Fast radio bursts (FRBs) probe the electron column density along the line of sight and hence can be used to probe foreground structures. One such structure is the Galactic halo. In this work, we use a total of 98 high Galactic latitude ($|b| \gt 20^\circ$) FRBs detected by ASKAP, Parkes, DSA, and FAST with 32 associated redshifts to constrain the dispersion measure (DM) contribution from the Galactic halo. We simultaneously fit unknown FRB population parameters, which show correlations with the Galactic halo but are not completely degenerate. We primarily use an isotropic model for the halo, but find no evidence favouring a particular halo model. We find DM$_\mathrm{MW,halo}$ = $68^{+27}_{-24}$ pc cm$^{-3}$, which is in agreement with other results within the literature. Previous constraints on DM$_\mathrm{MW,halo}$ with FRBs have used a few, low-DM FRBs. However, this is highly subject to fluctuations between different lines of sight, and hence using a larger number of sightlines as we do is more likely to be representative of the true average contribution. Nevertheless, we show that individual FRBs can still skew the data significantly and hence will be important in the future for more precise results.

We examine the potential improvements in constraints on the dark energy equation of state parameter w and matter density $\Omega_M$ from using clustering information along with number counts for future samples of thermal Sunyaev-Zel’dovich selected galaxy clusters. We quantify the relative improvement from including the clustering power spectrum information for three cluster sample sizes from 33 000 to 140 000 clusters and for three assumed priors on the mass slope and redshift evolution of the mass-observable relation. As expected, clustering information has the largest impact when (i) there are more clusters and (ii) the mass-observable priors are weaker. For current knowledge of the cluster mass-observable relationship, we find the addition of clustering information reduces the uncertainty on the dark energy equation of state, $\sigma(w)$, by factors of $1.023\pm 0.007$ to $1.079\pm 0.011$, with larger improvements observed with more clusters. Clustering information is more important for the matter density, with $\sigma(\Omega_M)$ reduced by factors of $1.068 \pm 007$ to $1.145 \pm 0.012$. The improvement in w constraints from adding clustering information largely vanishes after tightening priors on the mass-observable relationship by a factor of two. For weaker priors, we find clustering information improves the determination of the cluster mass slope and redshift evolution by factors of $1.389 \pm 0.041$ and $1.340 \pm 0.039$, respectively. These findings highlight that, with the anticipated surge in cluster detections from next generation surveys, self-calibration through clustering information will provide an independent cross-check on the mass slope and redshift evolution of the mass-observable relationship as well as enhancing the precision achievable from cluster cosmology.

Fast radio burst (FRB) science primarily revolves around two facets: the origin of these bursts and their use in cosmological studies. This work follows from previous redshift–dispersion measure (z–DM) analyses in which we model instrumental biases and simultaneously fit population parameters and cosmological parameters to the observed population of FRBs. This sheds light on both the progenitors of FRBs and cosmological questions. Previously, we have completed similar analyses with data from the Australian Square Kilometer Array Pathfinder (ASKAP) and the Murriyang (Parkes) Multibeam system. In this manuscript, we use 119 FRBs with 29 associated redshifts by additionally modelling the Deep Synoptic Array (DSA) and the Five-hundred-metre Aperture Spherical radio Telescope (FAST). We also invoke a Markov chain Monte Carlo (MCMC) sampler and implement uncertainty in the Galactic DM contributions. The latter leads to larger uncertainties in derived model parameters than previous estimates despite the additional data and indicate that precise measurements of DM$_\textrm{ISM}$ will be important in the future. We provide refined constraints on FRB population parameters and derive a new constraint on the minimum FRB energy of log $E_{\mathrm{min}}$(erg)=39.47$^{+0.54}_{-1.28}$ which is significantly higher than bursts detected from strong repeaters. This result likely indicates a low-energy turnover in the luminosity function or may alternatively suggest that strong repeaters have a different luminosity function to single bursts. We also predict that FAST will detect 25–41% of their FRBs at $z \gtrsim 2$ and DSA will detect 2–12% of their FRBs at $z \gtrsim 1$.

