The problem of finding an analytical solution of some families of Kepler transcendental equation is studied in some detail, by the Special Trans Functions Theory – STFT. Thus, the STFT mathematical approach in the form of STFT iterative methods with a novel analytical solutions are presented. Structure of the STFT solutions, numerical results and graphical simulations confirm the validity of the basic principle of the STFT. In addition, the obtained analytical results are compared with the calculated values of other analytical methods for alternative proving its significance. Undoubtedly, the proposed novel analytical approach implies qualitative improvement in comparison with conventional numerical and analytical methods.

One of the classical laws of planetary motion due to Kepler says that a planet revolves around the sun in an elliptic orbit (Fig. 1(a)). The planet revolves around sun can be described by a well known Kepler’s equation. Furthermore, many problems in celestial mechanics require a solution to Kepler’s equation.1,2 The Kepler transcendental equation of the form

(1)

which links the eccentric anomaly of elliptic motion E, mean anomaly M and eccentricity e, is of critical importance in celestial mechanics. The basic physical meaning of this equation is better explained by Fig. 1(b) in which is depicted an ellipse, with eccentricity e, that is the orbit of a body moving about the stationary gravitating center placed in focus of the ellipse S. Denote by C and A the center and pericenter of the ellipse, respectively. Construct also a circle with its center at point C and with a radius equal to the major semi axis of the ellipse. At some time let the position of the rotating body is determined by point P. From P we drop a perpendicular to the major axis of the ellipse and denote the foot of the perpendicular by letter R. Extend this perpendicular to intersect the circle at point Q. Then the angle ↑ ACQ is just the eccentric anomaly E. Suppose that the planet P, having passed thought perihelion A is at position P after elapsed time t, it is possible to express the polar coordinates of P (r, v), relative to the sun in terms of t.

FIG. 1.

The motion of the planets around the sun.

FIG. 1.

The motion of the planets around the sun.

Close modal

Kepler’s transcendental equation relates E to time by means of a quantity

(2)

where T is time required for the planet complete one trip in its orbit around the sun. The quantity M represents the average angular speed of the radius vector SP. Classical formulae to find r and v is

(3)

and

(4)

Therefore if T and M are known it is possible to solve the Kepler’s equation for E and to determine position (r, v) at time t by using equations (3) and (4).

Many algorithms have been derived for solving the Kepler’s equation as a result of its importance in celestial mechanics.1–7 Detailed characteristics of these methods will be discussed in the next section.

As it is noted in the Introduction, many algorithms have been derived for solving the Kepler’s equation. Thus, Colwell’s history of Kepler’s equation contains approximate half of thousand references.4 Our interest is oriented toward some analytical approaches1–7 where is presented procedure for solving this equation which implies writing a E as a power series in e as follows

(5)

where the coefficients an are given by the Lagrange inversion theorem as

(6)

It should be noted that this series diverges for e > 0.6627434…

On the other hand, equation (1) can be solved using Bessel functions of the first kind,4 as follows

(7)

where Jk is the kth-order Bessel function of the first kind, given by the following series:

(8)

All of the series solutions, at the first glance, appear to require an infinite number of terms, which are computationally impossible to generate.

In Ref. 5 polynomialization of Kepler’s equation through Chebyshev polynomial expansion of the sine is presented.

Also, Lambert W function can be used to truncate series solutions to Kepler’s equation.6 The above paper offers a simple solution for the truncation of previously known infinite series of solutions to the functions of Kepler’s transcendental equation. Presented method is based on many approximations, while its accuracy is not great, and expressions are complex and enormous. For example, in the above paper is presented analytical expansion for cos (v), within the 10−9 tolerance, correct to e = 0.1, (equation (24a)).

In Ref. 7 is presented the iterative solution to Kepler’s equation. Namely, in the above paper the solution for the relative motion is presented in the closed-form, in terms of the eccentric anomalies of the target and chaser orbits, while the eccentric anomalies themselves are expressed in terms of the orbits respective eccentricities, using an iterative method.

There would seem to the nothing further say.5 But, in this article we show that solving of the Kepler’s transcendental equation is possible within the Special Trans Functions Theory, by simple, and, also by advanced STFT iterative method. Advantage of this novel approach to the Kepler’s equation analytical solving, first of all, is conceptual simplicity, absent of initial values and unlimited of the theoretical accuracy of eccentric anomaly.

So, the subject of our theoretical analysis presented here is obtaining a new analytical solution of some families of Keller’s transcendental equation, by using some novel iterative methods within the Special trans functions theory. Consequently, a brief introductory observation concerning the STFT is presented.

Let us note that Perovich’s Special Trans Functions Theory has been proved to be a very powerful, consistent theory for solving a broad family of transcendental equations and obtaining exact analytical closed-form solutions in the real domain [Refs. 8–25 and 34–41et al. ]. Examples of its application are shown in articles concerning the genesis of an exact analytical solutions in: theory of neutron slowing down,8–10 nonlinear circuit theory,8,11,39 linear transport theory,8,12,13,19, Hopfield neuron analysis14 some families of transcendental equations,8,12,15,20,23–25,38 solar cell analysis,16,21,35 Plutonium temperature estimation,8,17,36 ambient temperature estimation,18,11 Lambert transcendental equations analysis,8,20 as well as in problem in engineering materials,22,34,40,41 ect.

The biggest impact of this work is in the usage of a new STF theory approach in formulae genesis for the determining position (r, v) in time t. All investigations and analysis of the value E in this paper have been consistently accomplished with the usage of STF theory. STF theory ensures reaching extreme precisions in numerical results (arbitrary number of accurate digits in the numerical structure of the transcendental numbers), which is reflected in this paper as well, where we show the highest precision in defining the eccentric of elliptic motion E achieved so far. That, of course, implies that the relevant constants (π, a ect.) have been used with greater number of exact digits than in conventional approaches.

Driven by the thorough analysis of the results obtained, we believe that STF theory, supported by Mathematica software, represents a novel theoretical approach in analysis of the many problems in celestial mechanics which require a solution to Kepler’s transcendental equation.

Within this section our interest is oriented toward determining analytical solutions for the Kepler’s transcendental equation by using a simple iterative procedure based on the Special Trans Functions Theory -STFT.8–25,34,35 The Kepler’s transcendental equation for determining the eccentric anomaly in celestial mechanics (1) after some symbolic modification of the type

(9)

takes the form

(10)

In addition, after an original structural modification, Kepler’s transcendental equation (10) takes the following form

(11)

and

(12)

where

(13)

and where

(14)

Structural modification of the transcendental equation (10) implies that solutions of equations (11) and (12) are unique in the real domain8,15,17,22et al. Namely, within the Special trans functions theory, the transcendental equation (11) (or (12)), for fixed real values of B, has unique analytical closed form solution in the real domain, in the form of the special tran function, tran + B . Consequently, we have sin X = tran + B and Y = α X β = tran + B . or X = M + e tran + B .

In some detail this special tran function is referred in [Refs. 8–11, 15, 22, and 35–41,] et al.

Also, from formulae (11) and (12) we have sin X exp sin X = B , and, Y exp Y = B , respectively. Consequently, since abs sin X < 1 , and abs Y < 1 , we have B 1 exp 1 , exp 1 .

The presented STFT concept implies application of the analytical closed form solution of Eqs. (11) and (12), as unique existing analytical closed-form expression for practical calculation of X, for all values of B.

Let us note that according to the usual traditional notations of quantities, which are used in the domain of Astronomy, the function that is an analytical solution of equations (11) and (12) is denoted Lambert W(x) function. This function is based and inspired by the works of famous scientist J. Lambert.26–29 But, historically, in the literature, we have not analytical closed form solution to the implementation of the Lambert W function, for all values of real B! All known solutions are fragmental analytical or approximate solutions (See Section III A). Because of that, in this article, the Perovich t r a n + B function, previously referred in [Refs. 8–11, 25, 15, 22, and 35–41] et al., is implemented. Of course, the analytical closed form solution to the Lambert transcendental equations (11) and (12) is the Perovich tran + B function. In some detal, explanations are given in the Section III A.

