Unified Pan-Spectrum Fitting Formula for Suprathermal Particles

 
Pan-spectrum Fitting Formula
for Suprathermal particles
 
Zixuan Liu
1
, Linghua Wang
1
, Robert F. Wimmer–
Schweingruber
2
, S
a
m Krucker
3,4
, and Glenn M.
Mason
5
 
1
School of Earth and Space Science, Peking University
2
Institute of Experimental and Applied Physics, University of
Kiel
3
Space Sciences Laboratory, University of California, Berkeley
4
Institute of 4D Technologies, University of Applied Sciences
Northwestern Switzerland
5
Applied Physics Laboratory, Johns Hopkins University
 
EGU zoom meeting, May 6th, 2020
 
Outline
 
Introduction
Pan-spectrum
 
formula
 
&
 
Fitting
 
method
Applications
Summery
 
and
 
discussion
 
Introduction
 
Spectrum
 
formulae
 
for
 
suprathermal
 
particles
 
Classic
 
Double-power-law:
 
Ellison-Ramaty
 
function
 
(
Ellison
and Ramaty, 1985
)
:
 
Band
 
function
 
(
Band
 
et
 
al.,
 
1993)
:
 
Kappa
 
distribution
 
(e.g.,
 
Maksimovic et al., 2005; Livadiotis
and McComas, 2010; Tao et al., 2016 
)
:
 
High
 
energy
 
tail
with
 
power-law
distribution
 
When
 
κ
 
tends
 
to
infinity,
 
it
 
becomes
a
 
Maxwellian
distribution
 
Motivation
 
Unify
 
these
 
commonly-used
 
spectrum
 
formulas
to
 
make
 
fitting
 
more
 
general
Provide
 
more
 
abundant
 
and
 
accurate
 
spectrum
information
Improve
 
the
 
fitting
 
method
 
by
 
considering
 
the
energy
 
uncertainties
 
Pan-spectrum
 
formula
 
Variants
 
Fitting
 
method
 
Test
 
data
 
The red solid, dashed and dotted curves indicate the
boundaries of 1
σ, 2σ 
and 3
σ 
confidence regions
 
Applications
 
for
 
model
 
selection (
e.g., West et al., 2012
)
 
More
 
Summery
 
and
 
discussion
 
 
Slide Note
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Unifying spectrum formulas for suprathermal particles, the proposed pan-spectrum formula provides a versatile fitting method encompassing classic double-power-law, band function, and kappa distribution. Motivated by the need for more accurate spectrum information, the formula introduces five parameters for fitting enhancement and takes into account energy uncertainties. This innovative approach aims to advance the understanding of particle distributions in astrophysical environments.

  • Spectrum Formulas
  • Fitting Method
  • Suprathermal Particles
  • Pan-Spectrum
  • Particle Distribution

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  1. Pan-spectrum Fitting Formula for Suprathermal particles Zixuan Liu1, Linghua Wang1, Robert F. Wimmer Schweingruber2, Sam Krucker3,4, and Glenn M. Mason5 1School of Earth and Space Science, Peking University 2Institute of Experimental and Applied Physics, University of Kiel 3Space Sciences Laboratory, University of California, Berkeley 4Institute of 4D Technologies, University of Applied Sciences Northwestern Switzerland 5Applied Physics Laboratory, Johns Hopkins University EGU zoom meeting, May 6th, 2020

  2. Outline Introduction Pan-spectrum formula & Fitting method Applications Summery and discussion

  3. Introduction Spectrum formulae for suprathermal particles Ellison-Ramaty function (Ellison and Ramaty, 1985): Classic Double-power-law:

  4. Band function (Band et al., 1993): Double-power-law with a gradual energy transition Transition energy is defined as: ???= ?2 ?1??

  5. Kappa distribution (e.g., Maksimovic et al., 2005; Livadiotis and McComas, 2010; Tao et al., 2016 ): High energy tail with power-law distribution When tends to infinity, it becomes a Maxwellian distribution

  6. Motivation Unify these commonly-used spectrum formulas to make fitting more general Provide more abundant and accurate spectrum information Improve the fitting method by considering the energy uncertainties

  7. Pan-spectrum formula We require its first derivative to satisfy: ? ln? ? ln? we come up with the tanh function: ? ln? ? ln? 2 Integrate it and we get the pan-spectrum (PS) formula: = ?1, ?2, ? ?0 ? ?0 = ?1+ ?2 +?1 ?2 ? ln? ln?0 2 tanh 2 ?1 ?2 ? ? ? ?0 ? = ?? ?11 + It accidentally appears to have a form close to the empirical Nuker law (Lauer et al., 1995).

  8. 5 parameters: ?,?1,?2,?0and ?

  9. Variants

  10. Fitting method In non-linear least-square algorithm, the reduced chi-square statistic is usually defined as: ? 2 ?? ? ??,? ??? 1 2= ?? ? ? 2 ?=1 where ? and ? are number of data points and parameters, ???is the standard deviation of ??, and ? = ?1,?2, ,?? is the vector of unknow parameters. If both ??and ??are not precise, the reduced chi-square statistic can have the form defined as: ? 2 ?? ? ??,? ??? 1 2= ?? ? ? 2??? 2+ ??? 2 ?=1 =?? ?? ?=?? where ???

  11. Test data The red solid, dashed and dotted curves indicate the boundaries of 1 , 2 and 3 confidence regions

  12. Applications for model selection (e.g., West et al., 2012)

  13. More

  14. Summery and discussion We propose a PS fitting formula for suprathermal particles measured in space, with 5 parameters: ?,?1,?2,?0and ? It incorporates the single-power-law, CDPL and ER functions, as well as the Kappa and Maxwellian distributions It provides an accurate transition energy and the sharpness of transition region It considers the uncertainties both in J and E With PS fitting, we are able to compare the spectral feature of different suprathermal particles, and quantitatively examine the interplanetary evolution of the spectral shape of solar suprathermal particles in the future.

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