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Radosław Wojtak

Publications and source records attributed to Radosław Wojtak.

At least 19 recordsLinked to original sources

Two-population model of type Ia supernovae and their associations with host galaxies in ZTF DR2

We constrain type Ia supernova intrinsic properties, extinction, and probabilistic supernova-host associations using the volume-limited sample from the Zwicky Transient Factory DR2, the largest selection-free data set of type Ia supernovae to date. We employ Bayesian hierarchical modelling to jointly analyse the distribution of SALT2 light-curve parameters and global host-galaxy properties (stellar mass and rest-frame g-z colour). The adopted model is a mixture of distributions representing two supernova populations corresponding to two distinct modes of the stretch-parameter distribution, and two host-galaxy populations corresponding to two modes in the host-galaxy parameter space (red/massive and blue/less massive). Motivated by observations, high-stretch supernovae are allowed to populate both host-galaxy populations, whereas low-stretch supernovae are assumed to be exclusively associated with the red/massive host-galaxy population. The apparent non-linearity of the supernova magnitude-stretch relation implies a luminosity gap between the supernova populations, with the low-stretch population being Delta MB=0.14+/-0.03 mag brighter at x1=0, and different slopes (Delta alpha=0.064+/-0.023, steeper for the low-stretch population). The mean extinction coefficient is RB=3.89+/-0.29 (consistent with typical Milky Way values) in the blue/less massive host-galaxy population, which contains 68 per cent of high-stretch supernovae, and RB=3.08+/-0.08 in the red/massive host-galaxy population. Host-galaxy step corrections, both in stellar mass and colour, naturally emerge from the way the two supernova populations, characterised by different intrinsic luminosities and exctinctions, are distributed across host-galaxy populations. The adopted framework for modelling supernova populations and supernova-host associations makes host-galaxy step corrections redundant.

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Stretch to stretch, dust to dust: lower-value local $H_{0}$ measurement from two-population modelling of type Ia supernovae

We revisit the local Hubble constant measurement from type Ia supernovae calibrated with Cepheids (SH0ES) by remodelling the supernova data using two supernova populations emerging from the observed bimodal distribution of the SALT2 stretch parameter. Our analysis accounts for population differences in both intrinsic properties (related to possible initial conditions, including supernova progenitor channels) and host-galaxy extinction (expected from well-known environmental differences associated observationally with the two populations). Based on a two-population Bayesian hierarchical modelling of the SALT2 light-curve parameters from the Pantheon+ compilation, we simultaneously constrain intrinsic and extrinsic properties of both supernova populations, match probabilistically the calibration supernovae with the corresponding population in the Hubble flow, and derive the Hubble constant. The difference between the two supernova populations is primarily driven by their mean absolute magnitudes and total-to-selective extinction coefficients. This is related but not equivalent to the traditional mass-step correction (including its broadening for reddened supernovae). The mean extinction coefficient of the supernova population used to propagate distances from the calibration galaxies to the Hubble flow is found to be consistent with the Milky Way-like interstellar dust model with R_B~4 and substantially higher than the extinction model assumed in the SH0ES measurement. Allowing for possible differences between reddening in the calibration galaxies and the corresponding population in the Hubble flow, we obtain H_0=70.59+/-1.15 km/s/Mpc. For the most conservative choice assuming equal prior distributions, we find H_0=71.45+/-1.03 km/s/Mpc. Our reanalysis of type Ia supernovae results in a reduction of the discrepancy with the Planck H_0 by at least 30 and up to 50 per cent (3.5-2.2sigma).

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Inferring the Hubble Constant Using Simulated Strongly Lensed Supernovae and Neural Network Ensembles

Strongly lensed supernovae are a promising new probe to obtain independent measurements of the Hubble constant (${H_0}$). In this work, we employ simulated gravitationally lensed Type Ia supernovae (glSNe Ia) to train our machine learning (ML) pipeline to constrain $H_0$. We simulate image time-series of glSNIa, as observed with the upcoming Nancy Grace Roman Space Telescope, that we employ for training an ensemble of five convolutional neural networks (CNNs). The outputs of this ensemble network are combined with a simulation-based inference (SBI) framework to quantify the uncertainties on the network predictions and infer full posteriors for the $H_0$ estimates. We illustrate that the combination of multiple glSN systems enhances constraint precision, providing a $4.4\%$ estimate of $H_0$ based on 100 simulated systems, which is in agreement with the ground truth. This research highlights the potential of leveraging the capabilities of ML with glSNe systems to obtain a pipeline capable of fast and automated $H_0$ measurements.