In conceptual sense, the Simple iterative method, within the Special trans function theory, implies the following form of iteration:

(15)

or, form

(16)

where

(17)

and,

(18)

where (k) is number of iteration. Note that equations (10) and (13) imply the statement abs k Y < 1 . Of course, k X is value of X in kth iteration? The Error Criterion is defined as

(19)

where ε is an arbitrary small real positive number, and, k B is real value of B in k’th iteration.

Also, the initial iteration takes the form 1 B = exp 1 . The outline of the simple STFT iterative process begins with the certain value of B = 1 B = exp 1 , and, for this value of 1 B , from equation (12) we have 1 Y = tran + 1 B and, from equation (17) follows 1 X = M + e tran + 1 B . After that, the second value of B is obtained from equation (18) in the form 2 B = sin 1 X exp sin 1 X . If 2 B does not satisfy the error criterion 1 B 2 B ε , where ε is an arbitrary small real positive number, then using 2 B , from equation (12), we have 2 Y = tran + 2 B and 2 X = M + e tran + 2 B , or, more explicitly, 2 X = M + etran + sin 1 X exp sin 1 X . After that, the next value of B is obtained from equation (18) in the form 3 B = sin 2 X exp sin 2 X . If 3 B does not satisfy the error criterion 2 B 3 B ε the whole procedure is repeated. Let us note that general scheme of the Simple STFT iterative procedure for determining of values B takes the form (18), where (k) is number of iteration. Thus, for k=2, we have

Also,

ect. Let us note that within STF theory tran + n S exp n S = n S , where n S x = sin n X . Consequently, based on the Eqs. (16) and (14), we have:

Finally, for N iteration a simple STFT iterative formula takes the form

(20)

where

(21)

and

(22)

For practical analysis and numerical calculations the formula (20) takes the form

(23)

where N X P denotes the value of the Nth iteration of X given with P accurate digits. P is defined as P = 1 abs log G , where the error function G is defined as G = sinX − αX + β.

Let us note that convergence condition within the simple STFT iterative method takes the form

The STF theory genetic implies the above condition of convergence. Of course, the Kepler’s transcendental equation parameters determine the dynamic of the convergence process.

In this section, as above mentioned, the problem of finding an exact analytical solution of transcendental equations (11) and (12), will be discussed. First of all, note that equations (11) and (12) can be presented in the unique form

(24)

For convenience, we restrict ourselves to the one dimensional transcendental equations. Let us note that equation (24) has one real solution: ψ ξ > 0 , for B ξ 0 , exp 1 , and ψ ξ < 0 for B ξ 1 exp 1 , 0 . Since equation (10) implies the statement of the form abs k Y < 1 , consequently, we have that parameter B (ξ) is within B ξ 1 exp 1 , exp 1 .

Let us note, that historically, an equation proposed by Lambert (1758) and studied by Euler in 1779

when α → β, becomes

and, for β < 0 has the solution

where W is Lambert’s W function.

The Lambert W-function has the series expansion

The Lagrange inversion theorem gives the equivalent series expansion

However, the series oscillates between ever larger positive and negative values for real z ≥ 0.4, and so cannot be used for practical numerical computation.

An asymptotic formula which yields reasonably accurate results for z ≥ 3 is

where

Another expansion due to Gosper is the double series

where S1 is a nonnegative Stirling number of the first kind, and a is a first approximation which can be used to select between branches. The Lambert W-function is two-valued for 1 / exp 1 x < 0 . For W x 1 the function is denoted W 0 x or simply W x , and this is called the principal branch. For W x 1 the function is denoted as W 1 x .

Numerical methods for solving modified Lambert transcendental equation is presented in many different domain.30 Let us briief review some of thet: Recursion, Halley’s iteration, Fritsch’s iteration, et al. Presented methods are complicated and complexed. For an instance below is given a formulae (24a) as an example of the complexity formulae which appears in Ref. 6 

(24a)

Of course, within Maple, Matlab, and Mathematica different solver are developed. While the Lambert W function is simply called W in the mathematics software tool Maple31 and lambertw in the Matlab programming environment,32 in the Mathematica computer algebra framework this function is implemented under the name ProductLog.33 

Fortunately, within the Perovich’s Special Trans Functions Theory [Refs. 8–11, 15, 22, and 35–41] et al., we have analytical closed form solution, to the Lambert Transcendental Equation, in the form

(25)

where the Perovich trans+(B) function is defined as:

(26)

where

(27)

with [t] denotes the greatest integer less than or equal to t.

For practical analysis and numerical calculation, an expression (25) (including Eq. (26)) takes the form:

(28)

where 〈ψ〉P denotes numerical values of the transcendental number ψ given with

(29)

accurate digits, where the error function G is defined as:

(30)

More explicitly, for fixed values of sumlimits, [t], 〈ψ〉P takes the form:

(31)

Expression (31) gives the number of accurate digits in the numerical structure of the transcendental number ψ, which depend of [t].

In addition, solution of equation (12) directly follows by formula (26) in the form

(32)

For practical numerical calculations, we have

(33)

Let us note, that we have already had experience with some forms similar to equation (31) by considering the problem of number of accurate digits in the numerical structure of transcendental numbers, as certain physical parameters, in different scientific areas (Refs. 8, 11, 15–17, 22, and 25et al.).

The concept of the STFT exact analytical solutions is fundamentally different from that of conventional numerical techniques and analytical methods. Thus, the STFT solutions for Kepler’s transcendental equation should yield significant information that could be successfully used for the Kepler parameters recognition and classification. It is possible, due to the fact that the theoretical accuracy of the STFT numerical results is unlimited, and extreme precision is attainable with this approach. Consequently, we believe that novel STFT techniques represent an original theoretical and numerical analysis of many problems in celestial mechanics requires a solution to Kepler equation for different structures. Note, they should be extended in several directions in order to be both accurate enough and accept table regarding the calculation complexity.

In the other words, from a theoretical point of view STFT analytical solutions can be found with an arbitrary order of accuracy. Namely, the number of accurate digits in the numerical structure of the analytical STFT result depends upon the sumlimit in the STFT formulae ([t], in this case). Of course, this may be a disadvantage in some cases (large sumlimit for small number of accurate digits, for example). Within Tables I-IX, given below, the above statement concerning the sumlimit significance will be represented by obtained numerical results for error criterion (19).

TABLE Ia.

Numerical comparison analysis between Lambert W0series(B) function and Perovich trans+(B) function for | B | < 1 exp ( 1 ) .

