An Ultra Fast Image Generator (UFig) for wide-field astronomy

Simulated wide-field images are becoming an important part of observational astronomy, either to prepare for new surveys or to test measurement methods. In order to efficiently explore vast parameter spaces, the computational speed of simulation codes is a central requirement to their implementation. We introduce the Ultra Fast Image Generator (UFig) which aims to bring wide-field imaging simulations to the current limits of computational capabilities. We achieve this goal through: (1) models of galaxies, stars and observational conditions, which, while simple, capture the key features necessary for realistic simulations, and (2) state-of-the-art computational and implementation optimizations. We present the performances of UFig and show that it is faster than existing public simulation codes by several orders of magnitude. It allows us to produce images more quickly than SExtractor needs to analyze them. For instance, it can simulate a typical 0.25 deg^2 Subaru SuprimeCam image (10k x 8k pixels) with a 5-sigma limiting magnitude of R=26 in 30 seconds on a laptop, yielding an average simulation time for a galaxy of 30 microseconds. This code is complementary to end-to-end simulation codes and can be used as a fast, central component of observational methods relying on simulations.Comment: Submitted to Astronomy and Computing. 13 pages, 9 figure

Calibrated Ultra Fast Image Simulations for the Dark Energy Survey

Weak lensing by large-scale structure is a powerful technique to probe the dark components of the universe. To understand the measurement process of weak lensing and the associated systematic effects, image simulations are becoming increasingly important. For this purpose we present a first implementation of the $\textit{Monte Carlo Control Loops}$ ($\textit{MCCL}$; Refregier & Amara 2014), a coherent framework for studying systematic effects in weak lensing. It allows us to model and calibrate the shear measurement process using image simulations from the Ultra Fast Image Generator (UFig; Berge et al. 2013). We apply this framework to a subset of the data taken during the Science Verification period (SV) of the Dark Energy Survey (DES). We calibrate the UFig simulations to be statistically consistent with DES images. We then perform tolerance analyses by perturbing the simulation parameters and study their impact on the shear measurement at the one-point level. This allows us to determine the relative importance of different input parameters to the simulations. For spatially constant systematic errors and six simulation parameters, the calibration of the simulation reaches the weak lensing precision needed for the DES SV survey area. Furthermore, we find a sensitivity of the shear measurement to the intrinsic ellipticity distribution, and an interplay between the magnitude-size and the pixel value diagnostics in constraining the noise model. This work is the first application of the $\textit{MCCL}$ framework to data and shows how it can be used to methodically study the impact of systematics on the cosmic shear measurement.Comment: 14 pages, 9 Figures, submitted to Ap

HOPE: A Python Just-In-Time compiler for astrophysical computations

The Python programming language is becoming increasingly popular for scientific applications due to its simplicity, versatility, and the broad range of its libraries. A drawback of this dynamic language, however, is its low runtime performance which limits its applicability for large simulations and for the analysis of large data sets, as is common in astrophysics and cosmology. While various frameworks have been developed to address this limitation, most focus on covering the complete language set, and either force the user to alter the code or are not able to reach the full speed of an optimised native compiled language. In order to combine the ease of Python and the speed of C++, we developed HOPE, a specialised Python just-in-time (JIT) compiler designed for numerical astrophysical applications. HOPE focuses on a subset of the language and is able to translate Python code into C++ while performing numerical optimisation on mathematical expressions at runtime. To enable the JIT compilation, the user only needs to add a decorator to the function definition. We assess the performance of HOPE by performing a series of benchmarks and compare its execution speed with that of plain Python, C++ and the other existing frameworks. We find that HOPE improves the performance compared to plain Python by a factor of 2 to 120, achieves speeds comparable to that of C++, and often exceeds the speed of the existing solutions. We discuss the differences between HOPE and the other frameworks, as well as future extensions of its capabilities. The fully documented HOPE package is available at http://hope.phys.ethz.ch and is published under the GPLv3 license on PyPI and GitHub.Comment: Accepted for publication in Astronomy and Computing. 14 pages, 1 figure. The code is available at http://hope.phys.ethz.c

A new framework for high-resolution pedestrian data processing using rule-based algorithms and real-time alarm systems

