potential of two or more spheres
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Paper by Philip T. Metzger and John E. Lane (The Open Applied Physics Journal, 2009), downloaded into Phil's transmission lines folder. It gives the full series of image charges for two or more conducting spheres, building on Jackson's single-sphere treatment. It develops a charge normalization that improves truncated low-order solutions via matrix inversion, and a gradient search to optimize a set of point charges for M spheres.
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32 The Open Applied Physics Journal, 2009, 2, 32-48
1874-1835/09 2009 Bentham Open Open Access
Electric Potential Due to a System of Conducting Spheres
Philip T. Metzger*,1 and John E. Lane2
1NASA Granular Mechanics and Regolith Operations Laboratory, Mail Code: KT-D3, Kennedy Space Center, FL
32899, USA
2ASRC Aerospace, MS: ASRC-24, Kennedy Space Center, FL 32899, USA
Abstract: Equations describing the complete series of image charges for a system of conducting spheres are presented.
The method of image charges, originally described by J. C. Maxwell in 1873, has been and continues to be a useful
method for solving many three dimensional electrostatic problems. Here we demonstrate that as expected when the series is truncated to any finite order N, the electric field resulting from the truncated series becomes qualitatively more similar
to the correct field as N increases. A method of charge normalization is developed which provides significant
improvement for truncated low order solutions. The formulation of the normalization technique and its solution via a
matrix inversion has similarities to the method of moments, which is a numerical solution of Poisson’s equation, using an integral equation for the unknown charge density with a known boundary potential. The last section of this paper presents a gradient search method to optimize a set of L point charges for M spheres. This method may use the image charge series
to initialize the gradient search. We demonstrate quantitatively how the metric can be optimized by adjusting the locations and amounts of charge for the set of points, and that an optimized set of charges generally performs better than truncated
normalized image charges, at the expense of gradient search iteration time.
INTRODUCTION
The first year graduate physics student is likely to be
introduced to the problem of calculating the electric field
surrounding a conducting sphere in the presence of a point charge during the first few weeks of a standard course in electromagnetism. When this problem is extended to include a cluster of spheres, things get interesting, as well as more difficult. One application of this problem may be found in
nuclear physics. Nuclear physicists sometimes need to sum
the probability of nuclei breaking into every possible configuration of clusters, each cluster being modeled by a set of charged spheres, and this entails a large number of configurations, each of which must be solved individually. The probability of the nuclei breaking requires a calculation
of the stored energy of the electric charges, which depends
upon their actual distribution on the spheres, and it is computationally expensive for such a large number of configurations. Therefore, they use the image charge method truncating the series of image charges for computational efficiency, but at the cost of some accuracy.
Another application involves a proposed spacecraft
electrostatic radiation shield [1], made up of a cluster of conducting spheres surrounding the spacecraft. Similarly, a lunar radiation shield [2] study incorporated conducting spheres of various sizes and potentials. In order to simulate
the benefits of a radiation shield configuration, the electric
field is needed at every location around the spacecraft in order to calculate the trajectories of the charged particles that constitute the cosmic radiation in space. The electric field throughout space depends upon the actual distribution of
*Address correspondence to this author at the NASA Granular Mechanics
and Regolith Operations Laboratory, Mail Code: KT-D3, Kennedy Space Center, FL 32899, USA; E-mail: Ph ilip.T.Metzger@nasa. gov charge on the spheres, and it is computationally expensive to
(first) solve for the actual distribution of charge, and
(second), integrate the contributions to the electric field in
each location of space resulting from all the portions of the surfaces of the charged spheres. For computational efficiency, we use the image charge method truncating the series of image charges so that only a finite set of point charges contribute to the electric field in all locations of
space around the spheres, and thus summing these
contributions is a simple sum over only a finite set of point charges rather than an integral over a set of surfaces.
In many applications it is computationally expensive to
solve the exact distribution of charges since the charge
distribution on the spheres is not uniform when multiple
charged spheres interact with one another. As spheres move increasingly close to one another, the charges on each sphere are pushed around by the electric fields of adjacent spheres. Since the electric fields from adjacent spheres are also changing, as their own charge distributions are perturbed, the
final distribution of charge on the spheres becomes difficult
to calculate.
