Difference between revisions of "User:Tohline/Appendix/Ramblings/Azimuthal Distortions"
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[[File:HI11Fig16Animate.gif350pxFigure 16 from HI11]]  
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Revision as of 01:07, 28 January 2016
Analyzing Azimuthal Distortions
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In what follows, we will draw heavily from three publications: (1) J. E. Tohline & I. Hachisu (1990, ApJ, 361, 394407) — hereafter, TH90 — (2) J. W. Woodward, J. E. Tohline, & I. Hachisu (1994, ApJ, 420, 247267) — hereafter, WTH94 — and (3) K. Hadley & J. N. Imamura (2011, Astrophysics and Space Science, 334, 1) — hereafter, HI11.
Adopted Notation
Beginning with equation (2) of TH90 but ignoring variations in the vertical coordinate direction, the mass density is given by the expression,
<math>~\rho</math> 
<math>~=</math> 
<math>~\rho_0 \biggl[ 1 + f(\varpi)e^{i(\omega t  m\phi)} \biggr] \, ,</math> 
where it is understood that <math>~\rho_0</math>, which defines the structure of the initial axisymmetric equilibrium configuration, is generally a function of the cylindrical radial coordinate, <math>~\varpi</math>.
Using the subscript, <math>~m</math>, to identify the timeinvariant coefficients and functions that characterize the intrinsic eigenvector of each azimuthal eigenmode, and acknowledging that the associated eigenfrequency will in general be imaginary, that is,
<math>~\omega_m</math> 
<math>~=</math> 
<math>~\omega_R + i\omega_I \, ,</math> 
we expect each unstable mode to display the following behavior:
<math>~\biggl[ \frac{\rho}{\rho_0}  1 \biggr]</math> 
<math>~=</math> 
<math>~f_m(\varpi)e^{i[\omega_R t + i \omega_I t  m\phi_m(\varpi)]} </math> 

<math>~=</math> 
<math>~\biggl\{ f_m(\varpi)e^{im\phi_m(\varpi)}\biggr\} e^{i\omega_R t } \cdot e^{\omega_I t} </math> 

<math>~=</math> 
<math>~\biggl\{ f_m(\varpi)e^{i[\omega_R t + m\phi_m(\varpi)]} \biggr\} e^{\omega_I t} \, .</math> 
Adopting Kojima's (1986) notation, that is, defining,
<math>~y_1 \equiv \frac{\omega_R}{\Omega_0}  m</math> 
and 
<math>~y_2 \equiv \frac{\omega_I}{\Omega_0} \, ,</math> 
the eigenvector's behavior can furthermore be described by the expression,
<math>~\biggl[ \frac{\rho}{\rho_0}  1 \biggr]</math> 
<math>~=</math> 
<math>~\biggl\{ f_m(\varpi)e^{i[(y_1+m) (\Omega_0 t) + m\phi_m(\varpi)]} \biggr\} e^{y_2 (\Omega_0 t)} </math> 

