Cosmic rays and molecular clouds

This paper deals with the cosmic-ray penetration into molecular clouds and with the related gamma--ray emission. High energy cosmic rays interact with the dense gas and produce neutral pions which in turn decay into two gamma rays. This makes molecular clouds potential sources of gamma rays, especially if they are located in the vicinity of a powerful accelerator that injects cosmic rays in the interstellar medium. The amplitude and duration in time of the cosmic--ray overdensity around a given source depend on how quickly cosmic rays diffuse in the turbulent galactic magnetic field. For these reasons, gamma-ray observations of molecular clouds can be used both to locate the sources of cosmic rays and to constrain the properties of cosmic-ray diffusion in the Galaxy.Comment: To appear in the proceedings of the San Cugat Forum on Astrophysics 2012, 27 pages, 10 figure

Silica burial enhanced by iron limitation in oceanic upwelling margins

In large swaths of the ocean, primary production by diatoms may be limited by the availability of silica, which in turn limits the biological uptake of carbon dioxide. The burial of biogenic silica in the form of opal is the main sink of marine silicon. Opal burial occurs in equal parts in iron-limited open-ocean provinces and upwelling margins, especially the eastern Pacific upwelling zone. However, it is unclear why opal burial is so efficient in this margin. Here we measure fluxes of biogenic material, concentrations of diatom-bound iron and silicon isotope ratios using sediment traps and a sediment core from the Gulf of California upwelling margin. In the sediment trap material, we find that periods of intense upwelling are associated with transient iron limitation that results in a high export of silica relative to organic carbon. A similar correlation between enhanced silica burial and iron limitation is evident in the sediment core, which spans the past 26,000 years. A global compilation also indicates that hotspots of silicon burial in the ocean are all characterized by high silica to organic carbon export ratios, a diagnostic trait for diatoms growing under iron stress. We therefore propose that prevailing conditions of silica limitation in the ocean are largely caused by iron deficiency imposing an indirect constraint on oceanic carbon uptake

Decadal to monthly timescales of magma transfer and reservoir growth at a caldera volcano

International audienceCaldera-forming volcanic eruptions are low-frequency, highimpact events capable of discharging tens to thousands of cubic kilometres of magma explosively on timescales of hours to days, with devastating effects on local and global scales1. Because no such eruption has been monitored during its long build-up phase, the precursor phenomena are not well understood. Geophysical signals obtained during recent episodes of unrest at calderas such as Yellowstone, USA, and Campi Flegrei, Italy, are difficult to interpret, and the conditions necessary for large eruptions are poorly constrained2,3. Here we present a study of pre-eruptive magmatic processes and their timescales using chemically zoned crystals from the 'Minoan' caldera-formingeruption of Santorini volcano,Greece4, which occurred in the late 1600s BC. The results provide insights into how rapidly large silicic systems may pass from a quiescent state to one on the edge of eruption5,6. Despite the large volume of erupted magma4 (40-60 cubic kilometres), and the 18,000-year gestation period between the Minoan eruption and the previous major eruption, most crystals in the Minoan magma record processes that occurred less than about 100 years before the eruption. Recharge of the magma reservoir by large volumes of silicic magma (and some mafic magma) occurred during the century before eruption, and mixing between different silicicmagmabatches was still taking place during the final months. Final assembly of large silicic magma reservoirs may occur on timescales that are geologically very short by comparison with the preceding repose period, with major growth phases immediately before eruption. These observations have implications for the monitoring of long-dormant, but potentially active, caldera systems

OzDES Reverberation Mapping Programme: Mg II lags and R−L relation

The correlation between the broad line region radius and continuum luminosity (R-L relation) of active galactic nuclei (AGNs) is critical for single-epoch mass estimates of supermassive black holes (SMBHs). At z ∼ 1-2, where AGN activity peaks, the R-L relation is constrained by the reverberation mapping (RM) lags of the Mg II line. We present 25 Mg II lags from the Australian Dark Energy Survey RM project based on 6 yr of monitoring. We define quantitative criteria to select good lag measurements and verify their reliability with simulations based on both the damped random walk stochastic model and the rescaled, resampled versions of the observed light curves of local, well-measured AGN. Our sample significantly increases the number of Mg II lags and extends the R-L relation to higher redshifts and luminosities. The relative iron line strength RFe has little impact on the R-L relation. The best-fitting Mg II R-L relation has a slope α = 0.39 ± 0.08 with an intrinsic scatter σrl = 0.15+−000203. The slope is consistent with previous measurements and shallower than the H β R-L relation. The intrinsic scatter of the new R-L relation is substantially smaller than previous studies and comparable to the intrinsic scatter of the H β R-L relation. Our new R-L relation will enable more precise single-epoch mass estimates and SMBH demographic studies at cosmic noon