A mathematical technique that can lead to an exact
solution in many electrostatic problems is based on conformal mapping in the complex plane. Solving Laplace’s
equation by conformal mapping has been primarily restricted
(until recently) to two-dimensional problems, or to three-dimensional problems that have rotational symmetry, or to cases where the Separation of Variables method can be applied [3, 4]. These cases do not encompass the problem solved in this paper, charged spheres placed arbitrarily in
three-dimensional space, which is not generally reducible to
a two-dimensional problem or amenable to the Separation of Variables. However, the techniques of conformal mapping are advancing at a rapid pace, extending the scope of
Electric Potential Due to a System of Conducting Spheres The Open Applied Physics Journal, 2009, Volume 2 33
problems that can be solved by this method [5-7]. At least
some of these advances involve infinite products and/or infinite series as a part of the solution, and therefore may provide no advantage in computing a numerical solution in electrostatics. However, that waits to be seen, and this paper
makes no attempt to evaluate the rapidly advancing methods
in conformal mapping.
Another technique that is of general usefulness in three-
dimensional electrostatic problems is the Method of Moments [8, 9]. The Method of Moments can be used to solve Poisson’s
equation by finding the unknown charge density on the surface
of a conductor when the potential of the conductor is known.
Fairly large matrices can result which are inverted to find the surface charge density. A key strategy to this method is find useful basis functions that can be solved analytically, thus reducing the number of matrix elements that need to be solved
numerically. The Method of Moments is a powerful method
which can be used to solve a large variety of electrostatic, as well as general electromagnetic problems. For the specific problem discussed in this paper, the Method of Images leads to a more direct approach, which is simpler conceptually and requires less complex computer code to implement as compared
to the Method of Moments. Also, since the problem addressed
by this paper generally involves three-dimensional geometry without rotational symmetry, the Method of Images is a simpler solution method compared to a method based on conformal mapping into the complex plane.
IMAGE CHARGE SOLUTIONS
The Method of Images [10, 11] is a convenient procedure
for finding the electric potential due to a system of conductors and point charges without having to solve a differential equation, where the solution is guaranteed to be a solution of Laplace’s equation in the exterior region . The
work involved with this method is to simply match boundary
conditions via vector algebra using a finite or infinite series
of point charge solutions. However, finding the necessary
image point charges is not necessarily trivial. Since image charge solutions generally involve an infinite series of images, except in very simple cases, truncation of the series will always result in a less than perfect solution.
Point Charge Near a Conducting Sphere
The simplest example problem that will help lead into the
general problem of calculating the electric potential due to a system of conducting spheres, is that of a single point charge outside of a conducting sphere of radius a held a constant
potential V
0. This problem is presented in detail in Jackson
[11], but will be repeated below in brief to serve as an introduction into the more difficult cases to be considered next.
The point charge has a charge q and is a distance d from
the sphere’s center, noting that d > a The potential can be
written as that due to one real charge plus two image
charges:
U(r)=1
40q0
r+q1
rbex+q
rdex
=aV0
r+q
40
rbex+1
rdex
(1) where the charges are placed on the x-axis for convenience,
without loss of generality and where ex denotes the unit
vector along the x-axis, as shown in Fig. ( 1). The first term is
that due to an image charge at the center of the sphere,
proportional to sphere’s potential. The second term is a
single image charge that is induced at r = b ex by the
proximity of the real charge (the third term), located at r =
dex. Note that b < a. The magnitude of the image charge is
designated as q.
Fig. (1). Point charge q a distance d from a conducting sphere of
radius a.
The solution for the position and magnitude of the image
charge, as described in the references [11-13] is:
b=a2/d ( 2 a )
=a/d ( 2 b )
A demonstration of the single conducting sphere and single point charge is shown in Fig. ( 2a) with a = 1.2, d =
2.5, and V
0 = 0, with the image charge parameters arbitrarily
set to = -1 and b = 0. In Fig. ( 2b), and b are set to the
correct values, according to Eq. (2).
