Astron. Astrophys. 362, 383-394 (2000)
4. Derivation of moment expressions
Application of the above theory requires information on the single
particle distribution function , that
describes the propagation of a single injected particle. More
precisely, moments of f are needed. These have been calculated
analytically by Conway et al. (1998) for the case of non-relativistic
electrons in a constant magnetic field
. Here we develop the use of the
preceding theory by using those results.
4.1. Stochastic variables and single particle moments
A single particle distribution function,
, µ, s;
, ,
, ,
describes the distribution associated with a single particle, that was
injected at time , with energy
, pitch angle cosine
at position
. We will consider the case where the
background density distribution is arbitrary but the magnetic field
strength is constant. For this case, MacKinnon & Craig (1991)
showed that the Fokker-Planck equation is equivalent to 3 coupled
Stochastic Differential Equations (SDEs), also known as Îto
equations:
![[EQUATION]](img75.gif)
where . These express the progress
of a particle as a series of increments in each of the dependent
variables: ,
and
(or z, v and
µ in MacKinnon & Craig 1991). The hat symbol is used
to emphasise that these variables are stochastic variables .
Stochastic variables do not necessarily have a given value at a given
time; they have a distribution of possible values that is described by
the single particle distribution .
Each equation contains a dt term; this represents a
conventional deterministic change in that variable with the
independent variable t. The
equation also contains a term; this
term represents a stochastic change in
in an infinitesimal time step
dt. is known as a Wiener
process, which formally is a (Dirac) delta-correlated white noise time
series. It can be defined in a number of other ways. For example, it
can be considered as the limit of a discrete white noise time series
of time-step , as
. Integration of
from 0 to time t gives
, which is a white noise, normally
(Gaussian) distributed stochastic variable with mean 0 and variance
. To clarify the meaning of
, it is helpful to consider how it
would be implemented in a numerical code. Let the code's time-step be
, and let
be the coefficient of dt in
the equation. The
equation is implemented by adding
to the previous
value, plus a zero-mean,
variance 2, Gaussian distributed random number multiplied by
. (Note the convention of the Wiener
process having a variance of 2, rather than 1).
The presence of the Wiener process is only explicit in the
equation, though
appears in the
equation, making
a stochastic variable also. If the
density n is not spatially uniform, then the density at the
particle's position will become a
stochastic quantity. This means that, in general,
is also a stochastic variable. If
the density is uniform however, then the
equation becomes deterministic and
can be integrated to give an explicit function of time. This is a
tremendous simplification, as it makes the system of equations
(nearly) linear, and thus easily soluble. The same simplification can
be made for the non-uniform density if the path depth P is used
as the independent variable instead of t. The cost is of course
that the time dependence is no longer explicit. Changing from t
to P yields the following set of equations:
![[EQUATION]](img90.gif)
where and
. The middle equation can be
integrated straightforwardly, allowing the appearances of
in the first and second equations to
be substituted with an explicit function of P. This means that
these equations are essentially linear in nature (despite the
appearance of in the stochastic
term). The correspondence of the notation of Conway et al. (1998) to
the present notation (the right hand sides) is as follows:
, ,
where is the path depth (integrated
along a particle's path) required to stop a particle of initial energy
.
It is clear that is a
deterministic function of P. In other words, it has a mean that
is a function of P and always has zero variance. The physical
reason for this deterministic relationship is that the energy of the
fast particle is assumed to be much greater than the thermal energies
of the background particles. As a result it is pulled inexorably back
into the background distribution. Once a particle's energy nears the
thermal energy, neglected terms in the fast particle Fokker-Planck
equation will become important, and this treatment will no longer be
appropriate. Contrast this with situation when the µ
distribution is far from being isotropic, e.g. for a directed beam
with (zero pitch angle). As can be
seen from the equation in (11), the
stochastic term vanishes for this case, and the deterministic term
pulls to lower values. As this
happens, the stochastic term grows, and by the stopping time,
will in fact b be distributed
uniformly, i.e. the particle velocity will have an isotropic
distribution.
Now that stochastic variables have been introduced, it is much
easier to interpret the meaning of the expectation operator. For
example, is the expected pitch angle
cosine for a particle with given injection parameters
( ) at a time t after its
injection. Similarly, is the
particle's expected location. The spread about this position is
measured by . Similar expressions
can be used when working with path depth P as the independent
variable. The moments denoted by
represent averages over the transports effects, together with the
initial distribution, weighted according to the cross-section of
interest .
4.2. Time independent: arbitrary density
The results below apply to the case of continuous steady injection of
a distribution of electrons. So as to remain general to any density
distribution, we will work with column depth
(i.e. density integrated along the
magnetic field). We wish to answer the following questions: 1) Where
is the centroid of the HXR emission? 2) What is the apparent size of
the HXR source? 3) Where is the electron distribution's energy mainly
deposited? 4) What is the extent of this energy deposition region? We
will answer the first two questions in detail, but just state the
results for the last two, as the calculations involved are very
similar.
Before proceeding, we quote the main results of Conway et al.
