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Register a new userTWOPEG: An Event Generator for Charged Double Pion Electroproduction off Proton
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The new event generator TWOPEG for the channel $e p rightarrow e p pi^{+} pi^{-}$ has been developed. It uses an advanced method of event generation with weights and employs the five-fold differential structure functions from the rece
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Intuitively, a scientist might assume that a more complex regression model will necessarily yield a better predictive model of experimental data. Herein, we disprove this notion in the context of extracting the proton charge radius from charge form factor data. Using a Monte Carlo study, we show that a simpler regression model can in certain cases be the better predictive model. This is especially true with noisy data where the complex model will fit the noise instead of the physical signal. Thus, in order to select the appropriate regression model to employ, a clear technique should be used such as the Akaike information criterion or Bayesian information criterion, and ideally selected previous to seeing the results. Also, to ensure a reasonable fit, the scientist should also make regression quality plots, such as residual plots, and not just rely on a single criterion such as reduced chi2. When we apply these techniques to low four-momentum transfer cross section data, we find a proton radius that is consistent with the muonic Lamb shift results. While presented for the case of proton radius extraction, these concepts are applicable in general and can be used to illustrate the necessity of balancing bias and variance when building a regression model and validating results, ideas that are at the heart of modern machine learning algorithms.
Signal estimation in the presence of background noise is a common problem in several scientific disciplines. An On/Off measurement is performed when the background itself is not known, being estimated from a background control sample. The frequentist and Bayesian approaches for signal estimation in On/Off measurements are reviewed and compared, focusing on the weakness of the former and on the advantages of the latter in correctly addressing the Poissonian nature of the problem. In this work, we devise a novel reconstruction method, dubbed BASiL (Bayesian Analysis including Single-event Likelihoods), for estimating the signal rate based on the Bayesian formalism. It uses information on event-by-event individual parameters and their distribution for the signal and background population. Events are thereby weighted according to their likelihood of being a signal or a background event and background suppression can be achieved without performing fixed fiducial cuts. Throughout the work, we maintain a general notation, that allows to apply the method generically, and provide a performance test using real data and simulations of observations with the MAGIC telescopes, as demonstration of the performance for Cherenkov telescopes. BASiL allows to estimate the signal more precisely, avoiding loss of exposure due to signal extraction cuts. We expect its applicability to be straightforward in similar cases.
We provide a method to correct the observed azimuthal anisotropy in heavy-ion collisions for the event plane resolution in a wide centrality bin. This new procedure is especially useful for rare particles, such as Omega baryons and J/psi mesons, which are difficult to measure in small intervals of centrality. Based on a Monte Carlo calculation with simulated v_2 and multiplicity, we show that some of the commonly used methods have a bias of up to 15%.
The fixed-target MIPP experiment, Fermilab E907, was designed to measure the production of hadrons from the collisions of hadrons of momenta ranging from 5 to 120 GeV/c on a variety of nuclei. These data will generally improve the simulation of particle detectors and predictions of particle beam fluxes at accelerators. The spectrometer momentum resolution is between 3 and 4%, and particle identification is performed for particles ranging between 0.3 and 80 GeV/c using $dE/dx$, time-of-flight and Cherenkov radiation measurements. MIPP collected $1.42 times10^6$ events of 120 GeV Main Injector protons striking a target used in the NuMI facility at Fermilab. The data have been analyzed and we present here charged pion yields per proton-on-target determined in bins of longitudinal and transverse momentum between 0.5 and 80 GeV/c, with combined statistical and systematic relative uncertainties between 5 and 10%.
The invariant amplitudes for pion electroproduction on the nucleon are evaluated by dispersion relations at constant t with MAID as input for the imaginary parts of these amplitudes. In the threshold region these amplitudes are confronted with the predictions of several low-energy theorems derived in the soft-pion limit. In general agreement with Chiral Perturbation Theory, the dispersive approach yields large corrections to these theorems because of the finite pion mass.
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