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This work presents the first comprehensive study of structure formation at the peak epoch of cosmic star formation over $1.4\leq z \leq 3.6$ in the COSMOS field, including the most massive high redshift galaxy proto-clusters at that era. We apply the extended COSMIC BIRTH algorithm to account for a multi-tracer and multi-survey Bayesian analysis at Lagrangian initial cosmic times. Combining the data of five different spectroscopic redshift surveys (zCOSMOS-deep, VUDS, MOSDEF, ZFIRE, and FMOS-COSMOS), we show that the corresponding unbiased primordial density fields can be inferred, if a proper survey completeness computation from the parent photometric catalogs, and a precise treatment of the non-linear and non-local evolution on the light-cone is taken into account, including (i) gravitational matter displacements, (ii) peculiar velocities, and (iii) galaxy bias. The reconstructions reveal a holistic view on the known proto-clusters in the COSMOS field and the growth of the cosmic web towards lower redshifts. The inferred distant dark matter density fields concurrently with other probes like tomographic reconstructions of the intergalactic medium will explore the interplay of gas and dark matter and are ideally suited to study structure formation at high redshifts in the light of upcoming deep surveys., Comment: 20 pages, 15 figures, accepted by MNRAS

We investigate higher order symplectic integration strategies within Bayesian cosmic density field reconstruction methods. In particular, we study the fourth-order discretisation of Hamiltonian equations of motion (EoM). This is achieved by recursively applying the basic second-order leap-frog scheme (considering the single evaluation of the EoM) in a combination of even numbers of forward time integration steps with a single intermediate backward step. This largely reduces the number of evaluations and random gradient computations, as required in the usual second-order case for high-dimensional cases. We restrict this study to the lognormal-Poisson model, applied to a full volume halo catalogue in real space on a cubical mesh of 1250 $h^{-1}$ Mpc side and 256$^3$ cells. Hence, we neglect selection effects, redshift space distortions, and displacements. We note that those observational and cosmic evolution effects can be accounted for in subsequent Gibbs-sampling steps within the COSMIC BIRTH algorithm. We find that going from the usual second to fourth-order in the leap-frog scheme shortens the burn-in phase by a factor of at least $\sim30$. This implies that 75-90 independent samples are obtained while the fastest second-order method converges. After convergence, the correlation lengths indicate an improvement factor of about 3.0 fewer gradient computations for meshes of 256$^3$ cells. In the considered cosmological scenario, the traditional leap-frog scheme turns out to outperform higher order integration schemes only at lower dimensional problems, e.g. meshes with 64$^3$ cells. This gain in computational efficiency can help to go towards a full Bayesian analysis of the cosmological large-scale structure for upcoming galaxy surveys., Comment: 19 pages, 12 figures, 4 tables, accepted at MNRAS, additional robust mathematical argument supported by numerical tests with longer HMC chains and a solid statistical analysis

We present COSMIC BIRTH: COSMological Initial Conditions from Bayesian Inference Reconstructions with THeoretical models: an algorithm to reconstruct the primordial and evolved cosmic density fields from galaxy surveys on the light-cone. The displacement and peculiar velocity fields are obtained from forward modelling at different redshift snapshots given some initial cosmic density field within a Gibbs-sampling scheme. This allows us to map galaxies, observed in a light-cone, to a single high redshift and hereby provide tracers and the corresponding survey completeness in Lagrangian space including phase-space mapping. These Lagrangian tracers in turn permit us to efficiently obtain the primordial density field, making the COSMIC BIRTH code general to any structure formation model. Our tests are restricted for the time being to Augmented Lagrangian Perturbation theory. We show how to robustly compute the non-linear Lagrangian bias from clustering measurements in a numerical way, enabling us to get unbiased dark matter field reconstructions at initial cosmic times. We also show that we can greatly recover the information of the dark matter field from the galaxy distribution based on a detailed simulation. Novel key ingredients to this approach are a higher-order Hamiltonian sampling technique and a non-diagonal Hamiltonian mass-matrix. This technique could be used to study the Eulerian galaxy bias from galaxy surveys and could become an ideal baryon acoustic reconstruction technique. In summary, this method represents a general reconstruction technique, including in a self-consistent way a survey mask, non-linear and non-local bias and redshift space distortions, with an efficiency about 10 times superior to previous comparable methods., Comment: 21 pages, 14 figs (accepted at MNRAS)

The FastCam instrument platform, jointly developed by the IAC and the UPCT, allows, in real-time, acquisition, selection and storage of images with a resolution that reaches the diffraction limit of medium-sized telescopes. FastCam incorporates a specially designed software package to analyse series of tens of thousands of images in parallel with the data acquisition at the telescope. Wide FastCam is a new instrument that, using the same software for data acquisition, does not look for lucky imaging but fast observations in a much larger field of view. Here we describe the commissioning process and first observations with Wide FastCam at the Telescopio Carlos S\'anchez (TCS) in the Observatorio del Teide., Comment: 7 pages, 8 figures, Proc. SPIE. 9908, Ground-based and Airborne Instrumentation for Astronomy VI, 99082O. (August 09, 2016)