As TeV gamma-ray astronomy progresses into the era of the Cherenkov Telescope Array (CTA), instantaneously following up on gamma-ray transients is becoming more important than ever. To this end, a worldwide network of Imaging Atmospheric Cherenkov Telescopes has been proposed. Australia is ideally suited to provide coverage of part of the Southern Hemisphere sky inaccessible to H.E.S.S. in Namibia and the upcoming CTA-South in Chile. This study assesses the sources detectable by a small, transient-focused array in Australia based on CTA telescope designs. The TeV emission of extragalactic sources (including the majority of gamma-ray transients) can suffer significant absorption by the extragalactic background light. As such, we explored the improvements possible by implementing stereoscopic and topological triggers, as well as lowered image cleaning thresholds, to access lower energies. We modelled flaring gamma-ray sources based on past measurements from the satellite-based gamma-ray telescope Fermi-LAT. We estimate that an array of four Medium-Sized Telescopes (MSTs) would detect $\sim$24 active galactic nucleus flares >5$\sigma$ per year, up to a redshift of $z\approx1.5$. Two MSTs achieved $\sim$80–90% of the detections of four MSTs. The modelled Galactic transients were detectable within the observation time of one night, 11 of the 21 modelled gamma-ray bursts were detectable, as were $\sim$10% of unidentified transients. An array of MST-class telescopes would thus be a valuable complementary telescope array for transient TeV gamma-ray astronomy.

The order-disorder behavior of the isomorphous cation substitution of the octahedral sheet of phyllosilicates was investigated by Monte Carlo simulations based only on atomistic models in some three-species systems Al/Fe/Mg including a wide range of different octahedral compositions that can be relevant to clay compositions found in nature, especially for smectites and illites. In many cases, phase transitions do not occur, in that long-range order is not attained, but most systems exhibit short-range order at low temperature. The ordering of the octahedral cations is highly dependent on the cation composition. Variations in the tetrahedral charge (smectite vs. illite) produce slight differences in the cation distribution and the short-range and long-range order of octahedral cations do not change drastically. The average size of Fe clusters and the long-range order of Fe are not larger in illites than in smectites as previous reports concluded, but the proportion of Fe3+ cations non-clustered is higher in smectites than in illites. This behavior supports the experimental behavior of the Fe effect on the Al-NMR signal, which is lower in illites than in smectites.

Political scientists commonly use Grambsch and Therneau’s (1994, Biometrika 81, 515–526) ubiquitous Schoenfeld-based test to diagnose proportional hazard violations in Cox duration models. However, some statistical packages have changed how they implement the test’s calculation. The traditional implementation makes a simplifying assumption about the test’s variance–covariance matrix, while the newer implementation does not. Recent work suggests the test’s performance differs, depending on its implementation. I use Monte Carlo simulations to more thoroughly investigate whether the test’s implementation affects its performance. Surprisingly, I find the newer implementation performs very poorly with correlated covariates, with a false positive rate far above 5%. By contrast, the traditional implementation has no such issues in the same situations. This shocking finding raises new, complex questions for researchers moving forward. It appears to suggest, for now, researchers should favor the traditional implementation in situations where its simplifying assumption is likely met, but researchers must also be mindful that this implementation’s false positive rate can be high in misspecified models.

As TeV gamma-ray astronomy progresses into the era of the Cherenkov Telescope Array (CTA), there is a desire for the capacity to instantaneously follow up on transient phenomena and continuously monitor gamma-ray flux at energies above $10^{12}\,\mathrm{eV}$ . To this end, a worldwide network of Imaging Air Cherenkov Telescopes (IACTs) is required to provide triggers for CTA observations and complementary continuous monitoring. An IACT array sited in Australia would contribute significant coverage of the Southern Hemisphere sky. Here, we investigate the suitability of a small IACT array and how different design factors influence its performance. Monte Carlo simulations were produced based on the Small-Sized Telescope (SST) and Medium-Sized Telescope (MST) designs from CTA. Angular resolution improved with larger baseline distances up to 277 m between telescopes, and energy thresholds were lower at 1 000 m altitude than at 0 m. The ${\sim} 300\,\mathrm{GeV}$ energy threshold of MSTs proved more suitable for observing transients than the ${\sim}1.2\,\mathrm{TeV}$ threshold of SSTs. An array of four MSTs at 1 000 m was estimated to give a 5.7 $\sigma$ detection of an RS Ophiuchi-like nova eruption from a 4-h observation. We conclude that an array of four MST-class IACTs at an Australian site would ideally complement the capabilities of CTA.

