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Ofer Lahav

Publications and source records attributed to Ofer Lahav.

At least 91 records · Page 5Linked to original sources
arXiv2019

Cosmological Measurements from Angular Power Spectra Analysis of BOSS DR12 Tomography

We constrain cosmological parameters by analysing the angular power spectra of the Baryon Oscillation Spectroscopic Survey DR12 galaxies, a spectroscopic follow-up of around 1.3 million SDSS galaxies over 9,376 deg$^2$ with an effective volume of $\sim 6.5$ (Gpc $h^{-1}$)$^3$ in the redshift range $0.15 \leq z < 0.80$. We split this sample into 13 tomographic bins ($Δz = 0.05$); angular power spectra were calculated using a Pseudo-$C_{\ell}$ estimator, and covariance matrices were estimated using log-normal simulated maps. Cosmological constraints obtained from these data were combined with constraints from Planck CMB experiment as well as the JLA supernovae compilation. Considering a $w$CDM cosmological model measured on scales up to $k_{max} = 0.07h$ Mpc$^{-1}$, we constrain a constant dark energy equation-of-state with a $\sim 4\%$ error at the 1-$σ$ level: $w_0 = -0.993^{+0.046}_{-0.043}$, together with $Ω_m = 0.330\pm 0.012$, $Ω_b = 0.0505 \pm 0.002$, $S_8 \equiv σ_8 \sqrt{Ω_m/0.3} = 0.863 \pm 0.016$, and $h = 0.661 \pm 0.012$. For the same combination of datasets, but now considering a $Λ$CDM model with massive neutrinos and the same scale cut, we find: $Ω_m = 0.328 \pm 0.009$, $Ω_b = 0.05017^{+0.0009}_{-0.0008}$, $S_8 = 0.862 \pm 0.017$, and $h = 0.663^{+0.006}_{-0.007}$ and a 95\% credible interval (CI) upper limit of $\sum m_ν < 0.14$ eV for a normal hierarchy. These results are competitive if not better than standard analyses with the same dataset, and demonstrate this should be a method of choice for future surveys, opening the door for their full exploitation in cross-correlations probes.

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arXiv2019

Upper Bound of Neutrino Masses from Combined Cosmological Observations and Particle Physics Experiments

We investigate the impact of prior models on the upper bound of the sum of neutrino masses, $\sum m_ν$. We use data from Large Scale Structure of galaxies, Cosmic Microwave Background, Type Ia SuperNovae, and Big Bang Nucleosynthesis. We probe physically motivated neutrino mass models (respecting oscillation experiment constraints) and compare them to constraints using standard cosmological approximations. The former give a consistent upper bound of $\sum m_ν \lesssim 0.26$ eV ($95\%$ CI) and yields a strong competitive upper bound for the lightest neutrino mass species, $m_0^ν < 0.086$ eV ($95\%$ CI). By contrast one of the approximations, which is somewhat inconsistent with oscillation experiments, yields an upper bound of $\sum m_ν \lesssim 0.15$ eV ($95\%$ CI), which differs substantially from the former upper bound. We, therefore, argue that cosmological neutrino mass and hierarchy determination should be pursued using physically motivated models since approximations might lead to incorrect and nonphysical upper bounds.

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arXiv2019

The Dark Energy Spectroscopic Instrument (DESI)

We present the status of the Dark Energy Spectroscopic Instrument (DESI) and its plans and opportunities for the coming decade. DESI construction and its initial five years of operations are an approved experiment of the US Department of Energy and is summarized here as context for the Astro2020 panel. Beyond 2025, DESI will require new funding to continue operations. We expect that DESI will remain one of the world's best facilities for wide-field spectroscopy throughout the decade. More about the DESI instrument and survey can be found at https://www.desi.lbl.gov.

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arXiv2019

Primordial Non-Gaussianity

Our current understanding of the Universe is established through the pristine measurements of structure in the cosmic microwave background (CMB) and the distribution and shapes of galaxies tracing the large scale structure (LSS) of the Universe. One key ingredient that underlies cosmological observables is that the field that sources the observed structure is assumed to be initially Gaussian with high precision. Nevertheless, a minimal deviation from Gaussianityis perhaps the most robust theoretical prediction of models that explain the observed Universe; itis necessarily present even in the simplest scenarios. In addition, most inflationary models produce far higher levels of non-Gaussianity. Since non-Gaussianity directly probes the dynamics in the early Universe, a detection would present a monumental discovery in cosmology, providing clues about physics at energy scales as high as the GUT scale.

