L∞ Error and Bandwidth Selection for Kernel Density Estimates of Large Data

Kernel density estimates are a robust way to reconstruct a continuous distribution from a discrete point set. Typically their effectiveness is measured either in L1 or L2 error. In this paper we investigate the challenges in using L ∞ (or worst case) error, a stronger measure than L1 or L2. We present efficient solutions to two linked challenges: how to evaluate the L ∞ error between two kernel density estimates and how to choose the bandwidth parameter for a kernel density estimate built on a subsample of a large data set. 1 1

Fly a Rocket! ESA's hands-on programme for undergraduate students

The Fly a Rocket! programme is a hands-on project offered by the European Space Agency’s (ESA’s) Education Office in collaboration with Andøya Space Education and the Norwegian Space Agency (Norsk Romsenter). The programme represents a unique opportunity for entry-level university students from diverse backgrounds to build, test, and launch an actual sounding rocket and obtain otherwise unattainable practical experience. In September 2020, the ESA Education Office announced the third edition of the programme, for which 30 students from the ESA Member States and the Associate Member States were selected. Of these, 24 participated in the launch campaign which took place throughout the second week of October 2021 at the Andøya Space in Northern Norway. The Fly a Rocket! programme comprises an online pre-course with two assignments and a hands-on launch campaign. The pre-course is self-paced and aims to widen the participants’ understanding of basic rocket science topics such as the rocket principle, aerodynamics, and orbital mechanics in preparation for the campaign. During their stay at Andøya Space, the students were assigned to one of three teams, each with different responsibilities: Sensor Experiments, Telemetry and Data Readout, and Payload. As members of the Telemetry and Data Readout team, the authors’ role was to set up the student telemetry station and ensure that accurate data was collected from the sensors on the rocket. In addition, they were an integral part of the countdown procedure, operating two of the three telemetry stations used for the mission. Following the launch, all the teams worked in conjunction to analyse and present the data according to four previously defined scientific cases. This paper will be concerned with the activities carried out throughout Fly a Rocket!’s third cycle, with a particular focus on the work done by the Telemetry and Data Readout tea