(1998) in the notation of this paper, adding terms that generalise
those results, which assumed injection at
, to have injection at
:
![[EQUATION]](img104.gif)
where and the stopping path
depth is . It is interesting to note
that the final ( ) spread of the
electrons' positions in terms of column depth N is given by
![[EQUATION]](img108.gif)
So for a completely directed, zero pitch angle
( ) monoenergetic beam, this spread
will be , which is about a quarter
of the stopping depth in terms of .
For a distribution with only pitch
angles initially ( ), the final
spread is . Note that in using such
expressions to make rough estimates of HXR source sizes or positions
at photon energy ,
should be used instead of
. This leads to smaller values for
such quantities.
Inserting the above expressions into (7), changing variable from
path depth P to energy and
using the Bethe-Heitler cross-section (8) will result in having to
deal with integrals of the form
![[EQUATION]](img117.gif)
where are integers. The second
integral, which is more convenient to evaluate, is obtained by
reversing the order of integration of E and
. Explicit higher and lower energy
limits, and
respectively, are placed on the
injected distribution function here because we will see later that the
spatial HXR variance can become infinite if electrons of infinite
energy are present. The practical justification for assuming upper and
lower cutoffs is discussed in Sect. 4.3. To proceed from here
requires assumptions to be made about the form of h. We will
assume that the distribution is a power law, and that it is separable
in and
, i.e. it can be written as follows
. Here
, where
is commonly used electron flux
power law index. is defined so that
the total number of electrons injected per unit time is given by
![[EQUATION]](img126.gif)
Evaluating the integral of (15)
yields
![[EQUATION]](img127.gif)
where . By splitting the integral
at , it can be evaluated to
![[EQUATION]](img130.gif)
where and
. The function
is the same as the standard Beta
function, except that its limits are replaced by x and
y:
![[EQUATION]](img134.gif)
At this point we can make two simplifying assumptions, which are
commonly made elsewhere in HXR bremsstrahlung calculations:
and the photon energy of interest
is higher than the lower cutoff of the injected distribution, this
means we can replace all occurrences of
with
. This results in a much simpler
expression:
![[EQUATION]](img136.gif)
Notice that is simply the HXR
thick target expression.
We are now in a position to calculate the desired moments. Firstly,
from (11) we can write that, for
:
![[EQUATION]](img139.gif)
Therefore, the average pitch angle of the electrons emitting HXRs
is simply:
![[EQUATION]](img140.gif)
which is actually independent of the photon energy
.
is the average pitch angle of the injected distribution.
To calculate the spread of pitch angles, we need to calculate
, which for
is given by
![[EQUATION]](img144.gif)
In a similar fashion, the following two column depth moments can be
shown to be:
![[EQUATION]](img145.gif)
where
![[EQUATION]](img146.gif)
Note that remains finite only
for , and
for
. The appearance of a factor
in a denominator does not
necessarily mean that a moment is undefined at
, though the above expressions
are undefined. Careful consideration of the integration in
these cases can yield well-behaved mathematical expressions.
Assuming an upper cut-off, for whatever reason, can lead to
counter-intuitive results, especially in light of the usual situation
where it is assumed that only a lower cutoff is important. One
surprise is that the size of a HXR source does not simply scale as
. This is illustrated in Fig. 1
for an isotropic source, for a range of photon energies, and for three
upper cut-off values, keV,
keV and
keV.. The departure from
scaling is most pronounced for low
values of . The tangent of these
curves only accords with a line of gradient
for large
and
. When
becomes a sizeable fraction of
, the source size can even decrease
with photon energy. This behaviour was observed for the 13th Jan. 1992
(Masuda) flare (Masuda et al. 1995), which had a hard (low
) spectrum. There are two
explanations for this counter-intuitive effect. One is simply that for
close to
, only the highest energy electrons
contribute, and do so only for a short time, during which they cannot
move too far. Secondly, the relatively long collisional time for these
higher energy electron means that those with large pitch angle
electrons will take longer to diffuse away from their starting
position than electrons with lower energy. This can be seen from the
expression derived for ` ' in Conway
et al. (1998).
![[FIGURE]](img183.gif) |
Fig. 1a-f. Plots of the apparent size of a HXR source in terms of: column depth, i.e. ; and , the spatial extent along a loop of constant density cm-3. For the largest values, L is unrealistically large, which can be interpreted as being too large. Curves for three different values are shown on each plot: is the upper (solid) curve, is middle (dotted) curve and is the lowest (dashed) curve. The injected distribution is isotropic, i.e. and .
|
The heating moments are easier to calculate and the relevant
expressions for µ N, where
, are
![[EQUATION]](img186.gif)
It is interesting to note that the pitch angle moments are
independent of the electron energy spectrum. In contrast, the column
depth moments can be very sensitive to assumptions made about the
electron spectrum, especially the upper cutoff
. In general, this will correspond
to a real cutoff in the electron distribution. However, in certain
applications an effective upper cutoff may be appropriate, as
previously discussed in relation to HXR moments. For example, in
computing the H impact polarisation
due to a particle beam, knowledge of pitch angle moments is needed in
a restricted range of depths for particular electron energies (Henoux
& Vogt 1998).
