Cosmic Dawn fellow at NBI/University of Copenhagen
Lyngbyvej 2, 2100 København
+45 60 90 29 22
also associated to INAF Astronomical Observatory of Bologna
Hi! First of all I must clarify that my name contains a couple of misspellings (something went wrong during the registry for my birth record...). It should be read 'Yari Davidsohn' (a mix of Hebrew and German).
Anyway, I'm now working at the brand-new Cosmic Dawn Center, which is part of the Niels Bohr Institute in Copenhagen. One of my main goals is to investigate high-z galaxy growth and mechanisms halting star formation in the first, massive galaxies. I leverage state-of-the-art data sets and rely on innovative machine learning techniques (without falling for the ML hype).
As a full member of the COSMOS team I am involved in many other complementary projects, especially with my colleagues at Caltech where I spent two wonderful years. Recently I also started to be more active in the Euclid Consortium.
Sometimes I try to take a day off to further exploit the VIPERS data I used in the early stage of my career... but invariably I use such a spare time to go biking or read on the couch...
The past decade has seen significant advances in the study of galaxy
evolution prompted by large astronomical surveys. They have been
devised to conduct a census of star-forming and quiescent galaxies at
different redshifts, by sampling wide portions of the sky and going
deeper and deeper to span very large intervals of cosmic time.
My work is based on such large surveys, which collect large amounts of data
thus facilitating statistical studies. The large volumes probed allow me
to study rare massive galaxies, in particular those mechanisms that halted their star formation.
Moreover, such observatoinal statistics are pivotal to calibrate and/or test models of galaxy formation.
Some of the scientific questions that lead my work are: What are the processes responsible for baryonic/stellar mass accretion in the early universe?
Are there passive galxies at z>4, and how did they stop forming stars?
What is the role played by active galactic nuclei?
On the technical side, I spend efforts to optimise IR photometric source extraction and SED fitting, along with complementary manifold learning techniques, to correctly identify high-z galaxies and their physical properties, recovering also the surrounding large-scale environment. I am also intrigued by new ways for (statistical) comparison between observations and simulations, instead of using luminosity/stellar mass functions and similar standard metrics.
In this work we use the mock galaxy catalog presented in Laigle, Davidzon, et al. (2019), which mimics the properties of the COSMOS survey up to z=4, to show how to compress the complex, high-dimensional data structure of a simulation into a 2D grid, which greatly facilitates the analysis of how galaxy observables are connected to intrinsic properties. The algorithm we adopted is the self organizing map (SOM, see figure below for a didactical representation), which we demonstrated is able to connect observed 0.3-5 μm broad-band colours of galaxies to their physical properties (not only redhsift but also stellar mass and SFR). In comparison to state-of-the-art techniques based on synthetic templates, our method is comparable in performance but less biased at estimating redshifts, and significantly better at predicting SFRs. In particular, our `data-driven' approach, in contrast to model libraries, intrinsically allows for the complexity of galaxy formation and can handle sample biases. We advocate that observations to calibrate this method should be one of the goals of next-generation galaxy surveys.
We trace the specific star formation rate (sSFR) of massive star-forming galaxies from z~2 to 7. Our method is substantially different from previous analyses, as it does not rely on direct estimates of star formation rate, but on the differential evolution of the galaxy stellar mass function (SMF). We show the reliability of this approach by means of semi-analytical and hydrodynamical cosmological simulations. We then apply it to real data, using the SMFs derived in the COSMOS and CANDELS fields (respectively, red circles and squares in the figure below). We find that the sSFR is proportional to (1+z)1.1±0.2 at z>2, in tension with the steeper evolution predicted by simulations between z=2 and 4. We investigate the impact of several sources of observational bias, which however cannot account for this discrepancy. At z>5 our results are affected by large uncertainties, but we show that future large-area surveys will substantially reduce them, making our method an effective tool to probe the massive end of the main sequence of star-forming galaxies.