As the scale of cosmological surveys increases, so does the complexity in the analyses. This complexity can often make it difficult to derive the underlying principles, necessitating statistically rigorous testing to ensure the results of an analysis are consistent and reasonable. This is particularly important in multi-probe cosmological analyses like those used in the Dark Energy Survey (DES) and the upcoming Legacy Survey of Space and Time, where accurate uncertainties are vital. In this paper, we present a statistically rigorous method to test the consistency of contours produced in these analyses and apply this method to the Pippin cosmological pipeline used for type Ia supernova cosmology with the DES. We make use of the Neyman construction, a frequentist methodology that leverages extensive simulations to calculate confidence intervals, to perform this consistency check. A true Neyman construction is too computationally expensive for supernova cosmology, so we develop a method for approximating a Neyman construction with far fewer simulations. We find that for a simulated dataset, the 68% contour reported by the Pippin pipeline and the 68% confidence region produced by our approximate Neyman construction differ by less than a percent near the input cosmology; however, they show more significant differences far from the input cosmology, with a maximal difference of 0.05 in $\Omega_{M}$ and 0.07 in w. This divergence is most impactful for analyses of cosmological tensions, but its impact is mitigated when combining supernovae with other cross-cutting cosmological probes, such as the cosmic microwave background.

One of the largest sources of systematics in time-delay cosmography arises from Mass Sheet Transformation (MST). The degeneracy associated with this transformation is often broken by an assumed profile shape, such as a power-law. A hierarchical strategy has been developed which constrains the global profile shape on a population level, constrained collectively by the kinematics measurements of the lenses. This framework allows one to include non-time-delay lenses to provide constraints to the global profile, improving the H0 constraints. This work tests the hierarchical framework using analytical profiles, and additionally tests the capacity to combine two populations which come from the same profiles but probe different radii due to a change in source redshift. We find that the hierarchical framework is able to compensate for this effect, and the addition of non-time-delay lenses improves the H0 constraint, even though these lenses have different Einstein radii than their time-delay counterparts.

Thanks to forthcoming large-scale surveys, a tremendous number of strong lenses will be discovered in the coming years. The gain in accuracy on H0 from such a large population of lensed quasars is a key question for the future of time-delay cosmography. In such context, lensed systems will have to be modeled in an automated way, with models that are sufficiently generic to apply to every lens. I explore the biases that may arise from unaccounted-for azimuthal structures in mass models. The non-modeled twists in lensing galaxies are expected to bias the shear inference but not H0. Disregarded ellipticity gradients, boxyness and discyness may impact the cosmological inference on a lens-by-lens basis. Nevertheless, the diversity of azimuthal mass profile in lenses balances the bias at a population level and the H0 inference can thus benefits from such large surveys.

The angular power spectrum is a natural tool to analyse the observed galaxy number count fluctuations. In a standard analysis, the angular galaxy distribution is sliced into concentric redshift bins and all correlations of its harmonic coefficients between bin pairs are considered—a procedure referred to as ‘tomography’. However, the unparalleled quality of data from oncoming spectroscopic galaxy surveys for cosmology will render this method computationally unfeasible, given the increasing number of bins. Here, we put to test against synthetic data a novel method proposed in a previous study to save computational time. According to this method, the whole galaxy redshift distribution is subdivided into thick bins, neglecting the cross-bin correlations among them; each of the thick bin is, however, further subdivided into thinner bins, considering in this case all the cross-bin correlations. We create a simulated data set that we then analyse in a Bayesian framework. We confirm that the newly proposed method saves computational time and gives results that surpass those of the standard approach.

