Potential Backup Targets for Comet Interceptor

Comet Interceptor is an ESA F-class mission expected to launch in 2028 on the same launcher as ESA's ARIEL mission. Comet Interceptor's science payload consists of three spacecraft, a primary spacecraft that will carry two smaller probes to be released at the target. The three spacecraft will fly-by the target along different chords, providing multiple simultaneous perspectives of the comet nucleus and its environment. Each of the spacecraft will be equipped with different but complementary instrument suites designed to study the far and near coma environment and surface of a comet or interstellar object (ISO). The primary spacecraft will perform a fly-by at ~1000 km from the target. The two smaller probes will travel deeper into the coma, closer to the nucleus. The mission is being designed and launched without a specific comet designated as its main target. Comet Interceptor will travel to the Sun-Earth L2 Lagrangian point with ARIEL and wait in hibernation until a suitable long-period comet (LPC) is found that will come close enough to the Sun for the spacecraft to maneuver to an encounter trajectory. To prepare for all eventualities, the science team has assembled a preliminary set of backup targets from the known Jupiter family comets, where a suitable fly-by trajectory can be achieved during the nominal mission timeline (including the possibility of some launch delay). To better prioritize this list, we are releasing our potential backup targets in order to solicit the planetary community's help with observations of these objects over future apparitions and to encourage publication of archival data on these objects.Comment: Accepted to RNAA

DAPHNE: An Open and Extensible System Infrastructure for Integrated Data Analysis Pipelines

Integrated data analysis (IDA) pipelines—that combine data management (DM) and query processing, high-performance computing (HPC), and machine learning (ML) training and scoring—become increasingly common in practice. Interestingly, systems of these areas share many compilation and runtime techniques, and the used—increasingly heterogeneous—hardware infrastructure converges as well. Yet, the programming paradigms, cluster resource management, data formats and representations, as well as execution strategies differ substantially. DAPHNE is an open and extensible system infrastructure for such IDA pipelines, including language abstractions, compilation and runtime techniques, multi-level scheduling, hardware (HW) accelerators, and computational storage for increasing productivity and eliminating unnecessary overheads. In this paper, we make a case for IDA pipelines, describe the overall DAPHNE system architecture, its key components, and the design of a vectorized execution engine for computational storage, HW accelerators, as well as local and distributed operations. Preliminary experiments that compare DAPHNE with MonetDB, Pandas, DuckDB, and TensorFlow show promising results

Building type classification with incomplete labels

Buildings can be distinguished by their form or function and maps of building types can be used by authorities for city planning. Training models to perform this classification re- quires appropriate training data. OpenStreetMap (OSM) data is globaly available and partly provides information on build- ing types. However, this data can be incomplete or wrong. In this work a U-Net is trained to group buildings into one of the three major function classes (commercial/industrial, residen- tial and other) using incomplete OSM data or ground-truth cadastral data. The model achieves overall accuracies of 72 and 75 percent. Given the OSM data has only around 20 per- cent of the ground truth labels this shows the incomplete data can be used to train for the building classification task

On graphical display of Prolog III results

Some experiments are reported on how to get a 'user friendly' graphical display of results obtained from numerical constraint solvers available in 'Constraint Logic Programming; (CLP) languages, like e.g. Prolog III. For larger sets of result data graphical visualization is a suitable and desirable way to enable users to quickly perceive, understand, and interpret main features of these results. In particular the issue is addressed of whether it is preferable to utilize the built-in Prolog III graphics primitives or to use external graphic user interface packages. Related questions of data transfer and communication control are discussed. As present result it is stated that for a language like Prolog III emphasis should be laid on constructing robust and easy to handle interfaces to external software packages, rather than to rebuild all kinds of useful and desirable graphics features within the language itself. This report is a summary of the main results of one of the authors' Master's Thesis (Guibert 1993), enlarged by the study on 3D plots. It is a complement to work performed by ESPRIT partners within work package 5 ('Environment') of the PRINCE project (PRolog INtegrated with Constraints and Environment for industrial and financial applications - contract no. 5246). FAW's role in this project is to study suitable examples of CLP-technology in view of user applicability. (orig.)SIGLEAvailable from TIB Hannover: RO 9630(94005) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekCommission of the European Communities (CEC), Brussels (Belgium)DEGerman