Monte Carlo simulations are commonly used in elemental quantification using energy-dispersive spectroscopy (EDS). Here, the Monte Carlo program MC X-ray was incorporated into the image processing software Dragonfly by Object Research Systems (ORS) as a simulation library. The simulation program has been transformed into a complete microscope simulator where the tools of Dragonfly allow complex voxel-based geometries to be constructed, and the electron beam and detectors can be freely placed inside the 3D space. Computation times of simulations have been improved drastically through new data structures and parallelization. Simulations of backscattered electron imaging and EDS mapping are presented here to demonstrate the capabilities of this new library.

The Pannonian basin in Central Europe is well known for its rich geothermal resources. Although geothermal energy has been utilised, mainly for direct use purposes, for a long time, there are still a lot of untapped resources. This paper presents novel methods for outlining and assessing the theoretical and technical potential of partly still unknown geothermal reservoirs, based on a case study from the Dráva basin, one of the sub-basins of the Pannonian basin along the Hungarian–Croatian border. The presented methods include reservoir delineation based on combining geological bounding surfaces of the Upper Pannonian basin-fill units with a set of isotherms deriving from a conductive geothermal model. The geothermal potential of each identified reservoir was calculated by a Monte Carlo method, which was considered as being represented by the heat content of the fluids stored in the effective pore space (‘moveable fluid’). The results underline the great untapped geothermal potential of the Dráva basin, especially that of the reservoir storing thermal water of 50–75°C, which has the largest volume and the greatest stored heat content.

Scanning electron microscopy (SEM) is one of the most common inspection methods in the semiconductor industry and in research labs. To extract the height of structures using SEM images, various techniques have been used, such as tilting a sample, or modifying the SEM tool with extra sources and/or detectors. However, none of these techniques focused on extraction of height information directly from top-down images. In this work, using Monte Carlo simulations, we studied the relation between step height and the emission of secondary electrons (SEs) resulting from exposure with primary electrons at different energies. It is found that part of the SE signal, when scanning over a step edge, is determined by the step height rather than the geometry of the step edge. We present a way to quantify this, arriving at a method to determine the height of structures from top-down SEM images. The method is demonstrated on three different samples using two different SEM tools, and atomic force microscopy is used to measure the step height of the samples. The results obtained are in qualitative agreement with the results from the Monte Carlo simulations.

The systematics of cation ordering in binary spinel solid solutions have been investigated using an interatomic potential model combined with Monte Carlo simulations. The formalism to describe a system containing three cation species ordering over two non-equivalent sub-lattices is developed and the method applied to the MgAl2O4-FeAl2O4 binary solid solution. Our results compare favourably with experimental measurements of site-occupancy data, although the experiments display a slightly larger degree of non-ideality than the simulations. A possible kinetic origin of the non-ideal behaviour was examined by performing simulations in which only exchange of Mg and Fe2+ between tetrahedral and octahedral sites was permitted below the Al-blocking temperature of 1160 K. This approach improves the agreement with the experimental site occupancies, and suggests that the blocking temperature for moving Mg and Fe2+ between tetrahedral and octahedral sites is significantly lower than for moving Al

Sensitivity analysis plays an important role in finding an optimal design of a structure under uncertainty. Quantifying relative importance of random parameters, which leads to a rank ordering, helps in developing a systematic and efficient way to reach the optimal design. In this work, lift prediction and sensitivity analysis of a potential flow around a submerged body is considered. Such flow is often used in the initial design stage of structures. The flow computation is carried out using a vortex-panel method. A few parameters of the submerged body and flow are considered as random variables. To improve the accuracy in lift prediction in a computationally efficient way, a new semi-intrusive stochastic perturbation method is proposed. Accordingly, a perturbation is applied at the linear system solving level involving the inuence coefficient matrix, as opposed to using perturbation in the lift quantity itself. This proposed method, which is partially analogous to the intrusive or Galerkin projection methods in spectral stochastic finite element methods, is found to be more accurate than using perturbation directly on the lift and faster than a direct simulation. The proposed semi-intrusive stochastic perturbation method is found to yield faster estimates of the Sobol’ indices, which are used for global sensitivity analysis. From global sensitivity analysis, the flow parameters are found to be more important than the parameters of the submerged body.

