Method of Separating Cosmic-Ray Positrons from Electrons in the DAMPE Experiment

2022 ◽  
Author(s):  
Haoting Dai ◽  
Zang Jingjing ◽  
Ying Wang ◽  
Yunlong Zhang ◽  
Yifeng Wei ◽  
...  
Keyword(s):  
Cosmic Rays ◽  
Geomagnetic Field ◽  
Cosmic Ray ◽  
Field Of View ◽  
Particle Identification ◽  
Present Observation ◽  
Observation Data ◽  
Flight Data ◽  
The Real ◽  
Positron Flux

Abstract A method of identifying positron/electron species from the cosmic rays was studied in the DAMPE experiment. As there is no onboard magnet on the satellite, the different features imposed by the geomagnetic field on these two species were exploited for the particle identification. Application of this method to the simulation of on-orbit electrons/positrons/protons and the real flight data proves that separately measuring the CR positrons/electrons with DAMPE is feasible, though limited by the field of view for the present observation data. Further analysis on the positron flux with this method can be expected in the future.

The anomalous entry of low-rigidity solar cosmic rays into the geomagnetic field

1963 ◽  
Vol 68 (19) ◽  
pp. 5327 ◽  
Author(s):  
S.-I. Akasofu ◽  
W. C. Lin ◽  
J. A. Van Allen
Keyword(s):  
Cosmic Rays ◽  
Geomagnetic Field ◽  
Solar Cosmic Rays

scholarly journals Reversals in the large-scale αΩ-dynamo with memory

2015 ◽  
Vol 22 (4) ◽  
pp. 361-369 ◽  
Author(s):  
L. K. Feschenko ◽  
G. M. Vodinchar
Keyword(s):  
Magnetic Field ◽  
Power Law ◽  
Geomagnetic Field ◽  
Large Scale ◽  
Magnetic Polarity ◽  
Power Law Model ◽  
The Real ◽  
Geomagnetic Polarity ◽  
With Memory ◽  
The Magnetic Field

Abstract. Inversion of the magnetic field in a model of large-scale αΩ-dynamo with α-effect with stochastic memory is under investigation. The model allows us to reproduce the main features of the geomagnetic field reversals. It was established that the polarity intervals in the model are distributed according to the power law. Model magnetic polarity timescale is fractal. Its dimension is consistent with the dimension of the real geomagnetic polarity timescale.

scholarly journals On the slow-time geomagnetic field modulation of cosmic rays

2019 ◽  
Vol 14 (15) ◽  
pp. 171-186
Author(s):  
Friday Egbunu ◽  
Kingsley Chukwudi Okpala
Keyword(s):  
Cosmic Rays ◽  
Geomagnetic Field ◽  
Slow Time ◽  
Field Modulation

scholarly journals Moon shadow by cosmic rays under the influence of geomagnetic field and search for antiprotons at multi-TeV energies

2007 ◽  
Vol 28 (1) ◽  
pp. 137-142 ◽  
Author(s):  
M. Amenomori ◽  
S. Ayabe ◽  
X.J. Bi ◽  
D. Chen ◽  
S.W. Cui ◽  
...  
Keyword(s):  
Cosmic Rays ◽  
Geomagnetic Field

AN ANALYTICAL SOLUTION OF THE COSMIC RAYS TRANSPORT EQUATION IN THE PRESENCE OF THE GEOMAGNETIC FIELD

2002 ◽  
Vol 17 (12n13) ◽  
pp. 1645-1653
Author(s):  
MARINA GIBILISCO
Keyword(s):  
Magnetic Field ◽  
Cosmic Rays ◽  
Analytical Solution ◽  
Transport Equation ◽  
Geomagnetic Field ◽  
The Earth ◽  
Factorization Technique ◽  
Diffusion Motion ◽  
Geomagnetic Fields ◽  
The Magnetic Field

In this work, I study the propagation of cosmic rays inside the magnetic field of the Earth, at distances d ≤ 500 Km from its surface; at these distances, the geomagnetic field deeply influences the diffusion motion of the particles. I compare the different effects of the interplanetary and of the geomagnetic fields, by also discussing their role inside the cosmic rays transport equation; finally, I present an analytical method to solve such an equation through a factorization technique.

Feature Extraction and Geomagnetic Matching

2013 ◽  
Vol 66 (6) ◽  
pp. 799-811 ◽  
Author(s):  
Caifa Guo ◽  
Hong Cai ◽  
G.H.M. van der Heijden
Keyword(s):  
Feature Extraction ◽  
Geomagnetic Field ◽  
Flight Vehicle ◽  
Match Probability ◽  
The Real ◽  
Geomagnetic Data ◽  
Better Than

In this paper, some improvements in feature extraction for geomagnetic matching are made. Geomagnetic entropy is extracted from the total intensity of the geomagnetic field and its performance for navigation is tested with real geomagnetic data. The matching progress is divided into two phrases: rough matching and precise matching. In the rough matching phase, a sub-region that includes the real position is obtained by using the total intensity of the geomagnetic field as the matching feature. The entropy is applied to precise matching in the sub-region to obtain the final result. Simulations show that the navigation effect is significantly improved with the entropy as an assistant feature. The combined match probability is much better than the results derived from those using only total intensity as the matching feature. This is especially true when the flight vehicle passes through an area without abundant magnetic information.

Sign in / Sign up

Export Citation Format

Share Document