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Consistent extinction model for type Ia supernovae in Cepheid-based calibration galaxies and its impact on $H_{0}$

The most recent SH0ES measurement of the Hubble constant employs corrections of type Ia supernova magnitudes due to extinction in their host galaxies. These corrections are estimated using a probabilistic model which is trained on Hubble flow (z>0.03) supernovae and extrapolated to the calibration galaxies (those with observed Cepheids), despite the fact that the latter are selected based on criteria favouring disky and dust-rich systems. We show that this standard approach underestimates the brightness of reddened supernovae in the high stellar-mass ($M_{\star}>10^{10}M_{\odot}$) calibration galaxies. This can be traced back to the fact that for these galaxies, a low total-to-selective extinction coefficient (R_B~3) is assumed, while for the low stellar-mass analogues a more standard R_ B~4 is adopted. We propose a minimalistic modification of the extinction model in the calibration galaxies in order to alleviate this systematic effect. The modification is twofold and it involves: (i) the same, Milky Way-like distribution of R_B (with mean R_B of 4.3 -- consistent with the extinction curve used for colour corrections of the Cepheids -- and scatter 0.4) and (ii) a modified shape of the E(B-V) reddening distribution while keeping the same effective slope of the supernova peak magnitude-colour relation and the same mean E(B-V) reddening as measured for supernovae in the Hubble flow. We show that this new approach yields a significantly better fit ($ΔBIC=-11$) to the calibration data and results in a lower value of $H_{0}$. Our result is $H_{0}=70.5\pm1$ km/s/Mpc implying a reduction of the Hubble constant tension from $5.2σ$ to $2.8σ$.

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Relative intrinsic scatter in hierarchical Type Ia supernova siblings analyses: Application to SNe 2021hpr, 1997bq & 2008fv in NGC 3147

We present Young Supernova Experiment $grizy$ photometry of SN 2021hpr, the third Type Ia supernova sibling to explode in the Cepheid calibrator galaxy, NGC 3147. Siblings are useful for improving SN-host distance estimates, and investigating the contributions towards the SN Ia intrinsic scatter (post-standardisation residual scatter in distance estimates). We thus develop a principled Bayesian framework for analyzing SN Ia siblings. At its core is the cosmology-independent relative intrinsic scatter parameter, $σ_{Rel}$: the dispersion of siblings distance estimates relative to one another within a galaxy. It quantifies the contribution towards the total intrinsic scatter, $σ_0$, from within-galaxy variations about the siblings' common properties. It also affects the combined-distance uncertainty. We present analytic formulae for computing a $σ_{Rel}$-posterior from individual siblings distances (estimated using any SN-model). Applying a newly trained BayeSN model, we fit the light curves of each sibling in NGC 3147 individually, to yield consistent distance estimates. However, the wide $σ_{Rel}$-posterior means $σ_{Rel}\approxσ_0$ is not ruled out. We thus combine the distances by marginalizing over $σ_{Rel}$ with an informative prior: $σ_{Rel}\sim U(0,σ_0)$. Simultaneously fitting the trio's light curves improves constraints on distance, and each sibling's individual dust parameters, compared to individual fits. Higher correlation also tightens dust parameter constraints. Therefore, $σ_{Rel}$-marginalization yields robust estimates of siblings distances for cosmology, and dust parameters for siblings-host correlation studies. Incorporating NGC 3147's Cepheid-distance yields $H_0=78.4\pm 6.5\,$km/s/Mpc. Our work motivates analyses of homogeneous siblings samples, to constrain $σ_{Rel}$, and its SN-model dependence.

