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The Gemini Planet Imager (GPI) is a high contrast imaging instrument that aims to detect and characterize extrasolar planets. GPI is being upgraded to GPI 2.0, with several subsystems receiving a re-design to improve its contrast. To enable observations on fainter targets and increase performance on brighter ones, one of the upgrades is to the adaptive optics system. The current Shack-Hartmann wavefront sensor (WFS) is being replaced by a pyramid WFS with an low-noise electron multiplying CCD (EMCCD). EMCCDs are detectors capable of counting single photon events at high speed and high sensitivity. In this work, we characterize the performance of the HNu ̈ 240 EMCCD from Nuvu Cameras, which was custom-built for GPI 2.0. Through our performance evaluation we found that the operating mode of the camera had to be changed from inverted-mode (IMO) to non-inverted mode (NIMO) in order to improve charge diffusion features found in the detector’s images. Here, we characterize the EMCCD’s noise contributors (readout noise, clock-induced charges, dark current) and linearity tests (EM gain, exposure time) before and after the switch to NIMO. 

The Gemini Planet Imager (GPI) is a high-contrast imaging instrument designed to directly detect and char- acterise young, Jupiter-mass exoplanets. After six years of operation at the Gemini South Telescope in Chile, the instrument is being upgraded and moved to the Gemini North Telescope in Hawaii as GPI 2.0. Several improvements have been made to the adaptive optics (AO) system as part of this upgrade. This includes re- placing the current Shack-Hartmann wavefront sensor with a pyramid wavefront sensor (PWFS) and a custom EMCCD. These changes will increase GPI’s sky coverage by accessing fainter targets, improving corrections on fainter stars and allowing faster and ultra-low latency operations on brighter targets. The PWFS subsystem was independently built and tested to verify its performance before being integrated into the GPI 2.0 instrument. This paper will present the pre-integration performance test results, including pupil image quality, throughput and linearity without modulation. 

Abstract The unprecedented medium-resolution (R_λ∼ 1500–3500) near- and mid-infrared (1–18μm) spectrum provided by JWST for the young (140 ± 20 Myr) low-mass (12–20M_Jup) L–T transition (L7) companion VHS 1256 b gives access to a catalog of molecular absorptions. In this study, we present a comprehensive analysis of this data set utilizing a forward-modeling approach applying our Bayesian framework,ForMoSA. We explore five distinct atmospheric models to assess their performance in estimating key atmospheric parameters:T_eff, log(g), [M/H], C/O,γ,f_sed, andR. Our findings reveal that each parameter’s estimate is significantly influenced by factors such as the wavelength range considered and the model chosen for the fit. This is attributed to systematic errors in the models and their challenges in accurately replicating the complex atmospheric structure of VHS 1256 b, notably the complexity of its clouds and dust distribution. To propagate the impact of these systematic uncertainties on our atmospheric property estimates, we introduce innovative fitting methodologies based on independent fits performed on different spectral windows. We finally derived aT_effconsistent with the spectral type of the target, considering its young age, which is confirmed by our estimate of log(g). Despite the exceptional data quality, attaining robust estimates for chemical abundances [M/H] and C/O, often employed as indicators of formation history, remains challenging. Nevertheless, the pioneering case of JWST’s data for VHS 1256 b has paved the way for future acquisitions of substellar spectra that will be systematically analyzed to directly compare the properties of these objects and correct the systematics in the models.