Active Pixel Sensors in ams H18/H35 HV-CMOS Technology for the ATLAS HL-LHC Upgrade

Deep sub micron HV-CMOS processes offer the opportunity for sensors built by industry standard techniques while being HV tolerant, making them good candidates for drift-based, fast collecting, thus radiation-hard pixel detectors. For the upgrade of the ATLAS Pixel Detector towards the HL-LHC requirements, active pixel sensors in HV-CMOS technology were investigated. These implement amplifier and discriminator stages directly in insulating deep n-wells, which also act as collecting electrodes. The deep n-wells allow for bias voltages up to 150V leading to a depletion depth of several 10um. Prototype sensors in the ams H18 180nm and H35 350nm HV-CMOS processes have been manufactured, acting as a potential drop-in replacement for the current ATLAS Pixel sensors, thus leaving higher level processing such as trigger handling to dedicated read-out chips. Sensors were thoroughly tested in lab measurements as well as in testbeam experiments. Irradiation with X-rays and protons revealed a tolerance to ionizing doses of 1Grad. An enlarged depletion zone of up to 100um thickness after irradiation due to the acceptor removal effect was deduced from Edge-TCT studies. The sensors showed high detection efficiencies after neutron irradiation to 1e15 n_eq cm-2 in testbeam experiments. A full reticle size demonstrator chip, implemented in the H35 process is being submitted to prove the large scale feasibility of the HV-CMOS concept.Comment: 6 pages, 12 figures, proceeding contribution to the 10th International Hiroshima Symposium 2016, submitted to NIM

Autonomous search for a diffusive source in an unknown environment

The paper presents an approach to olfactory search for a diffusive emitting source of tracer (e.g. aerosol, gas) in an environment with unknown map of randomly placed and shaped obstacles. The measurements of tracer concentration are sporadic, noisy and without directional information. The search domain is discretised and modelled by a finite two-dimensional lattice. The links is the lattice represent the traversable paths for emitted particles and for the searcher. A missing link in the lattice indicates a blocked paths, due to the walls or obstacles. The searcher must simultaneously estimate the source parameters, the map of the search domain and its own location within the map. The solution is formulated in the sequential Bayesian framework and implemented as a Rao-Blackwellised particle filter with information-driven motion control. The numerical results demonstrate the concept and its performance.Comment: 11 pages, 7 figure

Bernoulli Particle/Box-Particle Filters for Detection and Tracking in the Presence of Triple Measurement Uncertainty

This work presents sequential Bayesian detection and estimation methods for nonlinear dynamic stochastic systems using measurements affected by three sources of uncertainty: stochastic, set-theoretic and data association uncertainty. Following Mahler’s framework for information fusion, the paper develops the optimal Bayes filter for this problem in the form of the Bernoulli filter for interval measurements. Two numerical implementations of the optimal filter are developed. The first is the Bernoulli particle filter (PF), which turns out to require a large number of particles in order to achieve a satisfactory performance. For the sake of reduction in the number of particles, the paper also develops an implementation based on box particles, referred to as the Bernoulli Box-PF. A box particle is a random sample that occupies a small and controllable rectangular region of non-zero volume in the target state space. Manipulation of boxes utilizes the methods of interval analysis. The two implementations are compared numerically and found to perform remarkably well: the target is reliably detected and the posterior probability density function of the target state is estimated accurately. The Bernoulli Box-PF, however, when designed carefully, is computationally more efficient

Vulnerability Assessment of Settlements During Emergencies

During emergencies which occur as a result of uncontrolled effects of natural disasters, major technical and technological accidents and major epidemics of infectious diseases, the health and life of people and the persistent environmental degradation may be affected. Therefore, it is necessary to assess the vulnerability of the settlements from natural disasters and other accidents. The assessment must be professionally and scientifically established with a multidisciplinary approach. This paper defi nes methodology for vulnerability assessment of given populated areas during emergencies arising from uncontrolled effects of natural and other disasters which involves a complex analysis of actual hazard probabilities and the level of impact on humans, animals, property, cultural wealth, and the environment

Identification of the transition rule in a modified cellular automata model: the case of dendritic NH4Br crystal growth

A method of identifying the transition rule, encapsulated in a modified cellular automata (CA) model, is demonstrated using experimentally observed evolution of dendritic crystal growth patterns in NH4Br crystals. The influence of the factors, such as experimental set-up and image pre-processing, colour and size calibrations, on the method of identification are discussed in detail. A noise reduction parameter and the diffusion velocity of the crystal boundary are also considered. The results show that the proposed method can in principle provide a good representation of the dendritic growth anisotropy of any system

Identification of a spatio-temporal model of crystal growth based on boundary curvature

A new method of identifying the spatio-temporal transition rule of crystal growth is introduced based on the connection between growth kinetics and dentritic morphology. Using a modified three-point-method, curvatures of the considered crystal branch are calculated and curvature direction is used to measure growth velocity. A polynomial model is then produced based on a curvature-velocity relationship to represent the spatio-temporal growth process. A very simple simulation example is used initially to clearly explain the methodology. The results of identifying a model from a real crystal growth experiment show that the proposed method can produce a good representation of crystal growth

Identification of excitable media using a scalar coupled map lattice model

The identification problem for excitable media is investigated in this paper. A new scalar coupled map lattice (SCML) model is introduced and the orthogonal least squares algorithm is employed to determinate the structure of the SCML model and to estimate the associated parameters. A simulated pattern and a pattern observed directly from a real Belousov-Zhabotinsky reaction are identified. The identified SCML models are shown to possess almost the same local dynamics as the original systems and are able to provide good long term predictions