Beecroft Institute for Particle Astrophysics and Cosmology

Abstract:

We use the cosmological hydrodynamical simulation NewHorizon to study the effects of the baryonic component on the inner mass profile of dark matter haloes of isolated galaxies (). Dark matter deficits (‘cores’) develop only in galaxies in a narrow range of stellar mass, . The lower stellar mass limit arises because a minimum amount of star formation is required to drive the baryonic outflows that redistribute dark matter and create a core. The upper limit roughly coincides with the total amount of dark matter initially contained within the innermost 2 kpc (), which roughly coincides with the stellar half-mass radius of these dwarfs. This enclosed mass is quite insensitive to the total virial mass of the system. The same upper limit applies to other simulations, like NIHAO and EAGLE-CHT10, despite their rather different galaxy formation efficiencies. This suggests that it is the galaxy total stellar mass that determines when a core is formed, and not the galaxy-to-dark halo mass ratio, as argued in earlier work. This is consistent with a back-of-the-envelope estimate for a SN-induced rate of orbital diffusion. Although NewHorizon dwarfs reproduce the observed diversity of rotation curves better than other simulations, there are significant differences in the gravitational importance of baryons in the inner regions of dwarfs compared to observations. These differences prevent us from concluding that cosmological simulations are currently fully able to account for the observed diversity of rotation curve shapes.

Abstract:

<jats:p>We use the projected clustering of quasars in the Gaia-unWISE quasar catalog, Quaia, and its cross-correlation with CMB lensing data from Planck, to measure the large-scale turnover of the matter power spectrum, associated with the size of the horizon at the epoch of matter-radiation equality. The turnover is detected with a significance of between <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mn>2.3</mml:mn></mml:math> and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:mn>3.1</mml:mn><mml:mi>σ</mml:mi></mml:mrow></mml:math>, depending on the method used to quantify it. From this measurement, the equality scale is determined at the <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn>20</mml:mn><mml:mi>%</mml:mi></mml:mrow></mml:math> level. Using the turnover scale as a standard ruler alone (suppressing information from the large-scale curvature of the power spectrum), in combination with supernova data through an inverse distance ladder approach, we measure the current expansion rate to be . The addition of information coming from the power spectrum curvature approximately halves the standard ruler uncertainty. Our measurement in combination with calibrated supernovae from Pantheon <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mo>+</mml:mo></mml:math> and SH0ES constrains the CMB temperature to be , independently of CMB data. Alternatively, assuming the value of from COBE-FIRAS, we can constrain the effective number of relativistic species in the early Universe to be .</jats:p>

Abstract:

We present a spatially resolved analysis of four star-forming galaxies at using data from the JWST Public Release Imaging for Extragalactic Research (PRIMER) and ALMA-[C II] Resolved ISm in STar-forming galaxies with ALma (CRISTAL) surveys to probe the stellar and interstellar medium properties on the sub- scale. In the JWST NIRCam imaging we find that the galaxies are composed of multiple clumps (between 2 and ∼8) separated by , with comparable morphologies and sizes in the rest-frame ultraviolet (UV) and optical. Using BAGPIPES to perform pixel-by-pixel spectral energy distribution (SED) fitting to the JWST data, we show that the star formation rate (SFR) () and stellar mass ( ) derived from the resolved analysis are in close () agreement with those obtained by fitting the integrated photometry. In contrast to studies of lower mass sources, we thus find a reduced impact of outshining of the older (more massive) stellar populations in these normal galaxies. Our JWST analysis recovers bluer rest-frame UV slopes () and younger ages () than archival values. We find that the dust continuum from ALMA-CRISTAL seen in two of these galaxies correlates, as expected, with regions of redder rest-frame UV slopes and the SED-derived , as well as the peak in the stellar mass map. We compute the resolved –relation, showing that the IRX is consistent with the local starburst attenuation curve and further demonstrating the presence of an inhomogeneous dust distribution within the galaxies. A comparison of the CRISTAL sources to those from the FirstLight zoom-in simulation of galaxies with the same and SFR reveals similar age and colour gradients, suggesting that major mergers may be important in the formation of clumpy galaxies at this epoch.

Abstract:

To date, galaxy image simulations for weak lensing surveys usually approximate the light profiles of all galaxies as a single or double Sérsic profile, neglecting the influence of galaxy substructures and morphologies deviating from such a simplified parametric characterisation. While this approximation may be sufficient for previous data sets, the stringent cosmic shear calibration requirements and the high quality of the data in the upcoming Euclid survey demand a consideration of the effects that realistic galaxy substructures and irregular shapes have on shear measurement biases. Here we present a novel deep learning-based method to create such simulated galaxies directly from Hubble Space Telescope (HST) data. We first build and validate a convolutional neural network based on the wavelet scattering transform to learn noise-free representations independent of the point-spread function (PSF) of HST galaxy images. These can be injected into simulations of images from Euclid's optical instrument VIS without introducing noise correlations during PSF convolution or shearing. Then, we demonstrate the generation of new galaxy images by sampling from the model randomly as well as conditionally. In the latter case, we fine-tune the interpolation between latent space vectors of sample galaxies to directly obtain new realistic objects following a specific Sérsic index and half-light radius distribution. Furthermore, we show that the distribution of galaxy structural and morphological parameters of our generative model matches the distribution of the input HST training data, proving the capability of the model to produce realistic shapes. Next, we quantify the cosmic shear bias from complex galaxy shapes in Euclid-like simulations by comparing the shear measurement biases between a sample of model objects and their best-fit double-Sérsic counterparts, thereby creating two separate branches that only differ in the complexity of their shapes. Using the Kaiser, Squires, and Broadhurst shape measurement algorithm, we find a multiplicative bias difference between these branches with realistic morphologies and parametric profiles on the order of (6.9 ± 0.6)×10-3 for a realistic magnitude-Sérsic index distribution. Moreover, we find clear detection bias differences between full image scenes simulated with parametric and realistic galaxies, leading to a bias difference of (4.0 ± 0.9)×10-3 independent of the shape measurement method. This makes complex morphology relevant for stage IV weak lensing surveys, exceeding the full error budget of the Euclid Wide Survey (Δμ1,2 < 2 × 103).