2,748 research outputs found
Track-based alignement using a Kalman filter technique
An iterative method for track-based global alignment is proposed. It is derived from the Kalman filter and designed to avoid the inversion of large matrices. The update formulas for the alignment parameters and for the associated covariance matrix are described. The implementation and the computational complexity are discussed, and we show how to limit the latter to an acceptable level by restricting the update to detectors that are close in the sense of a certain metric. The performance of the Kalman filter in terms of precision and speed of convergence is studied with simulated tracks. Results from an implementation in the CMS reconstruction program CMSSW are presented, using two sections of the barrel part of the CMS Tracker
Application of the Kalman Alignment Algorithm to the CMS Tracker
One of the main components of the CMS experiment is the Silicon Tracker. This device, designed to measure the trajectories of charged particles, is composed of approximately 16,000 planar silicon detector modules, which makes it the biggest of its kind. However, systematic measurement errors, caused by unavoidable inaccuracies in the construction and assembly phase, reduce the precision of the measurements significantly. The geometrical corrections that are therefore required to be known to an accuracy that is better than the intrinsic resolution of the detector modules. The Kalman Alignment Algorithm is a novel approach to extract a set of alignment constants from a large collection of recorded particle tracks, and is applicable for a system even as big as the CMS Tracker. To show that the method is functional and well understood, and thus suitable for the data-taking period of the CMS experiment, two case studies are presented and discussed here
Representation and Estimation of Trajectories from Two-body Decays
A novel parametrization of the trajectories stemming from two-body decays is presented, based on the kinematics of the decay. The core component of this parametrization is a decay model which is derived using the relativistic energy-momentum conservation law and geometrical fundamentals. The estimation of the decay parameters, also including the beam profile and a mass constraint, is described. Some applications in realistics scenarios are presented. In addition, the representation of the trajectories for the use in track-based alignment algorithms is briefly discussed
A Large-scale Application of the Kalman Alignment Algorithm to the CMS Tracker
The Kalman alignment algorithm has been specifically developed to cope with the demands that arise from the specifications of the CMS Tracker. The algorithmic concept is based on the Kalman filter formalism and is designed to avoid the inversion of large matrices. Most notably, the algorithm strikes a balance between conventional global and local track-based alignment algorithms, by restricting the computation of alignment parameters not only to alignable objects hit by the same track, but also to all other alignable objects that are significantly correlated. Nevertheless, this feature also comes with various trade-offs: Mechanisms are needed that affect which alignable objects are significantly correlated and keep track of these correlations. Due to the large amount of alignable objects involved at each update (at least compared to local alignment algorithms), the time spent for retrieving and writing alignment parameters as well as the required user memory becomes a significant factor. The large-scale test presented here applies the Kalman alignment algorithm to the (misaligned) CMS Tracker barrel, and demonstrates the feasability of the algorithm in a realistic scenario. It is shown that both the computation time and the amount of required user memory are within reasonable bounds, given the available computing resources, and that the obtained results are satisfactory
Reconstruction of electrons with the Gaussian-sum filter in the CMS tracker at LHC
The bremsstrahlung energy loss distribution of electrons propagating in
matter is highly non Gaussian. Because the Kalman filter relies solely on
Gaussian probability density functions, it might not be an optimal
reconstruction algorithm for electron tracks. A Gaussian-sum filter (GSF)
algorithm for electron track reconstruction in the CMS tracker has therefore
been developed. The basic idea is to model the bremsstrahlung energy loss
distribution by a Gaussian mixture rather than a single Gaussian. It is shown
that the GSF is able to improve the momentum resolution of electrons compared
to the standard Kalman filter. The momentum resolution and the quality of the
estimated error are studied with various types of mixture models of the energy
loss distribution.Comment: Talk from the 2003 Computing in High Energy and Nuclear Physics
(CHEP03), La Jolla, Ca, USA, March 2003, LaTeX, 14 eps figures. PSN TULT00
Clustering with position-specific constraints on variance: Applying redescending M-estimators to label-free LC-MS data analysis
Confluence Modulo Equivalence in Constraint Handling Rules
Previous results on proving confluence for Constraint Handling Rules are
extended in two ways in order to allow a larger and more realistic class of CHR
programs to be considered confluent. Firstly, we introduce the relaxed notion
of confluence modulo equivalence into the context of CHR: while confluence for
a terminating program means that all alternative derivations for a query lead
to the exact same final state, confluence modulo equivalence only requires the
final states to be equivalent with respect to an equivalence relation tailored
for the given program. Secondly, we allow non-logical built-in predicates such
as var/1 and incomplete ones such as is/2, that are ignored in previous work on
confluence.