trans+(B) W0series(B)
B Solution [t] Error trans+(B) accuracy trans+(B) [t] Error W0series(B) accuracy W0series(B)
0.10  0.0912765271608  200  2.83996⋅10−360  361  200  2.36223⋅10−118  119 
62264299895721  400  6.05401⋅10−232  233 
42317956865311  600  2.38374⋅10−345  346 
92240514720… 
0.15  0.1315149280010  200  6.73202⋅10−324  325  200  5.48961⋅10−83  84 
34458047441666  400  2.32483⋅10−161  162 
73662417801276  600  1.51293⋅10−239  240 
51069693569…  800  1.17426⋅10−317  318 
0.20  0.1689159734991  200  3.94670⋅10−299  300  200  6.70696⋅10−58  59 
09565116474903  400  2.76072⋅10−111  112 
70581839872844  600  1.74647⋅10−164  165 
69135107297…  800  1.31777⋅10−217  218 
  1000  1.09518⋅10−270  271 
0.25    200  1.06520⋅10−280  281  200  1.91321⋅10−38  39 
  400  1.89748⋅10−72  73 
0.2038883547022  600  2.89263⋅10−106  107 
40164443181831  800  5.25968⋅10−140  141 
32713987014935  1000  1.05341⋅10−173  174 
24772101596…  1200  2.24282⋅10−207  208 
  1400  4.98108⋅10−241  242 
  1600  1.14096⋅10−274  275 
0.30    200  3.09505⋅10−266  267  200  1.49707⋅10−22  23 
  400  1.01820⋅10−40  41 
  600  1.06456⋅10−58  59 
  800  1.32763⋅10−76  77 
  1000  1.82372⋅10−94  95 
0.2367553107885  1200  2.66317⋅10−112  113 
59316871366991  1400  4.05671⋅10−130  131 
31310225298500  1600  6.37336⋅10−148  149 
76068942822…  1800  1.02521⋅10−165  166 
  2000  1.68014⋅10−183  184 
  2200  2.79527⋅10−201  202 
  2400  4.70872⋅10−219  220 
  2600  8.01530⋅10−236  237 
  2800  1.37657⋅10−254  255 
0.35  0.2677773368190  200  2.33910⋅10−254  255  200  4.08392⋅10−9  10 
37868568135532  400  6.80713⋅10−14  15 
92750654798521  4000  2.74721⋅10−93  94 
61492989819…  …  …  … 
  8000  2.73840⋅10−181  182 
trans+(B) W0series(B)
B Solution [t] Error trans+(B) accuracy trans+(B) [t] Error W0series(B) accuracy W0series(B)
0.10  0.0912765271608  200  2.83996⋅10−360  361  200  2.36223⋅10−118  119 
62264299895721  400  6.05401⋅10−232  233 
42317956865311  600  2.38374⋅10−345  346 
92240514720… 
0.15  0.1315149280010  200  6.73202⋅10−324  325  200  5.48961⋅10−83  84 
34458047441666  400  2.32483⋅10−161  162 
73662417801276  600  1.51293⋅10−239  240 
51069693569…  800  1.17426⋅10−317  318 
0.20  0.1689159734991  200  3.94670⋅10−299  300  200  6.70696⋅10−58  59 
09565116474903  400  2.76072⋅10−111  112 
70581839872844  600  1.74647⋅10−164  165 
69135107297…  800  1.31777⋅10−217  218 
  1000  1.09518⋅10−270  271 
0.25    200  1.06520⋅10−280  281  200  1.91321⋅10−38  39 
  400  1.89748⋅10−72  73 
0.2038883547022  600  2.89263⋅10−106  107 
40164443181831  800  5.25968⋅10−140  141 
32713987014935  1000  1.05341⋅10−173  174 
24772101596…  1200  2.24282⋅10−207  208 
  1400  4.98108⋅10−241  242 
  1600  1.14096⋅10−274  275 
0.30    200  3.09505⋅10−266  267  200  1.49707⋅10−22  23 
  400  1.01820⋅10−40  41 
  600  1.06456⋅10−58  59 
  800  1.32763⋅10−76  77 
  1000  1.82372⋅10−94  95 
0.2367553107885  1200  2.66317⋅10−112  113 
59316871366991  1400  4.05671⋅10−130  131 
31310225298500  1600  6.37336⋅10−148  149 
76068942822…  1800  1.02521⋅10−165  166 
  2000  1.68014⋅10−183  184 
  2200  2.79527⋅10−201  202 
  2400  4.70872⋅10−219  220 
  2600  8.01530⋅10−236  237 
  2800  1.37657⋅10−254  255 
0.35  0.2677773368190  200  2.33910⋅10−254  255  200  4.08392⋅10−9  10 
37868568135532  400  6.80713⋅10−14  15 
92750654798521  4000  2.74721⋅10−93  94 
61492989819…  …  …  … 
  8000  2.73840⋅10−181  182 
TABLE Ib.

Numerical comparison analysis between Lambert W B function and Perovich trans + B function for B > 1 exp 1 .

trans + B W 0 series B
B [t] ψ = trans + B Error abs(G) P ψ = W B Error abs(G) P
0.4  10  0.2971677…  9.472206  15  0.2  0.01816910433 
0.50  0.3517337…  1.26030⋅10−12  13  0.206612211  0.200055283 
0.75  0.4691502…  4.06124⋅10−11  12  −9.41242197  9189.021520 
0.5671432…  1.18640⋅10−10  11  −192.375945  3.53029⋅1083 
1.25  0.6515479…  8.64560⋅10−10  11  −1910.55742  6.94158⋅10829 
1.5  0.7258613…  6.89893⋅10−9  10  −12357.4328  8.72957⋅105366 
1.75  0.7923579…  2.51910⋅10−8  −59620.6123  1.39957⋅1025893 
0.8526055…  6.38839⋅10−8  −232335.374  1.87075⋅10100902 
2.2  0.8970741…  1.13129⋅10−7  −612432.740  3.17807⋅10265976 
2.4  0.9387136…  1.78170⋅10−7  −1.4821⋅106  2.07236⋅10643672 
2.6  0.9778800…  2.54256⋅10−7  −3.3387⋅106  8.75056⋅101450020 
2.7  0.9966288…  2.93655⋅10−7  −4.8952⋅106  3.09168⋅102125982 
trans + B W 0 series B
B [t] ψ = trans + B Error abs(G) P ψ = W B Error abs(G) P
0.4  10  0.2971677…  9.472206  15  0.2  0.01816910433 
0.50  0.3517337…  1.26030⋅10−12  13  0.206612211  0.200055283 
0.75  0.4691502…  4.06124⋅10−11  12  −9.41242197  9189.021520 
0.5671432…  1.18640⋅10−10  11  −192.375945  3.53029⋅1083 
1.25  0.6515479…  8.64560⋅10−10  11  −1910.55742  6.94158⋅10829 
1.5  0.7258613…  6.89893⋅10−9  10  −12357.4328  8.72957⋅105366 
1.75  0.7923579…  2.51910⋅10−8  −59620.6123  1.39957⋅1025893 
0.8526055…  6.38839⋅10−8  −232335.374  1.87075⋅10100902 
2.2  0.8970741…  1.13129⋅10−7  −612432.740  3.17807⋅10265976 
2.4  0.9387136…  1.78170⋅10−7  −1.4821⋅106  2.07236⋅10643672 
2.6  0.9778800…  2.54256⋅10−7  −3.3387⋅106  8.75056⋅101450020 
2.7  0.9966288…  2.93655⋅10−7  −4.8952⋅106  3.09168⋅102125982 
TABLE II.

Numerical results of equation sin ( X ) = 1 0 . 1 X 0 . 1 π 0 . 1 (Example I).

Iteration (k) B X [rad] Error = sin ( X ) 1 0 . 1 X + 0 . 1 π 0 . 1
2.71828182845904523 536028747135266249 
0.48020783341734928 131028867171478631  0.3482  0.0000458344 
10  0.48011215537177194 860651079745070208  0.3482881935  3.370749⋅10−10 
15  0.48011215466977440 001949053280359862  0.348288193513396  2.473258⋅10−15 
20  0.48011215466976924 917359975144007856  0.348288193513396 18854  1.814731⋅10−20 
25  0.48011215466976924 913580586818109284  0.348288193513396 1885402397  1.331543⋅10−25 
30  0.48011215466976924 913580559087176501  0.348288193513396 18854023977840  9.770084⋅10−30 
Iteration (k) B X [rad] Error = sin ( X ) 1 0 . 1 X + 0 . 1 π 0 . 1
2.71828182845904523 536028747135266249 
0.48020783341734928 131028867171478631  0.3482  0.0000458344 
10  0.48011215537177194 860651079745070208  0.3482881935  3.370749⋅10−10 
15  0.48011215466977440 001949053280359862  0.348288193513396  2.473258⋅10−15 
20  0.48011215466976924 917359975144007856  0.348288193513396 18854  1.814731⋅10−20 
25  0.48011215466976924 913580586818109284  0.348288193513396 1885402397  1.331543⋅10−25 
30  0.48011215466976924 913580559087176501  0.348288193513396 18854023977840  9.770084⋅10−30 
TABLE III.

Numerical results of equation sin ( X ) = 1 0 . 1 X 0 . 7 π 0 . 1 (Example II).