<math>~=</math> 
<math>~\biggl\{ f_m(\varpi)e^{im[(y_1/m+1) (\Omega_0 t) + \phi_m(\varpi)]} \biggr\} e^{y_2 (\Omega_0 t)} \, .</math> 
Note that, as viewed from a frame of reference that is rotating with the mode pattern frequency,
<math>\Omega_p \equiv \frac{\omega_R}{m} = \Omega_0\biggl(\frac{y_1}{m}+1\biggr) \, ,</math>
we should find an eigenvector of the form,
<math>~\biggl[ \frac{\delta\rho}{\rho_0}\biggr]_\mathrm{rot} \equiv \biggl[ \frac{\rho}{\rho_0}  1 \biggr]e^{im\Omega_p t}</math> 
<math>~=</math> 
<math>~\biggl\{ f_m(\varpi)e^{im[\phi_m(\varpi)]} \biggr\} e^{y_2 (\Omega_0 t)} \, ,</math> 
whose relative amplitude — with a radial structure as specified inside the curly braces — is undergoing a uniform exponential growth but is otherwise unchanging.
Drawing from figure 2 of WTH94, our Figure 1, immediately below, illustrates how the behavior of each factor in this expression can reveal itself during a numerical simulation that follows the timeevolutionary development of an unstable, nonaxisymmetric eigenmode. The initial model for this depicted evolution (model O3 from Table 1 of WTH94) is a zeromass — that is, it is a PapaloizouPringle like torus — with polytropic index,<math>~n = 3</math>, and a rotationlaw profile defined by uniform specific angular momentum.
 The topleft panel shows how, at any radial location, the phase angle, <math>~\phi_1/(2\pi)</math>, for the <math>~m=1</math> eigenmode, varies with time, <math>~t/t_\mathrm{rot}</math>, where, <math>~t_\mathrm{rot} \equiv 2\pi/\Omega_0</math> is the rotation period at the density maximum;
 Using a semilog plot, the topright panel shows the exponential growth of the amplitude of three separate modes: The dominant unstable mode, displaying the largest amplitude, is <math>~m = 1</math>.
 Using a semilog plot (log amplitude versus fractional radius, <math>~\varpi/r_+</math>), the bottomleft panel displays the shape of the eigenfunction, <math>~f_1(\varpi)</math>, for the unstable, <math>~m=1</math> mode;
 The bottomright panel displays the radial dependence of the equatorialplane phase angle, <math>~\phi_1(\varpi)</math>, for the unstable, <math>~m=1</math> mode; this is what HI11 refer to as the "constant phase loci."
Figure 1 
Four panels extracted^{†} from figure 2, p. 252 of J. W. Woodward, J. E. Tohline & I. Hachisu (1994)
"The Stability of Thick, Selfgravitating Disks in Protostellar Systems"
ApJ, vol. 420, pp. 247267 © American Astronomical Society 
^{†}As displayed here, the layout of figure panels (a, b, c, d) has been modified from the original publication layout; otherwise, each panel is unmodified. 
Empirical Construction of Eigenvector
Summary
While studying the series of three papers that was published recently by the Imamura & Hadley collaboration, I was particularly drawn to the pair of plots presented in Figure 6 — and, again, in the top portion of Figure 13 — of HI11. This pair of plots has been reprinted here, without modification, as our Figure 2. As in the bottom two panels of our Figure 1, the curves delineated by the blue dots in this pair of HI11 plots display (on the left) the shape of the eigenfunction, <math>~f_1(\varpi)</math>, and (on the right) the "constant phase loci," <math>~\phi_1(\varpi)</math>, for an unstable, <math>~m=1</math> mode. In this case, the initial model for the depicted evolution is the equilibrium model from Table 2 of HI11 that has <math>~T/W = 0.253</math>; it is a fully selfgravitating torus with polytropic index, <math>~n = 3/2</math>, and a rotationlaw profile defined by a "Keplerian" angular velocity profile.
Figure 2 
Panel pair extracted^{†} without modification from the topmost segment of Figure 13, p. 12 of K. Hadley & J. N. Imamura (2011)
"Nonaxisymmetric Instabilities of SelfGravitating Disks. I Toroids"
Astrophysics and Space Science, 334, 1  26 © Springer Science+Business Media B.V. 
^{†}This pair of plots also appears, by itself, as Figure 6 on p. 12 of K. Hadley & J. N. Imamura (2011). 
Figure 3: Our Empirically Constructed Eigenvector 

