Multiple Parton Interactions Studies at CMS

This paper summarizes the Multiple Parton Interactions studies in CMS, focusing on the already performed low pT QCD measurements up to highest centre of mass energies of 7 TeV and discussing the plans for the direct measurement of the multiple high-pT scatterings. The underlying event in pp interactions is studied measuring the charged multiplicity density and the charged energy density in the transverse region, which is defined considering the azimuthal distance of the reconstructed tracks with respect to the leading track-jet of the event, defined from tracks according to a jet clustering algorithms. In addition, we present the measurement of the underlying event using the jet-area/median approach, demonstrating its sensitivity to different underlying event scenarios. Observations in the central region are complemented by the mea- surement of the energy flow in the forward direction for minimum bias and central di-jet events. We compare our underlying event and forward results with the predictions from different Monte Carlo event generators and tunes, aiming to best parametrize the multiple parton interaction energy de- pendence starting from the Monte Carlo tunes developed to best fit the charged particle spectra measured at central rapidities. Finally we discuss the strategy to directly measure the multiple particle interactions rate focusing on the topologies with two hard scatterings in the same event

Underlying Events and Diffraction Studies at the LHC

The potential of the LHC experiments to study the underlying events and diffractive in proton-proton collisions at sqrt{s} =14 TeV is described. The underlying event is studied by examining charged particles in the region transverse to jets and in the central region of Drell-Yan muon-pair production. The diffractive program includes studies of QCD, low-x structure of the proton, and central exclusive production of SM and MSSM Higgs. The measurement of the scattered protons at appropriate locations along the beam-line is especially useful at high instantaneous luminosities

Measurement of the Underlying Event at LHC with the CMS detector

A study of \textit{Underlying Events} (UE) at \textit{Large Hadron Collider} (LHC) with CMS detector under nominal conditions is discussed. Using charged particle and charged particle jets, it will be possible to discriminate between various QCD models with different multiple parton interaction schemes, which correctly reproduce Tevatron data but give different predictions when extrapolated to the LHC energy. This will permit improving and tuning Monte Carlo models at LHC start-up, and opens prospects for exploring QCD dynamics in proton-proton collisions at 14TeV

Evolution of strange and multi-strange hadron production with relative transverse multiplicity activity in underlying event

In this work, relative Underlying Event (UE) transverse multiplicity activity classifier ($R_{\rm {T}}$) is used to study the strange and multi-strange hadron production in proton-proton collisions. Our study with $R_{\rm {T}}$ would allow to disentangle these particles which are originating from the soft and hard QCD processes. We have used the PYTHIA 8 MC with different implementation of color reconnection and rope hydronisation models to demonstrate the proton-proton collisions data at $\sqrt{s}$ = 13 TeV. The relative production of strange and multi-strange hadrons are discussed extensively in low and high transverse activity region. In this contribution, the relative strange hadron production is enhanced with increasing $R_{\rm {T}}$. This enhancement is significant for strange baryons as compared to mesons. In addition, the particle ratios as a function of $R_{\rm {T}}$ confirms the baryon enhancement in newCR, whereas Rope model confirms the baryon enhancement only with strange quark content. An experimental confirmation of such results will provide more insight into the soft physics in the transverse region which will be useful to investigate various tunes based on hadronization and color reconnection schemes

Bow-Tie Cavity for Terahertz Radiation

We report on the development, testing, and performance analysis of a bow-tie resonant cavity for terahertz (THz) radiation, injected with a continuous-wave 2.55 THz quantum cascade laser. The bow-tie cavity employs a wire-grid polarizer as input/output coupler and a pair of copper spherical mirrors coated with an unprotected 500 nm thick gold layer. The improvements with respect to previous setups have led to a measured finesse value F=123, and a quality factor Q = 5.1x10^5. The resonator performances and the relevant parameters are theoretically predicted and discussed, and a comparison among simulated and experimental spectra is given

Measuring Muon Reconstruction Efficiency from Data

We suggest a method of measuring the global muon reconstruction efficiency epsilon directly from data, which largely alleviates uncertainties associated with our ability to monitor and reproduce in Monte Carlo simulation all details of the underlying detector performance. With the data corresponding to an integrated luminosity L = 10 fb^-1, the precision of measuring epsilon for muons in the P_T range of 10-100~GeV will be better than 1%

The Underlying Event at the LHC

We discuss a study of "minimum-bias'' collisions and the "Underlying Event" at CMS (under nominal conditions) by measuring charged particles and muons. The Underlying Event is studied by examining charged particles in the "transverse" region in charged particle jet production and in the central region of Drell-Yan muon-pair production (after removing the muon-pair)

Increasing prevalence of multiple sclerosis in Tuscany: a study based on validated administrative data

AIMS Italy is a high-risk area for Multiple Sclerosis (MS) with a prevalence of around 140/105 (2009) with the exception of Sardinia, with about 224 cases/105 (2009). Nowadays, in Italy, prevalence is absolutely higher than the above estimates. Indeed, prevalence is rising due to annual incidence that is higher than annual mortality. In Tuscany a population MS register has been founded but, to date, it’s not yet completed. To monitor disease epidemiology, comorbidities and care pathways, but also to describe the disease burden and to plan its prevention, treatment and management strategies and resource allocation, population-based studies are preferable. Administrative data offer a unique opportunity for population-based prevalence study of chronic diseases such as MS. Our aim is to update the prevalence of MS in Tuscany and to demonstrate its progressive increment. METHODS The prevalence was calculated using a case-finding algorithm based on administrative data: hospitalization, specific MS drug dispensing, disease-specific exemptions from patient copayment, home and residential long-term care and inhabitant registry. To test algorithm sensitivity, we used a true-positive reference cohort of 302 MS patients from the Tuscan MS register. To test algorithm specificity, we used a general population cohort of 2,644,094 individuals who were presumably not affected by MS (who had never effectuated either cranial or spinal cord CT scan or MRI and had never received a neurological outpatient visit within the NHS). We calculated prevalence on three consecutive years (2011, 2012, 2013). RESULTS At prevalence date (31 December), we identified 6,890 cases in 2011, 7,057 in 2012 and 7,330 in 2013 with a rate of 187.9, 191.1 and 195.4/105, respectively. The female:male ratio slightly increased from 2.0 in 2011 to 2.1 in 2012-2013. The sensitivity of algorithm was 98% and its specificity was 99.99%. DISCUSSION We found a progressive increment of prevalence that confirmed our hypothesis of increasing prevalence. Although our validity study demonstrated a high level of sensibility, we could miss some patients, especially individuals with a severe MS, who did not access the healthcare system and who did not use the DMDs included in our algorithm. CONCLUSIONS We confirmed that Tuscany is a high-risk area for MS and that the prevalence is increasing over time. Despite some limitations, we also demonstrated that our algorithm can accurately identify patients and this cohort is suitable to monitor care pathways. Our future aim is to create an integrated dataset with administrative and clinical data from MS register