Image Charges for Two Conducting Spheres
Fig. ( 3) shows two conducting spheres at different
constant potentials, V1 and V 2. The electric field potential can
again be solved by use of image charges (see reference [14]
for historical insights). The result is an infinite series of image charges inside of each sphere where the magnitude decreases with increasing order. As the order increases, positions of the image charges move closer to the inside surface of the sphere. No image charges appear outside of
the spheres, in accordance with Laplace’s equation and the
uniqueness theorem.
The strategy (as well as similar notation) behind solving
this problem is based on Jackson [11]. Because the electric field potential can be decomposed into a sum of fields due to
image point charges, the solution of the single sphere with a
single external point charge, as described in the previous section, can be applied in an iterative fashion to solve this problem.
The zeroth order image charges are located at the center
of each sphere:
q1(0)=40a1V1 (i = 1) (3a)
q2(0)=40a2V2 (i = 2) (3b)
b
d q q
a V0
x
34 The Open Applied Physics Journal, 2009, Volume 2 Metzger and Lane
As the distance d between spheres increases, the effect of
the higher order terms is diminished. For many applications
where the sphere separation is much greater than the sphere radius, the zeroth order solution will suffice and higher order terms will not be necessary.
Fig. (3). Two conducting spheres at different constant potentials. First order image charges are determined one at a time
for each ith sphere ( i = 1, 2 in the current case). The diagram
for determining the i = 1 first order image charge is shown in
Fig. ( 4a). Comparing this figure with Fig. ( 1) with the sphere
grounded and Eqs. (2), lead immediately to the value and
location of the first order charge:
q1(1)=a1
d2(0)q2(0)
b1(1)=a12
d2(0)
d1(1)=db1(1) (i = 1) (4a)
Similarly, the i = 2 first order image is determined from
Fig. ( 4b): (a)
(b)
Fig. (2). A single point charge near a conducting sphere at z = 0 along the x-y plane, using Eq. (1) with V0 = 0. The potential U( r) is pseudo
colorized with a 3D plot on the left and corresponding contour plot on the right. The dotted white circle represents the correct potential on the
surface of the sphere. ( a) = -1, b = 0; ( b) and b are set according to Eq. (2).
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a1V1
xa2V2
d
Electric Potential Due to a System of Conducting Spheres The Open Applied Physics Journal, 2009, Volume 2 35
q2(1)=a2
d1(0)q1(0)
b2(1)=a22
d1(0)
d2(1)=db2(1) (i = 2) (4b)
(a)
(b)
Fi
g. (4). First order image charges: ( a) i = 1; ( b) i = 2.
This process continues in an iterative fashion, as
demonstrated in Fig. ( 5a-i), which shows the step by step
determination of zeroth order through third order terms. Note
that grounding a sphere is perfectly valid, since the zeroth order image charges account for the sphere’s potential.
The magnitude and positions of the kth image charges
belonging to the ith sphere can be summarized by the
following set of iterative formulas:
qi(k)=ai
dj(k1)qj(k1)
bi(k)=ai2
dj(k1)
di(k)=dbi(k) (5)
where i = 1, 2 and j = 1, 2, with j i. As is evident from
Figs. ( 4, 5), bi(k) is the offset of the kth order image charge
from the ith sphere’s center in the direction of the jth sphere.
The parameter d i(k) is redundant, even though it is useful in
developing the recursive set of formulas summarized in Eq.
(5). Eliminating d i(k) results in a minimum two parameter
set, describing the magnitude and position of all image charges in the two-sphere system:
qi(k)=ai
dbj(k1)qj(k1)
bi(k)=ai2
dbj(k1) (6) where bi(0) = 0. The electric potential for the two sphere
system, using terms up to Nth order is now:
U(r)=1
40q1(k)
rr1(k)+q2(k)
rr2(k)k=0N
k=0N
(7)
where the zeroth order charges are given by Eq. (3). In the
special case where sphere-1 is centered at the origin of the
xyz coordinate system and sphere-2 is centered at a distance
d along the x-axis, the location vectors in Equation (7)
simply to:
r1(k)=b1(k)ex, r2(k)=d2(k)ex (8)
where ex is the unit vector along the x-axis.