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Two-population Bayesian hierarchical model of type Ia supernovae

The currently used standardisation of type Ia supernovae results in Hubble residuals whose physical origin is unaccounted for. Here, we present a complete physical interpretation of the Hubble residuals based on a novel Bayesian hierarchical model of type Ia supernovae in which latent variables describing intrinsic and extrinsic (dust related) supernova properties originate from two populations. Fitting the model to SALT2 light curve parameters of supernovae in the Hubble flow we find strong ($4σ$) evidence for the presence of two overlapping, but distinct, populations differentiated primarily by their mean SALT2 shape parameter (stretch) x_1. Supernovae from the population with predominantly slow decliners (higher average x_1) are found to be intrinsically bluer (mean SALT2 colour c=-0.11) and twice as reddened by dust (mean reddening E(B-V)=0.10) than those from the opposite population dominated by fast decliners (lower average x_1) with c=-0.04$ and E(B-V)=0.05. The inferred extinction coefficient R_B in both supernova populations follows a broad (scatter 0.9) distribution with a mean of 4.1, which coincides closely with the mean extinction law measured in the Milky Way. We also find that the supernova data favour a peaked (two-tailed) distribution of selective extinction E(B-V) over the commonly adopted exponential model (one-tailed with maximum fixed at 0). Our model provides a complete explanation of the distribution of supernova light curve parameters in terms of extinction properties and the above-mentioned differences between the two populations, without the need for introducing any intrinsic scatter.

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Measuring the Hubble constant with kilonovae using the Expanding Photosphere Method

While gravitational wave (GW) standard sirens from neutron star (NS) mergers have been proposed to offer good measurements of the Hubble constant, we show in this paper how a variation of the expanding photosphere method (EPM) or spectral-fitting expanding atmosphere method, applied to the kilonovae (KNe) associated with the mergers, can provide an independent distance measurement to individual mergers that is potentially accurate to within a few percent. There are four reasons why the KN-EPM overcomes the major uncertainties commonly associated with this method in supernovae: 1) the early continuum is very well-reproduced by a blackbody spectrum, 2) the dilution effect from electron scattering opacity is likely negligible, 3) the explosion times are exactly known due to the GW detection, and 4) the ejecta geometry is, at least in some cases, highly spherical and can be constrained from line-shape analysis. We provide an analysis of the early VLT/X-shooter spectra AT2017gfo showing how the luminosity distance can be determined, and find a luminosity distance of $D_L = 44.5\pm0.8$ Mpc in agreement with, but more precise than, previous methods. We investigate the dominant systematic uncertainties, but our simple framework, which assumes a blackbody photosphere, does not account for the full time-dependent three-dimensional radiative transfer effects, so this distance should be treated as preliminary. The luminosity distance corresponds to an estimated Hubble constant of $H_0 = 67.0\pm 3.6$ km s$^{-1}$ Mpc$^{-1}$, where the dominant uncertainty is due to the modelling of the host peculiar velocity. We also estimate the expected constraints on $H_0$ from future KN-EPM-analysis with the upcoming O4 and O5 runs of the LIGO collaboration GW-detectors, where five to ten similar KNe would yield 1\% precision cosmological constraints.

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Intrinsic tension in the supernova sector of the local Hubble constant measurement and its implications

We reanalyse observations of type Ia supernovae (SNe) and Cepheids used in the local determination of the Hubble constant and find strong evidence that SN standardisation in the calibration sample (galaxies with observed Cepheids) require a steeper slope of the colour correction than in the cosmological sample (galaxies in the Hubble flow). The colour correction in the calibration sample is consistent with being entirely due to an extinction correction due to dust with properties similar to that of the Milky Way (R_B~4.6+/-0.4) and there is no evidence for intrinsic scatter in the SN peak magnitudes. An immediate consequence of this finding is that the local measurement of the Hubble constant becomes dependent on the choice of SN reference colour, i.e., the colour of an unreddened SN. Specifically, the Hubble constant inferred from the same observations decreases gradually with the reference colour assumed in the SN standardisation. We recover the Hubble constant measured by SH0ES for the standard choice of reference colour (SALT2 colour parameter c=0) while for a reference colour which coincides with the blue end of the observed SN colour distribution (c~-0.13), the Hubble constant from Planck observations of the CMB (assuming a flat LCDM cosmological model) is recovered. These results are intriguing in that they may provide an avenue for resolving the Hubble tension. However, since there is no obvious physical basis for the differences in colour corrections in the two SN samples, the origin of these require further investigations.

