A sampling algorithm to estimate the effect of fluctuations in particle physics data

Background properties in experimental particle physics are typically estimated using large data sets. However, different events can exhibit different features because of the quantum mechanical nature of the underlying physics processes. While signal and background fractions in a given data set can be evaluated using a maximum likelihood estimator, the shapes of the corresponding distributions are traditionally obtained using high-statistics control samples, which normally neglects the effect of fluctuations. On the other hand, if it was possible to subtract background using templates that take fluctuations into account, this would be expected to improve the resolution of the observables of interest, and to reduce systematics depending on the analysis. This study is an initial step in this direction. We propose a novel algorithm inspired by the Gibbs sampler that makes it possible to estimate the shapes of signal and background probability density functions from a given collection of particles, using control sample templates as initial conditions and refining them to take into account the effect of fluctuations. Results on Monte Carlo data are presented, and the prospects for future development are discussed.Comment: 6 pages, 1 figure. Edited to improve readability in line with the published article. This is based on a condensed version for publication in the Proceedings of the International Conference on Mathematical Modelling in the Physical Sciences, IC-MSQUARE 2012, Budapest, Hungary. A more detailed discussion can be found in the preceding version of this arXiv recor

Toward particle-level filtering of individual collision events at the Large Hadron Collider and beyond

Low-energy strong interactions are a major source of background at hadron colliders, and methods of subtracting the associated energy flow are well established in the field. Traditional approaches treat the contamination as diffuse, and estimate background energy levels either by averaging over large data sets or by restricting to given kinematic regions inside individual collision events. On the other hand, more recent techniques take into account the discrete nature of background, most notably by exploiting the presence of substructure inside hard jets, i.e. inside collections of particles originating from scattered hard quarks and gluons. However, none of the existing methods subtract background at the level of individual particles inside events. We illustrate the use of an algorithm that will allow particle-by-particle background discrimination at the Large Hadron Collider, and we envisage this as the basis for a novel event filtering procedure upstream of the official reconstruction chains. Our hope is that this new technique will improve physics analysis when used in combination with state-of-the-art algorithms in high-luminosity hadron collider environments

Toward the estimation of background fluctuations under newly-observed signals in particle physics

When the number of events associated with a signal process is estimated in particle physics, it is common practice to extrapolate background distributions from control regions to a predefined signal window. This allows accurate estimation of the expected, or average, number of background events under the signal. However, in general, the actual number of background events can deviate from the average due to fluctuations in the data. Such a difference can be sizable when compared to the number of signal events in the early stages of data analysis following the observation of a new particle, as well as in the analysis of rare decay channels. We report on the development of a data-driven technique that aims to estimate the actual, as opposed to the expected, number of background events in a predefined signal window. We discuss results on toy Monte Carlo data and provide a preliminary estimate of systematic uncertainty

On the frequency distribution of neutral particles from low-energy strong interactions

Copyright © 2017 Federico Colecchia and Akram Khan. The rejection of the contamination, or background, from low-energy strong interactions at hadron collider experiments is a topic that has received significant attention in the field of particle physics. This article builds on a particle-level view of collision events, in line with recently-proposed subtraction methods. While conventional techniques in the field usually concentrate on probability distributions, our study is, to our knowledge, the first attempt at estimating the frequency distribution of background particles across the kinematic space inside individual collision events. In fact, while the probability distribution can generally be estimated given a model of low-energy strong interactions, the corresponding frequency distribution inside a single event typically deviates from the average and cannot be predicted a priori. We present preliminary results in this direction, and establish a connection between our technique and the particle weighting methods that have been the subject of recent investigation at the Large Hadron Collider

Preface

Preface - The second International Conference on Mathematical Modeling in Physical Sciences (IC-MSQUARE) took place at Prague, Czech Republic, from Sunday 1 September to Thursday 5 September 2013

Data-driven estimation of neutral pileup particle multiplicity in high-luminosity hadron collider environments

The upcoming operation regimes of the Large Hadron Collider are going to place stronger requirements on the rejection of particles originating from pileup, i.e. from interactions between other protons. For this reason, particle weighting techniques have recently been proposed in order to subtract pileup at the level of individual particles. We describe a choice of weights that, unlike others that rely on particle proximity, exploits the particle-level kinematic signatures of the high-energy scattering and of the pileup interactions. We illustrate the use of the weights to estimate the number density of neutral pileup particles inside individual events, and we elaborate on the complementarity between ours and other methods. We conclude by suggesting the idea of combining different sets of weights with a view to exploiting different features of the underlying processes for improved pileup subtraction at higher luminosity.High Energy Physics Group at Brunel University Londo

Evidence for the Rare Decay B -> K*ll and Measurement of the B -> Kll Branching Fraction