Introduction. Family health history (FHx) is an important factor in breast and ovarian cancer risk assessment. As such, multiple risk prediction models rely strongly on FHx data when identifying a patient’s risk. These models were developed using verified information and when translated into a clinical setting assume that a patient’s FHx is accurate and complete. However, FHx information collected in a typical clinical setting is known to be imprecise and it is not well understood how this uncertainty may affect predictions in clinical settings. Methods. Using Monte Carlo simulations and existing measurements of uncertainty of self-reported FHx, we show how uncertainty in FHx information can alter risk classification when used in typical clinical settings. Results. We found that various models ranged from 52% to 64% for correct tier-level classification of pedigrees under a set of contrived uncertain conditions, but that significant misclassification are not negligible. Conclusions. Our work implies that (i) uncertainty quantification needs to be considered when transferring tools from a controlled research environment to a more uncertain environment (i.e, a health clinic) and (ii) better FHx collection methods are needed to reduce uncertainty in breast cancer risk prediction in clinical settings.

A new approach is presented to introduce the fine structure of core-loss excitations into the electron energy-loss spectra of ionization edges by Monte Carlo simulations based on an optical oscillator model. The optical oscillator strength is refined using the calculated electron energy-loss near-edge structure by density functional theory calculations. This approach can predict the effects of multiple scattering and thickness on the fine structure of ionization edges. In addition, effects of the fitting range for background removal and the integration range under the ionization edge on signal-to-noise ratio are investigated.

A forescatter electron detector (FSED) was used to acquire dark-field micrographs (DF-FSED) on thin specimens with a scanning electron microscope. The collection angles were adjusted with the detector distance from the beam axis, which is similar to the camera length of the scanning transmission electron microscope annular DF detectors. The DF-FSED imaging resolution was calculated with SMART-J on an aluminum alloy and carbon nanotubes (CNTs) decorated with platinum nanoparticles. The resolution was three to six times worse than with bright-field imaging. Measurements of nanometer-size objects showed a similar feature size in DF-FSED imaging despite a signal-to-noise ratio 12 times smaller. Monte Carlo simulations were used to predict the variation of the contrast of a CNT/Fe/Pt system as a function of the collection angles. It was constant for very high collection angles (>450 mrad) and confirmed experimentally. The reverse contrast between carbon black particles and the smallest titanium dioxide (TiO2) nanoparticles was predicted by Monte Carlo simulations and observed in the DF-FSED micrograph of a battery electrode coating. However, segmentation of the micrograph was not able to isolate the TiO2 nanoparticle phase because of the close contrast of small TiO2 nanoparticles compared to the C black particles.

Statistical inference about two binomial parameters implies that they are both estimated by binomial sampling. There are occasions in which one aims at testing the equality of two binomial parameters before and after the occurrence of the first success along a sequence of Bernoulli trials. In these cases, the binomial parameter before the first success is estimated by negative binomial sampling whereas that after the first success is estimated by binomial sampling, and both estimates are related. This paper derives statistical tools to test two hypotheses, namely, that both binomial parameters equal some specified value and that both parameters are equal though unknown. Simulation studies are used to show that in small samples both tests are accurate in keeping the nominal Type-I error rates, and also to determine sample size requirements to detect large, medium, and small effects with adequate power. Additional simulations also show that the tests are sufficiently robust to certain violations of their assumptions.

The Monte Carlo software CASINO has been expanded with new modules for the simulation of complex beam scanning patterns, for the simulation of cathodoluminescence (CL), and for the calculation of electron energy deposition in subregions of a three-dimensional (3D) volume. Two examples are presented of the application of these new capabilities of CASINO. First, the CL emission near threading dislocations in gallium nitride (GaN) was modeled. The CL emission simulation of threading dislocations in GaN demonstrated that a better signal-to-noise ratio was obtained with lower incident electron energy than with higher energy. Second, the capability to simulate the distribution of the deposited energy in 3D was used to determine exposure parameters for polymethylmethacrylate resist using electron-beam lithography (EBL). The energy deposition dose in the resist was compared for two different multibeam EBL schemes by changing the incident electron energy.