Charge Normalization of Two Conducting Spheres
The previous section shows that by increasing the order
of the solution N, the voltage Vk on the surface of the kth
sphere converges to the correct constant value at all points on the surface. For any specific practical application, one simply decides on a value N that should satisfy the precision
requirements for the application. For a given precision, the number of image charges needed to achieve that precision can be reduced by an order or more using an optimization
method based on normalization of the charge. In this way for
example, a normalized first order solution of two image charges per sphere should be approximately more accurate than a second order solution without normalization. The concept of parameter optimization is common to many fields involving use of a truncated infinite series.
Charge normalization is a special case of optimization
where the voltage specified in the zeorth order charges, Eqs. (3a) and (3b) are modified by a scaling parameter:
q1(0)=40a11V1() (9a)
q2(0)=40a22V2 () (9b)
By adjusting the ’s, the truncated solution given by Eq.
(7) can be optimized so that the voltage on the sphere surface U(r = r
k + ake) Vk for k = 1 and 2 (the next section will
consider the general case of any number of spheres). This can be summarized by the following matrix equation:
U(r1+a1e)
U(r2+a2e)
=C1
2
=V1
V2
(10)
where the components of C are obtained from Eq. (7) by re-
ordering terms so that the qk(0)’s can be grouped and
factored. The components of C are then:
c11(,)=q1(k)
a1eb1(k)exk=0
k evenN
+q2(k)
a1ed2(k)exk=1
k oddN
(11a)
c12(,)=q1(k)
a1eb1(k)exk=1
k oddN
+q2(k)
a1ed2(k)exk=0
k evenN
(11b)
xa1 q1(1)b1(1)
q2(0)d1(1)d2(0) = d
d1(0) = d
d2(1)
q1(0)b2(1)
a2q2(1)
x
36 The Open Applied Physics Journal, 2009, Volume 2 Metzger and Lane
(a) (b)
(c) (d )
(e) (f )
(g) (h )
(i)
Fig. (5). Demonstration of image charge series for two conducting spheres using Eq. (5): ( a) zeroth order term; ( b) first order term, i = 1; ( c)
first order term, i = 2; ( d) second order term, i = 1; ( e) second order term, i = 2; ( f) third order term, i = 1; ( g) third order term, i = 2; ( h) sum
of all Nth order terms from Eq. (7); (i ) exact solution using infinite series. /MT86/MT49
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Electric Potential Due to a System of Conducting Spheres The Open Applied Physics Journal, 2009, Volume 2 37
c21(,)=q1(k)
a2e+d1(k)exk=0
k evenN
+q2(k)
a2e+d1(k)exk=1
k oddN
(11c)
c22(,)=q1(k)
a2e+d1(k)exk=1
k oddN
+q2(k)
a2e+b2(k)exk=0
k evenN
(11d)
where the unit vector e is a function of the spherical angles
and :
e=sincos
sinsin
cos
( 1 2 )
The constants computed in Equations (11a) through (11d)
apply to a single arbitrary point on the surface of a sphere determined by the angles
and . These values need to be
integrated over the entire sphere surface in order to complete
the normalization procedure. A simple approximation to that
integration can be obtained by averaging the cij’s over
random values of the angles, as follows:
C=C11C12
C21C22
=1
NRc11(sn,un2)
n=1NR1
NRc12(sn,un2)
n=1NR
1
NRc21(sn,un2)
n=1NR1
NRc22(sn,un2)
n=1NR
(13)
where un is a uniform random number in the interval of 0 to
1, and s n is a sinusoidally distributed random number in the
interval of 0 to 1. A sinusoidally distributed random number
sn can be generated from a normally distributed random
number un by the following algorithm:
sn=cos1(12un)
(14)
To solve for the ’s, Equation (10) is inverted:
1
2
=C1V1
V2
(15)
An example of the benefit of optimization by charge
normalization is revealed by Fig. ( 6), where d = 3.5, a 1 = 1.5,
a2 = 1, V 1 = 0.6, and V 2 = 0.8. Again the dotted white circles
represent the location of the correct values of the sphere voltages V
1 and V 2 in the 3D plot space. As can be seen by
the voltage contour plots, alignment with the dotted circles representing the spheres, an
N1order solution with charge
normalization optimization appears as good or better than an Nth solution without optimization.
