21cm Intensity Mapping cross-correlation with galaxy surveys: current and forecasted cosmological parameters estimation for the SKAO

We present a comprehensive set of forecasts for the cross-correlation signal between 21cm intensity mapping and galaxy redshift surveys. We focus on the data sets that will be provided by the SKAO for the 21cm signal, DESI and Euclid for galaxy clustering. We build a likelihood which takes into account the effect of the beam for the radio observations, the Alcock-Paczynski effect, a simple parameterization of astrophysical nuisances, and fully exploit the tomographic power of such observations in the range $z=0.7-1.8$ at linear and mildly non-linear scales ($k<0.25 h/$Mpc). The forecasted constraints, obtained with Monte Carlo Markov Chains techniques in a Bayesian framework, in terms of the six base parameters of the standard $\Lambda$CDM model, are promising. The predicted signal-to-noise ratio for the cross-correlation can reach $\sim 50$ for $z\sim 1$ and $k\sim 0.1 h/$ Mpc. When the cross-correlation signal is combined with current Cosmic Microwave Background (CMB) data from Planck, the error bar on $\Omega_{\rm c}\,h^2$ and $H_0$ is reduced by a factor 3 and 6, respectively, compared to CMB only data, due to the measurement of matter clustering provided by the two observables. The cross-correlation signal has a constraining power that is comparable to the auto-correlation one and combining all the clustering measurements a sub-percent error bar of 0.33% on $H_0$ can be achieved, which is about a factor 2 better than CMB only measurement. Finally, as a proof-of-concept, we test the full pipeline on the real data measured by the MeerKat collaboration (Cunnington et al. 2022) presenting some (weak) constraints on cosmological parameters.Comment: 14 pages, 10 figures. arXiv admin note: text overlap with arXiv:2209.0759

Multipole expansion for 21cm Intensity Mapping power spectrum: forecasted cosmological parameters estimation for the SKA Observatory

The measurement of the large scale distribution of neutral hydrogen in the late Universe, obtained with radio telescopes through the hydrogen 21cm line emission, has the potential to become a key cosmological probe in the upcoming years. We explore the constraining power of 21cm intensity mapping observations on the full set of cosmological parameters that describe the $\Lambda$CDM model. We assume a single-dish survey for the SKA Observatory and simulate the 21cm linear power spectrum monopole and quadrupole within six redshift bins in the range $z=0.25-3$. Forecasted constraints are computed numerically through Markov Chain Monte Carlo techniques. We extend the sampler \texttt{CosmoMC} by implementing the likelihood function for the 21cm power spectrum multipoles. We assess the constraining power of the mock data set alone and combined with Planck 2018 CMB observations. We include a discussion on the impact of extending measurements to non-linear scales in our analysis. We find that 21cm multipoles observations alone are enough to obtain constraints on the cosmological parameters comparable with other probes. Combining the 21cm data set with CMB observations results in significantly reduced errors on all the cosmological parameters. The strongest effect is on $\Omega_ch^2$ and $H_0$, for which the error is reduced by almost a factor four. The percentage errors we estimate are $\sigma_{\Omega_ch^2} = 0.25\%$ and $\sigma_{H_0} = 0.16\%$, to be compared with the Planck only results $\sigma_{\Omega_ch^2} = 0.99\%$ and $\sigma_{H_0} = 0.79\%$. We conclude that 21cm SKAO observations will provide a competitive cosmological probe, complementary to CMB and, thus, pivotal for gaining statistical significance on the cosmological parameters constraints, allowing a stress test for the current cosmological model.Comment: 16 pages, 9 figure

Modelli di programmazione scalabile per Big Data: analisi comparativa e sperimentale

Analisi di alcuni modelli di programmazione scalabile per Big Data, presentando i principali framework in base al tipo di elaborazione: batch, stream, ibrida. Infine sperimentazione e confronti tra Apache Hadoop e Apache Spark, sia in modalità single-node che su cluster AWS

