thickness, the doping concentration in the semiconductor P-N junction, etc. Some of the parameters have an inverse effect on the battery outputs. So, a trade-off is sought between them to increase efficiency. Each part of the proposed structure is divided into much smaller parts in the simulations to ensure proper tracking of photons and the creation of electron holes in the semiconductor layer. Also, the passage of particles through each layer is carefully reviewed and calculated in terms of particle crossing percentage, their reflection percentage, rate of self-absorption, etc. Finally, the power, open-circuit voltage, and short-circuit current density of the proposed battery versus the main parameter changes are presented.

Physics of Pair Producing Gaps in Black Hole Magnetospheres. II. General Relativity

Abstract This is the second paper in a series where we examine the physics of pair producing gaps in low-luminosity accreting supermassive black hole systems. In this paper, we carry out time-dependent self-consistent fully general relativistic 1D particle-in-cell simulations of the gap, including full inverse Compton scattering and photon tracking. Similar to the previous paper, we find a highly time-dependent solution where a macroscopic vacuum gap can open quasiperiodically, producing bursts of pairs and high energy radiation. We present the light curve, particle spectrum, and photon spectrum from this process. Using an empirical scaling relation, we rescale the parameters to the inferred values at the base of the jet in M87, and find that the observed TeV flares could potentially be explained by this model under certain parameter assumptions.

Evaluation of the Snow Albedo Retrieved from the Snow Kernel Improved the Ross-Roujean BRDF Model

The original kernel-driven bidirectional reflectance distribution function (BRDF) models were developed based on soil-vegetation systems. To further improve the ability of the models to characterize the snow surface scattering properties, a snow kernel was derived from the asymptotic radiative transfer (ART) model and used in the kernel-driven BRDF model framework. However, there is a need to further evaluate the influence of using this snow kernel to improve the original kernel-driven models in snow albedo retrieval applications. The aim of this study is to perform such an evaluation using a variety of snow BRDF data. The RossThick-Roujean (RTR) model is used as a framework for taking in the new snow kernel (hereafter named the RTS model) since the Roujean geometric-optical (GO) kernel captures a neglectable hotspot effect and represents a more prominent dome-shaped BRDF, especially at a small solar zenith angle (SZA). We obtained the following results: (1) The RTR model has difficulties in reconstructing the snow BRDF shape, especially at large SZAs, which tends to underestimate the reflectance in the forward direction and overestimate reflectance in the backward direction for various data sources. In comparison, the RTS model performs very well in fitting snow BRDF data and shows high accuracy for all data. (2) The RTR model retrieved snow albedos at SZAs = 30°–70° are underestimated by 0.71% and 0.69% in the red and near-infrared (NIR) bands, respectively, compared with the simulation results of the bicontinuous photon tracking (bic-PT) model, which serve as “real” values. However, the albedo retrieved by the RTS model is significantly improved and generally agrees well with the simulation results of the bic-PT model, although the improved model still somewhat underestimates the albedo by 0.01% in the red band and overestimates the albedo by 0.05% in the NIR band, respectively, at SZAs = 30°–70°, which may be negligible. (3) The albedo derived by these two models shows a high correlation (R2 &gt; 0.9) between the field-measured and Polarization and Directionality of the Earth's Reflectances (POLDER) data, especially for the black-sky albedo. However, the albedo derived using the RTR model is significantly underestimated compared with the RTS model. The RTR model underestimates the black-sky albedo (white-sky albedo) retrievals by 0.62% (1.51%) and 0.93% (2.08%) in the red and NIR bands, respectively, for the field-measured data. The shortwave black-sky and white-sky albedos derived using the RTR model for the POLDER data are underestimated by 1.43% and 1.54%, respectively, compared with the RTS model. These results indicate that the snow kernel in the kernel-driven BRDF model frame is more accurate in snow albedo retrievals and has the potential for application in the field of the regional and global energy budget.

