End-to-end ground calibration and in-flight performance of the FIREBall-2 instrument

Abstract

The payload of the Faint Intergalactic Redshifted Emission Balloon (FIREBall-2), the second generation of the FIREBall instrument (PI: C. Martin, Caltech), has been calibrated and launched from the NASA Columbia Scientific Balloon Facility in Fort Sumner, New Mexico. FIREBall-2 was launched for the first time on the September 22, 2018, and the payload performed the very first multi-object acquisition from space using a multi-object spectrograph. Our performance-oriented paper presents the calibration and last ground adjustments of FIREBall-2, the in-flight performance assessed based on the flight data, and the predicted instrument's ultimate sensitivity. This analysis predicts that future flights of FIREBall-2 should be able to detect the HI Lyα resonance line in galaxies at z ∼ 0.67, but will find it challenging to spatially resolve the circumgalactic medium.

Balloon-borne FIREBall-2 ultraviolet spectrograph stray light control based on nonsequential reverse modeling of on-sky data

“…After the abrupt touchdown of FIREBall-2 and an inventory of damage sustained, the team conducted postflight calibrations, during which the primary stray light paths were confirmed 4 , 5 . Based on the results of the postflight calibration, a preliminary baffling strategy was proposed.…”

“…After the abrupt touchdown of FIREBall-2 and an inventory of damage sustained, the team conducted postflight calibrations, during which the primary stray light paths were confirmed. 4,5 Based on the results of the postflight calibration, a preliminary baffling strategy was proposed. We present the work done since to implement the proposed strategy and expand the scope and effectiveness of stray light control measures.…”

Student Behavior Detection in the Classroom Based on Improved YOLOv8

“…AugFPN fuses features after RoI pooling using spatial attention spectra. It is also important to address multi-scale target detection at a fine-grained level [21]. Res2Net achieves this by constructing hierarchical residual-like connections in a single residual block to represent multi-scale features at a fine-grained level, increasing the range of sensory fields at each network layer.…”