PPF - A Parallel Particle Filtering Library

We present the parallel particle filtering (PPF) software library, which enables hybrid shared-memory/distributed-memory parallelization of particle filtering (PF) algorithms combining the Message Passing Interface (MPI) with multithreading for multi-level parallelism. The library is implemented in Java and relies on OpenMPI's Java bindings for inter-process communication. It includes dynamic load balancing, multi-thread balancing, and several algorithmic improvements for PF, such as input-space domain decomposition. The PPF library hides the difficulties of efficient parallel programming of PF algorithms and provides application developers with the necessary tools for parallel implementation of PF methods. We demonstrate the capabilities of the PPF library using two distributed PF algorithms in two scenarios with different numbers of particles. The PPF library runs a 38 million particle problem, corresponding to more than 1.86 GB of particle data, on 192 cores with 67% parallel efficiency. To the best of our knowledge, the PPF library is the first open-source software that offers a parallel framework for PF applications.Comment: 8 pages, 8 figures; will appear in the proceedings of the IET Data Fusion & Target Tracking Conference 201

Comparison of Geometric Optimization Methods with Multiobjective Genetic Algorithms for Solving Integrated Optimal Design Problems

In this paper, system design methodologies for optimizing heterogenous power devices in electrical engineering are investigated. The concept of Integrated Optimal Design (IOD) is presented and a simplified but typical example is given. It consists in finding Pareto-optimal configurations for the motor drive of an electric vehicle. For that purpose, a geometric optimization method (i.e the Hooke and Jeeves minimization procedure) associated with an objective weighting sum and a Multiobjective Genetic Algorithm (i.e. the NSGA-II) are compared. Several performance issues are discussed such as the accuracy in the determination of Pareto-optimal configurations and the capability to well spread these solutions in the objective space

A track-before-detect labelled multi-Bernoulli particle filter with label switching

This paper presents a multitarget tracking particle filter (PF) for general track-before-detect measurement models. The PF is presented in the random finite set framework and uses a labelled multi-Bernoulli approximation. We also present a label switching improvement algorithm based on Markov chain Monte Carlo that is expected to increase filter performance if targets get in close proximity for a sufficiently long time. The PF is tested in two challenging numerical examples.Comment: Accepted for publication in IEEE Transactions on Aerospace and Electronic System

Technical design and commissioning of the KATRIN large-volume air coil system

The KATRIN experiment is a next-generation direct neutrino mass experiment with a sensitivity of 0.2 eV (90% C.L.) to the effective mass of the electron neutrino. It measures the tritium $\beta$-decay spectrum close to its endpoint with a spectrometer based on the MAC-E filter technique. The $\beta$-decay electrons are guided by a magnetic field that operates in the mT range in the central spectrometer volume; it is fine-tuned by a large-volume air coil system surrounding the spectrometer vessel. The purpose of the system is to provide optimal transmission properties for signal electrons and to achieve efficient magnetic shielding against background. In this paper we describe the technical design of the air coil system, including its mechanical and electrical properties. We outline the importance of its versatile operation modes in background investigation and suppression techniques. We compare magnetic field measurements in the inner spectrometer volume during system commissioning with corresponding simulations, which allows to verify the system's functionality in fine-tuning the magnetic field configuration. This is of major importance for a successful neutrino mass measurement at KATRIN.Comment: 32 pages, 16 figure