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AI-driven spatio-temporal engine for finding gravitationally lensed type Ia supernovae

We present a spatio-temporal AI framework that concurrently exploits both the spatial and time-variable features of gravitationally lensed supernovae in optical images to ultimately aid in future discoveries of such exotic transients in wide-field surveys. Our spatio-temporal engine is designed using recurrent convolutional layers, while drawing from recent advances in variational inference to quantify approximate Bayesian uncertainties via a confidence score. Using simulated Young Supernova Experiment (YSE) images of lensed and non-lensed supernovae as a showcase, we find that the use of time-series images adds relevant information from time variability of spatial light distribution of partially blended images of lensed supernova, yielding a substantial gain of around 20 per cent in classification accuracy over single-epoch observations. Preliminary application of our network to mock observations from the Legacy Survey of Space and Time (LSST) results in detections with accuracy reaching around 99 percent. Our innovative deep learning machinery is versatile and can be employed to search for any class of sources which exhibit variability both in flux and spatial distribution of light.

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Simulation-based inference of dynamical galaxy cluster masses with 3D convolutional neural networks

We present a simulation-based inference framework using a convolutional neural network to infer dynamical masses of galaxy clusters from their observed 3D projected phase-space distribution, which consists of the projected galaxy positions in the sky and their line-of-sight velocities. By formulating the mass estimation problem within this simulation-based inference framework, we are able to quantify the uncertainties on the inferred masses in a straightforward and robust way. We generate a realistic mock catalogue emulating the Sloan Digital Sky Survey (SDSS) Legacy spectroscopic observations (the main galaxy sample) for redshifts $z \lesssim 0.09$ and explicitly illustrate the challenges posed by interloper (non-member) galaxies for cluster mass estimation from actual observations. Our approach constitutes the first optimal machine learning-based exploitation of the information content of the full 3D projected phase-space distribution, including both the virialized and infall cluster regions, for the inference of dynamical cluster masses. We also present, for the first time, the application of a simulation-based inference machinery to obtain dynamical masses of around $800$ galaxy clusters found in the SDSS Legacy Survey, and show that the resulting mass estimates are consistent with mass measurements from the literature.

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Dynamical mass inference of galaxy clusters with neural flows

We present an algorithm for inferring the dynamical mass of galaxy clusters directly from their respective phase-space distributions, i.e. the observed line-of-sight velocities and projected distances of galaxies from the cluster centre. Our method employs normalizing flows, a deep neural network capable of learning arbitrary high-dimensional probability distributions, and inherently accounts, to an adequate extent, for the presence of interloper galaxies which are not bounded to a given cluster, the primary contaminant of dynamical mass measurements. We validate and showcase the performance of our neural flow approach to robustly infer the dynamical mass of clusters from a realistic mock cluster catalogue. A key aspect of our novel algorithm is that it yields the probability density function of the mass of a particular cluster, thereby providing a principled way of quantifying uncertainties, in contrast to conventional machine learning approaches. The neural network mass predictions, when applied to a contaminated catalogue with interlopers, have a mean overall logarithmic residual scatter of 0.028 dex, with a log-normal scatter of 0.126 dex, which goes down to 0.089 dex for clusters in the intermediate to high mass range. This is an improvement by nearly a factor of four relative to the classical cluster mass scaling relation with the velocity dispersion, and outperforms recently proposed machine learning approaches. We also apply our neural flow mass estimator to a compilation of galaxy observations of some well-studied clusters with robust dynamical mass estimates, further substantiating the efficacy of our algorithm.

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Low-redshift measurement of the sound horizon through gravitational time-delays

The matter sound horizon can be inferred from the cosmic microwave background within the Standard Model. Independent direct measurements of the sound horizon are then a probe of possible deviations from the Standard Model. We aim at measuring the sound horizon $r_s$ from low-redshift indicators, which are completely independent of CMB inference. We used the measured product $H(z)r_s$ from baryon acoustic oscillations (BAO) together with supernovae~\textsc{I}a to constrain $H(z)/H_{0}$ and time-delay lenses analysed by the H0LiCOW collaboration to anchor cosmological distances ($\propto H_{0}^{-1}$). {Additionally, we investigated the influence of adding a sample of quasars with higher redshift with standardisable UV-Xray luminosity distances. We adopted polynomial expansions in $H(z)$ or in comoving distances} so that our inference was completely independent of any cosmological model on which the expansion history might be based. Our measurements are independent of Cepheids and systematics from peculiar motions {to within percent-level accuracy.} The inferred sound horizon $r_s$ varies between $(133 \pm 8)$~Mpc and $(138 \pm 5)$~Mpc across different models. The discrepancy with CMB measurements is robust against model choice. Statistical uncertainties are comparable to systematics. The combination of time-delay lenses, supernovae, and BAO yields a distance ladder that is independent of cosmology (and of Cepheid calibration) and a measurement of $r_s $ that is independent of the CMB. These cosmographic measurements are then a competitive test of the Standard Model, regardless of the hypotheses on which the cosmology is based.