We obtain a view over 13 billion years of stellar mass assmebly in 10 snapshots, by deriving the stellar mass function and cosmic stellar mass density of galaxies in the COSMOS field up to z~6 (see figure below). We rely on the photometry included in the COSMOS2015 catalogue, but we provide a new estimate of photometric redhisfts at z>2.5 with an improved version of the code LePhare.
Our work provides a comprehensive view of galaxy stellar mass assembly between $z=0.1$ and 6, for the first time using consistent estimates across the entire redshift range. We select a mass-complete sample (>1010.2 ℳ⊙) of quiescent galaxy candidates at 3<z<4.
We investigate the link between stellar and dark matter by matching the GSMF with the mass function of their hosting haloes. Assuming a Schechter funtion profile, we find that the major limitation in this kind of studies is that the slope of the fit depends on the characterisation of the observational uncertainties, which is crucial to properly remove the Eddington bias. There is currently no consensus on the method to quantify such errors: even using state-of-the-art datasets, different recipes for error deconvolution result in different best-fit Schechter parameters.
I am part of the core team realising the COSMOS2015 catalog, which contains precise photometric redshifts (see plot) and stellar masses for more than half a million objects over the 2 sq deg of the COSMOS field. Including new YJHKs images from the UltraVISTA-DR2 survey, Y-band images from Subaru/HyperSuprime-Cam, and infrared data from the Spitzer Large Area Survey with the Hyper-Suprime-Cam Spitzer legacy program, this near-infrared-selected catalog is highly optimized for the study of galaxy evolution and environments in the early universe. The COSMOS2015 catalogue is available on the ESO website
We investigate environmental effects in the evolution of galaxies between z = 0.5 and 0.9, relying on the galaxy local density field measured in Cucciati, Davidzon, et al. (2017). Several studies have already derived the GSMF as a function of different galaxy environments (e.g., clusters vs field) but this is the first one in which their number denisty is correctly normalised (from a 3-D Voronoi decomposition of the probed volume). This allows us to compare not only the GSMF shape, but also their growth as a function of redshift (see plot).
We find that the evolution of low-density regions is described well by the formalism introduced by Peng et al. (2010, ApJ, 721, 193), and is consistent with the idea that galaxies become progressively passive because of internal physical processes. This mass quenching is not sufficient to describe the evolution of the mass function in the high-density regions: a significant contribution from dry mergers is required.
We use the final data of the VIMOS Public Extragalactic Redshift Survey (VIPERS) to investigate the effect of environment on the evolution of galaxies between z = 0.5 and 0.9. We use about 75,000 accurate spectroscopic redshift over an area of 23.5 sq deg. We also consider the photometric redshifts (and their probability distribution function) of the total sample of photometric galaxies with i<22.5 mag. We characterise local environment in terms of the density contrast (δ) smoothed over a cylindrical kernel, the scale of which is defined by the distance to the 5th nearest neighbour (see plot). We investigate the dependence of active and passive galaxy fractions as a function of δ. Comparing to the semi-analytical model of De Lucia & Blaizot we emphasize the discrepancies in the overdensities, a general result pointing out the improvments still needed in simulations to correctly describe environmental quenching mechanisms.
We measure the evolution of the GSMF from z = 1.3 to z = 0.5 using the
first public data
release of VIPERS.
Thanks to the large volume and depth of the survey,
Poisson noise and cosmic variance of our GSMF estimates are
comparable to the statistical uncertainties of large
surveys in the local universe.
We determine with unprecedented accuracy the high-mass
tail of the galaxy stellar mass function, which includes a significant
number of galaxies that are too rare to detect with any of the past
spectroscopic surveys. We are able
to separately trace the evolution of the number
density of blue and red galaxies with masses above 1011.4 ℳ⊙,
in a mass
range barely studied in previous work (see the plot below). We detect a
population of similarly massive blue galaxies, which are no longer
detectable below z = 0.7. These results give initial promising
indications of mass-dependent quenching of galaxies at z ≃ 1.