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Register a new userSensor Distortion Effects in Photon Monte Carlo Simulations
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We present a detailed method to simulating sensor distortions using a photon and electron Monte Carlo method. We use three dimensional electrostatic simulations to parameterize the perturbed electric field profile for non-ideal sensor details. We follow the conversion of simulated photons, and the subsequent response of the converted electrons to the electric field pattern. These non-ideal sensor details can be implemented efficiently in a Monte Carlo approach. We demonstrate that the non-ideal sensor distortions have a variety of observable consequence including the modification of the astrometric pattern, the distortion of the electron diffusion size and shape, and the distortion of flats. We show analytic validation of the diffusion physics, reproduce two kinds of edge distortion, and show qualitative validation of field-free regions, lithography errors, and fringing. We also demonstrate that there are two related effects of doping variation having different observable consequences. We show that field distortions from accumulated electrons lead to intensity-dependent point-spread-functions and the sub-linear variance in flats. The method is implemented in the Photon Simulator (PhoSim) and the code is publically available.
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We develop a comprehensive approach to simulate the deformation of mirrors and lenses due to thermal and mechanical stresses that couples efficiently to photon-based optics simulations. This expands upon previous work where we demonstrated a comprehensive ab initio approach to simulate astronomical images using a photon Monte Carlo method. We apply elasticity theory and estimate thermal effects by adapting a three-dimensional numerical method. We also consider the effect of active optics control systems and active cooling systems in further correcting distortions in the optics. We validate the approach by showing convergence to analytic estimates, and then apply the methodology to the WIYN 3.5m telescope primary mirror. We demonstrate that changes in the soak temperature result in second order point spread function (PSF) defocusing, the gravitational sag and positioning errors result in highly structured PSF distortions, and large-scale thermal gradients result in an elliptical PSF distortion patterns. All three aspects of the environment are larger than the intrinsic optical aberrations of the design, and further exploration with a variety of telescopes should lead to detailed PSF size and shape, astrometric distortion, and field variation predictions. The simulation capabilities developed in this work is publicly available with the Photon Simulation (PhoSim) package.
A crucial aspect of 3D Monte Carlo radiative transfer is the choice of the spatial grid used to partition the dusty medium. We critically investigate the use of octree grids in Monte Carlo dust radiative transfer, with two different octree construction algorithms (regular and barycentric subdivision) and three different octree traversal algorithms (top-down, neighbour list, and the bookkeeping method). In general, regular octree grids need higher levels of subdivision compared to the barycentric grids for a fixed maximum cell mass threshold criterion. The total number of grid cells, however, depends on the geometry of the model. Surprisingly, regular octree grid simulations turn out to be 10 to 20% more efficient in run time than the barycentric grid simulations, even for those cases where the latter contain fewer grid cells than the former. Furthermore, we find that storing neighbour lists for each cell in an octree, ordered according to decreasing overlap area, is worth the additional memory and implementation overhead: using neighbour lists can cut down the grid traversal by 20% compared to the traditional top-down method. In conclusion, the combination of a regular node subdivision and the neighbour list method results in the most efficient octree structure for Monte Carlo radiative transfer simulations.
Context: AGILE is a gamma-ray astrophysics mission which has been in orbit since 23 April 2007 and continues to operate reliably. The gamma-ray detector, AGILE-GRID, has observed Galactic and extragalactic sources, many of which were collected in the first AGILE Catalog. Aims: We present the calibration of the AGILE-GRID using in-flight data and Monte Carlo simulations, producing Instrument Response Functions (IRFs) for the effective area A_eff), Energy Dispersion Probability (EDP), and Point Spread Function (PSF), each as a function of incident direction in instrument coordinates and energy. Methods: We performed Monte Carlo simulations at different gamma-ray energies and incident angles, including background rejection filters and Kalman filter-based gamma-ray reconstruction. Long integrations of in-flight observations of the Vela, Crab and Geminga sources in broad and narrow energy bands were used to validate and improve the accuracy of the instrument response functions. Results: The weighted average PSFs as a function of spectra correspond well to the data for all sources and energy bands. Conclusions: Changes in the interpolation of the PSF from Monte Carlo data and in the procedure for construction of the energy-weighted effective areas have improved the correspondence between predicted and observed fluxes and spectra of celestial calibration sources, reducing false positives and obviating the need for post-hoc energy-dependent scaling factors. The new IRFs have been publicly available from the Agile Science Data Centre since November 25, 2011, while the changes in the analysis software will be distributed in an upcoming release.
We have examined the behavior of the compressibility, the dc-conductivity, the single-particle gap, and the Drude weight as probes of the density-driven metal-insulator transition in the Hubbard model on a square lattice. These quantities have been obtained through determinantal quantum Monte Carlo simulations at finite temperatures on lattices up to 16 X 16 sites. While the compressibility, the dc-conductivity, and the gap are known to suffer from `closed-shell effects due to the presence of artificial gaps in the spectrum (caused by the finiteness of the lattices), we have established that the former tracks the average sign of the fermionic determinant (<sign>), and that a shortcut often used to calculate the conductivity may neglect important corrections. Our systematic analyses also show that, by contrast, the Drude weight is not too sensitive to finite-size effects, being much more reliable as a probe to the insulating state. We have also investigated the influence of the discrete imaginary-time interval (Deltatau) on <sign>, on the average density (rho), and on the double occupancy (d): we have found that <sign> and rho are more strongly dependent on Delta tau away from closed-shell configurations, but d follows the Deltatau^2 dependence in both closed- and open-shell cases.
AGILE is a mission of the Italian Space Agency (ASI) Scientific Program dedicated to gamma-ray astrophysics, operating in a low Earth orbit since April 23, 2007. It is designed to be a very light and compact instrument, capable of simultaneously detecting and imaging photons in the 18 keV to 60 keV X-ray energy band and in the 30 MeV{50 GeV gamma-ray energy with a good angular resolution (< 1 deg at 1 GeV). The core of the instrument is the Silicon Tracker complemented with a CsI calorimeter and a AntiCoincidence system forming the Gamma Ray Imaging Detector (GRID). Before launch, the GRID needed on-ground calibration with a tagged gamma-ray beam to estimate its performance and validate the Monte Carlo simulation. The GRID was calibrated using a tagged gamma-ray beam with energy up to 500 MeV at the Beam Test Facilities at the INFN Laboratori Nazionali di Frascati. These data are used to validate a GEANT3 based simulation by comparing the data and the Monte Carlo simulation by measuring the angular and energy resolutions. The GRID angular and energy resolutions obtained using the beam agree well with the Monte Carlo simulation. Therefore the simulation can be used to simulate the same performance on-light with high reliability.
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