ar X iv : h ep - p h / 05 04 08 5 v 1 1 2 A pr 2 00 5 Error in Monte Carlo , quasi - error in Quasi - Monte Carlo

نویسنده

  • Achilleas Lazopoulos
چکیده

While the Quasi-Monte Carlo method of numerical integration achieves smaller integration error than standard Monte Carlo, its use in particle physics phenomenology has been hindered by the abscence of a reliable way to estimate that error. The standard Monte Carlo error estimator relies on the assumption that the points are generated independently of each other and, therefore, fails to account for the error improvement advertised by the Quasi-Monte Carlo method. We advocate the construction of an estimator of stochastic nature, based on the ensemble of pointsets with a particular discrepancy value. We investigate the consequences of this choice and give some first empirical results on the suggested estimators.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

ar X iv : h ep - p h / 04 04 24 1 v 1 2 7 A pr 2 00 4 LCG Monte - Carlo Data Base ( LCG Generator Services Subproject )

We present the Monte-Carlo events Data Base (MCDB) project and its development plans. MCDB facilitates communication between authors of Monte-Carlo generators and experimental users. It also provides a convenient book-keeping and an easy access to generator level samples. The first release of MCDB is now operational for the CMS collaboration. In this paper we review the main ideas behind MCDB a...

متن کامل

ar X iv : h ep - p h / 05 09 06 7 v 1 7 S ep 2 00 5 Neural network approach to parton distributions fitting

We will show an application of neural networks to extract information on the structure of hadrons. A Monte Carlo over experimental data is performed to correctly reproduce data errors and correlations. A neural network is then trained on each Monte Carlo replica via a genetic algorithm. Results on the proton and deuteron structure functions, and on the nonsinglet parton distribution will be shown.

متن کامل

ar X iv : h ep - p h / 05 09 06 7 v 2 1 8 O ct 2 00 5 Neural network approach to parton distributions fitting

We will show an application of neural networks to extract information on the structure of hadrons. A Monte Carlo over experimental data is performed to correctly reproduce data errors and correlations. A neural network is then trained on each Monte Carlo replica via a genetic algorithm. Results on the proton and deuteron structure functions, and on the nonsinglet parton distribution will be shown.

متن کامل

ar X iv : h ep - l at / 0 20 90 72 v 1 5 S ep 2 00 2 1 Four – loop logarithms in 3 d gauge + Higgs theory ∗

We discuss the logarithmic contributions to the vacuum energy density of the three-dimensional SU(3) + adjoint Higgs theory in its symmetric phase, and relate them to numerical Monte Carlo simulations. We also comment on the implications of these results for perturbative and non-perturbative determinations of the pressure of finite-temperature QCD.

متن کامل

ar X iv : h ep - p h / 95 04 34 9 v 2 2 6 M ar 1 99 7 QUANTUM INTERFERENCE AND MONTE - CARLO SIMULATIONS OF MULTIPARTICLE PRODUCTION

We show that the effects of quantum interference can be implemented in Monte-Carlo generators by modelling the generalized Wigner functions. A specific prescription for an appropriate modification of the weights of events produced by standard generators is proposed.

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2005