The VIMOS Ultra Deep Survey. Luminosity and stellar mass dependence of galaxy clustering at z~3

We present the study of the dependence of galaxy clustering on luminosity and stellar mass in the redshift range 2$<$z$<$3.5 using 3236 galaxies with robust spectroscopic redshifts from the VIMOS Ultra Deep Survey (VUDS). We measure the two-point real-space correlation function $w_p(r_p)$ for four volume-limited stellar mass and four luminosity, M$_{UV}$ absolute magnitude selected, sub-samples. We find that the scale dependent clustering amplitude $r_0$ significantly increases with increasing luminosity and stellar mass indicating a strong galaxy clustering dependence on these properties. This corresponds to a strong relative bias between these two sub-samples of $\Delta$b/b$^*$=0.43. Fitting a 5-parameter HOD model we find that the most luminous and massive galaxies occupy the most massive dark matter haloes with $\langle$M$_h$$\rangle$ = 10$^{12.30}$ h$^{-1}$ M$_{\odot}$. Similar to the trends observed at lower redshift, the minimum halo mass M$_{min}$ depends on the luminosity and stellar mass of galaxies and grows from M$_{min}$ =10$^{9.73}$ h$^{-1}$M$_{\odot}$ to M$_{min}$=10$^{11.58}$ h$^{-1}$M$_{\odot}$ from the faintest to the brightest among our galaxy sample, respectively. We find the difference between these halo masses to be much more pronounced than is observed for local galaxies of similar properties. Moreover, at z~3, we observe that the masses at which a halo hosts, on average, one satellite and one central galaxy is M$_1$$\approx$4M$_{min}$ over all luminosity ranges, significantly lower than observed at z~0 indicating that the halo satellite occupation increases with redshift. The luminosity and stellar mass dependence is also reflected in the measurements of the large scale galaxy bias, which we model as b$_{g,HOD}$($>$L)=1.92+25.36(L/L$^*$)$^{7.01}$. We conclude our study with measurements of the stellar-to-halo mass ratio (SHMR).Comment: 20 pages, 11 figures, A&A in press, v2. revised discussion in sec. 5.5, changed Fig. 4 and Fig. 11, added reference

Observational Evidence for the Co-evolution of Galaxy Mergers, Quasars, and the Blue/Red Galaxy Transition

We compile a number of observations to estimate the time-averaged rate of formation or buildup of red sequence galaxies, as a function of mass and redshift. Comparing this with the mass functions of mergers and quasar hosts, and independently comparing their clustering properties as a function of redshift, we find that these populations trace the same mass distribution, with similar evolution, at redshifts 0<z<~1.5. Knowing one of the quasar, merger, or elliptical mass/luminosity functions, it is possible to predict the others. Allowing for greater model dependence, we compare the rate of early-type buildup with the implied merger and quasar triggering rates as a function of mass and redshift and find agreement. Over this redshift range, observed merger fractions can account for the entire bright quasar luminosity function and buildup of the red sequence at all but the highest masses at low redshift (>~10^11 M_solar at z<~0.3) where 'dry' mergers appear to dominate. This supports a necessary prediction of theories where mergers between gas-rich galaxies produce ellipticals with an associated phase of quasar activity, after which the remnant becomes red. These populations trace a similar characteristic transition mass, possibly reflecting the mass above which the elliptical population is mostly (>~50%) assembled at a given redshift, which increases with redshift over the observed range in a manner consistent with suggestions that cosmic downsizing may apply to red galaxy assembly as well as star formation. These mass distributions as a function of redshift do not uniformly trace the all/red/blue galaxy population, ruling out models in which quasar activity is generically associated with star formation or is long lived in 'old' systems.Comment: 24 pages, 17 figures. Accepted to ApJ. Substantially revised and expanded to match published versio

Automatic Subthalamic Nucleus Targeting for Deep Brain Stimulation. A Validation Study

In functional stereotactic neurosurgery, one of the cornerstones upon which the success and the operating time depends is an accurate targeting. The subthalamic nucleus (STN) is the usual target involved when applying Deep Brain Stimulation (DBS) for the Parkinsons disease (PD). Unfortunately, STN is usually not clearly visible in common medical imaging modalities, which justifies the use of atlas-based segmentation techniques to infer the STN location. We propose a scheme that allows both, to perform a comparison between different non-rigid atlas registration algorithms and to evaluate their usability to locate the STN automatically. Using our validation evaluation scheme and accurate registration algorithms we demonstrate that automatic STN localization is possible and accurate

feature-segmentation-based registration for fast and accurate deep brain stimulation targeting

Objects Deep brain stimulation (DBS) has turned out to be the surgical technique of choice for the treatment of movement disorders, e.g. Parkinsons disease (PD), the usual target being the subthalamic nucleus (STN). The targeting of such a small structure is crucial for the outcome of the surgery. Unfortunately the STN is in general not easily distinguishable in common medical images. Material and Methods Eight bilaterally implanted PD patients were considered (16 STNs). A three-dimensional MR T1-weighted sequence and inversion recovery T2-weighted coronal slices were acquired pre-operatively. We study the influence on the STN location of several surrounding structures through a proposed methodology for the construction of a ground truth and an original validation scheme that allows evaluating performances of different targeting methods. Results The inter-expert variability in identifying the STN location is 1.61 ± 0.29 mm and 1.40 ± 0.38 mm for expert 1 and 2 respectively while the best choice of features using segmentation-based registration gives an error of 1.55 ± 0.73 mm. Conclusions By registering a binary mask of the third and lateral ventricles of the patient with its corresponding binary mask of the atlas we obtain a fast, automatic and accurate pre-operative targeting comparable to the experts variability

