Reconsidering the origin of the 21 micron feature: Oxides in carbon-rich PPNe?

The origin of the so-called "21 micron" feature which is especially prominent in the spectra of some carbon-rich protoplanetary nebulae (PPNe}) is the matter of a lively debate. A large number of potential band carriers have been presented and discarded within the past decade. The present paper gives an overview of the problems related to the hitherto proposed feature identifications, including the recently suggested candidate carrier silicon carbide. We also discuss the case for spectroscopically promising oxides. SiC is shown to produce a strong resonance band at 20-21 micron if coated by a layer of silicon dioxide. At low temperatures, core-mantle particles composed of SiC and amorphous SiO$_2$ indeed have their strongest spectral signature at a position of 20.1 micron, which coincides with the position of the "21 micron" emission band. The optical constants of another candidate carrier that has been relatively neglected so far -- iron monoxide -- are proven to permit a fairly accurate reproduction of the "21 micron" feature profile as well, especially when low-temperature measurements of the infrared properties of FeO are taken into account. As candidate carrier of the "21 micron" emission band, FeO has the advantage of being stable against further oxidation and reduction only in a narrow range of chemical and physical conditions, coinciding with the fact that the feature, too, is detected in a small group of objects only. However, it is unclear how FeO should form or survive particularly in carbon-rich PPNe.Comment: 28 pages, 15 figures, accepted for publication in ApJ (December

Lyapunov spectra of billiards with cylindrical scatterers: comparison with many-particle systems

The dynamics of a system consisting of many spherical hard particles can be described as a single point particle moving in a high-dimensional space with fixed hypercylindrical scatterers with specific orientations and positions. In this paper, the similarities in the Lyapunov exponents are investigated between systems of many particles and high-dimensional billiards with cylindrical scatterers which have isotropically distributed orientations and homogeneously distributed positions. The dynamics of the isotropic billiard are calculated using a Monte-Carlo simulation, and a reorthogonalization process is used to find the Lyapunov exponents. The results are compared to numerical results for systems of many hard particles as well as the analytical results for the high-dimensional Lorentz gas. The smallest three-quarters of the positive exponents behave more like the exponents of hard-disk systems than the exponents of the Lorentz gas. This similarity shows that the hard-disk systems may be approximated by a spatially homogeneous and isotropic system of scatterers for a calculation of the smaller Lyapunov exponents, apart from the exponent associated with localization. The method of the partial stretching factor is used to calculate these exponents analytically, with results that compare well with simulation results of hard disks and hard spheres.Comment: Submitted to PR

Feature Extraction using Spiking Convolutional Neural Networks

Spiking neural networks are biologically plausible counterparts of the artificial neural networks, artificial neural networks are usually trained with stochastic gradient descent and spiking neural networks are trained with spike timing dependant plasticity. Training deep convolutional neural networks is a memory and power intensive job. Spiking networks could potentially help in reducing the power usage. There is a large pool of tools for one to chose to train artificial neural networks of any size, on the other hand all the available tools to simulate spiking neural networks are geared towards computational neuroscience applications and they are not suitable for real life applications. In this work we focus on implementing a spiking CNN using Tensorflow to examine behaviour of the network and study catastrophic forgetting in the spiking CNN and weight initialization problem in R-STDP using MNIST data set. We also report classification accuracies that are achieved using N-MNIST and MNIST data sets

Analog Readout for the ATLAS Semiconductor Tracker

The context of the work, described in this document, is the development of electroniccomponents for future high-energy physics experiments.The first part deals with design and evaluation of an electronic device for reading and processingthe signals, created by charged elementary particles in solid state detectors. This device has to workwithin an experimental environment, which imposes very rigorous requirements in terms of signalprocessing speed, noise performance, power dissipation, radiation hardness and size as well as interms of system complexity. These constraints force its realization as a VLSI integrated circuit. Anemphasis is put on the major problem, which occurs when dealing with extremely small signals, as theones produced by a semiconductor detector..