Iteration (k) B X [rad] Error = sin ( X ) 1 0 . 1 X + 0 . 7 π 0 . 1
2.71828182845904523 536028747135266249  2.2  0.25370533081 
1.63237317284036636 114359800535709280  2.27530  4.5183320 ⋅ 10−6 
1.63235715488548550 142593327416363852  2.275307670  7.950067 ⋅ 10−11 
13  1.63235715460364832 545074320989478845  2.27530767019546  1.398824 ⋅ 10−15 
17  1.63235715460364336 648813427514353933  2.27530767019546 597073  2.461250 ⋅ 10−20 
21  1.63235715460364336 640088066825842294  2.27530767019546 5970733356  4.330603 ⋅ 10−25 
25  1.63235715460364336 640087913301960086  2.27530767019546 597073335668116  7.603192 ⋅ 10−30 
Iteration (k) B X [rad] Error = sin ( X ) 1 0 . 1 X + 0 . 7 π 0 . 1
2.71828182845904523 536028747135266249  2.2  0.25370533081 
1.63237317284036636 114359800535709280  2.27530  4.5183320 ⋅ 10−6 
1.63235715488548550 142593327416363852  2.275307670  7.950067 ⋅ 10−11 
13  1.63235715460364832 545074320989478845  2.27530767019546  1.398824 ⋅ 10−15 
17  1.63235715460364336 648813427514353933  2.27530767019546 597073  2.461250 ⋅ 10−20 
21  1.63235715460364336 640088066825842294  2.27530767019546 5970733356  4.330603 ⋅ 10−25 
25  1.63235715460364336 640087913301960086  2.27530767019546 597073335668116  7.603192 ⋅ 10−30 
TABLE IV.

Numerical results of equation sin ( X ) = 1 0 . 1 X 1 . 1 π 0 . 1 (Example III).

Iteration (k) B X [rad] Error = sin ( X ) 1 0 . 1 X + 1 . 1 π 0 . 1
2.71828182845904523 536028747135266223  3.  1.4007556967 
-0.2126860221228025 731328631595349522  3.4275  0.0001165214 
10  -0.2127436672729135 593863477332270172  3.427544811  9.481873⋅10−10 
15  -0.2127436668044339 107174667699706991  3.427544811622828  7.706870⋅10−15 
20  -0.2127436668044377 185217165270409961  3.427544811622828 12909  6.264147⋅10−20 
25  -0.2127436668044377 184907666805951829  3.427544811622828 1290975585  5.091500⋅10−25 
30  -0.2127436668044377 184907669321551257  3.427544811622828 129097558512720  4.138373⋅10−30 
Iteration (k) B X [rad] Error = sin ( X ) 1 0 . 1 X + 1 . 1 π 0 . 1
2.71828182845904523 536028747135266223  3.  1.4007556967 
-0.2126860221228025 731328631595349522  3.4275  0.0001165214 
10  -0.2127436672729135 593863477332270172  3.427544811  9.481873⋅10−10 
15  -0.2127436668044339 107174667699706991  3.427544811622828  7.706870⋅10−15 
20  -0.2127436668044377 185217165270409961  3.427544811622828 12909  6.264147⋅10−20 
25  -0.2127436668044377 184907666805951829  3.427544811622828 1290975585  5.091500⋅10−25 
30  -0.2127436668044377 184907669321551257  3.427544811622828 129097558512720  4.138373⋅10−30 
TABLE V.

Numerical results of equation sin ( X ) = 1 0 . 6 X 0 . 2 π 0 . 6 (Example IV).

Iteration (k) B X [rad] Error = sin ( X ) 1 0 . 6 X + 0 . 2 π 0 . 6
2.71828182845904523 536028747135266249  1.  0.0568571318 
2.33904021306652912 891108169692272956  1.18  0.0001370283 
13  2.33816199593542860 129527385735732750  1.18398955  9.620942 ⋅ 10−10 
21  2.33816198988821300 946212638051960933  1.18398955255870  6.626822 ⋅ 10−15 
29  2.33816198988817135 675554723429202456  1.18398955255870 3862  4.480964 ⋅ 10−20 
37  2.33816198988817135 646864693402751356  1.18398955255870 386258258  3.143988 ⋅ 10−25 
44  2.33816198988817135 646864495792917316  1.18398955255870 3862582581911  9.567704 ⋅ 10−30 
Iteration (k) B X [rad] Error = sin ( X ) 1 0 . 6 X + 0 . 2 π 0 . 6
2.71828182845904523 536028747135266249  1.  0.0568571318 
2.33904021306652912 891108169692272956  1.18  0.0001370283 
13  2.33816199593542860 129527385735732750  1.18398955  9.620942 ⋅ 10−10 
21  2.33816198988821300 946212638051960933  1.18398955255870  6.626822 ⋅ 10−15 
29  2.33816198988817135 675554723429202456  1.18398955255870 3862  4.480964 ⋅ 10−20 
37  2.33816198988817135 646864693402751356  1.18398955255870 386258258  3.143988 ⋅ 10−25 
44  2.33816198988817135 646864495792917316  1.18398955255870 3862582581911  9.567704 ⋅ 10−30 
TABLE VI.

Numerical results of equation sin ( X ) = 1 0 . 6 X 0 . 5 π 0 . 6 (Example V).

Iteration (k) B X [rad] Error = sin ( X ) 1 0 . 6 X + 0 . 5 π 0 . 6
2.71828182845904523 536028747135266249  2.  0.1726229483 
10  2.06570530964737771 785749208576319065  2.09132  3.3865485 ⋅ 10−6 
17  2.06571691037184475 5701112887449914650  2.091328966  7.135157 ⋅ 10−10 
27  2.06571690792819952 8358849994000421397  2.09132896603291  3.994569 ⋅ 10−15 
36  2.06571690792818584 744089427093154812  2.09132896603291 517  7.506763 ⋅ 10−20 
46  2.06571690792818584 7697558008150901580  2.09132896603291 517702993  4.195622 ⋅ 10−25 
55  2.06571690792818584 769755944510074857  2.09132896603291 51770299360708  7.871477 ⋅ 10−30 
Iteration (k) B X [rad] Error = sin ( X ) 1 0 . 6 X + 0 . 5 π 0 . 6
2.71828182845904523 536028747135266249  2.  0.1726229483 
10  2.06570530964737771 785749208576319065  2.09132  3.3865485 ⋅ 10−6 
17  2.06571691037184475 5701112887449914650  2.091328966  7.135157 ⋅ 10−10 
27  2.06571690792819952 8358849994000421397  2.09132896603291  3.994569 ⋅ 10−15 
36  2.06571690792818584 744089427093154812  2.09132896603291 517  7.506763 ⋅ 10−20 
46  2.06571690792818584 7697558008150901580  2.09132896603291 517702993  4.195622 ⋅ 10−25 
55  2.06571690792818584 769755944510074857  2.09132896603291 51770299360708  7.871477 ⋅ 10−30 
TABLE VII.

Numerical results of equation sin ( X ) = 1 0 . 6 X 1 . 2 π 0 . 6 (Example VI).

Iteration (k) B X [rad] Error = sin ( X ) 1 0 . 6 X + 1 . 2 π 0 . 6
2.718281828459045235 3602874713526624911 
22  -0.26249890522874061 322239453074325027  3.53815  6.432402⋅10−6 
37  -0.26249720008632693 5606876673261153521  3.538159074  8.170591⋅10−10 
57  -0.26249720032494621 8124450067563521092  3.53815907415536  5.937387⋅10−15 
76  -0.26249720032494795 2152729971501597730  3.53815907415536220  7.795967⋅10−20 
96  -0.26249720032494795 2129962122047771176  3.53815907415536220 7030404  6.161961⋅10−25 
115  -0.26249720032494795 2129961956595530936  3.53815907415536220 70304046246  8.090840⋅10−30 
Iteration (k) B X [rad] Error = sin ( X ) 1 0 . 6 X + 1 . 2 π 0 . 6
2.718281828459045235 3602874713526624911 
22  -0.26249890522874061 322239453074325027  3.53815  6.432402⋅10−6 
37  -0.26249720008632693 5606876673261153521  3.538159074  8.170591⋅10−10 
57  -0.26249720032494621 8124450067563521092  3.53815907415536  5.937387⋅10−15 
76  -0.26249720032494795 2152729971501597730  3.53815907415536220  7.795967⋅10−20 
96  -0.26249720032494795 2129962122047771176  3.53815907415536220 7030404  6.161961⋅10−25 
115  -0.26249720032494795 2129961956595530936  3.53815907415536220 70304046246  8.090840⋅10−30 
TABLE VIII.A.