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arXiv2019

Gravitational wave cosmology and astrophysics with large spectroscopic galaxy surveys

During the next decade, gravitational waves will be observed from hundreds of binary inspiral events. When the redshifts of the host galaxies are known, these events can be used as `standard sirens', sensitive to the expansion rate of the Universe. Measurements of the Hubble constant $H_0$ from standard sirens can be done independently of other cosmological probes, and events occurring at $z<0.1$ will allow us to infer $H_0$ independently of cosmological models. The next generation of spectroscopic galaxy surveys will play a crucial role in reducing systematic uncertainties in $H_0$ from standard sirens, particularly for the numerous `dark sirens' which do not have an electromagnetic counterpart. In combination with large spectroscopic data sets, standard sirens with an EM counterpart are expected to constrain $H_0$ to $\sim 1-2\%$ precision within the next decade. This is competitive with the best estimates of $H_0$ obtained to date and will help illuminate the current tension between existing measurements. Information on the galaxies that host the gravitational wave events will also shed light on the origin and evolution of compact object binaries.

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arXiv2019

Messengers from the Early Universe: Cosmic Neutrinos and Other Light Relics

The hot dense environment of the early universe is known to have produced large numbers of baryons, photons, and neutrinos. These extreme conditions may have also produced other long-lived species, including new light particles (such as axions or sterile neutrinos) or gravitational waves. The gravitational effects of any such light relics can be observed through their unique imprint in the cosmic microwave background (CMB), the large-scale structure, and the primordial light element abundances, and are important in determining the initial conditions of the universe. We argue that future cosmological observations, in particular improved maps of the CMB on small angular scales, can be orders of magnitude more sensitive for probing the thermal history of the early universe than current experiments. These observations offer a unique and broad discovery space for new physics in the dark sector and beyond, even when its effects would not be visible in terrestrial experiments or in astrophysical environments. A detection of an excess light relic abundance would be a clear indication of new physics and would provide the first direct information about the universe between the times of reheating and neutrino decoupling one second later.

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arXiv2019

Dark Matter Science in the Era of LSST

Astrophysical observations currently provide the only robust, empirical measurements of dark matter. In the coming decade, astrophysical observations will guide other experimental efforts, while simultaneously probing unique regions of dark matter parameter space. This white paper summarizes astrophysical observations that can constrain the fundamental physics of dark matter in the era of LSST. We describe how astrophysical observations will inform our understanding of the fundamental properties of dark matter, such as particle mass, self-interaction strength, non-gravitational interactions with the Standard Model, and compact object abundances. Additionally, we highlight theoretical work and experimental/observational facilities that will complement LSST to strengthen our understanding of the fundamental characteristics of dark matter.

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arXiv2019

Enhancing BOSS bispectrum cosmological constraints with maximal compression

We apply two compression methods to the galaxy power spectrum monopole/quadrupole and bispectrum monopole measurements from the BOSS DR12 CMASS sample. Both methods reduce the dimension of the original data-vector to the number of cosmological parameters considered, using the Karhunen-Loève algorithm with an analytic covariance model. In the first case, we infer the posterior through MCMC sampling from the likelihood of the compressed data-vector (MC-KL). The second, faster option, works by first Gaussianising and then orthogonalising the parameter space before the compression; in this option (G-PCA) we only need to run a low-resolution preliminary MCMC sample for the Gaussianization to compute our posterior. Both compression methods accurately reproduce the posterior distributions obtained by standard MCMC sampling on the CMASS dataset for a $k$-space range of $0.03-0.12\,h/\mathrm{Mpc}$. The compression enables us to increase the number of bispectrum measurements by a factor of $\sim 23$ over the standard binning (from 116 to 2734 triangles used), which is otherwise limited by the number of mock catalogues available. This reduces the $68\%$ credible intervals for the parameters $\left(b_1,b_2,f,σ_8\right)$ by $\left(-24.8\%,-52.8\%,-26.4\%,-21\%\right)$, respectively. The best-fit values we obtain are $(b_1=2.31\pm0.17,b_2=0.77\pm0.19,$ $f(z_{\mathrm{CMASS}})=0.67\pm0.06,σ_8(z_{\mathrm{CMASS}})=0.51\pm0.03)$. Using these methods for future redshift surveys like DESI, Euclid and PFS will drastically reduce the number of simulations needed to compute accurate covariance matrices and will facilitate tighter constraints on cosmological parameters.