An assessment of the performance of two snow kernels in characterizing snow scattering properties

ABSTRACTThe kernel-driven RossThick-LiSparseReciprocal (RTLSR) bidirectional reflectance distribution function (BRDF) model has been widely used in the quantitative remote sensing community. However, the performance of this model is challenged when modelling the optical scattering properties of pure snow surfaces. Recently, two snow kernels have been developed to improve the snow anisotropic reflectance in the kernel-driven RTLSR model framework. However, the performances of these two snow kernels must be assessed to identify their potential applications. Therefore, we assess the performances of these two kernels using various BRDF data sources. Our findings demonstrate their differences in several aspects. (1) These two kernels differ in characterizing the variability in BRDF shape as a function of the solar zenith angle (SZA). As the SZA increases, the shape of snow kernel derived by the asymptotic radiative transfer (ART) model (hereinafter named the ART method) changes from a dome shape to bowl shape, which agrees well with the simulation data of the bicontinuous photon tracking (bic-PT) model. The shape of the snow kernel proposed by Qu et al. (hereinafter named the Qu method) based on the Rahman-Pinty-Verstraete (RPV) model maintains a bowl shape for all SZAs. These differences in the kernel performances affect their abilities to fit snow BRDF data with different SZAs. (2) The corrected RTLSR models, with their respective snow kernels, are generally able to model the forward-scattering properties of snow surfaces compared with the original RTLSR model. However, the ART method performs better in capturing the BRDF variations in snow surfaces than the Qu method. This assessment provides an improved understanding of the performance of these two snow kernels and, thus, suggests further applications for the ART snow kernel in the kernel-driven BRDF model framework in the near future.

Physics of Pair Producing Gaps in Black Hole Magnetospheres

Abstract In some low-luminosity accreting supermassive black hole systems, the supply of plasma in the funnel region can be a problem. It is believed that a local region with an unscreened electric field can exist in the black hole magnetosphere, accelerating particles and producing high-energy gamma-rays that can create e ± pairs. We carry out time-dependent self-consistent 1D PIC simulations of this process, including inverse-Compton scattering and photon tracking. We find a highly time-dependent solution where a macroscopic gap opens quasi-periodically to create e ± pairs and high-energy radiation. If this gap is operating at the base of the jet in M87, we expect an intermittency on the order of a few r g /c, which coincides with the timescale of the observed TeV flares from the same object. For Sagittarius A* the gap electric field can potentially grow to change the global magnetospheric structure, which may explain the lack of a radio jet at the center of our galaxy.

On the performance of large monolithic LaCl3(Ce) crystals coupled to pixelated silicon photosensors

We investigate the performance of large area radiation detectors, with high energy- and spatial-resolution, intended for the development of a Total Energy Detector with gamma-ray imaging capability, so-called i-TED. This new development aims for an enhancement in detection sensitivity in time-of-flight neutron capture measurements, versus the commonly used C6D6 liquid scintillation total-energy detectors. In this work, we study in detail the impact of the readout photosensor on the energy response of large area (50×50 mm2) monolithic LaCl3(Ce) crystals, in particular when replacing a conventional mono-cathode photomultiplier tube by an 8×8 pixelated silicon photomultiplier. Using the largest commercially available monolithic SiPM array (25 cm2), with a pixel size of 6×6 mm2, we have measured an average energy resolution of 3.92% FWHM at 662 keV for crystal thicknesses of 10, 20 and 30 mm. The results are confronted with detailed Monte Carlo (MC) calculations, where optical processes and properties have been included for the reliable tracking of the scintillation photons. After the experimental validation of the MC model, we use our MC code to explore the impact of a smaller photosensor segmentation on the energy resolution. Our optical MC simulations predict only a marginal deterioration of the spectroscopic performance for pixels of 3×3 mm2.

Optimization for Realistic Real-Time Rendering Method for Subsurface Scattering

Monte Carlo photon tracking is used to render translucent materials such as marble, milk, skin, etc. The technique encompasses excessive amount of subsurface scattering that is computationally expensive. Faster approaches are based on approximate models derived from observed results. While such models are efficient, they tend to miss some translucency effects in the rendered results. We present an improved approximation model for real-time rendering of materials based upon computational graphs. Excellent results are obtained improving upon the previous studies.