The main sequence offers a method for the systematization of quasar spectral properties. Extreme FeII emitters (or extreme Population A, xA) are believed to be sources accreting matter at very high rates. They are easily identifiable along the quasar main sequence, in large spectroscopic surveys over a broad redshift range. The very high accretion rate makes it possible that massive black holes hosted in xA quasars radiate at a stable, extreme luminosity-to-mass ratio. After reviewing the basic interpretation of the main sequence, we report on the possibility of identifying virial broadening estimators from low-ionization line widths, and provide evidence of the conceptual validity of redshift-independent luminosities based on virial broadening for a known luminosity-to-mass ratio.

We aim to do forecasts for the Legacy Survey of Space and Time (LSST) with a theoretical modeling of the two point angular correlation function. The Fisher matrix is the starting point. This is a square matrix over the cosmological parameters, whose diagonal contains direct informations on the parameters expected uncertainties.

We have compiled the X-ray characteristic properties for a unique and homogeneous sample of Type 2 AGN with water megamaser activity observed by XMM-Newton and for a control sample of non-maser galaxies, both analyzed in a uniform way. A comparison of the luminosity distributions confirms previous results (from smaller and/or less systematic studies) that water maser galaxies appear more luminous than non-maser sources. In addition, the maser phenomenon is associated with more complex X-ray spectra, higher column densities and higher equivalent widths of the Fe Kα line. Both a sufficiently luminous X-ray source and a high absorbing column density in the line of sight favor the appearance of the water megamaser phenomenon in AGN.

Highly accreting quasars are possible cosmological probes, as their Eddington ratio is expected to saturate toward values of order unity. We present preliminary estimates of redshift- independent source luminosities and the Hubble diagram for quasars in the redshift range 0.1 ≲ z ≲ 2.6.

The wealth of strong lensing features observed in the Frontier Fields clusters offers insights on the nature of dark energy. The large number of multiple-images systems with redshifts allows to simultaneously estimate the lens model parameters and the cosmological parameters involved in the distances calculations. In particular for the ΛCDM model, it is possible to estimate the matter density Ωm and the dark energy equations parameters w X . In this talk, I will present recent analyses of systematic errors based on Frontier Fields observed and simulated data.

The accurate description of the properties of the Lyman-α forest is a spectacular success of the Cold Dark Matter theory of cosmological structure formation. After a brief review of early models, it is shown how numerical simulations have demonstrated the Lyman-α forest emerges from the cosmic web in the quasi-linear regime of overdensity. The quasi-linear nature of the structures allows accurate modeling, providing constraints on cosmological models over a unique range of scales and enabling the Lyman-α forest to serve as a bridge to the more complex problem of galaxy formation.

Peculiar motion introduces systematic variations in the observed luminosity distribution of galaxies. This allows one to constrain the cosmic peculiar velocity field from large galaxy redshift surveys. Using around half a million galaxies from the SDSS Data Release 7 at z ~ 0.1, we demonstrate the applicability of this approach to large datasets and obtain bounds on peculiar velocity moments and σ8, the amplitude of the linear matter power spectrum. Our results are in good agreement with the ΛCDM model and consistent with the previously reported ~ 1% zero-point tilt in the SDSS photometry. Finally, we discuss the prospects of constraining the growth rate of density perturbations by reconstructing the full linear velocity field from the observed galaxy clustering in redshift space.

Using redshifts from the 2M++ redshift compilation, we reconstruct the density of galaxies within 200 h −1 Mpc, and compare the predicted peculiar velocities Tully-Fisher and SNe peculiar velocities. The comparison yields a best-fit value of β ≡ Ωm 0.55/b* = 0.431 ± 0.021, suggesting Ωm 0.55σ8,lin = 0.401 ± 0.024, in good agreement with other probes. The predicted peculiar velocity of the Local Group from sources within the 2M++ volume is 540 ± 40 km s−1, towards l = 268° ± 4°, b = 38° ± 6°, which is misaligned by only 10° with the Cosmic Microwave Background dipole. To account for sources outside the 2M++ volume, we fit simultaneously for β* and an external bulk flow in our analysis. The external bulk flow has a velocity of 159 ± 23 km s−1 towards l = 304° ± 11°, b6° ± 13°.