Comparison of results obtained using Eqs. (20) and (23) and results obtained with different methods presented in Ref. 6.

e=0.1 Reference/ Equation P e=0.6 Reference/ Equation P
M = 2π ⋅ 0.05  6- kmax=8  M = 2π ⋅ 0.01  6 – k-max=43 
6- kmax=9  10  6- kmax=44 
6- Truncated Bessel Functions  10  6- Truncated Bessel Functions 
Eq(20), N=8  Eq(20), N=21 
Eq(20), N=9  10  Eq(20), N=26 
Eq(20), N=10  11  Eq(20), N=30 
Eq(20), N=20  21  Eq(20), N=34  10 
Eq(20), N=30  31  Eq(20), N=56  15 
M = 2π ⋅ 0.35  6- kmax=8  M = 2π ⋅ 0.1  6- kmax=43 
6- kmax=9  10  6- kmax=44 
6- Truncated Bessel Functions  10  6- Truncated Bessel Functions 
Eq(20), N=7  Eq(20), N=7 
Eq(20), N=8  10  Eq(20), N=9 
Eq(20), N=9  12  Eq(20), N=10 
Eq(20), N=17  21  Eq(20), N=29  21 
Eq(20), N=25  31  Eq(20), N=44  31 
M = 2π ⋅ 0.55  6- kmax=8  M = 2π ⋅ 0.25  6- kmax=43 
6- kmax=9  10  6- kmax=44 
6- Truncated Bessel Functions  10  6- Truncated Bessel Functions 
Eq(20), N=8  Eq(20), N=10 
Eq(20), N=9  Eq(20), N=11 
Eq(20), N=10  11  Eq(20), N=13 
Eq(20), N=20  21  Eq(20), N=36  21 
Eq(20), N=30  31  Eq(20), N=55  31 
M = 2π ⋅ 0.95  6- kmax=8  M = 2π ⋅ 0.6  6- kmax=43 
6- kmax=9  10  6- kmax=44 
6- Truncated Bessel Functions  10  6- Truncated Bessel Functions 
Eq(20), N=8  Eq(20), N=22 
Eq(20), N=9  10  Eq(20), N=26 
Eq(20), N=10  11  Eq(20), N=30 
Eq(20), N=13  15  Eq(20), N=37  11 
Eq(20), N=18  20  Eq(20), N=57  16 
e=0.1 Reference/ Equation P e=0.6 Reference/ Equation P
M = 2π ⋅ 0.05  6- kmax=8  M = 2π ⋅ 0.01  6 – k-max=43 
6- kmax=9  10  6- kmax=44 
6- Truncated Bessel Functions  10  6- Truncated Bessel Functions 
Eq(20), N=8  Eq(20), N=21 
Eq(20), N=9  10  Eq(20), N=26 
Eq(20), N=10  11  Eq(20), N=30 
Eq(20), N=20  21  Eq(20), N=34  10 
Eq(20), N=30  31  Eq(20), N=56  15 
M = 2π ⋅ 0.35  6- kmax=8  M = 2π ⋅ 0.1  6- kmax=43 
6- kmax=9  10  6- kmax=44 
6- Truncated Bessel Functions  10  6- Truncated Bessel Functions 
Eq(20), N=7  Eq(20), N=7 
Eq(20), N=8  10  Eq(20), N=9 
Eq(20), N=9  12  Eq(20), N=10 
Eq(20), N=17  21  Eq(20), N=29  21 
Eq(20), N=25  31  Eq(20), N=44  31 
M = 2π ⋅ 0.55  6- kmax=8  M = 2π ⋅ 0.25  6- kmax=43 
6- kmax=9  10  6- kmax=44 
6- Truncated Bessel Functions  10  6- Truncated Bessel Functions 
Eq(20), N=8  Eq(20), N=10 
Eq(20), N=9  Eq(20), N=11 
Eq(20), N=10  11  Eq(20), N=13 
Eq(20), N=20  21  Eq(20), N=36  21 
Eq(20), N=30  31  Eq(20), N=55  31 
M = 2π ⋅ 0.95  6- kmax=8  M = 2π ⋅ 0.6  6- kmax=43 
6- kmax=9  10  6- kmax=44 
6- Truncated Bessel Functions  10  6- Truncated Bessel Functions 
Eq(20), N=8  Eq(20), N=22 
Eq(20), N=9  10  Eq(20), N=26 
Eq(20), N=10  11  Eq(20), N=30 
Eq(20), N=13  15  Eq(20), N=37  11 
Eq(20), N=18  20  Eq(20), N=57  16 
TABLE VIII.B.

The general comparison between different methods for Kepler’s transcendental equation solving for all values of eccentricity e (e ∈ (0, 1]) and mean anomaly M (M ∈ [0, 2π]).

Method Conceptual Simplicity Computation Complexity Analytical Expression for Solutions (Formulae) Precision Speed of Convergence Dependence on initial condition
Method based on the Lambert W functions  Very low  Exist in high level  Eq. (24a)  Limited  low  Does not exist 
Simple STFT iterative method  Exist in high level  Does not exist  Eq. (20) and Eq. (23)  Unlimited  Linear  Does not exist 
Advanced STFT iterative method  Exist in medium level  Does not exist  Eq.(57) and Eq. (57a)  unlimited  Better then linear  Does not exist 
Newton method  Exist in high level  Does not exist  Does not exist  Unlimited and extremely high for some values of initial condition  Quadratic, if initial conditions is correct  Strongly Depends 
Method Conceptual Simplicity Computation Complexity Analytical Expression for Solutions (Formulae) Precision Speed of Convergence Dependence on initial condition
Method based on the Lambert W functions  Very low  Exist in high level  Eq. (24a)  Limited  low  Does not exist 
Simple STFT iterative method  Exist in high level  Does not exist  Eq. (20) and Eq. (23)  Unlimited  Linear  Does not exist 
Advanced STFT iterative method  Exist in medium level  Does not exist  Eq.(57) and Eq. (57a)  unlimited  Better then linear  Does not exist 
Newton method  Exist in high level  Does not exist  Does not exist  Unlimited and extremely high for some values of initial condition  Quadratic, if initial conditions is correct  Strongly Depends 
TABLE IX.

Examinations of the STFT method validity for possibilities: 10−15 < e < 1 − 10−15, 0.1π ≤ M < 2π by using a novel starting value of X, Eq. (64) or Eq. (65).