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arXiv2019

Geometrical compression: a new method to enhance the BOSS galaxy bispectrum monopole constraints

We present a novel method to compress galaxy clustering three-point statistics and apply it to redshift space galaxy bispectrum monopole measurements from BOSS DR12 CMASS data considering a $k$-space range of $0.03-0.12\,h/\mathrm{Mpc}$. The method consists in binning together bispectra evaluated at sets of wave-numbers forming closed triangles with similar geometrical properties: the area, the cosine of the largest angle and the ratio between the cosines of the remaining two angles. This enables us to increase the number of bispectrum measurements for example by a factor of $23$ over the standard binning (from 116 to 2734 triangles used), which is otherwise limited by the number of mock catalogues available to estimate the covariance matrix needed to derive parameter constraints. The $68\%$ credible intervals for the inferred parameters $\left(b_1,b_2,f,σ_8\right)$ are thus reduced by $\left(-39\%,-49\%,-29\%,-22\%\right)$, respectively. We find very good agreement with the posteriors recently obtained by alternative maximal compression methods. This new method does not require the a-priori computation of the data-vector covariance matrix and has the potential to be directly applicable to other three-point statistics (e.g. glaxy clustering, weak gravitational lensing, 21 cm emission line) measured from future surveys such as DESI, Euclid, PFS and SKA.

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arXiv2018

DES Science Portal: Computing Photometric Redshifts

A significant challenge facing photometric surveys for cosmological purposes is the need to produce reliable redshift estimates. The estimation of photometric redshifts (photo-zs) has been consolidated as the standard strategy to bypass the high production costs and incompleteness of spectroscopic redshift samples. Training-based photo-z methods require the preparation of a high-quality list of spectroscopic redshifts, which needs to be constantly updated. The photo-z training, validation, and estimation must be performed in a consistent and reproducible way in order to accomplish the scientific requirements. To meet this purpose, we developed an integrated web-based data interface that not only provides the framework to carry out the above steps in a systematic way, enabling the ease testing and comparison of different algorithms, but also addresses the processing requirements by parallelizing the calculation in a transparent way for the user. This framework called the Science Portal (hereafter Portal) was developed in the context the Dark Energy Survey (DES) to facilitate scientific analysis. In this paper, we show how the Portal can provide a reliable environment to access vast data sets, provide validation algorithms and metrics, even in the case of multiple photo-zs methods. It is possible to maintain the provenance between the steps of a chain of workflows while ensuring reproducibility of the results. We illustrate how the Portal can be used to provide photo-z estimates using the DES first year (Y1A1) data. While the DES collaboration is still developing techniques to obtain more precise photo-zs, having a structured framework like the one presented here is critical for the systematic vetting of DES algorithmic improvements and the consistent production of photo-zs in the future DES releases.

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arXiv2018

DES Science Portal: Creating Science-Ready Catalogs

We present a novel approach for creating science-ready catalogs through a software infrastructure developed for the Dark Energy Survey (DES). We integrate the data products released by the DES Data Management and additional products created by the DES collaboration in an environment known as DES Science Portal. Each step involved in the creation of a science-ready catalog is recorded in a relational database and can be recovered at any time. We describe how the DES Science Portal automates the creation and characterization of lightweight catalogs for DES Year 1 Annual Release, and show its flexibility in creating multiple catalogs with different inputs and configurations. Finally, we discuss the advantages of this infrastructure for large surveys such as DES and the Large Synoptic Survey Telescope. The capability of creating science-ready catalogs efficiently and with full control of the inputs and configurations used is an important asset for supporting science analysis using data from large astronomical surveys.