Validation of Experts Versus Atlas-Based and Automatic Registration Methods for Subthalamic Nucleus Targeting on MRI

Objects. In functional stereotactic neurosurgery, one of the cornerstones upon which the success and the operating time depends is an accurate targeting. The subthalamic nucleus (STN) is the usual target involved when applying Deep Brain Stimulation (DBS) for Parkinson's disease (PD). Unfortunately, STN is usually not clearly visible in common medical imaging modalities, which justifies the use of atlas-based segmentation techniques to infer the STN location. Materials and Methods. 8 bilaterally implanted PD patients were included in this study. A three-dimensional T1-weighted sequence and inversion recovery T2-weighted coronal slices were acquired pre-operatively. We propose a methodology for the construction of a ground truth of the STN location and a scheme that allows both, to perform a comparison between different non-rigid registration algorithms and to evaluate their usability to locate the STN automatically. Results. The intra-expert variability in identifying the STN location is 1.06 ± 0.61 mm while the best non-rigid registration method gives an error of 1.80 ± 0.62 mm. On the other hand, statistical tests show that an affine registration with only 12 degrees-of-freedom is not enough for this application. Conclusions. Using our validation-evaluation scheme we demonstrate that automatic STN localization is possible and accurate with non-rigid registration algorithms

Studying the evolution of large-scale structure with the VIMOS-VLT Deep Survey

The VIMOS-VLT Deep Survey (VVDS) currently offers a unique combination of depth, angular size and number of measured galaxies among surveys of the distant Universe: ~ 11,000 spectra over 0.5 deg2 to I_{AB}=24 (VVDS-Deep), 35,000 spectra over ~ 7 deg2 to I_{AB}=22.5 (VVDS-Wide). The current ``First Epoch'' data from VVDS-Deep already allow investigations of galaxy clustering and its dependence on galaxy properties to be extended to redshifts ~1.2-1.5, in addition to measuring accurately evolution in the properties of galaxies up to z~4. This paper concentrates on the main results obtained so far on galaxy clustering. Overall, L* galaxies at z~ 1.5 show a correlation length r_0=3.6\pm 0.7. As a consequence, the linear galaxy bias at fixed luminosity rises over the same range from the value b~1 measured locally, to b=1.5 +/- 0.1. The interplay of galaxy and structure evolution in producing this observation is discussed in some detail. Galaxy clustering is found to depend on galaxy luminosity also at z~ 1, but luminous galaxies at this redshift show a significantly steeper small-scale correlation function than their z=0 counterparts. Finally, red galaxies remain more clustered than blue galaxies out to similar redshifts, with a nearly constant relative bias among the two classes, b_{rel}~1.4, despite the rather dramatic evolution of the color-density relation over the same redshift range.Comment: 14 pages. Extended, combined version of two invited review papers presented at: 1) XXVIth Astrophysics Moriond Meeting: "From Dark Halos to Light", March 2006, proc. edited by L.Tresse, S. Maurogordato and J. Tran Thanh Van (Editions Frontieres); 2) Vulcano Workshop 2006 "Frontier Objects in Astrophysics and Particle Physics", May 2006, proc. edited by F. Giovannelli & G. Mannocchi, Italian Physical Society (Editrice Compositori, Bologna

Atlas-Based Segmentation of Pathological Brain MR Images

We propose a method for brain atlas deformation in presence of large space-occupying tumors, based on an a priori model of lesion growth that assumes radial expansion of the lesion from its starting point. First, an affine registration brings the atlas and the patient into global correspondence. Then, the seeding of a synthetic tumor into the brain atlas provides a template for the lesion. Finally, the seeded atlas is deformed, combining a method derived from optical flow principles and a model of lesion growth (MLG). Results show that the method can be applied to the automatic segmentation of structures and substructures in brains with gross deformation, with important medical applications in neurosurgery, radiosurgery and radiotherapy

The VIMOS Public Extragalactic Redshift Survey (VIPERS). Never mind the gaps: comparing techniques to restore homogeneous sky coverage

[Abridged] Non-uniform sampling and gaps in sky coverage are common in galaxy redshift surveys, but these effects can degrade galaxy counts-in-cells and density estimates. We carry out a comparison of methods that aim to fill the gaps to correct for the systematic effects. Our study is motivated by the analysis of the VIMOS Extragalactic Redshift Survey (VIPERS), a flux-limited survey (i<22.5) based on one-pass observations with VIMOS, with gaps covering 25% of the surveyed area and a mean sampling rate of 35%. Our findings are applicable to other surveys with similar observing strategies. We compare 1) two algorithms based on photometric redshift, that assign redshifts to galaxies based on the spectroscopic redshifts of the nearest neighbours, 2) two Bayesian methods, the Wiener filter and the Poisson-Lognormal filter. Using galaxy mock catalogues we quantify the accuracy of the counts-in-cells measurements on scales of R=5 and 8 Mpc/h after applying each of these methods. We also study how they perform to account for spectroscopic redshift error and inhomogeneous and sparse sampling rate. We find that in VIPERS the errors in counts-in-cells measurements on R<10 Mpc/h scales are dominated by the sparseness of the sample. All methods underpredict by 20-35% the counts at high densities. This systematic bias is of the same order as random errors. No method outperforms the others. Random and systematic errors decrease for larger cells. We show that it is possible to separate the lowest and highest densities on scales of 5 Mpc/h at redshifts 0.5<z<1.1, over a large volume such as in VIPERS survey. This is vital for the characterisation of cosmic variance and rare populations (e.g, brightest galaxies) in environmental studies at these redshifts.Comment: 17 pages, 13 figures, accepted for publication in A&A (revised version after minor revision and language editing