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Einstein-Vlasov Calculations of Structure Formation

We study the dynamics of small inhomogeneities in an expanding universe collapsing to form bound structures using full solutions of the Einstein-Vlasov (N-body) equations. We compare these to standard Newtonian N-body solutions using quantities defined with respect to fiducial observers in order to bound relativistic effects. We focus on simplified initial conditions containing a limited range of length scales, but vary the inhomogeneities from small magnitude, where the Newtonian and general-relativistic calculations agree quite well, to large magnitude, where the background metric receives an order one correction. For large inhomogeneities, we find that the collapse of overdensities tends to happen faster in Newtonian calculations relative to fully general-relativistic ones. Even in this extreme regime, the differences in the spacetime evolution outside the regions of large gravitational potential and velocity are small. For standard cosmological values, we corroborate the robustness of Newtonian N-body simulations to model large scale perturbations and the related cosmic variance in the local expansion rate.

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The Hubble-Lemaître constant and sound horizon from low-redshift probes

We revisit the claimed tension, or lack thereof, of measured values of the Hubble-Lemaître parameter $H_0$ from Cosmic Microwave Background (CMB) data and low-redshift indicators. Baryon Acoustic Oscillations (BAO) rely on the scale of the sound horizon at recombination $r_s$ to convert angular measurements into angular-diameter distances, so fixing $r_s$ from CMB measurements already constrains $H_0.$ If departures from concordance cosmology are to be constrained, truly independent measurements of $H_0$ are needed. We use the angular-diameter distances to three time-delay lenses from the H0LiCOW collaboration to calibrate the distance ladder, combine them with relative distances from Supernovae Ia and BAO, leaving $r_s$ completely free, and provide the inferred coefficients ($q_{0},j_{0},s_{0}$) in the polynomial expansion of H(z). We obtain $H_{0}r_{s}=(9895\pm161)$km/s and $H_0=(72\pm7)$km/s/Mpc. Combined with $H_0$ from H0LiCOW, then $r_s=(137\pm4.5)$Mpc is consistent with previous work and systematically lower than the CMB-inferred value. Our results are independent of the adopted cosmology, and removing Supernovae with z<0.1 has a negligible effect.

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Magnified or multiply imaged? - Search strategies for gravitationally lensed supernovae in wide-field surveys

Strongly lensed supernovae can be detected as multiply imaged or highly magnified transients. In order to compare the performances of these two observational strategies, we calculate expected discovery rates as a function of survey depth in five grizy filters and for different classes of supernovae (Ia, IIP, IIL, Ibc and IIn). We find that detections via magnification is the only effective strategy for relatively shallow pre-LSST surveys. For survey depths about the LSST capacity, both strategies yield comparable numbers of lensed supernovae. Supernova samples from the two methods are to a large extent independent and combining them increases detection rates by about 50 per cent. While the number of lensed supernovae detectable via magnification saturates at the limiting magnitudes of LSST, detection rates of multiply imaged supernova still go up drastically at increasing survey depth. Comparing potential discovery spaces, we find that lensed supernovae found via image multiplicity exhibit longer time delays and larger image separations making them more suitable for cosmological constraints than their counterparts found via magnification. We find that the ZTF will find about 2 type Ia and 4 core-collapse lensed supernovae per year at a limiting magnitude of 20.6 in the r band. Applying a hybrid method which combines searching for highly magnified or multiply imaged transients, we find that LSST will detect 89 type Ia and 254 core-collapse lensed supernovae per year. In all cases, lensed core-collapsed supernovae will be dominated by type IIn supernovae contributing to 80 per cent of the total counts, although this prediction relies quite strongly on the adopted spectral templates for this class of supernovae. Revisiting the case of the lensed supernova iPTF16geu, we find that it is consistent within the 2σcontours of predicted redshifts and magnifications for the iPTF survey.