IMAGE CHARGES FOR M CONDUCTING SPHERES
The concepts of the previous section can now be
extended to the general case of M spheres. In order to
proceed, the notation of Jackson [11] will be aba ndoned and
replaced with a notation more suitable for the general case.
Jackson’s notation is efficient for representing the general
case of N th order, but practically restricted to only two
spheres. This new notation is efficient for representing M
spheres, but tends to become unwieldy for N > 3. Never-the-
less, this notation provides the a roadmap to those formulas describing higher order image terms. The zeroth order image charges, analogous to the
notation of Eqs. (3), can be alternately expressed by:
qi=40aiVi (16)
where the index i corresponds to the i th sphere of M spheres.
The number of zeroth order image charges is equal to the number of spheres, M.
The first order image charges comparable to Eqs. (4) can
be expressed as:
qij
ji=ai
rirjqj ( 1 7 a )
and is located at:
rij
ji=riai2rirj
rirj2 (17b)
where ri is the location of the ith sphere. The interpretation
of Eq. (17a) is that qij is the first order image charge inside of
sphere i located at rij that is induced by the zeroth order
image charge inside of sphere j. The number of first order
image charges is equal to M(M – 1), since for each of the M
spheres, there are M - 1 first order images contained in that
sphere. Note that in the special case where the jth sphere is
grounded (i.e., the jth sphere has no zeroth order charge), the
first order image charge induced in the ith sphere by the j th
sphere is also zero.
Now consider the second order image charges, and this
time there are M(M – 1)2 possibilities:
qijk
ji
kj=ai
rirjkqjk (18a)
located at:
rijk
ji
kj=riai2rirjk
rirjk2 (18b)
As in the first order case, the interpretation is that qijk is
the second order image charge inside of sphere i, located at
rijk, that is induced by the first order image charge qjk located
at rjk. The total number of images charges L including Nth
order for M spheres is:
LM (M1)n
n=0N
(19)
The inequality considers the case where one or more
spheres may be grounded, in which case the number of images charges is reduced, as previously discussed.
Using the above definitions for image charges and their
positions the electric potential for M conducting spheres,
analogous to Eq. (7), can be expressed by the following series:
U(r)=1
40qi
rri+qij
rrij+qijk
rrijk+
k=1
kjM
j=1
jiM
i=1M
(20)
38 The Open Applied Physics Journal, 2009, Volume 2 Metzger and Lane
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Electric Potential Due to a System of Conducting Spheres The Open Applied Physics Journal, 2009, Volume 2 39
(Fig. 6) contd…..
(d)
(e)
(f)
Fig. (6). Comparison of zeroth order through second order image method electric field potentials of two conducting spheres. The potentia l
U(r) is pseudo colorized, and is computed from Eq. (7) at z = 0 along the x-y plane without and with charge normalization using Eqs. (9) and
(15). The dotted white circle represents the correct potential on the sphere surfaces: ( a) zeroth order image term only; ( b) zeroth order term
with normalization; ( c) include first image order term; ( d) including first order terms with normalization; ( e) includes second order image
order term; ( f) including second order terms with normalization.
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40 The Open Applied Physics Journal, 2009, Volume 2 Metzger and Lane
(a) (b )
(c) (d )
(e) (f )
Fig. (7). Demonstration of image charge determinations for M conducting spheres.: ( a) M = 3 example; ( b) zeroth order images using Eq.
(16); ( c) first order images using Eqs. (17); ( d) second order images using Eqs. (18); ( e) all zeroth, first, and second order image charges; ( f)
truncated potential from Eq. (20) for M = 3 spheres and order N = 2.
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Electric Potential Due to a System of Conducting Spheres The Open Applied Physics Journal, 2009, Volume 2 41
In the two sphere case, Eqs. (20) and (7) are equivalent, as
they should be, for the same image order. This can be easily seen by noting that the summations in Eq. (20) reduce to single terms for M = 2. Fig. ( 7) demonstrates the application of the
equations discussed in this section for the M = 3 case.
