A Monte Carlo Approach to Cutoffs and Charge State Measurements With SAMPEX/MAST Data

Mathematics – Probability

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

7513 Coronal Mass Ejections (2101), 7514 Energetic Particles (2114), 7519 Flares, 7594 Instruments And Techniques

Scientific paper

High energy ionic charge states in large, gradual solar energetic particle events have been reported using a geomagnetic rigidity filter technique. The current technique involves accumulating particle counts vs. invariant latitude and fitting geomagnetic cutoffs to these profiles in order to extract charge state measurements. However, the current technique does not yield cutoffs or charge states for situations involving low statistics, e.g. low particle abundances or smaller SEP events. To supplement the current technique, we have developed a Monte Carlo simulation to model the MAST data and to fit particle count vs. invariant latitude profiles. This simulation can also model the underlying probability distributions for low statistics situations, allowing us to attempt cutoff and charge states estimates for elements and SEP events for which we have not previously attempted measurements. We will report on the details of the simulation and the resulting SEP charge state estimates arising from new fits to the data.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

A Monte Carlo Approach to Cutoffs and Charge State Measurements With SAMPEX/MAST Data does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with A Monte Carlo Approach to Cutoffs and Charge State Measurements With SAMPEX/MAST Data, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and A Monte Carlo Approach to Cutoffs and Charge State Measurements With SAMPEX/MAST Data will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-968879

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.