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Comparing Fully General Relativistic and Newtonian Calculations of Structure Formation

In the standard approach to studying cosmological structure formation, the overall expansion of the Universe is assumed to be homogeneous, with the gravitational effect of inhomogeneities encoded entirely in a Newtonian potential. A topic of ongoing debate is to what degree this fully captures the dynamics dictated by general relativity, especially in the era of precision cosmology. To quantitatively assess this, we directly compare standard N-body Newtonian calculations to full numerical solutions of the Einstein equations, for cold matter with various magnitude initial inhomogeneities on scales comparable to the Hubble horizon. We analyze the differences in the evolution of density, luminosity distance, and other quantities defined with respect to fiducial observers. This is carried out by reconstructing the effective spacetime and matter fields dictated by the Newtonian quantities, and by taking care to distinguish effects of numerical resolution. We find that the fully general relativistic and Newtonian calculations show excellent agreement, even well into the nonlinear regime. They only notably differ in regions where the weak gravity assumption breaks down, which arise when considering extreme cases with perturbations exceeding standard values.

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The Distance to NGC 4993: The Host Galaxy of the Gravitational-wave Event GW170817

The historic detection of gravitational waves from a binary neutron star merger (GW170817) and its electromagnetic counterpart led to the first accurate (sub-arcsecond) localization of a gravitational-wave event. The transient was found to be $\sim$10" from the nucleus of the S0 galaxy NGC 4993. We report here the luminosity distance to this galaxy using two independent methods. (1) Based on our MUSE/VLT measurement of the heliocentric redshift ($z_{\rm helio}=0.009783\pm0.000023$) we infer the systemic recession velocity of the NGC 4993 group of galaxies in the cosmic microwave background (CMB) frame to be $v_{\rm CMB}=3231 \pm 53$ km s$^{-1}$. Using constrained cosmological simulations we estimate the line-of-sight peculiar velocity to be $v_{\rm pec}=307 \pm 230$ km s$^{-1}$, resulting in a cosmic velocity of $v_{\rm cosmic}=2924 \pm 236$ km s$^{-1}$ ($z_{\rm cosmic}=0.00980\pm 0.00079$) and a distance of $D_z=40.4\pm 3.4$ Mpc assuming a local Hubble constant of $H_0=73.24\pm 1.74$ km s$^{-1}$ Mpc$^{-1}$. (2) Using Hubble Space Telescope measurements of the effective radius (15.5" $\pm$ 1.5") and contained intensity and MUSE/VLT measurements of the velocity dispersion, we place NGC 4993 on the Fundamental Plane (FP) of E and S0 galaxies. Comparing to a frame of 10 clusters containing 226 galaxies, this yields a distance estimate of $D_{\rm FP}=44.0\pm 7.5$ Mpc. The combined redshift and FP distance is $D_{\rm NGC 4993}= 41.0\pm 3.1$ Mpc. This 'electromagnetic' distance estimate is consistent with the independent measurement of the distance to GW170817 as obtained from the gravitational-wave signal ($D_{\rm GW}= 43.8^{+2.9}_{-6.9}$ Mpc) and confirms that GW170817 occurred in NGC 4993.

astro-ph.GA↗

Redshift remapping and cosmic acceleration in dark-matter-dominated cosmological models

The standard relation between the cosmological redshift and cosmic scale factor underlies cosmological inference from virtually all kinds of cosmological observations, leading to the emergence of the LambdaCDM cosmological model. This relation is not a fundamental theory and thus observational determination of this function (redshift remapping) should be regarded as an insightful alternative to holding its standard form in analyses of cosmological data. Here we present non-parametric reconstructions of redshift remapping in dark-matter-dominated models and constraints on cosmological parameters from a joint analysis of all primary cosmological probes including the local measurement of the Hubble constant, Type Ia supernovae, baryonic acoustic oscillations (BAO), Planck observations of the cosmic microwave background (CMB) radiation (temperature power spectrum) and cosmic chronometers. The reconstructed redshift remapping points to an additional boost of redshift operating in late epoch of cosmic evolution, but affecting both low-redshift observations and the CMB. The model predicts a significant difference between the actual Hubble constant, h=0.48+/-0.02, and its local determination, h_obs=0.73+/-0.02. The ratio of these two values coincides closely with the maximum expansion rate inside voids formed in the corresponding open cosmological model with Omega_m=0.87+/-0.03, whereas the actual value of the Hubble constant implies the age of the Universe that is compatible with the Planck LambdaCDM cosmology. The new dark-matter-dominated model with redshift remapping provides excellent fits to all data and eliminates recently reported tensions between the Planck LambdaCDM cosmology, the local determination of the Hubble constant and the BAO measurements from the Ly-alpha forest of high-redshift quasars.

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