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arXiv2018

Morpho-z: improving photometric redshifts with galaxy morphology

We conduct a comprehensive study of the effects of incorporating galaxy morphology information in photometric redshift estimation. Using machine learning methods, we assess the changes in the scatter and catastrophic outlier fraction of photometric redshifts when galaxy size, ellipticity, Sérsic index and surface brightness are included in training on galaxy samples from the SDSS and the CFHT Stripe-82 Survey (CS82). We show that by adding galaxy morphological parameters to full $ugriz$ photometry, only mild improvements are obtained, while the gains are substantial in cases where fewer passbands are available. For instance, the combination of $grz$ photometry and morphological parameters almost fully recovers the metrics of $5$-band photometric redshifts. We demonstrate that with morphology it is possible to determine useful redshift distribution $N(z)$ of galaxy samples without any colour information. We also find that the inclusion of quasar redshifts and associated object sizes in training improves the quality of photometric redshift catalogues, compensating for the lack of a good star-galaxy separator. We further show that morphological information can mitigate biases and scatter due to bad photometry. As an application, we derive both point estimates and posterior distributions of redshifts for the official CS82 catalogue, training on morphology and SDSS Stripe-82 $ugriz$ bands when available. Our redshifts yield a 68th percentile error of $0.058(1+z)$, and a catastrophic outlier fraction of $5.2$ per cent. We further include a deep extension trained on morphology and single $i$-band CS82 photometry.

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arXiv2018

Maximal compression of the redshift space galaxy power spectrum and bispectrum

We explore two methods of compressing the redshift space galaxy power spectrum and bispectrum with respect to a chosen set of cosmological parameters. Both methods involve reducing the dimension of the original data-vector ( e.g. 1000 elements ) to the number of cosmological parameters considered ( e.g. seven ) using the Karhunen-Loève algorithm. In the first case, we run MCMC sampling on the compressed data-vector in order to recover the one-dimensional (1D) and two-dimensional (2D) posterior distributions. The second option, approximately 2000 times faster, works by orthogonalising the parameter space through diagonalisation of the Fisher information matrix before the compression, obtaining the posterior distributions without the need of MCMC sampling. Using these methods for future spectroscopic redshift surveys like DESI, EUCLID and PFS would drastically reduce the number of simulations needed to compute accurate covariance matrices with minimal loss of constraining power. We consider a redshift bin of a DESI-like experiment. Using the power spectrum combined with the bispectrum as a data-vector, both compression methods on average recover the 68% credible regions to within 0.7% and 2% of those resulting from standard MCMC sampling respectively. These confidence intervals are also smaller than the ones obtained using only the power spectrum by (81%, 80%, 82%) respectively for the bias parameter b_1, the growth rate f and the scalar amplitude parameter A_s.

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arXiv2017

Estimating the Mass of the Local Group using Machine Learning Applied to Numerical Simulations

We revisit the estimation of the combined mass of the Milky Way and Andromeda (M31), which dominate the mass of the Local Group. We make use of an ensemble of 30,190 halo pairs from the Small MultiDark simulation, assuming a $Λ$CDM (Cosmological Constant with Cold Dark Matter) cosmology, to investigate the relationship between the bound mass and parameters characterising the orbit of the binary and their local environment with the aid of machine learning methods (artificial neural networks, ANN). Results from the ANN are most successful when information about the velocity shear is provided, which demonstrates the flexibility of machine learning to model physical phenomena and readily incorporate new information as it becomes available. The resulting estimate for the Local Group mass, when shear information is included, is $4.9 \times 10^{12} M_\odot$, with an error of $\pm0.8 \times 10^{12} M_\odot$ from the 68% uncertainty in observables, and a 68% confidence interval of $^{+1.3}_{-1.4} \times 10^{12}M_\odot$ from the intrinsic scatter from the differences between the model and simulation masses. We also consider a recently reported large transverse velocity of M31 relative to the Milky Way, and produce an alternative mass estimate of $3.6\pm0.3\pm1.4 \times 10^{12}M_\odot$. Although different methods predict similar values for the most likely mass of the LG, application of ANN compared to the Timing Argument reduces the scatter in the log mass by over half when tested on samples from the simulation.