Left panel: A plot of our empirically constructed radial amplitude function, <math>~f_\ln(\varpi)</math>; the function has been normalized as explained in the boxedin PRACTICAL IMPLEMENTATION remark, below. Right panel: A plot of our empirically constructed phase function, <math>~\phi_1(\varpi)</math> with <math>~\aleph = 8.0</math>; after extraction from the animation sequence presented in Figure 4, here each point along this "constant phase loci" has been shifted by an additional phase of <math>~\pi/10</math> in order to better highlight its resemblance to the HI11 "constant phase loci" plot shown in the righthand panel of our Figure 2. In both panels, blue dots trace the function's behavior over the inner region of the torus <math>~(r_ < \varpi < r_\mathrm{mid})</math> and green dots trace the function's behavior over the outer region of the torus <math>~(r_\mathrm{mid} < \varpi < r_+)</math>. 
As is described in the subsections that follow, we have devised two related and relatively simple analytic expressions whose behaviors, as a function of <math>~\varpi</math>, qualitatively resemble the two blue, HI11 curves. Our two empirically constructed functions have been plotted in Figure 3, immediately below Figure 2, to aid visual comparison with the eigenfunctions that were generated by HI11 via a proper stability analysis. Next we describe the thought process that led to the construction of the amplitude and phase eigenfunctions presented in Figure 3.
Radial Eigenfunction
It occurred to me, first, that the blue curve displayed in the lefthand panel of HI11's figure 6 (our Figure 2) might be reasonably well approximated by piecing together a pair of archyperbolictangent (ATANH) functions. In an effort to demonstrate this, I began by specifying a "midway" radial location, <math>~r_ < r_\mathrm{mid} < r_+ \, ,</math> at which the two ATANH functions meet and at which the density fluctuation is smallest. Then I defined a function of the form,
<math>~f_\ln(\varpi)</math> 
<math>~=</math> 
<math>~\tanh^{1}\biggl[1  2 \biggl( \frac{\varpi  r_}{r_\mathrm{mid}r_} \biggr) \biggr]</math> 
for 
<math>r_ < \varpi < r_\mathrm{mid} \, ;</math> 

and  
<math>~f_\ln(\varpi)</math> 
<math>~=</math> 
<math>~\tanh^{1}\biggl[1  2 \biggl( \frac{\varpi  r_+}{r_\mathrm{mid}r_+} \biggr) \biggr]</math> 
for 
<math>r_\mathrm{mid} < \varpi < r_+ \, .</math> 
This empirically specified, twopiece <math>~f_\ln(\varpi)</math> function has been plotted in the lefthand panel of Figure 3. (To facilitate quantitative comparison with Figure 2, the function has been normalized as explained in the boxedin PRACTICAL IMPLEMENTATION remark that follows.) Blue dots trace the function's behavior over the lower radialcoordinate range while green dots trace its behavior over the upper radialcoordinate range. This plot of <math>~f_\ln(\varpi)</math> closely resembles the plot of the eigenfunction, <math>~\delta\rho/\rho (\varpi)</math> (see the lefthand panel of our Figure 2) that developed spontaneously via HI11's linear stability analysis.
PRACTICAL IMPLEMENTATION: At the two limits, <math>~\varpi = r_</math> and <math>~\varpi = r_+</math>, the function, <math>~f_\ln(\varpi) \rightarrow +\infty</math>; while, at the limit, <math>~\varpi = r_\mathrm{mid}</math>, the function, <math>~f_\ln(\varpi) \rightarrow \infty</math>. In practice, after dividing the relevant radial extent into 100 zones, we stay half of a radial zone away from these three limiting radial boundaries, so that the maximum and minimum values of <math>~f_\ln(\varpi)</math> are finite; specifically, in the example plotted here, we have set <math>~[f_\ln]_\mathrm{min} = 2.99448</math> and <math>~[f_\ln]_\mathrm{max} = 2.64665</math>. Then we strategically employ the finite values of the function at these nearboundary limits to rescale the function such that, in the plot shown here, it lies between 3 (minimum amplitude) and 0 (maximum amplitude). 
Recognizing that the figure depicting the HI11 eigenfunction is a semilog plot, it seems clear that the relationship between our constructed function, <math>~f_\ln(\varpi)</math>, and the eigenfunction, <math>~f_1(\varpi)</math>, is,
<math>~f_1(\varpi) = e^{f_\ln(\varpi)} \, .</math>
Now, in general, the following mathematical relation holds:
<math>~\tanh^{1}x</math> 
<math>~=</math> 
<math>~\ln\biggl( \frac{1+x}{1x} \biggr)^{1/2} </math> 
for 
<math>x^2 < 1 \, .</math> 
Hence, for the innermost region of the toroidal configuration — that is, over the lower radialcoordinate range — we can set,
<math>~x</math> 
<math>~=</math> 
<math>~1  2 \biggl( \frac{\varpi  r_}{r_\mathrm{mid}r_} \biggr) </math> 
<math>~\Rightarrow ~~~~ \frac{1+x}{1x}</math> 
<math>~=</math> 
<math> ~\biggl[2  2 \biggl( \frac{\varpi  r_}{r_\mathrm{mid}r_} \biggr)\biggr] \biggl[2 \biggl( \frac{\varpi  r_}{r_\mathrm{mid}r_} \biggr)\biggr]^{1} </math> 