Probabilistic machine learning and artificial intelligence.

How can a machine learn from experience? Probabilistic modelling provides a framework for understanding what learning is, and has therefore emerged as one of the principal theoretical and practical approaches for designing machines that learn from data acquired through experience. The probabilistic framework, which describes how to represent and manipulate uncertainty about models and predictions, has a central role in scientific data analysis, machine learning, robotics, cognitive science and artificial intelligence. This Review provides an introduction to this framework, and discusses some of the state-of-the-art advances in the field, namely, probabilistic programming, Bayesian optimization, data compression and automatic model discovery.The author acknowledges an EPSRC grant EP/I036575/1, the DARPA PPAML programme, a Google Focused Research Award for the Automatic Statistician and support from Microsoft Research.This is the author accepted manuscript. The final version is available from NPG at http://www.nature.com/nature/journal/v521/n7553/full/nature14541.html#abstract

Multiwavelength optical and NIR variability analysis of the Blazar PKS 0027-426

We present multiwavelength spectral and temporal variability analysis of PKS 0027-426 using optical griz observations from Dark Energy Survey between 2013 and 2018 and VEILS Optical Light curves of Extragalactic TransienT Events (VOILETTE) between 2018 and 2019 and near-infrared (NIR) JKs observations from Visible and Infrared Survey Telescope for Astronomy Extragalactic Infrared Legacy Survey (VEILS) between 2017 and 2019. Multiple methods of cross-correlation of each combination of light curve provides measurements of possible lags between optical–optical, optical–NIR, and NIR–NIR emission, for each observation season and for the entire observational period. Inter-band time lag measurements consistently suggest either simultaneous emission or delays between emission regions on time-scales smaller than the cadences of observations. The colour–magnitude relation between each combination of filters was also studied to determine the spectral behaviour of PKS 0027-426. Our results demonstrate complex colour behaviour that changes between bluer when brighter, stable when brighter, and redder when brighter trends over different time-scales and using different combinations of optical filters. Additional analysis of the optical spectra is performed to provide further understanding of this complex spectral behaviour

Candidate periodically variable quasars from the Dark Energy Survey and the Sloan Digital Sky Survey

Periodically variable quasars have been suggested as close binary supermassive black holes. We present a systematic search for periodic light curves in 625 spectroscopically confirmed quasars with a median redshift of 1.8 in a 4.6 deg2 overlapping region of the Dark Energy Survey Supernova (DES-SN) fields and the Sloan Digital Sky Survey Stripe 82 (SDSS-S82). Our sample has a unique 20-yr long multicolour (griz) light curve enabled by combining DES-SN Y6 observations with archival SDSS-S82 data. The deep imaging allows us to search for periodic light curves in less luminous quasars (down to r ∼23.5 mag) powered by less massive black holes (with masses ≳ 108.5M⊙) at high redshift for the first time. We find five candidates with significant (at >99.74 per cent single-frequency significance in at least two bands with a global p-value of ∼7 × 10−4–3 × 10−3 accounting for the look-elsewhere effect) periodicity with observed periods of ∼3–5 yr (i.e. 1–2 yr in rest frame) having ∼4–6 cycles spanned by the observations. If all five candidates are periodically variable quasars, this translates into a detection rate of ∼0.8+0.5−0.3 per cent or ∼1.1+0.7−0.5 quasar per deg2. Our detection rate is 4–80 times larger than those found by previous searches using shallower surveys over larger areas. This discrepancy is likely caused by differences in the quasar populations probed and the survey data qualities. We discuss implications on the future direct detection of low-frequency gravitational waves. Continued photometric monitoring will further assess the robustness and characteristics of these candidate periodic quasars to determine their physical origins