Plots of the average column depth of heat deposition
and the spread of depths
are shown for selected values of
,
,
and , in Figs. 2a, 2b and
2c.
![[FIGURE]](img190.gif) |
Fig. 2a-d. Plots of the mean column depth of energy deposition (solid) and the standard deviation (dashed) for a variety of parameters.
|
The sensitivity of spatial moments to high energy features in the
spectrum, and also their insensitivity to the lower cut-off, could
lead to new diagnostics of otherwise unobservably high energy
electrons. To achieve this, calibration of the relationships is needed
from observations where both the spatial and spectral information is
available. Also, any effective upper cut-off, as discussed above, must
be carefully considered in applying the results in this way.
4.3. Cutoffs
It is clear that cutoffs in the electron spectrum have to be assumed
to avoid unphysically infinite moments. We now discuss what determines
these cutoffs in practice, giving particular attention to the upper
cutoff because it will often be the most problematic in applying the
present theory. It is important to realise that the value of the upper
cutoff, , need not arise from basic
physics alone, but can often depend on how moments are deduced from
the observations. As such, the relevance of the considerations
discussed below can vary from application to application. Another
point to note is that a literal cut-off is not necessarily required, a
more gradual roll-over, or a break to a different spectral index can
serve the same purpose.
The most obvious justification for assuming a cutoff in the
electron spectrum is if there is evidence for one in the observed HXR
photon spectrum. However, lower cutoffs are usually masked by thermal
emission and upper cutoffs are only rarely observed. An upper cutoff
at a few tens of MeV was reported by Trottet et al. (1998) for the
flare of 11 June 1990. In general,
will probably be less than 20 keV and
will be greater 1 MeV; though
more restrictive limits will be possible for some large flares.
Depending on the value of , and the
moment in question, one or other of these cutoffs may dominate the
moment expressions, and the other may be set to its extreme value
(i.e. zero or infinity).
In many cases of interest, an effective cutoff can be more
important than any real cutoff in the electron spectrum. For example,
an upper cutoff of 10 MeV in the electron spectrum cannot
possibly be relevant in determining the apparent size of a coronal HXR
(say 10-100 keV) source. This is because electrons at energies of
a few MeV will contribute much less to this emission than electrons at
energies of a few tens of keV. The effective upper cutoff in this case
would depend on both the observed photon energy range and the energy
corresponding to the column depth of the coronal material. Similarly
in applying the results to H impact
polarisation, only electrons in certain ranges of energy and depth are
relevant, thus introducing effective lower and upper cutoffs.
4.4. Time dependent: constant density
The time dependent case can only be considered if the density is
uniform in space, because then the path depth P is a
deterministic function of time t:
![[EQUATION]](img192.gif)
where is the stopping time. For
the same reason, N and s are simply related to each
other: . Given the extra freedom of
choosing how the injection function h varies with time,
specific results can only be obtained by making further assumptions.
Here we are only concerned with calculating
and
, which tells us the time, and the
time interval, during which the HXR emission at a particular photon
energy will take place. These times
are defined in relation to the moments
and
, which are obtained by integrating
multiplied by
and
respectively, over all
and also
. Although it is possible to
calculate the time-dependent moments of µ and s
(E is deterministic in time here), as defined in (5), doing so
requires more information than the first two temporal moments of
h provide. Further assumptions must be made relating to
specific circumstances in order to give useful results, so we will not
consider this case in this paper.
Firstly, the temporal moments of the HXR intensity distribution,
are defined:
![[EQUATION]](img201.gif)
remembering that is the HXR
intensity as discussed in Sect. 2. It is therefore clear that the
normalised moments in time are given by:
and
.
Using (5) to expand (25) with the Bethe-Heitler cross-section given
by (8) will result in time integrals (in t) of the form:
![[EQUATION]](img205.gif)
where E (and therefore ) is
a function of . Changing variable to
E using the relation
![[EQUATION]](img207.gif)
gives the integral in the following form:
![[EQUATION]](img208.gif)
This integral must also be integrated over
and
. The integration over
can be written in terms of
introduced in (15). Doing so
gives:
![[EQUATION]](img210.gif)
The integral over simply means
replacing instances of with
. Doing this assuming that
and using the expression for
q in (17), gives the final results:
![[EQUATION]](img214.gif)
where
![[EQUATION]](img215.gif)
This result is valid for . A more
general expression can be calculated using the general expression for
q in (16). Note also that the form used for h above
assumes that the distribution is separable in
and
- i.e. the injection spectrum is
time-independent. The time delay between the HXR flux's peak at photon
energy and the peak in the rate of
electron injection is simply . This
is clearly proportional to which
itself is proportional to .
Numerical evaluation of the factor involving
show that it decreases with
. This is expected as larger
means relatively more low energy
electrons, and so shorter electron life-times. The same conclusions
can be made for the width of the HXR peak of emission,
. Note that all of these conclusions
can be radically changed, and become much less intuitive, when
approaches 5 and the upper cut-off
(or break in the power law) is not much larger than
.
© European Southern Observatory (ESO) 2000
Online publication: October 30, 19100
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