Multidimensional sampling for simulation and integration: measures, discrepancies, and quasi-random numbers
Fred James, Jiri Hoogland, Ronald Kleiss
Abstract
This is basically a review of the field of Quasi-Monte Carlo intended for computational physicists and other potential users of quasi-random numbers. As such, much of the material is not new, but is presented here in a style hopefully more accessible to physicists than the specialized mathematical literature. There are also some new results: On the practical side we give important empirical properties of large quasi-random point sets, especially the exact quadratic discrepancies; on the theoretical side, there is the exact distribution of quadratic discrepancy for random point sets.
Create a lesson
Related papers
Chiral soliton lattice in inhomogeneous magnetic fields
Tomas Brauner, Ramkumar Radhakrishnan
From the November Revolution toward the Millennium
Chris Quigg
An Axial UA(1)Lμ-Lτ: UV Completion and Experimental Searches
Rundong Fang, Jinhui Guo, Ming Li et al.
Hunting long-lived doubly charged scalars at the HL-LHC
Biplob Bhattacherjee, Rituparna Ghosh, Swagata Mukherjee et al.
Enigmatic properties of Ξ(1620) and Ξ(1690)
Taísa Veloso, K. P. Khemchandani, A. Martinez Torres et al.
Exploring Z/γ-mediated heavy FCNCs at the FCC-ee
Abhik Sarkar, Subhajit Kala, Amir Subba et al.