Abstract
Resolution and sensitivity of the wavefront sensor (WFS) are key requirements for eXtreme Adaptive Optics (XAO) applications. We present a new class of WFSs, the Bi-Orthogonal Foucault-knife-edge (Bi-O edge), that is directly inspired by the Foucault knife-edge test. The idea consists of using a beam-splitter producing two foci, each of which is sensed by an edge with an orthogonal direction to the other. We describe two implementation concepts. The first one, the tip-tilt modulated sharp Bi-O-edge, can be seen as a mild evolution of the Pyramid. The second one uses a smooth, gradual amplitude mask over a 'grey' zone on the edge (grey Bi-O edge). We analyze the increased gain in sensitivity and the super-resolution capability, we compare these properties to the Pyramid sensor and produce end-to-end simulations. An important advantage of the grey Bi-O edge is the static modulation which is well adapted for fast XAO systems. The grey edge consists of a rectangular zone on the edge of the same size as the modulation circle. We will discuss the manufacturability of loss-less grey Foucault-knife edges, and we develop a polarization-based technique for the Bi-O edge prototype for the ESO GHOST test bench.

Abstract
The Adaptive Optics Telemetry (AOT) format has recently been proposed to standardize the telemetry data generated by adaptive optics systems. Yet its usability remains limited by the user's programming expertise and familiarity with the accompanying Python package. There is an opportunity for substantial improvement in data accessibility by offering users an alternative tool for conducting exploratory data analysis in a visual and intuitive manner. We aim to design and develop an open-source Python visualization tool for exploring AOT data. This tool should support researchers and users by offering a broad set of interactive features for the analysis and exploration of the data. We designed a prototype dashboard and performed user testing to validate its usability. We compared the prototype with existing data visualization and exploration tools to ensure we provided the necessary functionality. We made publicly available a user-friendly dashboard for analyzing and exploring AOT data.

Abstract
Estimating turbulence parameters is essential during commissioning and optimising adaptive optics or fringe tracking systems. It also gained new relevance with free-space optical communication applications. The estimation of such parameters is done under the assumption of stationarity. Yet, the stationarity time scale of the atmospheric turbulence is unknown. The breakdown of this assumption leads to incorrect estimates and added error terms. In this paper, we illustrate stationarity detection with unit root testing and the pitfalls of its application to turbulence parameter time series.

Abstract
To facilitate easy prediction and estimation of Adaptive Optics performance, we have created a fast algorithm named TipTop. This algorithm generates the expected AO Point Spread Function (PSF) for any existing AO observing mode (SCAO, LTAO, MCAO, GLAO) and any set of atmospheric conditions. Developed in Python, TipTop is based on an analytical approach, with simulations performed in the Fourier domain, enabling very fast computation times (less than a second per PSF) and efficient exploration of the extensive parameter space. TipTop can be used for several applications, from assisting in the observation preparation with the Exposure Time Calculator (ETC), to providing PSF models for post-processing. TipTop can also be used to help users in selecting the best NGSs asterism and optimizing their observation. Over the past years, the code has been intensively tested against different other simulation tools, showing very good agreements. TipTop is also currently deployed for VLT instruments, as proof of concepts in preparation of the ELT. The code is available here: https://tiptop.readthedocs.io/en/main/, and we encourage all future observers of the ELT to test it and provide feedback !

Abstract
The first scientific observations with adaptive optics (AO) at W. M. Keck Observatory (WMKO) began in 1999. Through 2023, over 1200 refereed science papers have been published using data from the WMKO AO systems. The scientific competitiveness of AO at WMKO has been maintained through a continuous series of AO and instrument upgrades and additions. This tradition continues with AO being a centerpiece of WMKO's scientific strategic plan for 2035. We will provide an overview of the current and planned AO projects from the context of this strategic plan. The current projects include implementation of new real-time controllers, the KAPA laser tomography system and the HAKA high-order deformable mirror system, the development of multiple advanced wavefront sensing and control techniques, the ORCAS space-based guide star project, and three new AO science instruments. We will also summarize steps toward the future strategic directions which are centered on ground-layer, visible and high-contrast AO.

Abstract
The Real Time Controllers (RTCs) for the W. M. Keck Observatory Adaptive Optics (AO) systems have been upgraded from a Field Programmable Gate Array (FPGA) to a Graphics Processing Unit (GPU) based solution. The previous RTCs, operating since 2007, had reached their limitations after upgrades to support new hardware including an Infra-Red (IR) Tip/Tilt (TT) Wave Front Sensor (WFS) on Keck I and a Pyramid WFS on Keck II. The new RTC, fabricated by a Microgate-led consortium with SUT leading the computation engine development, provides a flexible platform that improves processing bandwidth and allows for easier integration with new hardware and control algorithms. Along with the new GPU-based RTC, the upgrade includes a new hardware Interface Module (IM), new OCAM2K EMCCD cameras, and a new Telemetry Recording Server (TRS). The first system upgrade to take advantage of the new RTC is the Keck I All-sky Precision Adaptive Optics (KAPA) Laser Tomography AO (LTAO) system, which uses the larger and more sensitive OCAM2K EMCCD camera, tomographic reconstruction from four Laser Guide Stars (LGS), and improvements to the IR TT WFS. On Keck II the new RTC will enable a new higher-order Deformable Mirror (DM) as part of the HAKA (High order Advanced Keck Adaptive optics) project, which will also use an EMCCD camera. In the future, the new RTC will allow the possibility for new developments such as the proposed 'IWA (Infrared Wavefront sensor Adaptive optics) system. The new RTC saw first light in 2021. The Keck I system was released for science observations in late 2023, with the Keck II system released for science in early 2024.