Charge Normalization of M Conducting Spheres
Optimization of the potential in Eq. (20) by charge
normalization proceeds in a manner similar to that previously discussed for the two sphere case. Analogous to Eqs. (9), the voltages of the zeroth order charges are adjusted
by scaling factors
i:
qi=40aiiVi() ( 2 1 )
A truncated solution given by Equation (20) can be optimized by adjusting the i’s so that the voltage on the sphere surface
U(r = r i + a ie) Vi for i = 1 to M . This can be summarized by the following matrix equation:
U(r1+a1e)
U(r2+a2e)
U(rM+aMe)
=V
1
V2
VM
=C
1
2
M
( 2 2 )
where the components of C are obtained from Eq. (20) by re-ordering terms so that the qi’s can be grouped and factored. The
reordering is accomplished by first reversing the order of the indices of the q’s in Eq. (20), substituting in Eqs. (17a) and (18a),
then factoring out qi. For the second order case, this proceeds as follows:
U(rl+ale)=1
40qi
rl+aleri+qij
rl+alerij+qijk
rl+alerijk k=1
kjM
j=1
jiM
i=1M
=1
40qi
rl+aleri+qji
rl+alerji+qkji
rl+alelrkji k=1
kjN
j=1
jiN
i=1N
=1
40qi
rl+aleri+ qji1
rl+alerji+ak
rkrjirl+alerkji k=1
kjN
j=1
jiN
i=1N
=1
40qi1
rl+aleri+aj
rjrirl+alerji+ajak
rjrirkrjirl+alerkji k=1
kjN
j=1
jiN
i=1N
= cli
i=1N
(23)
Analogous to Eq. (13), the components of C when averaged over the surface of sphere l are:
Cli=1
NRcli(sn,un2)
n=1NR
( 2 4 )
where,
cli(,)=aiVi1
rl+aleri+aj
rjrirl+alerji+ajak
rjrirkrjirl+alerkji k=1
kjN
j=1
jiN
(25)
and sn is defined by Eq. (14). Finally, the i
’s are found by inverting C, similar to Eq. (15):
1
2
M
=C
1V1
V2
VM
( 2 6 )
An example is given in Fig. ( 8), using three spheres with the following parameters: V1 = 0.2, V 2 = 0.8, V 3 = -0.5, a 2 = 1.0, a3
= 0.7, r 1 = (0, 0, 0), r2 = (d, 0, 0), r3 = (0, d , 0), a 1 = 1.5, and d = 3.5. The significant improvement due to charge normalization
is readily apparent.
42 The Open Applied Physics Journal, 2009, Volume 2 Metzger and Lane
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Electric Potential Due to a System of Conducting Spheres The Open Applied Physics Journal, 2009, Volume 2 43
(Fig. 8) contd…..
(d)
(e)
(f)
Fig. (8). Comparison of zeroth order through second order image method electric field potentials of three conducting spheres. The potent ial
U(r) is pseudo colorized, and is computed from Eq. (20) at z = 0 along the x-y plane without and with charge normalization using Eqs. (24)
through (26). The dotted white circle represents the correct potential on the sphere surfaces: ( a) zeroth order image term only; ( b) zeroth
order term with normalization; ( c) include first order image term; ( d) including first order terms with normalization; ( e) includes second
order image order term; ( f) including second order terms with normalization.
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44 The Open Applied Physics Journal, 2009, Volume 2 Metzger and Lane
GENERAL IMAGE CHARGE OPTIMIZATION
The charge normalization described by Eq. (26) is a
special case of a parameter optimization procedure where only the magnitude of the zeroth order charge is modified so that the calculated electrical field potential matches the
actual voltage on all sphere surfaces. A more general
approach is to parameterize the position of each charge as well as its magnitude. With this approach comes the philosophy that image charges are not necessarily intrinsic to a solution, but simply provide an initial guess for position and magnitude of some number of charges inside each
sphere that will approximate a solution to Laplace’s
equation, in all space and on the surface of the spheres. The potential field due to a system of M conducting spheres can
be approximated by L point charges, where L M. The
potential from a system of L point charges is then:
U(r)=j
rrj j=1L
=j
(xxj)2+(yyj)2+(zzj)2
j=1L
(27)
In the case of L = M , the numerator of Eq. (27) is due to
the zeroth image charge of the ith sphere, as described by Eq.
