scholarly journals Accurate specific molecular state densities by phase space integration. II. Comparison with quantum calculations on H+3and HD+2

1992 ◽  
Vol 96 (9) ◽  
pp. 6842-6849 ◽  
Author(s):  
Michael Berblinger ◽  
Christoph Schlier ◽  
Jonathan Tennyson ◽  
Steven Miller
1969 ◽  
Author(s):  
F.M. Mueller ◽  
J.W. Garland ◽  
M.H. Cohen ◽  
K.H. Bennemann

1997 ◽  
Vol 65 (6) ◽  
pp. 563-564 ◽  
Author(s):  
Sharada Nagabhushana ◽  
B. A. Kagali ◽  
Sivramkrishna Vijay

2020 ◽  
Vol 9 (4) ◽  
Author(s):  
Matthew Klimek ◽  
Maxim Perelstein

Monte Carlo methods are widely used in particle physics to integrate and sample probability distributions on phase space. We present an Artificial Neural Network (ANN) algorithm optimized for this task, and apply it to several examples of relevance for particle physics, including situations with non-trivial features such as sharp resonances and soft/collinear enhancements. Excellent performance has been demonstrated, with the trained ANN achieving unweighting efficiencies between 30% – 75%. In contrast to traditional algorithms, the ANN-based approach does not require that the phase space coordinates be aligned with resonant or other features in the cross section.


1965 ◽  
Vol 33 (12) ◽  
pp. 987-994 ◽  
Author(s):  
W. Williamson

1992 ◽  
Vol 07 (22) ◽  
pp. 2029-2038 ◽  
Author(s):  
A.B. ARBUZOV ◽  
D. YU. BARDIN ◽  
A. LEIKE

Analytic results for final state corrections to the differential and total cross-section for e+e−→massive fermions are presented. In the phase space integration a cut 011 the photon energy was included. The numerical importance of the obtained results is shown for QED and QCD corrections to r, b and t-quark production. Final state corrections are changed considerably by applying a cut on the photon energy. All results are immediately applicable to theories with several neutral gauge bosons.


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