<math>~=</math> 
<math> ~[(r_\mathrm{mid}r_)  ( \varpi  r_)] [(\varpi  r_)]^{1} </math> 

<math>~=</math> 
<math> ~\frac{r_\mathrm{mid}  \varpi}{\varpi  r_} \, . </math> 
Therefore we can write,
<math>~f_1(\varpi) = e^{f_\ln(\varpi)}</math> 
<math>~=</math> 
<math>~\biggl( \frac{r_\mathrm{mid}  \varpi}{\varpi  r_} \biggr)^{1/2} </math> 
for 
<math>r_ < \varpi < r_\mathrm{mid} \, .</math> 
Similarly, we find that, over the upper radialcoordinate range,
<math>~f_1(\varpi) = e^{f_\ln(\varpi)}</math> 
<math>~=</math> 
<math>~\biggl( \frac{r_\mathrm{mid}  \varpi}{\varpi  r_+} \biggr)^{1/2} </math> 
for 
<math>r_\mathrm{mid} < \varpi < r_+ \, .</math> 
Constant Phase Loci
Now let's work on the phase function, <math>~\phi_1(\varpi)</math>. The phase function displayed in the righthand panel of our Figure 2 — that is, the phase function that developed spontaneously from the linear stability analysis performed by HI11 — appears to be fairly constant (i.e., the phase is independent of radius) in the innermost region of the torus and, then again, fairly constant in the outermost region of the torus with a smooth but fairly rapid phase shift of approximately <math>~\pi</math> radians between the two extremes. This is the behavior exhibited by an arctangent (ATAN) function. With this in mind, we have defined a new function, <math>~D(\varpi)</math>, in terms of our empirically derived radial eigenfunction, <math>~f_\ln(\varpi)</math>, as follows:
<math>~D(\varpi)</math> 
<math>~=</math> 
<math>~\frac{f_\ln(\varpi)  [f_\ln]_\mathrm{min}}{[f_\ln]_\mathrm{max}  [f_\ln]_\mathrm{min}} \, .</math> 
It has the following behavior:
 At the inner edge of the torus <math>~(r_)</math>, where <math>~f_\ln(\varpi) = [f_\ln]_\mathrm{max}</math>, <math>~D(\varpi) = 1</math>;
 At <math>~r_\mathrm{mid}</math>, where <math>~f_\ln(\varpi) = [f_\ln]_\mathrm{min}</math>, <math>~D(\varpi) = 0</math>;
 At the outer edge of the torus <math>~(r_+)</math>, where again <math>~f_\ln(\varpi) = [f_\ln]_\mathrm{max}</math>, <math>~D(\varpi) = 1</math>.
This function can therefore satisfactorily serve as an argument of the ATAN function, swinging the phase by <math>~\pi/2</math> over the inner (blue) region of the torus, then swinging the phase by an additional <math>~\pi/2</math> over the outer (green) region of the torus. If we furthermore multiply the function by a variable coefficient — call it, <math>~\aleph</math> — before feeding it to the ATAN function, we can adjust the thickness of the radial domain over which the total phase transition occurs. What appears to work well is the following:
<math>~\phi_1(\varpi) + \frac{\pi}{2} </math> 
<math>~=</math> 
<math>~+~\tan^{1}[\aleph \cdot D(\varpi)]</math> 
for 
<math>r_ < \varpi < r_\mathrm{mid} \, ;</math> 
and
<math>~\phi_1(\varpi) + \frac{\pi}{2} </math> 
<math>~=</math> 
<math>~~\tan^{1}[\aleph \cdot D(\varpi)] </math> 
for 
<math>r_\mathrm{mid} < \varpi < r_+ \, .</math> 
In the lefthand panel of Figure 4, the "constant phase loci" defined by this empirically constructed phase function has been mapped onto a polarcoordinate grid for ten different values of the leading coefficient in the range, <math>~1.0 \le \aleph \le 40.0</math>, as recorded in the bottomright corner of the plot. The constant phase loci created by setting <math>~\aleph = 8.0</math> has been singled out and displayed in the middle panel of Figure 4, because it closely resembles the constant phase loci plot published by HI11a (reprinted here as the righthand panel of Figure 4 to facilitate comparison).
Figure 4  