M = 0.1π M = 0.2π M = 0.3π M = 0.4π M = 0.5π
e Iterations P Iterations P Iterations P Iterations P Iterations P
1-10−15  17 
14  10  10  15  10  27  10  46  10 
23  15  10  15  25  15  45  15  75  15 
33  20  14  20  35  20  62  20  104  20 
1-10−10  17  25 
14  10  11  15  10  27  10  46  10 
23  15  10  16  25  15  45  15  75  15 
33  20  14  21  35  20  62  20  105  20 
1-10−5  17  29 
14  10  11  15  10  27  10  46  10 
23  15  10  16  25  15  45  15  75  15 
33  20  14  21  35  20  62  20  104  20 
0.9  11  13  21 
18  10  12  11  10  21  10  33  10 
30  15  16  19  15  34  15  54  15 
42  20  12  20  27  20  47  20  75  20 
0.7  14  12 
23  10  10  10  11  12  10  13  10 
38  15  17  15  15  20  15  31  15 
54  20  24  20  13  20  28  20  44  20 
0.5  13 
21  10  13  10  11  11  12  10 
34  15  21  15  11  15  12  15  20  15 
47  20  29  20  15  20  17  20  27  20 
0.3  10 
15  10  13  11  10  10  10 
24  15  19  15  13  15  15  12  15 
33  20  26  20  18  20  20  17  20 
0.1 
10  10  10  10  10 
14  15  13  15  11  15  15  16 
19  20  17  20  15  20  11  20  20 
10−5  22 
12  12  13  14  31 
17  17  18  19  41 
22  22  23  25  50 
10−10  12  12  12  13  22 
22  22  23  24  34 
32  32  33  34  43 
42  42  47  43  63 
10−15  17  17  17  18  32 
31  32  33  34  68 
47  47  48  49  82 
62  62  63  65  98 
M = 0.1π M = 0.2π M = 0.3π M = 0.4π M = 0.5π
e Iterations P Iterations P Iterations P Iterations P Iterations P
1-10−15  17 
14  10  10  15  10  27  10  46  10 
23  15  10  15  25  15  45  15  75  15 
33  20  14  20  35  20  62  20  104  20 
1-10−10  17  25 
14  10  11  15  10  27  10  46  10 
23  15  10  16  25  15  45  15  75  15 
33  20  14  21  35  20  62  20  105  20 
1-10−5  17  29 
14  10  11  15  10  27  10  46  10 
23  15  10  16  25  15  45  15  75  15 
33  20  14  21  35  20  62  20  104  20 
0.9  11  13  21 
18  10  12  11  10  21  10  33  10 
30  15  16  19  15  34  15  54  15 
42  20  12  20  27  20  47  20  75  20 
0.7  14  12 
23  10  10  10  11  12  10  13  10 
38  15  17  15  15  20  15  31  15 
54  20  24  20  13  20  28  20  44  20 
0.5  13 
21  10  13  10  11  11  12  10 
34  15  21  15  11  15  12  15  20  15 
47  20  29  20  15  20  17  20  27  20 
0.3  10 
15  10  13  11  10  10  10 
24  15  19  15  13  15  15  12  15 
33  20  26  20  18  20  20  17  20 
0.1 
10  10  10  10  10 
14  15  13  15  11  15  15  16 
19  20  17  20  15  20  11  20  20 
10−5  22 
12  12  13  14  31 
17  17  18  19  41 
22  22  23  25  50 
10−10  12  12  12  13  22 
22  22  23  24  34 
32  32  33  34  43 
42  42  47  43  63 
10−15  17  17  17  18  32 
31  32  33  34  68 
47  47  48  49  82 
62  62  63  65  98 

Also, the subject of the theoretical analysis presented here, is the numerical efficiency comparison between the Lambert W B function and the Perovich tran + B function. It is not difficult to see that the special tran function, tran + B , has superior accuracy (Tables Ia and Ib), as well as, theoretical superior. We must declare that tran + B is the novel exact standard in domain of family of transcendental equations (24). In this case we have also that tran + B has superior time computational efficiency for all values of B. It becomes clear, from the presented numerical values in Tables Ia and Ib, that the proposed formula for tran + B gives superior numerical computation. In addition, for B > 1 exp 1 the series expansion of Lambert W function, is unusable, while the Perovich tran + B function, (formula (33)), becomes unique existing analytical expression for calculation of k Y !

Our interest within this subsection is oriented toward determining formulae to the position P (coordinates r and ν), by using the Simple iterative procedure within STFT (equations (1), (3), (4) and (20), (23)). Consequently, from equation (1) we have

(34)

and, from equation (3) directly follows

(35)

In addition, from equations (1) and (34), expression for tan E 2 takes the form

(36)

Finally, from equations (4) and (36) we have complete express needed for determining position P:

(37)

Since, E = Σ ( Σ ( Σ . . . Σ ( Σ ( N = 2 ) ( Σ ( N = 1 ) ( Σ 1 ) ) ) ) . . . ) , then equations (35) and (37) take the following form:

(38)
(39)

respectively.

Also, we have

where

(40)

and, consequently, nonlinear equation for ν takes the form:

(41)

since

This section contains an attempt to find a STFT analytical solution of a family of Kepler’s transcendental equations of the form:

(42)

or, form

(43)

In addition, by using the STFT structural modifications Eq.(42) takes the following forms:

(44)
(45)

Analogically, from Eq. (43), we have

(46)
(47)

In addition, from equations (44) and (46), we have:

where B=B1/B2, or,

(48)

Also, from equations (45) and (47), a new transcendental equation takes the form

(49)

where

(50)

and

(51)

Of course, from Eqs. (48) and (51) directly follows

(52)

In addition, after simple modification Eq. (49) takes the form

(53)

where, from Eqs. (49) and (62) directly follows

(54)

The outline of the novel Advanced STFT iterative process begins with the certain value of 1 w from Eqs. (14) and (50). Thus, we have 1 λ = λ 1 w , and, from equation (53) follow 2 w = tran + λ 1 w . After that, the second value of λ w is obtained from Eq. (54) for 2 w = tran + λ 1 w . Consequently, from Eq. (51) we have: 2 X = M + e 1 + e 2 w = M + e 1 + e tran + λ 1 w . If 2 X does not satisfy the Error Criterion G= 2 X 1 X = e 1 + e 2 w 1 w ε , where ε is an arbitrary small real positive number, then for 2 λ = λ 2 w , we have

and

After that, if 3 X does not satisfy the Error Criterion G= 3 X 2 X = e 1 + e 3 w 2 w ε , the whole procedure is repeated.

Let us note, that after N iterations Advanced STFT iterative formulae takes the form

(55)

where

(56)

tran + x is a special tran function defined in Eq. (26), and λ is function defined in Eqs. (53) and (54). Of course, from Eqs. (14) and (50), we have:

From Eqs. (55) and (56), finally, follows

(57)

For practical analysis and numerical calculations the formula (57) takes the form

(57a)

On the other hand, Eqs. (38), (39) and (40) take the forms:

(58)
(59)
(60)

The subject of the theoretical analysis presented here is structural modification of the transcendental equation (53) when the eccentricity e and mean anomaly M satisfy conditions: e≺≺1, M≻1 and, consequently e≺≺M. Under these conditions Eq. (54) takes the form

(61)

From Eqs. (53) and (54) we have

(62)

or, more explicitly,

(63)

In addition, it is easily verified that from Eqs. (51) and (63), we can establish the following asymptotic expression for X:

(64)

Note that Xapproximate, by using the Simple STFT iterative method, can be formulated, for instance, in the form

(65)

The value of the Xapproximate (Eq. (65)) is applicable as an initial condition for X within Newton’s numerical method, when M ∈ (0, 2π]. Of course, the eccentricity e and mean anomaly M must satisfy the above defined condition.

Let us note that, within STFT, the transcendental equation (53) in the form

(66)

has an analytical closed form solution of the form

(67)

where tran K e , M , B is a new special tran function defined as

(68)

where

(69)

and

(70)

where B is defined in the Eq. (48).

Let us note that relationship between Eq. (65) and the Newton’s numerical method will be the subject of our further research.

In this section will be presented some numerical results based on equations (20) (or (23)) and (57) (or (57a)). These numerical results, obtained by using simple and advanced STFT iterative procedure described in the previous section, for different parameters in the Kepler’s, equation are presented in Tables II-XII. Namely, a few numerical examples (Tables II-XII) are elaborated to illustrate the simple and the advanced STFT iterative procedure. Of course, values of X are estimated with arbitrary number of accurate digits in the numerical structure. Its graphical simulations are presented in Figs. 1, 2, 3, and 4.

TABLE X.

Confirmations of the stability of the STFT algorithm, against extreme small values of eccentricity e. 10−15 < e < 10−3, 1 < M < 2π.