OzDES Reverberation Mapping Program: H beta lags from the 6-yr survey

Reverberation mapping measurements have been used to constrain the relationship between the size of the broad-line region and luminosity of active galactic nuclei (AGN). This R–L relation is used to estimate single-epoch virial black hole masses, and has been proposed to use to standardize AGN to determine cosmological distances. We present reverberation measurements made with Hβ from the 6-yr Australian Dark Energy Survey (OzDES) Reverberation Mapping Program. We successfully recover reverberation lags for eight AGN at 0.12 < z < 0.71, probing higher redshifts than the bulk of Hβ measurements made to date. Our fit to the R–L relation has a slope of α = 0.41 ± 0.03 and an intrinsic scatter of σ = 0.23 ± 0.02 dex. The results from our multi-object spectroscopic survey are consistent with previous measurements made by dedicated source-by-source campaigns, and with the observed dependence on accretion rate. Future surveys, including LSST, TiDES, and SDSS-V, which will be revisiting some of our observed fields, will be able to build on the results of our first-generation multi-object reverberation mapping survey

The Dark Energy Survey supernova programme: modelling selection efficiency and observed core-collapse supernova contamination

The analysis of current and future cosmological surveys of Type Ia supernovae (SNe Ia) at high redshift depends on the accurate photometric classification of the SN events detected. Generating realistic simulations of photometric SN surveys constitutes an essential step for training and testing photometric classification algorithms, and for correcting biases introduced by selection effects and contamination arising from core-collapse SNe in the photometric SN Ia samples. We use published SN time-series spectrophotometric templates, rates, luminosity functions, and empirical relationships between SNe and their host galaxies to construct a framework for simulating photometric SN surveys. We present this framework in the context of the Dark Energy Survey (DES) 5-yr photometric SN sample, comparing our simulations of DES with the observed DES transient populations. We demonstrate excellent agreement in many distributions, including Hubble residuals, between our simulations and data. We estimate the core collapse fraction expected in the DES SN sample after selection requirements are applied and before photometric classification. After testing different modelling choices and astrophysical assumptions underlying our simulation, we find that the predicted contamination varies from 7.2 to 11.7 per cent, with an average of 8.8 per cent and an r.m.s. of 1.1 per cent. Our simulations are the first to reproduce the observed photometric SN and host galaxy properties in high-redshift surveys without fine-tuning the input parameters. The simulation methods presented here will be a critical component of the cosmology analysis of the DES photometric SN Ia sample: correcting for biases arising from contamination, and evaluating the associated systematic uncertainty

Supernova host galaxies in the Dark Energy Survey: I. Deep coadds, photometry, and stellar masses

The 5-yr Dark Energy Survey Supernova Programme (DES-SN) is one of the largest and deepest transient surveys to date in terms of volume and number of supernovae. Identifying and characterizing the host galaxies of transients plays a key role in their classification, the study of their formation mechanisms, and the cosmological analyses. To derive accurate host galaxy properties, we create depth-optimized coadds using single-epoch DES-SN images that are selected based on sky and atmospheric conditions. For each of the five DES-SN seasons, a separate coadd is made from the other four seasons such that each SN has a corresponding deep coadd with no contaminating SN emission. The coadds reach limiting magnitudes of order ∼27 in g band, and have a much smaller magnitude uncertainty than the previous DES-SN host templates, particularly for faint objects. We present the resulting multiband photometry of host galaxies for samples of spectroscopically confirmed type Ia (SNe Ia), core-collapse (CCSNe), and superluminous (SLSNe) as well as rapidly evolving transients (RETs) discovered by DES-SN. We derive host galaxy stellar masses and probabilistically compare stellar-mass distributions to samples from other surveys. We find that the DES spectroscopically confirmed sample of SNe Ia selects preferentially fewer high-mass hosts at high-redshift compared to other surveys, while at low redshift the distributions are consistent. DES CCSNe and SLSNe hosts are similar to other samples, while RET hosts are unlike the hosts of any other transients, although these differences have not been disentangled from selection effects