MathieuCharacteristicExponent[a,q]
gives the characteristic exponent r for Mathieu functions with characteristic value a and parameter q.
MathieuCharacteristicExponent
MathieuCharacteristicExponent[a,q]
gives the characteristic exponent r for Mathieu functions with characteristic value a and parameter q.
Details
- Mathematical function, suitable for both symbolic and numerical manipulation.
- All Mathieu functions have the form
where
has period
and r is the Mathieu characteristic exponent. - For certain special arguments, MathieuCharacteristicExponent automatically evaluates to exact values.
- MathieuCharacteristicExponent can be evaluated to arbitrary numerical precision.
- MathieuCharacteristicExponent automatically threads over lists.
Examples
open all close allBasic Examples (3)
MathieuCharacteristicExponent[2, 0.5]Plot over a subset of the reals:
Plot[MathieuCharacteristicExponent[3, x], {x, -2, 2}]Plot over a subset of the complexes:
ComplexPlot3D[MathieuCharacteristicExponent[3, z], {z, -7 - 7I, 7 + 7I}, PlotLegends -> Automatic]Scope (15)
Numerical Evaluation (7)
MathieuCharacteristicExponent[0.2, 0.4]N[MathieuCharacteristicExponent[Pi, E]]MathieuCharacteristicExponent threads elementwise over lists:
MathieuCharacteristicExponent[5, {0.5, 1.0, 1.5}]N[MathieuCharacteristicExponent[17 / 3, 1 / 2], 30]The precision of the output tracks the precision of the input:
MathieuCharacteristicExponent[5, 0.501111111111004564560000]N[MathieuCharacteristicExponent[Pi / 2, 2 + I]]Evaluate efficiently at high precision:
MathieuCharacteristicExponent[1 / 5647, 5`100]//TimingMathieuCharacteristicExponent[1 / 5271, 75`1000];//TimingCompute average-case statistical intervals using Around:
MathieuCharacteristicExponent[3, Around[1, 0.01]]Compute the elementwise values of an array:
MathieuCharacteristicExponent[.2, {{1, 0}, {0, 2}}]Or compute the matrix MathieuCharacteristicExponent function using MatrixFunction:
MatrixFunction[MathieuCharacteristicExponent[.2, #]&, {{1, 0}, {0, 2}}]Specific Values (2)
Simple exact values are generated automatically:
MathieuCharacteristicExponent[a, 0]Find a value of q for which MathieuCharacteristicExponent[3,q]=1.7:
qval = q /. FindRoot[MathieuCharacteristicExponent[3, q ] == 1.7, {q, 1}]Plot[MathieuCharacteristicExponent[3, q ], {q, -1, 2}, Epilog -> Style[Point[{qval, MathieuCharacteristicExponent[3, qval ]}], PointSize[Large], Red]]Visualization (3)
Plot the MathieuCharacteristicExponent function for integer parameters:
Plot[{MathieuCharacteristicExponent[3, x], MathieuCharacteristicExponent[5, x], MathieuCharacteristicExponent[7, x]}, {x, -2, 2}]Plot the MathieuCharacteristicExponent function for noninteger parameters:
Plot[{MathieuCharacteristicExponent[1 / 7, x], MathieuCharacteristicExponent[1 / 3, x], MathieuCharacteristicExponent[1 / 2, x]}, {x, -1, 1}]Plot the real part of MathieuCharacteristicExponent:
ComplexContourPlot[Re[MathieuCharacteristicExponent[10, z]], {z, -4 - 4I, 4 + 4I}, IconizedObject[«PlotOptions»]]Plot the imaginary part of MathieuCharacteristicExponent:
ComplexContourPlot[Im[MathieuCharacteristicExponent[10, z]], {z, -4 - 4I, 4 + 4I}, IconizedObject[«PlotOptions»]]Function Properties (3)
MathieuCharacteristicExponent[3,x] is neither non-decreasing nor non-increasing:
FunctionMonotonicity[MathieuCharacteristicExponent[3, x], x]MathieuCharacteristicExponent[3,x] is neither non-negative nor non-positive:
FunctionSign[MathieuCharacteristicExponent[3, x], x]MathieuCharacteristicExponent[3,x] is neither convex nor concave:
FunctionConvexity[MathieuCharacteristicExponent[3, x], x]Applications (2)
Solve the Schrödinger equation with periodic potential:
DSolve[-y''[x] + Cos[x]y[x] == ℰ y[x], y[x], x]By the Bloch theorem, solutions are bounded provided
is within an energy band. The energy gap corresponds to a range of
where MathieuCharacteristicExponent has a non-vanishing imaginary part:
Plot[{ArcTan[Re[MathieuS[a, 2, 100]]], Im[MathieuCharacteristicExponent[a, 2]]}, {a, 2, 8}, WorkingPrecision -> 16, PlotStyle -> {{Dashing[Tiny]}, {Thick}}]This shows the stability diagram for the Mathieu equation:
RegionPlot[Im[MathieuCharacteristicExponent[a, q]] == 0, {q, 0, 20}, {a, -5, 20}, PlotPoints -> 60, MaxRecursion -> 3]Properties & Relations (2)
The characteristic exponent and the characteristic are inverses of each other:
FindRoot[MathieuCharacteristicExponent[a, 1] == 3 / 2, {a, 0.8, 1.6}]MathieuCharacteristicA[1.5, 1]From the plot, you can see that MathieuCharacteristicExponent[x,0]=
:
Plot[{MathieuCharacteristicExponent[x, 0], Sqrt[x] + 1}, {x, 0, 5}]Tech Notes
Related Guides
Related Links
History
Introduced in 1996 (3.0)
Text
Wolfram Research (1996), MathieuCharacteristicExponent, Wolfram Language function, https://reference.wolfram.com/language/ref/MathieuCharacteristicExponent.html.
CMS
Wolfram Language. 1996. "MathieuCharacteristicExponent." Wolfram Language & System Documentation Center. Wolfram Research. https://reference.wolfram.com/language/ref/MathieuCharacteristicExponent.html.
APA
Wolfram Language. (1996). MathieuCharacteristicExponent. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/MathieuCharacteristicExponent.html
BibTeX
@misc{reference.wolfram_2026_mathieucharacteristicexponent, author="Wolfram Research", title="{MathieuCharacteristicExponent}", year="1996", howpublished="\url{https://reference.wolfram.com/language/ref/MathieuCharacteristicExponent.html}", note=[Accessed: 13-June-2026]}
BibLaTeX
@online{reference.wolfram_2026_mathieucharacteristicexponent, organization={Wolfram Research}, title={MathieuCharacteristicExponent}, year={1996}, url={https://reference.wolfram.com/language/ref/MathieuCharacteristicExponent.html}, note=[Accessed: 13-June-2026]}