We present evidence for the flavor-changing neutral current decay $B\to K^*\ell^+\ell^-$ and a measurement of the branching fraction for the related process $B\to K\ell^+\ell^-$, where $\ell^+\ell^-$ is either an $e^+e^-$ or $\mu^+\mu^-$ pair. These decays are highly suppressed in the Standard Model, and they are sensitive to contributions from new particles in the intermediate state. The data sample comprises $123\times 10^6$ $\Upsilon(4S)\to B\bar{B}$ decays collected with the Babar detector at the PEP-II $e^+e^-$ storage ring. Averaging over $K^{(*)}$ isospin and lepton flavor, we obtain the branching fractions ${\mathcal B}(B\to K\ell^+\ell^-)=(0.65^{+0.14}_{-0.13}\pm 0.04)\times 10^{-6}$ and ${\mathcal B}(B\to K^*\ell^+\ell^-)=(0.88^{+0.33}_{-0.29}\pm 0.10)\times 10^{-6}$, where the uncertainties are statistical and systematic, respectively. The significance of the $B\to K\ell^+\ell^-$ signal is over $8\sigma$, while for $B\to K^*\ell^+\ell^-$ it is $3.3\sigma$.Comment: 7 pages, 2 postscript figues, submitted to Phys. Rev. Let

Measurement of Branching Fraction and Dalitz Distribution for B0->D(*)+/- K0 pi-/+ Decays

We present measurements of the branching fractions for the three-body decays B0 -> D(*)-/+ K0 pi^+/-$and their resonant submodes$B0 -> D(*)-/+ K*+/- using a sample of approximately 88 million BBbar pairs collected by the BABAR detector at the PEP-II asymmetric energy storage ring. We measure: B(B0->D-/+ K0 pi+/-)=(4.9 +/- 0.7(stat) +/- 0.5 (syst)) 10^{-4} B(B0->D*-/+ K0 pi+/-)=(3.0 +/- 0.7(stat) +/- 0.3 (syst)) 10^{-4} B(B0->D-/+ K*+/-)=(4.6 +/- 0.6(stat) +/- 0.5 (syst)) 10^{-4} B(B0->D*-/+ K*+/-)=(3.2 +/- 0.6(stat) +/- 0.3 (syst)) 10^{-4} From these measurements we determine the fractions of resonant events to be : f(B0-> D-/+ K*+/-) = 0.63 +/- 0.08(stat) +/- 0.04(syst) f(B0-> D*-/+ K*+/-) = 0.72 +/- 0.14(stat) +/- 0.05(syst)Comment: 7 pages, 3 figures submitted to Phys. Rev. Let

Testicular germ-cell tumours and penile squamous cell carcinoma: Appropriate management makes the difference

Germ-cell tumours (GCT) of the testis and penile squamous cell carcinoma (PeSCC) are a rare and a very rare uro-genital cancers, respectively. Both tumours are well defined entities in terms of management, where specific recommendations - in the form of continuously up-to-dated guide lines-are provided. Impact of these tumour is relevant. Testicular GCT affects young, healthy men at the beginning of their adult life. PeSCC affects older men, but a proportion of these patients are young and the personal consequences of the disease may be devastating. Deviation from recommended management may be a reason of a significant prognostic worsening, as proper treatment favourably impacts on these tumours, dramatically on GCT and significantly on PeSCC. RARECAREnet data may permit to analyse how survivals may vary according to geographical areas, histology and age, leading to assume that non-homogeneous health-care resources may impact the cure and definitive outcomes. In support of this hypothesis, some epidemiologic datasets and clinical findings would indicate that survival may improve when appropriate treatments are delivered, linked to a different accessibility to the best health institutions, as a consequence of geographical, cultural and economic barriers. Finally, strong clues based on epidemiological and clinical data support the hypothesis that treatment delivered at reference centres or under the aegis of a qualified multi-institutional network is associated with a better prognosis of patients with these malignancies. The ERN EURACAN represents the best current European effort to answer this clinical need

Multi organ assessment of compensated cirrhosis patients using quantitative magnetic resonance imaging

Background and Aims: Advancing liver disease results in deleterious changes in a number of critical organs. The ability to measure structure, blood flow and tissue perfusion within multiple organs in a single scan has implications for determining the balance of benefit versus harm for therapies. Our aim was to establish the feasibility of Magnetic Resonance Imaging to assess changes in compensated cirrhosis (CC), and relate this to disease severity and future liver related outcomes (LROs). Methods: 60 CC patients, 40 healthy volunteers and 7 decompensated cirrhotics were recruited. In a single scan session, MRI measures comprised phase-contrast MRI vessel blood flow, arterial spin labelling tissue perfusion, T1 longitudinal relaxation time and volume assessment of liver, spleen and kidneys, heart rate and cardiac index. We explore MRI parameters with disease severity and differences in baseline MRI parameters in those 11 (18%) of CC patients who had future LROs. Results: In the liver compositional changes were reflected by increased T1 in progressive disease (p<0.001) and an increase in liver volume in CC (p=0.006), with associated progressive reduction in liver (p < 0.001) and splenic (p<0.001) perfusion. A significant reduction in renal cortex T1 and increase in cardiac index and superior mesenteric arterial (SMA) blood flow was seen with increasing disease severity. Baseline liver T1 (p=0.01) and perfusion (p< 0.01), and renal cortex T1 (p<0.01) were significantly different in CC patients who subsequently developed negative LROs. Conclusions: MRI allows the contemporaneous assessment of organs in liver cirrhosis in a single scan without the requirement of contrast agent. MRI parameters of liver T1, renal T1, hepatic and splenic perfusion, and SMA blood flow were related to risk of LROs