New mechanistic insight into replication fork reversal and restart

An emerging model of how stalled or damaged forks are processed is that replication fork s can reverse to aid repair of the damage. The first evidence that replication forks regress in human cells came from a recent study with topoisomerase I (T op 1) inhibitors, an important class of anticancer drugs currently in clinical use. Their cytotoxicit y, and thus their efficacy, has been generally linked to their ability to cause the accumulation of DNA nicks, which are later converted into double - stranded breaks (DSBs) by the collision of the DNA replication fork with the primary lesion. The discovery that replic ation forks can regress upon Top 1 inhibition provided new insight into the molecular basis of Top 1 cytotoxicity by showing that clinically relevant , nanomolar doses of Top 1 poisons induce replication fork slowing and reversal in a process that c an be uncoupled from DSB formation and requires poly(ADP - ribose) polymerase 1 ( PARP1) activity. However, w hether re versed forks can efficiently restart and wh ich factors are involved in this mechanism was still unknown. In this thesis , u sing a combination of biochemical and cellular approaches, we provided the first evidence that regressed forks can restart in vivo and identified a key role for the human RECQ1 helicase in promoting efficient re plication fork restart after Top 1 inhibition that is not shared by other human RecQ members . Our data also provided the first insight into the molecular role of PARP1 in fork reversal by showing that the poly(ADP - ribosyl)ation activity of PARP inhibits RECQ1 activity on replication forks after Top 1 inhibition. Thus, PARP activity is not required to form, but rather to "accumulate" reversed fork structures by maintaining/protecting them from a counteracting activity (RECQ1), which would otherwise cause an untimely restart of reversed forks, leading to DSB formation. The identification of a specific and controlled biochemical activity that drives the restart of reversed forks strongly supports the physiological relevance of this DNA transaction during replication stress in human cells. Moreover, our studies provide new mec hanistic insights into the roles of RECQ1 and PARP 1 in DNA replication and offer molecular perspectives to potentiate chemo therapeutic regimens based on Top 1 inhibition

MAMODIS - A low-cost monitoring system for debris flows based on infrasound and seismic signals

The automatic detection of sediment related disasters like landslides, debris flows and debris floods, gets increasing importance for hazard mitigation and early warning. Past studies showed that such processes induce characteristic seismic signals and acoustic signals in the infrasonic spectrum which can be used for event detection. The presented system MAMODIS (MAss MOvement Detection and Identification System) is a detection system for debris flows, debris floods and avalanches based on a combination of infrasound and seismic signals. The detection system consists of one infrasound sensor, one geophone and a microcontroller, where a specially designed detection algorithm is executed. This algorithm reliably detects events in real time directly at the sensor site. The setup can be easily installed beside a torrent or an avalanche path and therefore can be used as a low-cost and practicable solution for early warning. In addition, this system offers first information of the process-type and a rough estimation of the peak discharge and the total volume for debris flows and debris floods. These values are calculated from the infrasound and seismic signals. Currently the system is installed on several test sites in Austria, Switzerland and Italy

Starry sky' rash in a child

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Debris-flow monitoring and warning: review and examples

Debris flows represent one of the most dangerous types of mass movements, because of their high velocities, large impact forces and long runout distances. This review describes the available debris-flow monitoring techniques and proposes recommendations to inform the design of future monitoring and warning/alarm systems. The selection and application of these techniques is highly dependent on site and hazard characterization, which is illustrated through detailed descriptions of nine monitoring sites: five in Europe, three in Asia and one in the USA. Most of these monitored catchments cover less than ~10 km2 and are topographically rugged with Melton Indices greater than 0.5. Hourly rainfall intensities between 5 and 15 mm/h are sufficient to trigger debris flows at many of the sites, and observed debris-flow volumes range from a few hundred up to almost one million cubic meters. The sensors found in these monitoring systems can be separated into two classes: a class measuring the initiation mechanisms, and another class measuring the flow dynamics. The first class principally includes rain gauges, but also contains of soil moisture and pore-water pressure sensors. The second class involves a large variety of sensors focusing on flow stage or ground vibrations and commonly includes video cameras to validate and aid in the data interpretation. Given the sporadic nature of debris flows, an essential characteristic of the monitoring systems is the differentiation between a continuous mode that samples at low frequency (“non-event mode”) and another mode that records the measurements at high frequency (“event mode”). The event detection algorithm, used to switch into the “event mode” depends on a threshold that is typically based on rainfall or ground vibration. Identifying the correct definition of these thresholds is a fundamental task not only for monitoring purposes, but also for the implementation of warning and alarm systemsPeer ReviewedPostprint (author's final draft

Simulations of the occurrence of runoff-generated debris flows by means of hydrological models in headwater rocky basins

The simulation of the occurrence of the runoff-generated debris flows can be approached by means of hydrological models. In this work, we show that a rainfall-runoff model designed for the simulation of runoff in headwater rocky basins can capture both the transit timing of the first debris-flow surge and its hydrograph. We successfully compared the stage hydrograph of debris flows with that of the simulated runoff in two headwater rocky basins of Dolomites