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We present a design for a wide-field spectroscopic telescope. The only large powered mirror is spherical, the resulting spherical aberration is corrected for each target separately, giving exceptional image quality. The telescope is a transit design, but still allows all-sky coverage. Three simultaneous modes are proposed: (a) natural seeing multi-object spectroscopy with 12m aperture over 3dg FoV with ~25,000 targets; (b) multi-object AO with 12m aperture over 3dg FoV with ~100 AO-corrected Integral Field Units each with 4 arcsec FoV; (c) ground layer AO-corrected integral field spectroscopy with 15m aperture and 13 arcmin FoV. Such a telescope would be uniquely powerful for large-area follow-up of imaging surveys; in each mode, the AOmega and survey speed exceed all existing facilities combined. The expected cost of this design is relatively modest, much closer to $500M than $1000M., Comment: 10 pages. SPIE 13094-191, Ground-based and Airborne Telescopes X, Yokohama 2024. 4th version, error in figure 6 corrected 8th Sept 2024

BlueMUSE is a blue-optimised, medium spectral resolution, panoramic integral field spectrograph under development for the Very Large Telescope (VLT). With an optimised transmission down to 350 nm, spectral resolution of R$\sim$3500 on average across the wavelength range, and a large FoV (1 arcmin$^2$), BlueMUSE will open up a new range of galactic and extragalactic science cases facilitated by its specific capabilities. The BlueMUSE consortium includes 9 institutes located in 7 countries and is led by the Centre de Recherche Astrophysique de Lyon (CRAL). The BlueMUSE project development is currently in Phase A, with an expected first light at the VLT in 2031. We introduce here the Top Level Requirements (TLRs) derived from the main science cases, and then present an overview of the BlueMUSE system and its subsystems fulfilling these TLRs. We specifically emphasize the tradeoffs that are made and the key distinctions compared to the MUSE instrument, upon which the system architecture is built., Comment: 20 pages, 10 figures, proceedings of the SPIE astronomical telescopes and instrumentation conference, Yokohama, 16-21 June

While neural network approaches have made significant strides in resolving classical signal processing problems, it is often the case that hybrid approaches that draw insight from both signal processing and neural networks produce more complete solutions. In this paper, we present a hybrid classical digital signal processing/deep neural network (DSP/DNN) approach to source separation (SS) highlighting the theoretical link between variational autoencoder and classical approaches to SS. We propose a system that transforms the single channel under-determined SS task to an equivalent multichannel over-determined SS problem in a properly designed latent space. The separation task in the latent space is treated as finding a variational block-wise disentangled representation of the mixture. We show empirically, that the design choices and the variational formulation of the task at hand motivated by the classical signal processing theoretical results lead to robustness to unseen out-of-distribution data and reduction of the overfitting risk. To address the resulting permutation issue we explicitly incorporate a novel differentiable permutation loss function and augment the model with a memory mechanism to keep track of the statistics of the individual sources.

Slow rotator galaxies are distinct amongst galaxy populations, with simulations suggesting that a mix of minor and major mergers are responsible for their formation. A promising path to resolve outstanding questions on the type of merger responsible, is by investigating deep imaging of massive galaxies for signs of potential merger remnants. We utilise deep imaging from the Subaru-Hyper Suprime Cam Wide data to search for tidal features in massive ($\log_{10}(M_*/M_{\odot}) > 10$) early-type galaxies (ETGs) in the SAMI Galaxy Survey. We perform a visual check for tidal features on images where the galaxy has been subtracted using a Multi-Gauss Expansion (MGE) model. We find that $31\pm 2$ percent of our sample show tidal features. When comparing galaxies with and without features, we find that the distributions in stellar mass, light-weighted mean stellar population age and H$\alpha$ equivalent width are significantly different, whereas spin ($\lambda_{R_e}$), ellipticity and bulge to total ratio have similar distributions. When splitting our sample in age, we find that galaxies below the median age (10.8 Gyr) show a correlation between the presence of shells and lower $\lambda_{R_e}$, as expected from simulations. We also find these younger galaxies which are classified as having "strong" shells have lower $\lambda_{R_e}$. However, simulations suggest that merger features become undetectable within $\sim 2-4$ Gyr post-merger. This implies that the relationship between tidal features and merger history disappears for galaxies with older stellar ages, i.e. those that are more likely to have merged long ago., Comment: Accepted for publication in MNRAS. 22 pages, 14 figures

We use the SAMI galaxy survey to study the the kinematic morphology-density relation: the observation that the fraction of slow rotator galaxies increases towards dense environments. We build a logistic regression model to quantitatively study the dependence of kinematic morphology (whether a galaxy is a fast rotator or slow rotator) on a wide range of parameters, without resorting to binning the data. Our model uses a combination of stellar mass, star-formation rate (SFR), $r$-band half-light radius and a binary variable based on whether the galaxy's observed ellipticity ($\epsilon$) is less than 0.4. We show that, at fixed mass, size, SFR and $\epsilon$, a galaxy's local environmental surface density ($\log_{10}(\Sigma_5/\mathrm{Mpc}^{-2})$) gives no further information about whether a galaxy is a slow rotator, i.e. the observed kinematic-morphology density relation can be entirely explained by the well-known correlations between environment and other quantities. We show how our model can be applied to different galaxy surveys to predict the fraction of slow rotators which would be observed and discuss its implications for the formation pathways of slow rotators., Comment: 12 pages, 6 figures. Accepted for publication in MNRAS

We introduce a real-time, multichannel speech enhancement algorithm which maintains the spatial cues of stereo recordings including two speech sources. Recognizing that each source has unique spatial information, our method utilizes a dual-path structure, ensuring the spatial cues remain unaffected during enhancement by applying source-specific common-band gain. This method also seamlessly integrates pretrained monaural speech enhancement, eliminating the need for retraining on stereo inputs. Source separation from stereo mixtures is achieved via spatial beamforming, with the steering vector for each source being adaptively updated using post-enhancement output signal. This ensures accurate tracking of the spatial information. The final stereo output is derived by merging the spatial images of the enhanced sources, with its efficacy not heavily reliant on the separation performance of the beamforming. The algorithm runs in real-time on 10-ms frames with a 40 ms of look-ahead. Evaluations reveal its effectiveness in enhancing speech and preserving spatial cues in both fully and sparsely overlapped mixtures., Comment: Accepted for ICASSP 2024, 5 pages