Pedestrian flows and densities have increased in recent years within transport-related public facilities such as train stations, as well as in private buildings such as shopping centers, event halls or convention centers. Increasing flows and high densities often raise comfort, safety, operational and delay issues; and therefore, require pedestrian flow optimization, intervention or even revised regulation. Recent technological advances enhanced pedestrian sensing; however, they disregard adaptive data capture, processing, and strategic communication within reasonable time, or real-time, such as tactic occupancy or density alarms trigger rules. Content of this research is twofold. First, new data capturing and processing advances of recent technological developments are combined in an integral software and hardware-based framework. Second, applied methods highlight projects and experiences on both pedestrian research and on existing and operating pedestrian facilities. Based on the described, two-sided approach, proposed framework is able to fulfil high safety and comfort standards of facilities such as train stations, retail facilities or event halls. In this research, past semi-automatic video analysis processing of pedestrian behavioral studies is replaced with combined sensor and data processing system within proposed framework. In train stations of major operators, real-time pedestrian observation increases safety levels on station platforms. Tactic algorithms and alarm trigger schemes enable on-time surveillance, e.g. at overcrowded floor levels in shopping centers for escalator or door closure. Sensor data is used to train models for underpass pedestrian flow regarding path choice and fundamental diagram. In retail, queue length, trajectory analysis and floor occupancy are determined for economic, comfort as well as safety evaluation. Using trajectory classification, movement and dwell time is analyzed for staff and visitors separately (see Figure 1)

A simple and portable method for on-line texture measurement of Italian “Speck Alto Adige"

Texture is a relevant parameter for the assessment of cured ham's quality. In this study a rapid on-line instrumental technique for the measurement of the texture of pieces of cured smoked ham intended for sale as “Speck Alto Adige” PGI was developed. Speck samples were subjected to a compression test using a portable Shore A tester, and instrumental data were compared with conventional texture analyses (texture profile analysis and stress relaxation test) and with sensory evaluations. First, a hardness range in which a threshold value could be identified for the eligibility of 120 speck samples for the “Speck Alto Adige” PGI indication was established; afterwards, a Shore A hardness threshold value of 48 was defined based on measurements of more than 1000 samples. These findings may help manufacturers to determine the textural properties of Speck, based on a simple and rapid instrumental analysisinfo:eu-repo/semantics/publishedVersio

Topological Phases: An Expedition off Lattice

Motivated by the goal to give the simplest possible microscopic foundation for a broad class of topological phases, we study quantum mechanical lattice models where the topology of the lattice is one of the dynamical variables. However, a fluctuating geometry can remove the separation between the system size and the range of local interactions, which is important for topological protection and ultimately the stability of a topological phase. In particular, it can open the door to a pathology, which has been studied in the context of quantum gravity and goes by the name of `baby universe', Here we discuss three distinct approaches to suppressing these pathological fluctuations. We complement this discussion by applying Cheeger's theory relating the geometry of manifolds to their vibrational modes to study the spectra of Hamiltonians. In particular, we present a detailed study of the statistical properties of loop gas and string net models on fluctuating lattices, both analytically and numerically.Comment: 38 pages, 22 figure

ALPSCore/ALPSCore: Version 0.5.6-alpha3

The ALPSCore project, based on the ALPS (Algorithms and Libraries for Physics Simulations) project, provides generic algorithms and utilities for physics problems. It strives to increase software reuse in the physics community. This pre-release: Green's Functions module extensions and improvements: real-frequency meshes with linear, quadratic, logarithmic grids. Parameters module improvements: Direct comparizon of porameters with string literals. Documentation improvements: Tutorials expanded and cleaned. Various improvements and bugfixes. For copyright see COPYRIGHT.TXT. For licensing see LICENSE.TXT. For acknowledgment in scientific publications see ACKNOWLEDGE.TXT

Genetic diversity and host plant preferences revealed by simple sequence repeat and mitochondrial markers in a population of the arbuscular mycorrhizal fungus Glomus intraradices

Arbuscular mycorrhizal fungi (AMF) are important symbionts of plants that improve plant nutrient acquisition and promote plant diversity. Although within-species genetic differences among AMF have been shown to differentially affect plant growth, very little is actually known about the degree of genetic diversity in AMF populations. This is largely because of difficulties in isolation and cultivation of the fungi in a clean system allowing reliable genotyping to be performed. - A population of the arbuscular mycorrhizal fungus Glomus intraradices growing in an in vitro cultivation system was studied using newly developed simple sequence repeat (SSR), nuclear gene intron and mitochondrial ribosomal gene intron markers. - The markers revealed a strong differentiation at the nuclear and mitochondrial level among isolates. Genotypes were nonrandomly distributed among four plots showing genetic subdivisions in the field. Meanwhile, identical genotypes were found in geographically distant locations. AMF genotypes showed significant preferences to different host plant species (Glycine max, Helianthus annuus and Allium porrum) used before the fungal in vitro culture establishment. - Host plants in a field could provide a heterogeneous environment favouring certain genotypes. Such preferences may partly explain within-population patterns of genetic diversity.