HeunD[q,α,γ,δ,ϵ,z]
gives the double-confluent Heun function.
HeunD
HeunD[q,α,γ,δ,ϵ,z]
gives the double-confluent Heun function.
Details
- HeunD belongs to the Heun class of functions and occurs in quantum mechanics, mathematical physics and applications.
- Mathematical function, suitable for both symbolic and numerical manipulation.
- HeunD[q,α,γ,δ,ϵ,z] satisfies the double-confluent Heun differential equation
. - The HeunD function is the power-series solution
of the double-confluent Heun equation that satisfies the conditions
and
. - For certain special arguments, HeunD automatically evaluates to exact values.
- HeunD can be evaluated for arbitrary complex parameters.
- HeunD can be evaluated to arbitrary numerical precision.
- HeunD automatically threads over lists.
Examples
open all close allBasic Examples (3)
HeunD[4, -0.6, -0.7 , -0.18, 0.3 , 0.12]Plot the double-confluent Heun function:
Plot[HeunD[4, -0.6, -0.7 , -0.18, 0.3 , x], {x, 3 / 10, 2}]Series expansion of HeunD:
Series[HeunD[q, α, γ, δ, ϵ, z], {z, 1, 2}]Scope (25)
Numerical Evaluation (9)
N[HeunD[9 / 10, -14 / 10, 12 / 100, 3 / 100, -2 / 10, 1 / 10], 50]The precision of the output tracks the precision of the input:
HeunD[9 / 10, -14 / 10, 12 / 100, 3 / 100, -2 / 10, 0.10000000000000000001]HeunD can take one or more complex number parameters:
HeunD[1.2 + I, -1.4, 0.12, 0.03, -0.2, 0.1]HeunD[1.2 + I, -1.4 + 0.I, 0.12 - I, 0.03 + 0.123I, -0.2 - 0.2I, 0.1]HeunD can take complex number arguments:
HeunD[1.2, -1.4, 0.12, 0.03, -0.2, 0.1 + I]Finally, HeunD can take all complex number input:
HeunD[1.2 + I, -1.4 + 0.I, 0.12 - I, 0.03 + 0.123I, -0.2 - 0.2I, 0.1 + I]Evaluate HeunD efficiently at high precision:
HeunD[1 / 2, -1 / 3, 1 / 4, 1 / 5, -1 / 6, 1 / 7`100]//TimingHeunD[1 / 2, -1 / 3, 1 / 4, 1 / 5, -1 / 6, 1 / 7 + I / 2`100]//TimingHeunD[1.2, -1.4, 0.12, 0.03, -0.2, {0.1, 0.1 + I, I, 4}]HeunD[1.2, -1.4, 0.12, 0.03, -0.2, (| | |
| :- | :---- |
| π | u |
| v | (π/2) |) ]Evaluate HeunD for points on the real negative axis, bypassing irregular singular origin:
HeunD[-0.2 + I, -0.3, 0.12, 0.12, -0.32, -1.1]Compute the elementwise values of an array:
HeunD[.1 + I, I, 0.12, 0, -0.32, {{1 / 2, -1}, {1, 1 / 2}}]Or compute the matrix HeunD function using MatrixFunction:
MatrixFunction[HeunD[.1 + I, I, 0.12, 0, -0.32, #]&, {{1 / 2, -1}, {0, 1 / 2}}]Specific Values (2)
Visualization (5)
Plot the HeunD function:
Plot[HeunD[4, -0.6, -0.7 , -0.18, 0.3 , z], {z, 3 / 10, 19 / 10}]Plot the absolute value of the HeunD function for complex parameters:
Plot[Abs[HeunD[4 + I, -0.6 + 0.9 I, -0.7 I, -0.18 - 0.03 I, 0.3 + 0.6 I, z]], {z, 3 / 10, 19 / 10}]Plot HeunD as a function of its second parameter
:
Plot[HeunD[4, α, -0.7, -0.18, 0.3 , z] /. α -> {-2, Sqrt[20], 1 / 10}//Evaluate, {z, 3 / 10, 19 / 10}]Plot HeunD as a function of
and
:
{α, γ, ϵ, δ} = {0.2 + I, -0.6 + 0.9 I, -0.7 I, 0.3 + 0.6 I};Plot3D[Abs[HeunD[q, α, γ, δ, ϵ, z]], {q, -20, 2}, {z, 1 / 2, 2}, ColorFunction -> Function[{q, z, HD}, Hue[HD]], PlotRange -> All]Plot the family of HeunD functions for different accessory parameter
:
{α, γ, δ, ϵ} = {0.8 + 0.7 I, 0.9 - 0.6I, 0.2 - 0.7 I, -0.7 - 0.8I};Plot[Evaluate[Table[Abs[HeunD[q, α, γ, δ, ϵ, z]], {q, -10, 4, 1}]], {z, 1 / 10, 19 / 10}, PlotStyle -> Table[{Hue[i / 20], Thickness[0.002]}, {i, 20}], PlotRange -> {0, 3}, Frame -> True, Axes -> False]Differentiation (2)
The
-derivative of HeunD is HeunDPrime:
D[HeunD[q, α, γ, δ, ϵ, z], z]Higher derivatives of HeunD are calculated using HeunDPrime:
D[HeunD[q, α, γ, δ, ϵ, z], {z, 2}]//SimplifyIntegration (3)
Indefinite integrals of HeunD are not expressed in elementary or other special functions:
Integrate[HeunD[q, α, γ, δ, ϵ, z], z]Definite numerical integral of HeunD:
NIntegrate[HeunD[12 / 10, -14 / 10, 12 / 100, 3 / 100, -2 / 10, z], {z, 1 / 3, 1}]More integrals with HeunD:
NIntegrate[z ^ 2 HeunD[12 / 10, -14 / 10, 12 / 100, 3 / 100, -2 / 10, z], {z, 1 / 3, 1}]NIntegrate[Sin[Sqrt[z]] ^ 2 HeunD[12 / 10, -14 / 10, 12 / 100, 3 / 100, -2 / 10, z], {z, 1 / 3, 1}]Series Expansions (4)
Taylor expansion for HeunD at regular point
:
Series[HeunD[q, α, γ, δ, ϵ, z], {z, 1, 2}]Coefficient of the second term in the series expansion of HeunD at
:
SeriesCoefficient[HeunD[q, α, γ, δ, ϵ, z], {z, 1, 2}]Plot the first three approximations for HeunD around
:
{q, α, γ, δ, ϵ} = {2, 9 / 10, 1 / 10, 1 / 10, 3 / 2};terms = Normal@Table[Series[HeunD[q, α, γ, δ, ϵ, z], {z, 1, m}], {m, 1, 3}];Plot[{HeunD[q, α, γ, δ, ϵ, z], terms}, {z, 1 / 3, 3}, PlotLegends -> {"HeunD[q, α, γ, δ, ϵ, z]", "1st approximation", "2nd approximation", "3rd approximation"}]Series expansion for HeunD at any ordinary complex point:
Series[HeunD[q, α, γ, δ, ϵ, z], {z, 1 / 2, 1}]//FullSimplifyApplications (3)
Solve the double-confluent Heun differential equation using DSolve:
sol = DSolve[ y''[z] + ((γ/z^2) + (δ/z) + ϵ)y'[z] + (α z - q/z^2)y[z] == 0, y[z], z]{q, α, γ, δ, ϵ} = {4, -2, -7 / 10, -1 / 5, 1 / 3 };Plot[Abs[y[z]] /. sol /. {{C[1] -> 1, C[2] -> 0}, {C[1] -> 0, C[2] -> 10}, {C[1] -> 1 / 3, C[2] -> 1}}//Evaluate, {z, 1 / 10, 19 / 10}, PlotRange -> {0, 3}]Solve the initial value problem for the double-confluent Heun differential equation:
sol = DSolveValue[ {y''[z] + ((γ/z^2) + (δ/z) + ϵ)y'[z] + (α z - q/z^2)y[z] == 0, y[1] == 1, y'[1] == 0}, y[z], z]Plot the solution for different values of the accessory parameter q:
{α, γ, δ, ϵ} = {-3 / 5, -17 / 10, 5, -1 / 3 };Plot[sol /. q -> {-2, -1, 0, 1, 2}//Evaluate, {z, 1 / 10, 2}, PlotRange -> {{1 / 10, 2}, {-1, 8}}]Directly solve the double-confluent Heun differential equation:
y[z_] := HeunD[q, α, γ, δ, ϵ, z]Simplify[y''[z] + ((γ/z^2) + (δ/z) + ϵ)y'[z] + (α z - q/z^2)y[z] == 0]Properties & Relations (3)
HeunD is analytic at the point
:
Series[HeunD[q, α, γ, δ, ϵ, z], {z, 1, 2}]Origin is a singular point of the HeunD function:
HeunD[q, α, γ, δ, ϵ, 0]Except for this singular point, HeunD can be calculated at any finite complex
:
HeunD[4 + I, -1 / 2, 1 / 4, -7 / 5, 2, z] /. z -> RandomComplex[{-5 - I, 5 + I}, 5]The derivative of HeunD is HeunDPrime:
D[HeunD[q, α, γ, δ, ϵ, z], z]Possible Issues (1)
HeunD diverges for big arguments:
HeunD[4.3 + I, 1.3, 1, 0.12, 4.32, 1000]Related Guides
History
Text
Wolfram Research (2020), HeunD, Wolfram Language function, https://reference.wolfram.com/language/ref/HeunD.html.
CMS
Wolfram Language. 2020. "HeunD." Wolfram Language & System Documentation Center. Wolfram Research. https://reference.wolfram.com/language/ref/HeunD.html.
APA
Wolfram Language. (2020). HeunD. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/HeunD.html
BibTeX
@misc{reference.wolfram_2026_heund, author="Wolfram Research", title="{HeunD}", year="2020", howpublished="\url{https://reference.wolfram.com/language/ref/HeunD.html}", note=[Accessed: 12-June-2026]}
BibLaTeX
@online{reference.wolfram_2026_heund, organization={Wolfram Research}, title={HeunD}, year={2020}, url={https://reference.wolfram.com/language/ref/HeunD.html}, note=[Accessed: 12-June-2026]}