Goldstone modes in Lyapunov spectra of hard sphere systems

In this paper, we demonstrate how the Lyapunov exponents close to zero of a system of many hard spheres can be described as Goldstone modes, by using a Boltzmann type of approach. At low densities, the correct form is found for the wave number dependence of the exponents as well as for the corresponding eigenvectors in tangent-space. The predicted values for the Lyapunov exponents belonging to the transverse mode are within a few percent of the values found in recent simulations, the propagation velocity for the longitudinal mode is within 1%, but the value for the Lyapunov exponent belonging to the longitudinal mode deviates from the simulations by 30%. For higher densities, the predicted values deviate more from the values calculated in the simulations. These deviations may be due to contributions from ring collisions and similar terms, which, even at low densities, can contribute to the leading order.Comment: 12 pages revtex, 5 figures, accepted by Physical Review

PCA-RECT: An Energy-efficient Object Detection Approach for Event Cameras

We present the first purely event-based, energy-efficient approach for object detection and categorization using an event camera. Compared to traditional frame-based cameras, choosing event cameras results in high temporal resolution (order of microseconds), low power consumption (few hundred mW) and wide dynamic range (120 dB) as attractive properties. However, event-based object recognition systems are far behind their frame-based counterparts in terms of accuracy. To this end, this paper presents an event-based feature extraction method devised by accumulating local activity across the image frame and then applying principal component analysis (PCA) to the normalized neighborhood region. Subsequently, we propose a backtracking-free k-d tree mechanism for efficient feature matching by taking advantage of the low-dimensionality of the feature representation. Additionally, the proposed k-d tree mechanism allows for feature selection to obtain a lower-dimensional dictionary representation when hardware resources are limited to implement dimensionality reduction. Consequently, the proposed system can be realized on a field-programmable gate array (FPGA) device leading to high performance over resource ratio. The proposed system is tested on real-world event-based datasets for object categorization, showing superior classification performance and relevance to state-of-the-art algorithms. Additionally, we verified the object detection method and real-time FPGA performance in lab settings under non-controlled illumination conditions with limited training data and ground truth annotations.Comment: Accepted in ACCV 2018 Workshops, to appea

The Lyapunov spectrum of the many-dimensional dilute random Lorentz gas

For a better understanding of the chaotic behavior of systems of many moving particles it is useful to look at other systems with many degrees of freedom. An interesting example is the high-dimensional Lorentz gas, which, just like a system of moving hard spheres, may be interpreted as a dynamical system consisting of a point particle in a high-dimensional phase space, moving among fixed scatterers. In this paper, we calculate the full spectrum of Lyapunov exponents for the dilute random Lorentz gas in an arbitrary number of dimensions. We find that the spectrum becomes flatter with increasing dimensionality. Furthermore, for fixed collision frequency the separation between the largest Lyapunov exponent and the second largest one increases logarithmically with dimensionality, whereas the separations between Lyapunov exponents of given indices not involving the largest one, go to fixed limits.Comment: 8 pages, revtex, 6 figures, submitted to Physical Review

Assessing emission reduction targets with dynamic models: deriving target load functions for use in integrated assessment

International audienceInternational agreements to reduce the emission of acidifying sulphur (S) and nitrogen (N) compounds have been negotiated on the basis of an understanding of the link between acidification related changes in soil and surface water chemistry and terrestrial and aquatic biota. The quantification of this link is incorporated within the concept of critical loads. Critical loads are calculated using steady state models and give no indication of the time within which acidified ecosystems might be expected to recover. Dynamic models provide an opportunity to assess the timescale of recovery and can go further to provide outputs which can be used in future emission reduction strategies. In this respect, the Target Load Function (TLF) is proposed as a means of assessing the deposition load necessary to restore a damaged ecosystem to some pre-defined acceptable state by a certain time in the future. A target load represents the deposition of S and N in a defined year (implementation year) for which the critical limit is achieved in a defined time (target year). A TLF is constructed using an appropriate dynamic model to determine the value of a chemical criterion at a given point in time given a temporal pattern of S and N deposition loads. A TLF requires information regarding: (i) the chemical criterion required to protect the chosen biological receptor (i.e. the critical limit); (ii) the year in which the critical limit is required to be achieved; and (iii) time pattern of future emission reductions. In addition, the TLF can be assessed for whole regions to incorporate the effect of these three essentially ecosystem management decisions. Keywords: emission reduction, critical load, target load, dynamic model, recovery tim