(21), so that i=qi
40=aiiVi () .
The means to a general optimization approach is to define an error function. It is imperative to select a metric that when maximized or minimized will ensure that the field more accurately represents the exact field of the non-truncated series in a relevant way. In this sense, "accurately"
may be difficult to define, but we show below that it is made
easier to define by noting that the electric field in all space will be correct as long as the electric field on the surf ace of
the spheres themselves is correct. Also, (as demonstrated
below) it is obvious along the surface of the charged spheres that the field resulting from a truncated series of image
charges is qualitatively different from the correct field,
whereas the field resulting from an optimized set of charges is qualitatively more similar to the correct field. Therefore, we should expect in almost all applications that the field resulting from the optimized set of charges will more "accurately" represent the field in the relevant way. For
example, it would appear obvious seeing the qualitative
improvement that the calculated trajectories of space radiation particles will follow the correct trajectories more closely when the field is qualitatively correct rather than qualitatively incorrect. We thus propose to use a least
squares of the value of electric potential as the metric, and
we calculate it only upon the surface of the charged spheres.
We demonstrate below the quantitative improvement of this metric via the Gradient Search Method [15].
By defining an error E, based on the sum of potentials on
the surface over all M spheres, the best fit
j and r j in Eq.
(27) can be determined by minimizing the error function:
E=1
4 d
0 2 ViUi(,) []2sin d
0
i=1M
(28)
where, Ui(,)=k
(xi+aisincosxj)2
+(yi+aisinsinyj)2
+(zi+aicoszj)2
1/2
j=1L
(29)
The integral over the spherical angles and in Eq. (28)
is more formal way of describing the averaging over NR
points described in Eq. (13) and again by Equation (24). The
Monte Carlo method of randomly picking points on the
surface for evaluation can also be used here to perform the integration.
Equation (28) can be minimized by searching for the zero
of its gradient:
E=
1
x1
y1
z1
E(P)0
, where
P=1
L
x1
xL
y1
yL
z1
zL
(30)
The error E(P) is a function of 4L parameters, designated
by the parameter vector P. The problem is to find the
minimum of E(P) in 4 L dimensional parameter space. (The
difficulties associated with finding a global versus local
minimum are intrinsic to gradient search methods and will not be discussed here.) The gradient search is implemented
by the following recursion relation:
P(n+1)=P(n)μE(n) (31)
where n denotes the nth step of the recursion, and μ is the
convergence constant . Note that μ can be determined
empirically and is not necessarily a constant. For all time
steps n, if μ is too small, convergence will require an
unreasonably large number of iterations of Eq. (31). If μ is
too large, Eq. (31) may diverge, usually towards infinity, or
oscillate wildly about the solution.
