Skip to main content

differential geometry - How to calculate scalar curvature Ricci tensor and Christoffel symbols in Mathematica?


I am seeking a convenient and effective way to calculate such geometric quantities. I've used packages like TensoriaCalc, but they don't work at all time. Sometimes, I run into the following error:



Symbol Tensor is Protected.
Symbol TensorType is Protected.
Symbol TensorName is Protected.



Here is the code I'm using:


Clear [i, j, φ, τ, σ] 
q["case"] = Metric[ SubMinus[i], SubMinus[j],

E^(2 φ[σ]) (\[DifferentialD]τ^2 + \[DifferentialD] σ^2),
CoordinateSystem -> {τ, σ}, TensorName -> "T", StartIndex -> 1 ]

I think the above is correct, since I merely modified the example from the package manual. It gives me the correct answer sometimes (if I only use one notebook).


Also, I ran the codes from the chapter "General Relativity" in the book "Mathmatica for theoretical physics" by Gerd Baumann, but none of them work


Is there more efficient way to calculate them? Please give me some suggestions about this.



Answer



I stumbled upon this question via Google. Thanks for using my TensoriaCalc package!


My response is probably too late, but I believe the problem you cited




Symbol Tensor is Protected.
Symbol TensorType is Protected.
Symbol TensorName is Protected.



is because you loaded TensoriaCalc more than once in the same kernel session.


When writing the package, I had to Protect all the symbols used in the package, such as Tensor, Metric, etc. This means their definitions cannot be altered by an external user, as otherwise, it will create inconsistencies. This is why loading TensoriaCalc more than once gives an error, because you are essentially trying to define these symbols yet again.


Hope this helps.


Comments

Popular posts from this blog

plotting - Plot 4D data with color as 4th dimension

I have a list of 4D data (x position, y position, amplitude, wavelength). I want to plot x, y, and amplitude on a 3D plot and have the color of the points correspond to the wavelength. I have seen many examples using functions to define color but my wavelength cannot be expressed by an analytic function. Is there a simple way to do this? Answer Here a another possible way to visualize 4D data: data = Flatten[Table[{x, y, x^2 + y^2, Sin[x - y]}, {x, -Pi, Pi,Pi/10}, {y,-Pi,Pi, Pi/10}], 1]; You can use the function Point along with VertexColors . Now the points are places using the first three elements and the color is determined by the fourth. In this case I used Hue, but you can use whatever you prefer. Graphics3D[ Point[data[[All, 1 ;; 3]], VertexColors -> Hue /@ data[[All, 4]]], Axes -> True, BoxRatios -> {1, 1, 1/GoldenRatio}]

plotting - Filling between two spheres in SphericalPlot3D

Manipulate[ SphericalPlot3D[{1, 2 - n}, {θ, 0, Pi}, {ϕ, 0, 1.5 Pi}, Mesh -> None, PlotPoints -> 15, PlotRange -> {-2.2, 2.2}], {n, 0, 1}] I cant' seem to be able to make a filling between two spheres. I've already tried the obvious Filling -> {1 -> {2}} but Mathematica doesn't seem to like that option. Is there any easy way around this or ... Answer There is no built-in filling in SphericalPlot3D . One option is to use ParametricPlot3D to draw the surfaces between the two shells: Manipulate[ Show[SphericalPlot3D[{1, 2 - n}, {θ, 0, Pi}, {ϕ, 0, 1.5 Pi}, PlotPoints -> 15, PlotRange -> {-2.2, 2.2}], ParametricPlot3D[{ r {Sin[t] Cos[1.5 Pi], Sin[t] Sin[1.5 Pi], Cos[t]}, r {Sin[t] Cos[0 Pi], Sin[t] Sin[0 Pi], Cos[t]}}, {r, 1, 2 - n}, {t, 0, Pi}, PlotStyle -> Yellow, Mesh -> {2, 15}]], {n, 0, 1}]

plotting - Mathematica: 3D plot based on combined 2D graphs

I have several sigmoidal fits to 3 different datasets, with mean fit predictions plus the 95% confidence limits (not symmetrical around the mean) and the actual data. I would now like to show these different 2D plots projected in 3D as in but then using proper perspective. In the link here they give some solutions to combine the plots using isometric perspective, but I would like to use proper 3 point perspective. Any thoughts? Also any way to show the mean points per time point for each series plus or minus the standard error on the mean would be cool too, either using points+vertical bars, or using spheres plus tubes. Below are some test data and the fit function I am using. Note that I am working on a logit(proportion) scale and that the final vertical scale is Log10(percentage). (* some test data *) data = Table[Null, {i, 4}]; data[[1]] = {{1, -5.8}, {2, -5.4}, {3, -0.8}, {4, -0.2}, {5, 4.6}, {1, -6.4}, {2, -5.6}, {3, -0.7}, {4, 0.04}, {5, 1.0}, {1, -6.8}, {2, -4.7}, {3, -1....