Constant Phase Loci Generated by Our Empirically Constructed Phase Function, <math>~\phi_1(\varpi)</math>  HI11's Published Constant Phase Loci  
Ten Values of <math>~\aleph</math>  For <math>~\aleph = 8</math>  
Material that appears after this point in our presentation is under development and therefore
may contain incorrect mathematical equations and/or physical misinterpretations.
 Go Home 
Discussion
Simpler Connection Between Radial and Phase Eigenfunctions
When it is used as an argument of ATAN, the function, <math>~D(\varpi)</math>, as defined above smoothly steers <math>~\phi_1</math> through a phase shift of approximately <math>~\pi</math> radians principally because the function itself smoothly varies between <math>~+1</math> and <math>~0</math> (then back again). Let's play with some simpler expressions for this governing function that also vary smoothly between these limits.
Define,
<math>~\Delta_\mathrm{inner}</math> 
<math>~\equiv</math> 
<math>~\biggl( \frac{\varpi  r_}{r_\mathrm{mid}r_} \biggr)</math> 
has range of 
<math>~+0 ~~\rightarrow ~~ +1 \, ;</math> 
<math>~\Delta_\mathrm{outer}</math> 
<math>~\equiv</math> 
<math>~\biggl( \frac{\varpi  r_+}{r_\mathrm{mid}r_+} \biggr)</math> 
has range of 
<math>~+1 ~~\rightarrow ~~ +0 \, .</math> 
The argument of ATANH, as presented above, was obtained from this relatively simple expression via the shift,
<math>~12\Delta_\mathrm{inner}</math> 
<math>~\equiv</math> 
<math>~\biggl( \frac{\varpi  r_}{r_\mathrm{mid}r_} \biggr)</math> 
has range of 
<math>~+1 ~~\rightarrow ~~ 1 \, ;</math> 
<math>~12\Delta_\mathrm{outer}</math> 
<math>~\equiv</math> 
<math>~\biggl( \frac{\varpi  r_+}{r_\mathrm{mid}r_+} \biggr)</math> 
has range of 
<math>~1 ~~\rightarrow ~~ +1 \, .</math> 
For the argument of <math>~D(\varpi)</math> function, we could therefore use,
<math>~1\Delta_\mathrm{inner}</math> 
<math>~\equiv</math> 
<math>~\biggl( \frac{\varpi  r_}{r_\mathrm{mid}r_} \biggr)</math> 
has range of 
<math>~+1 ~~\rightarrow ~~ 0 \, ;</math> 
<math>~1\Delta_\mathrm{outer}</math> 
<math>~\equiv</math> 
<math>~\biggl( \frac{\varpi  r_+}{r_\mathrm{mid}r_+} \biggr)</math> 
has range of 
<math>~0 ~~\rightarrow ~~ +1 \, .</math> 
Playing with the Radial Eigenfunction
Up to this point, we've only considered radial eigenfunctions composed of two components (a "blue" inner component and a "green" outer component) that do not overlap. Here we'll allow the two components to overlap by assigning different values of <math>~r_\mathrm{mid}</math> to the two separate components — more specifically, we'll allow <math>~r_\mathrm{mid}_\mathrm{green} \le r_\mathrm{mid}_\mathrm{blue}</math> — then add the two functions over the region of overlap. Let's consider components of the following form:
<math>~f_\mathrm{blue}(\varpi) </math> 
<math>~=</math> 
<math>~\biggl( \frac{r_\mathrm{blue}  \varpi}{\varpi  r_} \biggr)^{p} </math> 
for 
<math>r_ < \varpi < r_\mathrm{blue} \, ,</math> 
and,
<math>~f_\mathrm{green}(\varpi) </math> 
<math>~=</math> 
<math>~\biggl( \frac{r_\mathrm{green}  \varpi}{\varpi  r_+} \biggr)^{p} </math> 
for 
<math>r_\mathrm{green} < \varpi < r_+ \, ,</math> 
where, <math>~p</math> is a exponent yet to be specified. So, for fixed values of the inner and outer radii of the torus, <math>~r_</math> and <math>~r_+</math>, this twocomponent function has three adjustable variables. They are, <math>~r_\mathrm{blue}</math>, <math>~r_\mathrm{green}</math>, and <math>~p</math>.
Experimenting
In Figure 5, <math>~r_\mathrm{blue}</math> and <math>~r_\mathrm{green}</math> are fixed, and <math>~p</math> is varied.
Figure 5: Variable exponent, <math>~p</math> 

