Extremely Large Telescope

Abstract:

Atmospheric optical turbulence (OT) monitoring is crucial for site characterization at astronomical observatories and optical communications ground stations. The Shack–Hartmann image motion monitor (SHIMM) instrument implements a fast, infrared Shack–Hartmann sensor to measure a low-resolution OT profile continuously throughout the day and night. This work presents advances made in Shack–Hartman optical turbulence profiling techniques implemented on the SHIMM, including a derivation and validation of Z-tilt weighting functions, implementation of methods for correcting for non-zero exposure times, and for estimating the coherence time of optical turbulence using the profile coupled with the fast defocus method. These techniques were tested via end-to-end Monte Carlo simulations of the SHIMM instrument using real turbulence profiles from the Paranal stereo-SCIDAR instrument with an augmented ground layer. All measurements of integrated OT parameters were in strong agreement with the simulation inputs, evidenced by correlation coefficients close to one, small RMS error, and bias. The accuracy of the four-layer SHIMM model was also investigated, which showed high correlation with simulation inputs for all layers even in daytime OT conditions. This study suggests that, for the turbulence database used, and under realistic daytime noise conditions, a C n 2 ( h )d h sensitivity limit in the region of 2×10 −15 m 1/3 was encountered in the highest altitude layer. There was also evidence of a cross-talk effect between the strong ground layer and the first atmospheric layer.

Abstract:

Pictoris b is one of the closest known directly imaged gas giant exoplanets with an orbit that is almost edge-on to our line of sight, making it an ideal target for radial velocity monitoring to search for massive exomoons. We measure the radial velocity of Pictoris b over several epochs between October 2024 and March 2025 by using the cross-correlation of a template spectrum with absorption lines in the planet’s atmosphere, giving a mean precision of 160 m s. The resultant set of radial velocities is analysed with a periodogram to search for candidate radial velocity (RV) signals indicating a massive exomoon. Although we do not detect an exomoon signal in our data, our detection limits for a single moon are 80 Earth masses at d and 1 Jupiter at d, comparable to RV exomoon searches around other substellar companions. The RV limit is comparable with the astrometric exomoon limit at a period of 7 d and a mass of 150 , where for longer periods the astrometric searches have lower mass limits. With an additional observing season, the upgraded CRyogenic InfraRed Echelle Spectrograph (CRIRES+) can detect a planet/moon mass ratio of () with a period of up to one day, and can detect a Neptune-mass moon at hundreds of Jupiter radii.

Abstract:

Despite its proximity, the mass of the supermassive black hole (SMBH) in the spiral galaxy M81 (NGC 3031) has remained a subject of discussion, with doubts previously cast on the reliability of available dynamical measurements. We present the first robust stellar-dynamics measurement of its mass using high-resolution, two-dimensional kinematics from JWST/NIRSpec observations of the central 3″ × 3″. By tracing stellar motions in the near-infrared, our data penetrate the obscuring nuclear dust and allow for the separation of stellar light from the nonthermal AGN continuum. We modeled the kinematics using the Jeans anisotropic modelling method. Rather than relying on a standard Bayesian approach for error estimation, we constructed a suite of 24 independent models, each employing a unique combination of different physical assumptions regarding stellar mass-to-light (M/L) ratio gradients, the point-spread function, the masking of the central active galactic nucleus, and the orientation of the velocity ellipsoid. This ensemble approach allows us to robustly account for the impact of systematic uncertainties. To estimate our systematic uncertainties, we performed a bootstrap of the MBH values derived from these 24 models, thereby incorporating the variance between different physical assumptions. Our analysis yields a precise SMBH mass of MBH = (4.77 ± 0.37) × 107 M⊙ (1σ confidence, including systematic and statistical uncertainties). This result is consistent with previous determinations within their uncertainties, while providing a crucial and highly reliable anchor point for SMBH–galaxy scaling relations in spiral galaxies.

Abstract:

We conduct a search for strong gravitational lenses in the Dark Energy Survey (DES) Year 6 imaging data. We implement a pre-trained Vision Transformer (ViT) for our machine learning (ML) architecture and adopt interactive machine learning to construct a training sample with multiple classes to address common types of false positives. Our ML model reduces ∼236 million DES cutout images to 22,564 targets of interest, including ∼85% of previously reported galaxy–galaxy lens candidates discovered in DES. These targets were visually inspected by citizen scientists, who ruled out ∼90% as false positives. Of the remaining 2618 candidates, 149 were expert-classified as “definite” lenses and 516 as “probable” lenses, for a total of 665 systems, with 147 of these candidates being newly identified. Additionally, we trained a second ViT to find double-source plane lens systems, finding at least one double-source system. Our main ViT excels at identifying galaxy–galaxy lenses, consistently assigning high scores to candidates with high expert assessments. The top 800 ViT-scored images include ∼100 of our “definite” lens candidates. This selection is an order of magnitude higher in purity than previous convolutional neural-network-based lens searches and demonstrates the feasibility of applying our methodology for discovering large samples of lenses in future surveys.