This article reviews different methods used to perform quantitative X-ray microanalysis in the electron microscope and also demonstrates the urgency of measuring the fundamental parameters of X-ray generation for the development of accurate standardless quantitative methods. Using ratios of characteristic lines acquired on the same X-ray spectrum, it is shown that the Cliff and Lorimer KA-B factor can be used in a general correction method that is appropriate for all types of specimens and electron microscopes, providing that appropriate corrections are made for X-ray absorption, fluorescence, and indirect generation. Since the fundamental parameters appear in the KA-B factor, only the ratio of the ionization cross sections needs to be known, not their absolute values. In this regard, the measurement of ratios of the KA-B factor (or intensities at different beam energies of the same material with no change of beam spreading in the material) permits the validation for the best models to compute the ratio of ionization cross sections. It is shown, using this method, that the nonrelativistic Bethe equation, to compute ionization cross section, is very close to the equation of E. Casnati et al. (J Phys B15, 155–167, 1982) and also to the equations proposed by D. Bote and F. Salvat (Phys Rev A77, 042701, 2008) for the computation of the ratio of ionization cross sections. The method is extended to show that it could be used to determine the values of the Coster-Kronig transitions factors, an important fundamental parameter for the generation of L and M lines that is mostly known with poor accuracy. The detector efficiency can be measured with specimens where their intensities were measured with an energy dispersive spectrometer detector, the efficiency of which has been measured in an X-ray synchrotron (M. Alvisi et al., Microsc Microanal12, 406–415, 2006). The spatial resolution should always be computed when performing quantitative X-ray microanalysis and the equations of R. Gauvin (Microsc Microanal13(5), 354–357, 2007) for bulk materials and the one presented in this article for thin films should be used. The effects of X-rays generated by fast secondary electrons and by Auger electrons are reviewed, and their effect can be detrimental for the spatial resolution of materials involving low-energy X-ray lines, in certain specific conditions. Finally, quantitative X-ray microanalysis of heterogeneous materials is briefly reviewed.

Lateral profiles of the electron probe of scanning transmission electron microscopy (STEM) were simulated at different vertical positions in a micrometers-thick carbon sample. The simulations were carried out using the Monte Carlo method in CASINO software. A model was developed to fit the probe profiles. The model consisted of the sum of a Gaussian function describing the central peak of the profile and two exponential decay functions describing the tail of the profile. Calculations were performed to investigate the fraction of unscattered electrons as a function of the vertical position of the probe in the sample. Line scans were also simulated over gold nanoparticles at the bottom of a carbon film to calculate the achievable resolution as a function of the sample thickness and the number of electrons. The resolution was shown to be noise limited for film thicknesses less than 1 μm. Probe broadening limited the resolution for thicker films. The validity of the simulation method was verified by comparing simulated data with experimental data. The simulation method can be used as quantitative method to predict STEM performance or to interpret STEM images of thick specimens.

Scanning transmission electron microscope (STEM) images of three-dimensional (3D) samples were simulated. The samples consisted of a micrometer(s)-thick substrate and gold nanoparticles at various vertical positions. The atomic number (Z) contrast as obtained via the annular dark-field detector was generated. The simulations were carried out using the Monte Carlo method in the CASINO software (freeware). The software was adapted to include the STEM imaging modality, including the noise characteristics of the electron source, the conical shape of the beam, and 3D scanning. Simulated STEM images of nanoparticles on a carbon substrate revealed the influence of the electron dose on the visibility of the nanoparticles. The 3D datasets obtained by simulating focal series showed the effect of beam broadening on the spatial resolution and on the signal-to-noise ratio. Monte Carlo simulations of STEM imaging of nanoparticles on a thick water layer were compared with experimental data by programming the exact sample geometry. The simulated image corresponded to the experimental image, and the signal-to-noise levels were similar. The Monte Carlo simulation strategy described here can be used to calculate STEM images of objects of an arbitrary geometry and amorphous sample composition. This information can then be used, for example, to optimize the microscope settings for imaging sessions where a low electron dose is crucial for the design of equipment, or for the analysis of the composition of a certain specimen.

The paper studies the convergence behavior ofMonte Carlo schemes for semiconductors.A detailed analysis of the systematic error with respect to numerical parameters is performed.Different sources of systematic error are pointed out andillustrated in a spatially one-dimensional test case.The error with respect to the number of simulation particlesoccurs during the calculation of the internal electric field.The time step error, which is related to the splitting of transport andelectric field calculations, vanishes sufficiently fast.The error due to the approximation of the trajectories ofparticles depends on the ODE solver used in the algorithm.It is negligible compared to the other sources of time steperror, when a second order Runge-Kutta solver is used. The error related to the approximate scattering mechanismis the most significant source of error with respect to the time step.

High-angle annular dark-field (HAADF) scanning transmission electron microscopy (STEM) images of electron-transparent samples show dominant atomic number (Z-) contrast with a high lateral resolution. HAADF STEM at low electron energies <30 keV is applied in this work for quantitative composition analyses of InGaAs quantum wells. To determine the local composition, normalized experimental image intensities are compared with results of Monte Carlo simulations. For verification of the technique, InGaAs/GaAs quantum-well structures with known In concentration are used. Transmission electron microscopy samples with known thickness are prepared by the focused-ion-beam technique. The method can be extended to other material systems and is particularly promising for the analysis of materials that are sensitive toward knock-on damage.