M = 0.1π M = 0.2π M = 0.3π M = 0.4π M = 0.5π M = 0.6π M = 0.7π M = 0.8π M = 0.9π
e Iter. P Iter. P Iter. P Iter. P Iter. P Iter. P Iter. P Iter. P Iter. P
10−15  17  17  17  18  32  18  17  17  17 
31  32  33  34  68  34  33  32  32 
47  47  48  49  82  49  48  47  47 
62  62  63  65  98  65  63  62  62 
10−13  15  15  15  16  16  16  15  15  15 
27  28  29  30  30  30  29  28  28 
41  41  41  43  43  43  42  41  40 
54  54  55  57  57  57  55  54  54 
10−10  12  12  12  13  22  13  12  12  12 
22  22  23  24  34  24  23  22  22 
32  32  33  34  43  34  33  32  32 
42  42  47  43  63  45  43  42  42 
10−7  10  10  10 
16  16  17  18  18  18  17  16  16 
23  23  24  25  25  25  24  23  23 
30  30  31  33  33  33  31  30  30 
10−5  22 
12  12  13  14  31  14  13  12  12 
17  17  18  19  41  19  18  17  17 
22  22  23  25  50  25  23  22  21 
10−3  10  10  10 
11  11  12  13  13  13  12  11  11 
14  14  15  17  17  17  15  14  14 
20  20  22  20  20  20  22  20  20 
0.1 
10  10  10  10  10  10  10  10  10 
14  15  13  15  11  15  15  16  10  15  12  15  13  15  14  15 
19  20  17  20  15  20  11  20  20  14  21  16  20  18  20  19  20 
M = 0.1π M = 0.2π M = 0.3π M = 0.4π M = 0.5π M = 0.6π M = 0.7π M = 0.8π M = 0.9π
e Iter. P Iter. P Iter. P Iter. P Iter. P Iter. P Iter. P Iter. P Iter. P
10−15  17  17  17  18  32  18  17  17  17 
31  32  33  34  68  34  33  32  32 
47  47  48  49  82  49  48  47  47 
62  62  63  65  98  65  63  62  62 
10−13  15  15  15  16  16  16  15  15  15 
27  28  29  30  30  30  29  28  28 
41  41  41  43  43  43  42  41  40 
54  54  55  57  57  57  55  54  54 
10−10  12  12  12  13  22  13  12  12  12 
22  22  23  24  34  24  23  22  22 
32  32  33  34  43  34  33  32  32 
42  42  47  43  63  45  43  42  42 
10−7  10  10  10 
16  16  17  18  18  18  17  16  16 
23  23  24  25  25  25  24  23  23 
30  30  31  33  33  33  31  30  30 
10−5  22 
12  12  13  14  31  14  13  12  12 
17  17  18  19  41  19  18  17  17 
22  22  23  25  50  25  23  22  21 
10−3  10  10  10 
11  11  12  13  13  13  12  11  11 
14  14  15  17  17  17  15  14  14 
20  20  22  20  20  20  22  20  20 
0.1 
10  10  10  10  10  10  10  10  10 
14  15  13  15  11  15  15  16  10  15  12  15  13  15  14  15 
19  20  17  20  15  20  11  20  20  14  21  16  20  18  20  19  20 
FIG. 2.

Eccentric anomalies of elliptic motion E as function of eccentricity e for various values of mean anomaly M.

FIG. 2.

Eccentric anomalies of elliptic motion E as function of eccentricity e for various values of mean anomaly M.

Close modal
FIG. 3.

Eccentric anomaly of elliptic motion E as function of mean anomaly M for various values of eccentricity.

FIG. 3.

Eccentric anomaly of elliptic motion E as function of mean anomaly M for various values of eccentricity.

Close modal
FIG. 4.

3D graphical presentation of the function E=f (e, M).

FIG. 4.

3D graphical presentation of the function E=f (e, M).

Close modal

It is not difficult to see that simple and advanced STFT iterative procedure gives impressive results which suggest that a novel STFT approach (approximate analytical solution to the eccentric anomaly in celestial mechanics E) works. Also, it can be concluded that this iterative procedure gives very high accuracy even with a comprehensive number of iteration. In Tables II-XII, and on Fig. 1, for the different Kepler equation parameters, the convergence of the iterative procedure is proved practically.

Let us note that advantages of the STFT simple and advanced iterative procedure are: Conceptual simplicity, absent of boundary conditions (starting value of B is exp (1), or, starting value of w is (1+e)), easy numerical implementation supported by Mathematica program. Also, computational time is small.

For concrete examples, accuracy of calculations which are realized using the proposed analytical solution and using methods which are found in the literature (Ref. 6): Lagrange method, Bessel functions, and Lambert W functions) were compared. It is clearly demonstrated that the proposed approximate analytical solution, for the small number of members, reaches higher accuracy than other observed method. It is important to note that, once again, the method6 is based on the combined application of Lambert equations as well as iterative procedure. Thus, the approximate STFT analytical results are compared with the calculated values of other methods, presented in Ref. 6, for alternative proving its significance (Table VIII.A).

Finally, the general comparison between different methods for Kepler’s transcendental equation solving, for all values of eccentricity e (e ∈ (0, 1]) and mean anomaly M (M ∈ [0, 2π]) is given in Table VIII.B.

In this subsection, the numerical results and graphical presentations of function E=f (e) for different value of mean anomaly M, and the numerical results and graphical presentations of function E=f(M) for different value of eccentricity e are given using equations (23) and (57a). Tables and graphics are given respectively. Namely, the mentioned numerical simulations and graphical presentations imply the following:

a) Examinations of the STFT method for possibilities 10−15 < e < 1 − 10−15, 0 < M < 2π (Table IX);

b) Confirmations of the stability of the STFT algorithm, against extreme small values of eccentricity e, 10−15 < e < 10−3, 1 < M < 2π by using a novel starting value of X, Eq. (64) or Eq. (65), respectively (Table X); Note that these results are impressive;

c) Examinations of the STFT method validity, for 0.1 < e < 0.9, 0.1 ⋅ π < M < 0.95 ⋅ 2π (Table XI);

TABLE XI.

Examinations of the STFT method validity, for possibilities: 0.1 < e < 0.9, 0.1π < M < 0.9π.