<math>~r_ = 0.5</math>, <math>~r_+ = 1.5</math> … <math>~r_\mathrm{blue} = 1.25</math>, <math>~r_\mathrm{green}= 1.1</math> 
In this example, the exponent, <math>~p</math>, is varied over the range, <math>~0.25 \le p \le 1.2</math>, as indicated by the numerical values shown in the upperlefthand corner of each panel. 
Based on the above discussion, I expected that the best match to the eigenfunctions found in HI11 would be <math>~p=0.5</math>, that is, a squareroot. However, as illustrated in Figure 5, this and other fractional exponents less than unity generate noncontinuous derivatives at the overlapping edges of our twopiece function. Instead, a value of <math>~p = 1.2</math> seems to exhibit a more desired, smooth behavior.
In Figure 6, <math>~r_\mathrm{green}</math> and <math>~p</math> are fixed, and <math>~r_\mathrm{blue}</math> is varied.
Figure 6: Variable <math>~r_\mathrm{blue}</math> 

<math>~r_ = 0.5</math>, <math>~r_+ = 1.5</math> … <math>~p = 1.2</math>, <math>~r_\mathrm{green}= 0.9</math> 
In this example, the "blue" edge is varied over the range, <math>~0.91 \le r_\mathrm{blue} \le 1.25</math>, as indicated by the numerical values shown in the upperlefthand corner of each panel. 
The frames of Figure 6 illustrate the qualitative behavior we have been seeking. Setting the exponent, <math>~p</math>, to a value greater than unity then varying one of the edges of the twopart eigenfunction provides a natural variation from "pointed" curves that look like adjoined archyperbolic tangents to others that look more like a parabola.
Trial Comparison with HI11
In Figure 7, we show how a straightforward, smooth adjustment of one parameter — namely, <math>~r_\mathrm{blue}</math> — generates a series of eigenfunctions that nicely match the set of radial eigenfunctions that are displayed in Figure 16 of HI11.
Figure 7: Radial Eigenfunction Comparison 

