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Using the CoDa II simulation, we study the Lyαtransmissivity of the intergalactic medium (IGM) during reionization. Atz> 6, a typical galaxy without an active galactic nucleus fails to form a proximity zone around itself due to the overdensity of the surrounding IGM. The gravitational infall motion in the IGM makes the resonance absorption extend to the red side of Lyα, suppressing the transmission up to roughly the circular velocity of the galaxy. In some sight lines, an optically thin blob generated by a supernova in a neighboring galaxy results in a peak feature, which can be mistaken for a blue peak. Redward of the resonance absorption, the damping-wing opacity correlates with the global IGM neutral fraction and the UV magnitude of the source galaxy. Brighter galaxies tend to suffer lower opacity because they tend to reside in larger Hiiregions, and the surrounding IGM transmits redder photons, which are less susceptible to attenuation, owing to stronger infall velocity. The Hiiregions are highly nonspherical, causing both sight-line-to-sight-line and galaxy-to-galaxy variation in opacity. Also, self-shielded systems within Hiiregions strongly attenuate the emission for certain sight lines. All these factors add to the transmissivity variation, requiring a large sample size to constrain the average transmission. The variation is largest for fainter galaxies at higher redshift. The 68% range of the transmissivity is similar to or greater than the median for galaxies withM_UV≥ −21 atz≥ 7, implying that more than a hundred galaxies would be needed to measure the transmission to 10% accuracy.

 

Cosmic reionization was driven by the imbalance between early sources and sinks of ionizing radiation, both of which were dominated by small-scale structure and are thus usually treated in cosmological reionization simulations by subgrid modelling. The recombination rate of intergalactic hydrogen is customarily boosted by a subgrid clumping factor, 〈n2〉/〈n〉2, which corrects for unresolved fluctuations in gas density n on scales below the grid-spacing of coarse-grained simulations. We investigate in detail the impact of this inhomogeneous subgrid clumping on reionization and its observables, as follows: (1) Previous attempts generally underestimated the clumping factor because of insufficient mass resolution. We perform a high-resolution N-body simulation that resolves haloes down to the pre-reionization Jeans mass to derive the time-dependent, spatially varying local clumping factor and a fitting formula for its correlation with local overdensity. (2) We then perform a large-scale N-body and radiative transfer simulation that accounts for this inhomogeneous subgrid clumping by applying this clumping factor-overdensity correlation. Boosting recombination significantly slows the expansion of ionized regions, which delays completion of reionization and suppresses 21 cm power spectra on large scales in the later stages of reionization. (3) We also consider a simplified prescription in which the globally averaged, time-evolving clumping factor from the same high-resolution N-body simulation is applied uniformly to all cells in the reionization simulation, instead. Observables computed with this model agree fairly well with those from the inhomogeneous clumping model, e.g. predicting 21 cm power spectra to within 20 per cent error, suggesting it may be a useful approximation.

 

Abstract Many measurements at the LHC require efficient identification of heavy-flavour jets, i.e. jets originating from bottom (b) or charm (c) quarks. An overview of the algorithms used to identify c jets is described and a novel method to calibrate them is presented. This new method adjusts the entire distributions of the outputs obtained when the algorithms are applied to jets of different flavours. It is based on an iterative approach exploiting three distinct control regions that are enriched with either b jets, c jets, or light-flavour and gluon jets. Results are presented in the form of correction factors evaluated using proton-proton collision data with an integrated luminosity of 41.5 fb -1 at  √s = 13 TeV, collected by the CMS experiment in 2017. The closure of the method is tested by applying the measured correction factors on simulated data sets and checking the agreement between the adjusted simulation and collision data. Furthermore, a validation is performed by testing the method on pseudodata, which emulate various mismodelling conditions. The calibrated results enable the use of the full distributions of heavy-flavour identification algorithm outputs, e.g. as inputs to machine-learning models. Thus, they are expected to increase the sensitivity of future physics analyses.