M = 0.1π M = 0.2π M = 0.3π M = 0.4π M = 0.5π M = 0.6π M = 0.7π M = 0.8π M = 0.9π
E Iter. P Iter. P Iter. P Iter. P Iter. P Iter. P Iter. P Iter. P Iter. P
0.2 
12  10  10  10  10  10  10  10  10  10  12  10  13  10 
19  15  16  15  13  15  15  10  16  13  15  16  15  18  15  20  15 
26  20  22  20  17  20  11  20  13  20  18  20  22  20  25  20  27  20 
0.35  10  10  11  12 
16  10  12  10  10  10  10  12  10  15  10  17  10  19  10 
26  15  20  15  13  15  16  14  15  19  15  23  15  27  15  29  15 
36  20  27  20  18  20  20  19  20  26  20  32  20  37  20  40  20 
0.5  13  11  13  16  18 
21  10  13  10  11  10  12  10  17  10  21  10  25  10  25  10 
34  15  21  15  11  15  12  15  20  15  27  15  34  15  39  15  44  15 
47  20  29  20  15  20  17  20  27  20  37  20  46  20  54  20  60  20 
0.65  17  11  15  20  24  28 
23  10  11  10  11  11  10  17  10  25  10  31  10  38  10  43  10 
38  15  19  15  16  18  15  28  15  39  15  50  15  61  15  70  15 
54  20  26  20  20  25  20  39  20  53  20  69  20  83  20  94  20 
0.8  13  10  16  23  32  42  51 
22  10  10  10  16  10  25  10  36  10  50  10  66  10  80  10 
36  15  13  15  14  15  26  15  41  15  59  15  81  15  106  15  128  15 
50  20  19  20  20  20  36  20  56  20  81  20  112  20  147  20  176  20 
0.95  14  24  39  65  111  180 
16  10  10  13  10  24  10  39  10  63  10  104  10  177  10  287  10 
27  15  15  22  15  39  15  63  15  102  15  169  15  286  15  466  15 
37  20  21  31  20  54  20  87  20  141  20  233  20  396  20  645  20 
M = 0.1π M = 0.2π M = 0.3π M = 0.4π M = 0.5π M = 0.6π M = 0.7π M = 0.8π M = 0.9π
E Iter. P Iter. P Iter. P Iter. P Iter. P Iter. P Iter. P Iter. P Iter. P
0.2 
12  10  10  10  10  10  10  10  10  10  12  10  13  10 
19  15  16  15  13  15  15  10  16  13  15  16  15  18  15  20  15 
26  20  22  20  17  20  11  20  13  20  18  20  22  20  25  20  27  20 
0.35  10  10  11  12 
16  10  12  10  10  10  10  12  10  15  10  17  10  19  10 
26  15  20  15  13  15  16  14  15  19  15  23  15  27  15  29  15 
36  20  27  20  18  20  20  19  20  26  20  32  20  37  20  40  20 
0.5  13  11  13  16  18 
21  10  13  10  11  10  12  10  17  10  21  10  25  10  25  10 
34  15  21  15  11  15  12  15  20  15  27  15  34  15  39  15  44  15 
47  20  29  20  15  20  17  20  27  20  37  20  46  20  54  20  60  20 
0.65  17  11  15  20  24  28 
23  10  11  10  11  11  10  17  10  25  10  31  10  38  10  43  10 
38  15  19  15  16  18  15  28  15  39  15  50  15  61  15  70  15 
54  20  26  20  20  25  20  39  20  53  20  69  20  83  20  94  20 
0.8  13  10  16  23  32  42  51 
22  10  10  10  16  10  25  10  36  10  50  10  66  10  80  10 
36  15  13  15  14  15  26  15  41  15  59  15  81  15  106  15  128  15 
50  20  19  20  20  20  36  20  56  20  81  20  112  20  147  20  176  20 
0.95  14  24  39  65  111  180 
16  10  10  13  10  24  10  39  10  63  10  104  10  177  10  287  10 
27  15  15  22  15  39  15  63  15  102  15  169  15  286  15  466  15 
37  20  21  31  20  54  20  87  20  141  20  233  20  396  20  645  20 

d) Tested of the STFT method validity for very high eccentricity (Table XII)

TABLE XII.

Examinations of the STFT method validity for very high eccentricity 1 − 10−3 < e < 1 − 10−15, 0.1π < M < 2π.

M = 0.1π M = 0.2π M = 0.3π M = 0.4π M = 0.5π M = 0.6π M = 0.7π M = 0.8π M = 0.9π
E Iter. P Iter. P Iter. P Iter. P Iter. P Iter. P Iter. P Iter. P Iter. P
1-10−3  16  27  45  73 
16  10  12  13  10  24  10  39  10  63  10  104  10  177  10  288  10 
27  15  15  22  15  39  15  63  15  102  15  169  15  287  15  467  15 
1-10−5  11  19  36  77  214 
14  10  10  15  10  27  10  45  10  77  10  144  10  315  10  931  10 
24  15  15  25  15  44  15  73  15  126  15  234  15  513  15  1528  15 
1-10−10  11  20  38  87  315 
14  10  11  15  10  27  10  46  10  80  10  154  10  358  10  1422  10 
23  15  10  16  25  15  45  15  75  15  131  15  249  15  628  15  2344  14 
1-10−15  11  20  38  87  316 
14  10  11  15  10  27  10  46  10  80  10  153  10  358  10  1427  10 
23  15  10  16  25  15  45  15  75  15  131  15  249  15  583  15  2352  15 
M = 0.1π M = 0.2π M = 0.3π M = 0.4π M = 0.5π M = 0.6π M = 0.7π M = 0.8π M = 0.9π
E Iter. P Iter. P Iter. P Iter. P Iter. P Iter. P Iter. P Iter. P Iter. P
1-10−3  16  27  45  73 
16  10  12  13  10  24  10  39  10  63  10  104  10  177  10  288  10 
27  15  15  22  15  39  15  63  15  102  15  169  15  287  15  467  15 
1-10−5  11  19  36  77  214 
14  10  10  15  10  27  10  45  10  77  10  144  10  315  10  931  10 
24  15  15  25  15  44  15  73  15  126  15  234  15  513  15  1528  15 
1-10−10  11  20  38  87  315 
14  10  11  15  10  27  10  46  10  80  10  154  10  358  10  1422  10 
23  15  10  16  25  15  45  15  75  15  131  15  249  15  628  15  2344  14 
1-10−15  11  20  38  87  316 
14  10  11  15  10  27  10  46  10  80  10  153  10  358  10  1427  10 
23  15  10  16  25  15  45  15  75  15  131  15  249  15  583  15  2352  15 

In addition, in Fig. 2. eccentric anomalies of elliptic motion E as function of eccentricity e for various values of mean anomaly M are presented. In Fig. 3. Eccentric anomaly of elliptic motion E as function of mean anomaly for various values of eccentricity e is presented. Finally, the 3D graphical presentation of the function E=f (elm) is given in Fig. 4.

Also, we repeat that this paper presents a completely new and original method for Kepler’s transcendental equations solving. This novel method is based on the application of the Perovich’s Special Trans Functions Theory. The various examples of Kepler’s equation solving, based on the proposed Simple and Advanced STFT iterative procedure, are presented. It is shown that proposed iterative procedure works for full region of parameters M and e. On the other hand, the presented STFT procedure has a high accuracy with small number of iterations, for M < π/2, and for all values of eccentricity e.

Based on the developed iterative procedure, the approximate analytical solution of Kepler’s transcendental equation is determined (equations (23) and (57a)) and numerically and graphically simulated.

From the previous sections it is obvious that the Special Tran Functions Theory is a consistent general approach to solving Kepler’s transcendental equations in celestial mechanics domain.

A new formulae within Kepler’s equation analysis – Eqs. (20), and Eqs. (57) (or, Eqs. (23) and (57a)), being derived in the paper, using the STFT, is valid in the numerical sense (See Tables I-XII) Thus, obtained analytical solutions apart from theoretical value have practical application. The theoretical accuracy of the STFT is unlimited, and extreme precision is attainable with this approach (See numerical results for error functions in Tables I-XI). Also, a new, original STFT advanced iterative procedure for determination of the Kepler’s equation solutions with high level of precision is applied in the paper. Advantage of this STFT iterative procedure is evident comparing to the conventional analytical methods, because in conceptual sense is simple and starting conditions are not needed. Actually, procedure can begin with the value of B= (exp(1)), or, consequently, from Eqs. (50) and (51) of value (1)W = (1 + e). It has to be underlined that computation complexity is far better than in other conventional methods based on the Lambert W function. For instance, the iterative methods referred in Ref. 6, approved to demand great number of iterations or a great number of approximations has been made and presentations of these methods are not comprehensive. The mentioned problems do not imply STFT. Let us note that advantage of the STFT iterative procedure for solving the Kepler’s transcendental equation, is conceptual simplicity, absent of boundary conditions and easy numerical implementation by using Mathematica program. In other words, it should be noted that the STFT simple and advanced iterative procedures show very good computation time, very good accuracy for all region for M (<0M < 2π) and e (0 < e < 1).

Consequently, it is more than obvious that STFT presents a very interesting theory for the analysis of Kepler’s transcendental equations. We have found, using the Mathematica program those STFT simple and advanced iterative models implies obtaining numerical results with arbitrary number of significant figs. (Tables I-XII).

According to the authors’ knowledge this is the first direct application of STFT iterative procedures to the genesis an analytical solution of the Kepler’s transcendental equation with high precision (with arbitrary number of accurate digits in the numerical structure of the eccentric anomaly in celestial mechanic E, and, consequently, in the position P(r, v) et time t)

The paper is a part of the research done within the project No.01/2337/14, supported and financed by Ministry of Science of Montenegro. The authors would like to thank to this continuous interest and support.

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