To this end, a new operational semantics for CHR is developed which includes
such predicates. In addition, this semantics differs from earlier approaches by
its simplicity without loss of generality, and it may also be recommended for
future studies of CHR.
For the purely logical subset of CHR, proofs can be expressed in first-order
logic, that we show is not sufficient in the present case. We have introduced a
formal meta-language that allows reasoning about abstract states and
derivations with meta-level restrictions that reflect the non-logical and
incomplete predicates. This language represents subproofs as diagrams, which
facilitates a systematic enumeration of proof cases, pointing forward to a
mechanical support for such proofs
An Adaptive Interacting Wang-Landau Algorithm for Automatic Density Exploration
While statisticians are well-accustomed to performing exploratory analysis in
the modeling stage of an analysis, the notion of conducting preliminary
general-purpose exploratory analysis in the Monte Carlo stage (or more
generally, the model-fitting stage) of an analysis is an area which we feel
deserves much further attention. Towards this aim, this paper proposes a
general-purpose algorithm for automatic density exploration. The proposed
exploration algorithm combines and expands upon components from various
adaptive Markov chain Monte Carlo methods, with the Wang-Landau algorithm at
its heart. Additionally, the algorithm is run on interacting parallel chains --
a feature which both decreases computational cost as well as stabilizes the
algorithm, improving its ability to explore the density. Performance is studied
in several applications. Through a Bayesian variable selection example, the
authors demonstrate the convergence gains obtained with interacting chains. The
ability of the algorithm's adaptive proposal to induce mode-jumping is
illustrated through a trimodal density and a Bayesian mixture modeling
application. Lastly, through a 2D Ising model, the authors demonstrate the
ability of the algorithm to overcome the high correlations encountered in
spatial models.Comment: 33 pages, 20 figures (the supplementary materials are included as
appendices
Longitudinal landscapes of serum antibody repertoires after influenza infection and vaccination
Vaccination is the most effective means of infectious disease prevention. Despite its success, however, we still lack a clear understanding of vaccine responses in humans. For example, influenza vaccines still leave a large fraction of population vulnerable. Over the past decade, single B-cell analysis and next-generation sequencing (NGS) technologies have become invaluable tools for studying the antibody repertoire to influenza. Such studies have led to discoveries of broadly-neutralizing antibodies (bNAbs), which can neutralize across multiple strains of influenza virus, promoting the notion of designing a universal vaccine that will elicit such antibodies. One of such isolated bNAbs, called FI6, showed remarkable ability to neutralize all of the influenza A virus strains through targeting the conserved epitope in the stem of hemagglutinin (HA). However, it remains unclear whether such bNAbs actually play a role in conferring protection against influenza since antibody proteins (not B-cells) need to circulate at physiologically relevant concentrations in serum to have implications in protection. Using high-resolution proteomics coupled with NGS, we quantitatively determined the serological antibody repertoire to CA09 HA (H1) at the individual clonotype-level in a donor (whom FI6 was isolated from) following influenza infection (in 2010 with pandemic CA09) and vaccination across five years (2010-2014 with seasonal flu vaccine). We analyzed the temporal changes of head-targeting and stem-binding antibodies, illustrating the gradual increase of stem-targeting antibodies following repeated exposures to CA09 HA. Following vaccination in 2014, \u3e60% of the repertoire consisted of one single clonotype of stem-binding antibody that was present at very low abundance in 2010. Our data demonstrate that the repetitive exposure to influenza skews the serological repertoire toward antibodies that target conserved epitopes, and these antibodies continue to be boosted every time the same epitopes are encountered. Once elicited, stem-binding antibodies displayed a tendency to persist in serum across multiple years while head-specific antibodies decayed quicker. The differential longevity of stem-binding and head-specific antibodies presented here has direct implications for the design of the future universal vaccine
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