ROSE: Untersuchungen zur Modellierung technischer Systeme

Available from TIB Hannover: RO 9630(92002) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekSIGLEDEGerman

Working with the first prototype version of the Prince _-prolog definiteness analysis tools

Constraint Logic Programming (CLP) aims at providing more powerful and flexible programs than can be obtained in 'traditional' Logic Programming. However, situations may arise where there is a tradeoff in terms of runtime efficiency at which these programs can be executed. 'Definiteness Analysis', based on Bruynooghe's abstract interpretation framework, targets at achieving faster CLP programs. The present work summarizes work performed during a visiting scientiest exchange of one of the authors (E.O.) at FAW-Ulm in Summer/Fall 1993. The objective was to test the definiteness analyser prototype developed at UPM as part of the ESPRIT project PRINCE (contract no. 5246) research, based on test examples provided by PRINCE application partners. In addition, a short background and some suggestions for possible future work are given. (orig.)Available from TIB Hannover: RO 9630(94004) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekSIGLECommission of the European Communities (CEC), Brussels (Belgium)DEGerman

CLP and spacecraft attitude control

SIGLECopy held by FIZ Karlsruhe; available from UB/TIB Hannover / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekDEGerman

IMEM2: a meteoroid environment model for the inner solar system

International audienceContext. The interplanetary dust complex is currently understood to be largely the result of dust production from Jupiter-family comets, with contributions also from longer-period comets (Halley- and Oort-type) and collisionally produced asteroidal dust.Aims. Here we develop a dynamical model of the interplanetary dust cloud from these source populations in order to develop a risk and hazard assessment tool for interplanetary meteoroids in the inner solar system.Methods. The long-duration (1 Myr) integrations of dust grains from Jupiter-family and Halley-type comets and main belt asteroids were used to generate simulated distributions that were compared to COBE infrared data, meteor data, and the diameter distribution of lunar microcraters. This allowed the constraint of various model parameters.Results. We present here the first attempt at generating a model that can simultaneously describe these sets of observations. Extended collisional lifetimes are found to be necessary for larger (radius ≥ 150 μm) particles. The observations are best fit with a differential size distribution that is steep (slope = 5) for radii ≥ 150 μm, and shallower (slope = 2) for smaller particles. At the Earth the model results in ~ 90–98% Jupiter-family comet meteoroids, and small contributions from asteroidal and Halley-type comet particles. In COBE data we find an approximately 80% contribution from Jupiter-family comet meteoroids and 20% from asteroidal particles. The resulting flux at the Earth is mostly within a factor of about two to three of published measurements

DAPHNE: An Open and Extensible System Infrastructure for Integrated Data Analysis Pipelines

Integrated data analysis (IDA) pipelines—that combine data management (DM) and query processing, high-performance computing (HPC), and machine learning (ML) training and scoring—become increasingly common in practice. Interestingly, systems of these areas share many compilation and runtime techniques, and the used—increasingly heterogeneous—hardware infrastructure converges as well. Yet, the programming paradigms, cluster resource management, data formats and representations, as well as execution strategies differ substantially. DAPHNE is an open and extensible system infrastructure for such IDA pipelines, including language abstractions, compilation and runtime techniques, multi-level scheduling, hardware (HW) accelerators, and computational storage for increasing productivity and eliminating unnecessary overheads. In this paper, we make a case for IDA pipelines, describe the overall DAPHNE system architecture, its key components, and the design of a vectorized execution engine for computational storage, HW accelerators, as well as local and distributed operations. Preliminary experiments that compare DAPHNE with MonetDB, Pandas, DuckDB, and TensorFlow show promising results