The gradient of the error function in Eq. (31) is computed
as follows:
E=1
4 d
0 2 ViUi(,) []2sin d
0
i=1M
=1
4 d
0 2 ViUi(,) []2{} sin d
0
i=1M
=1
2 d
0 2 ViUi(,) [] Ui(,) {} sin d
0
i=1M
(32)
The gradient term in Equation (32) is a vector:
Electric Potential Due to a System of Conducting Spheres The Open Applied Physics Journal, 2009, Volume 2 45
Ui(,) {} i=()1
()L
(x)1
(x)L
(y)1
(y)L
(z)1
(z)L
i (33)
where,
()j ()i=Ui(,)
j
=1
(xi+aisincosxj)2
+(yi+aisinsinyj)2
+(zi+aicoszj)2
1/2 (34a)
(x)j ()i=Ui(,)
xj
=2j(xi+aisincosxj)
(xi+aisincosxj)2
+(yi+aisinsinyj)2
+(zi+aicoszj)2
1/2 (34b)
(y)j ()i=Ui(,)
yj
=2j(yi+aisincosyj)
(xi+aisincosxj)2
+(yi+aisinsinyj)2
+(zi+aicoszj)2
1/2 (34c)
(z)j ()i=Ui(,)
zj
=2j(zi+aisincoszj)
(xi+aisincosxj)2
+(yi+aisinsinyj)2
+(zi+aicoszj)2
1/2 (34d)
Fig. ( 9) revisits the three sphere example, including the
zeroth, first, and second order normalized image charge
solutions, using the same parameters from the Fig. ( 8). For
comparison, the three zeroth order charges are optimized by
the gradient search algorithm, with L = M = 3. A second
gradient search case is included for comparison with L = 4,
where two charges are located within sphere-1. By
implementing the gradient search algorithm described by
Equation (31), the point charges change in magnitude and
position to minimize the error function defined by Eq. (28). The final magnitude and charge positions are given by the
P(n) vector from Eq. (30). The initial P(0) vector is
determined by a set of image charges, three zeroth order and
one first order charge. The final solution vector P(n) is
somewhat arbitrarily determined to be solution when the
error falls below some predefined value, are the change in
error between iterations converges to zero. For comparison, the gradient search case in Fig. ( 9d) with L = 4 is
qualitatively better than the full first order case of Fig. ( 9c)
where the total number of image charges is equal to 9, and not as good as the full second order case of Fig. ( 9e) where
the total number of charges is equal to 21.
The potential U(r) is pseudo colorized, and is computed
from Eq. (20) at z = 0 along the x-y plane without with
charge normalization using Eqs. (21) and (26). The dotted
white circle represents the correct potential on the sphere
surfaces: ( a) zeroth order normalized image charges ( L = 3);
(b) zeroth order normalized image charges with gradient
search optimization, L = 3; ( c) include first order normalized
images ( L = 9); ( d) initialized gradient search with L = 4; ( e)
includes second order image order term with normalization
(L = 21).
SUMMARY AND DISCUSSION
It is desirable to improve the accuracy of the estimated
electrical field and its energy when using the image charge method. The non-truncated series of image charges gives the exact solution, so we wish to improve the accuracy of the truncated series of image charges so that it will better
approximate the fields that would have resulted from a non-
truncated series. Accuracy can be improved by three methods:
(1) Increase the length of the series of image charges
(i.e., include increasingly higher order charges). This
is the straight-forward method, of course. It works
because the series is an alternating series and
converges to the correct electric field as the order
N , and thus the magnitude of the error in the
energy of the field decreases to zero.
(2) Truncating the series results in a set of image charges
for each sphere that do not sum to the correct overall
charge of the sphere. A simple improvement is therefore to renormalize the total charge by rescaling all the image charges associated with one sphere by the same factor so that they do sum to the correct
overall charge of the sphere. In the case of spheres
held at a constant potential, the normalization is implemented to match the specified potential. This procedure is a special case of optimization and produces significant improvement for low order truncations.
(3) Optimize a system of L image charges for M spheres
by (i) moving the point charges individually away from the locations that were specified by the image charge series and (ii) redistributing the charge between them so that the amount of charge for each
point is different than was initially specified by the
image charge series. This may be accomplished by a gradient search algorithm that seeks to optimize some
46 The Open Applied Physics Journal, 2009, Volume 2 Metzger and Lane
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metric of the fidelity of the overall field. This method
is possible because a set of N point charges in a
truncated series is not necessarily more accurate at approximating the non-truncated series as is some other set of L point charges where L < M. This may
seem counter-intuitive at first, but upon reflection there is no reason why the series truncated to N point
charges should be the most accurate solution. The only feature that makes the first N terms in the image
charge series special is that they contribute to the exact solution when an infinite set of additional points
in the series is included. However, if we know a priori
that only a finite number of point charges are going to be included, then there is no reason to expect the first N terms of a truncated series to be the best solution.
This concept is generally true in all practical applications of infinite mathematical series. For example, transcendental functions implemented on a computer often make use of this characteristic of
truncated infinite series.
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Received: November 17, 2008 Revised: March 16, 2009 Accepted: March 16, 2009
© Metzger and Lane; Licensee Bentham Open.
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