(a) Extracted from Figure 16 of HI11  (b) Our Empirically Constructed Function 
Here we set <math>~r_ = 0.6</math>, <math>~r_+ = 1.5</math>, <math>~r_\mathrm{blue}= 1.15</math>, and <math>~p = 1.2</math>, then let the "green" edge vary over the range, <math>~0.605 \le r_\mathrm{green} \le 1.144</math>. Via an animation, the middle panel illustrates the behavior of our empirically constructed eigenfunction over this entire range of values as indicated by the numerical value shown in the bottomrighthand corner of the panel; the top and bottom panels display the shape of our eigenfunction at the two extreme values of <math>~r_\mathrm{green}</math>. 
Relationship to Fourier Series Amplitude and Phase
Recalling that,
<math>~e^{i\alpha}</math> 
<math>~=</math> 
<math>~\cos\alpha + i\sin\alpha \, ,</math> 
we appreciate that the real part of the amplitude term — the term inside the curly braces of the expression found in Figure 1, above — can be written as,
<math>~\mathcal{A}_m \equiv \Re\{f_m e^{im\phi}\}</math> 
<math>~=</math> 
<math>~f_m \cos(m\phi_m) \, .</math> 
When viewed in the context of a discrete Fourier series, we also recognize that the two functions, <math>~f_m</math> and <math>~\phi_m</math>, can be transformed into the pair of amplitude functions,
<math>~f_m ~~~\rightarrow ~~~ (a_m^2 + b_m^2)^{1/2}</math> 
and 
<math>~m\phi_m ~~~\rightarrow ~~~ \tan^{1}\biggl(\frac{b_m}{a_m}\biggr) \, ;</math> 
that is,
<math>~a_m ~=~ f_m\cos(m\phi_m)</math> 
and 
<math>~b_m ~=~ f_m\sin(m\phi_m) \, .</math> 
Let's see where these expression lead us, given our aboveadopted expressions for <math>~f_m</math> and <math>~\phi_m</math>. Given,
<math>~f = e^{f_\ln}</math> 
<math>~=</math> 
<math>~\biggl( \frac{r_\mathrm{blue}  \varpi}{\varpi  r_} \biggr)^{p} \, ,</math> 
and,
<math>~m\phi_m</math> 
<math>~=</math> 
<math>~\tan^{1}[\aleph \cdot D(\varpi)] \, </math> 
where,
<math>~D(\varpi)</math> 
<math>~=</math> 
<math>~\frac{f_\ln(\varpi)  [f_\ln]_\mathrm{min}}{[f_\ln]_\mathrm{max}  [f_\ln]_\mathrm{min}} \, ,</math> 
we have,
<math>~a_m</math> 
<math>~=</math> 
<math>~ \biggl( \frac{r_\mathrm{blue}  \varpi}{\varpi  r_} \biggr)^{p} \cos\biggl[ \tan^{1}\biggl( \aleph \cdot D \biggr) \biggr] </math> 

<math>~=</math> 
<math>~ e^{f_\ln} \biggl[ 1+(\aleph \cdot D )^2 \biggr]^{1/2} </math> 

<math>~=</math> 
<math>~ e^{f_\ln} \bigg\{ 1+\aleph^2_\mathrm{norm} \biggl( f_\ln(\varpi)  [f_\ln]_\mathrm{min} \biggr)^2 \biggr\}^{1/2} \, , </math> 
where,
<math>~\aleph_\mathrm{norm} \equiv \frac{\aleph}{[f_\ln]_\mathrm{max}  [f_\ln]_\mathrm{min}} \, .</math>
Another Improvement
See Also
 Imamura & Hadley collaboration:
 K. Hadley & J. N. Imamura (2011, Astrophysics and Space Science, 334, 126), "Nonaxisymmetric instabilities in selfgravitating disks. I. Toroids"
 K. Z. Hadley, P. Fernandez, J. N. Imamura, E. Keever, R. Tumblin, & W. Dumas (2014, Astrophysics and Space Science, 353, 191222), "Nonaxisymmetric instabilities in selfgravitating disks. II. Linear and quasilinear analyses"
 K. Z. Hadley, W. Dumas, J. N. Imamura, E. Keever, & R. Tumblin (2015, Astrophysics and Space Science, 359, article id. 10, 23 pp.), "Nonaxisymmetric instabilities in selfgravitating disks. III. Angular momentum transport"
© 2014  2021 by Joel E. Tohline 