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arXiv2017

The cosmic microwave background Cold Spot anomaly: the impact of sky masking and the expected contribution from the Integrated Sachs-Wolfe effect

We re-analyse the cosmic microwave background (CMB) Cold Spot (CS) anomaly with particular focus on understanding the bias a mask (contaminated by Galactic and point sources) may introduce. We measure the coldest spot, found by applying the Spherical Mexican Hat Wavelet transform on 100 000 cut-sky (masked) and full-sky CMB simulated maps. The CS itself is barely affected by the mask; we estimate a 94 per cent probability that the CS is the full-sky temperature minimum. However, approximately 48 per cent (masked fraction of the mask) of full-sky minima are obscured by the mask. Since the observed minima are slightly hotter than the full-sky ensemble of minima, a cut-sky analysis would have found the CS to be significant at approximately 2.2 sigma with a wavelet angular scale of R = 5 degrees. None the less, comparisons to full-sky minima show the CS significance to be only approximately 1.9 sigma and less than 2 sigma for all R. The CS on the last scattering surface may be hotter due to the integrated Sachs-Wolfe effect in the line of sight. However, our simulations show that this on average only approximately 10 per cent (about 10 micro K but consistent with zero) of the CS temperature profile. This is consistent with Lambda and cold dark matter reconstructions of this effect based on observed line-of-sight voids.

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arXiv2017

Science-Driven Optimization of the LSST Observing Strategy

The Large Synoptic Survey Telescope is designed to provide an unprecedented optical imaging dataset that will support investigations of our Solar System, Galaxy and Universe, across half the sky and over ten years of repeated observation. However, exactly how the LSST observations will be taken (the observing strategy or "cadence") is not yet finalized. In this dynamically-evolving community white paper, we explore how the detailed performance of the anticipated science investigations is expected to depend on small changes to the LSST observing strategy. Using realistic simulations of the LSST schedule and observation properties, we design and compute diagnostic metrics and Figures of Merit that provide quantitative evaluations of different observing strategies, analyzing their impact on a wide range of proposed science projects. This is work in progress: we are using this white paper to communicate to each other the relative merits of the observing strategy choices that could be made, in an effort to maximize the scientific value of the survey. The investigation of some science cases leads to suggestions for new strategies that could be simulated and potentially adopted. Notably, we find motivation for exploring departures from a spatially uniform annual tiling of the sky: focusing instead on different parts of the survey area in different years in a "rolling cadence" is likely to have significant benefits for a number of time domain and moving object astronomy projects. The communal assembly of a suite of quantified and homogeneously coded metrics is the vital first step towards an automated, systematic, science-based assessment of any given cadence simulation, that will enable the scheduling of the LSST to be as well-informed as possible.

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arXiv2017

Core or cusps: The central dark matter profile of a redshift one strong lensing cluster with a bright central image

We report on SPT-CLJ2011-5228, a giant system of arcs created by a cluster at $z=1.06$. The arc system is notable for the presence of a bright central image. The source is a Lyman Break galaxy at $z_s=2.39$ and the mass enclosed within the 14 arc second radius Einstein ring is $10^{14.2}$ solar masses. We perform a full light profile reconstruction of the lensed images to precisely infer the parameters of the mass distribution. The brightness of the central image demands that the central total density profile of the lens be shallow. By fitting the dark matter as a generalized Navarro-Frenk-White profile---with a free parameter for the inner density slope---we find that the break radius is $270^{+48}_{-76}$ kpc, and that the inner density falls with radius to the power $-0.38\pm0.04$ at 68 percent confidence. Such a shallow profile is in strong tension with our understanding of relaxed cold dark matter halos; dark matter only simulations predict the inner density should fall as $r^{-1}$. The tension can be alleviated if this cluster is in fact a merger; a two halo model can also reconstruct the data, with both clumps (density going as $r^{-0.8}$ and $r^{-1.0}$) much more consistent with predictions from dark matter only simulations. At the resolution of our Dark Energy Survey imaging, we are unable to choose between these two models, but we make predictions for forthcoming Hubble Space Telescope imaging that will decisively distinguish between them.

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