Related papers: New achievements in optical turbulence forecast sy…
Long distance imaging is subject to the impact of the turbulent atmosphere. This results into geometric distortions and some blur effect in the observed frames. Despite the existence of several turbulence mitigation algorithms in the…
This paper introduces temporally local metrics for Multi-Object Tracking. These metrics are obtained by restricting existing metrics based on track matching to a finite temporal horizon, and provide new insight into the ability of trackers…
Test-Time Adaptation (TTA) enables pre-trained models to adjust to distribution shift by learning from unlabeled test-time streams. However, existing methods typically treat these streams as independent samples, overlooking the supervisory…
These last years ground-based astronomy has been looking towards Antarctica, especially its summits and the internal continental plateau where the optical turbulence (OT) appears to be confined in a shallow layer close to the surface.…
Earth system predictability is challenged by the complexity of environmental dynamics and the multitude of variables involved. Current AI foundation models, although advanced by leveraging large and heterogeneous data, are often constrained…
The amount of Adaptive Optics (AO) telemetry generated by VIS/NIR ground-based observatories is ever greater, leading to a growing need for a standardised data exchange format to support performance analysis and AO research and development…
With the prospect of the next generation of ground-based telescopes, the extremely large telescopes (ELTs), increasingly complex and demanding adaptive optics (AO) systems are needed. This is to compensate for image distortion caused by…
Adaptive optics systems are essential on all large telescopes where image quality is important. These are complex systems with many design parameters requiring optimisation before good performance can be achieved. The simulation of adaptive…
We propose a new programming language called ALTA and a compiler that can map ALTA programs to Transformer weights. ALTA is inspired by RASP, a language proposed by Weiss et al. (2021), and Tracr (Lindner et al., 2023), a compiler from RASP…
Atmospheric optical turbulence (OT) monitoring is crucial for site characterisation at astronomical observatories and optical communications ground stations. The Shack-Hartmann Image Motion Monitor (SHIMM) instrument implements a fast,…
The Adaptive Optics (AO) performance significantly depends on the available Natural Guide Stars (NGSs) and a wide range of atmospheric conditions (seeing, Cn2, windspeed,...). In order to be able to easily predict the AO performance, we…
Knowledge of the Earth's atmospheric optical turbulence is critical for astronomical instrumentation. Not only does it enable performance verification and optimisation of existing systems but it is required for the design of future…
Using an observational derived model optical turbulence profile (model-OTP) we have investigated the performance of Adaptive Optics (AO) at Siding Spring Observatory (SSO), Australia. The simulations cover the performance for AO techniques…
Accurate precipitation forecasting is becoming increasingly important in the context of climate change. In response, machine learning-based approaches have recently gained attention as an emerging alternative to traditional methods such as…
There is a great need to accurately predict short-term precipitation, which has socioeconomic effects such as agriculture and disaster prevention. Recently, the forecasting models have employed multi-source data as the multi-modality input,…
Time-domain astronomy (TDA) is facing a paradigm shift caused by the exponential growth of the sample size, data complexity and data generation rates of new astronomical sky surveys. For example, the Large Synoptic Survey Telescope (LSST),…
The strength and vertical distribution of atmospheric turbulence is a key factor determining the performance of optical and infrared telescopes, with and without adaptive optics. Yet, this remains challenging to measure. We describe a new…
This study introduces OTCliM (Optical Turbulence Climatology using Machine learning), a novel approach for deriving comprehensive climatologies of atmospheric optical turbulence strength ($C_n^2$) using gradient boosting machines. OTCliM…
The orbital angular momentum (OAM) of photons is a promising degree of freedom for high-dimensional quantum key distribution (QKD). However, effectively mitigating the adverse effects of atmospheric turbulence is a persistent challenge in…
Geospatial Copilots hold immense potential for automating Earth observation (EO) and climate monitoring workflows, yet their reliance on large-scale models such as GPT-4o introduces a paradox: tools intended for sustainability studies often…