/// <summary>
/// Computes the regular Coulomb wave function.
/// </summary>
/// <param name="L">The angular momentum number, which must be non-negative.</param>
/// <param name="eta">The charge parameter, which can be positive or negative.</param>
/// <param name="rho">The radial distance parameter, which must be non-negative.</param>
/// <returns>The value of F<sub>L</sub>(η,ρ).</returns>
/// <remarks>
/// <para>For information on the Coulomb wave functions, see the remarks on <see cref="Coulomb" />.</para>
/// </remarks>
/// <exception cref="ArgumentOutOfRangeException"><paramref name="L"/> or <paramref name="rho"/> is negative.</exception>
/// <seealso cref="Coulomb"/>
/// <seealso cref="CoulombG"/>
/// <seealso href="http://en.wikipedia.org/wiki/Coulomb_wave_function" />
/// <seealso href="http://mathworld.wolfram.com/CoulombWaveFunction.html" />
public static double CoulombF(int L, double eta, double rho)
{
if (L < 0)
{
throw new ArgumentOutOfRangeException(nameof(L));
}
if (rho < 0)
{
throw new ArgumentOutOfRangeException(nameof(rho));
}
double rho0 = Coulomb_Series_Limit(L, eta);
if (rho <= rho0)
{
//if ((rho < 4.0 + 2.0 * Math.Sqrt(L)) && (Math.Abs(rho * eta) < 8.0 + 4.0 * L)) {
// If rho and rho * eta are small enough, use the series expansion at the origin.
CoulombF_Series(L, eta, rho, out double F, out double FP);
double C = CoulombFactor(L, eta);
return(C * F);
}
else if (rho >= Coulomb_Asymptotic_Limit(L, eta))
{
// If rho is large enough, use the asymptotic expansion.
SolutionPair s = Coulomb_Asymptotic(L, eta, rho);
return(s.FirstSolutionValue);
}
else if (rho >= CoulombTurningPoint(L, eta))
{
// Beyond the turning point, use the Barnett/Steed method.
SolutionPair result = Coulomb_Steed(L, eta, rho);
return(result.FirstSolutionValue);
}
else
{
// We are below the transition point but above the series limit.
// Choose the approach with the least cost.
ISolutionStrategy <double> above = new CoulombFFromSeriesAbove(L, eta, rho);
ISolutionStrategy <double> left = new CoulombFFromOutwardIntegration(L, eta, rho);
if (left.Cost < above.Cost)
{
return(left.Evaluate());
}
else
{
return(above.Evaluate());
}
}
}
/// <summary>
/// Computes both Airy functions and their derivatives.
/// </summary>
/// <param name="x">The argument.</param>
/// <returns>The values of Ai(x), Ai'(x), Bi(x), and Bi'(x).</returns>
public static SolutionPair Airy(double x)
{
if (x < -2.0)
{
// Map to Bessel functions for negative values
double z = 2.0 / 3.0 * Math.Pow(-x, 3.0 / 2.0);
SolutionPair p = Bessel(1.0 / 3.0, z);
double a = (p.FirstSolutionValue - p.SecondSolutionValue / Global.SqrtThree) / 2.0;
double b = (p.FirstSolutionValue / Global.SqrtThree + p.SecondSolutionValue) / 2.0;
double sx = Math.Sqrt(-x);
return(new SolutionPair(
sx * a, (x * (p.FirstSolutionDerivative - p.SecondSolutionDerivative / Global.SqrtThree) - a / sx) / 2.0,
-sx * b, (b / sx - x * (p.FirstSolutionDerivative / Global.SqrtThree + p.SecondSolutionDerivative)) / 2.0
));
}
else if (x < 2.0)
{
// Use series near origin
return(Airy_Series(x));
}
else
{
// Map to modified Bessel functions for positive values
double z = 2.0 / 3.0 * Math.Pow(x, 3.0 / 2.0);
SolutionPair p = ModifiedBessel(1.0 / 3.0, z);
double a = 1.0 / (Global.SqrtThree * Math.PI);
double b = 2.0 / Global.SqrtThree * p.FirstSolutionValue + p.SecondSolutionValue / Math.PI;
double sx = Math.Sqrt(x);
return(new SolutionPair(
a * sx * p.SecondSolutionValue, a * (x * p.SecondSolutionDerivative + p.SecondSolutionValue / sx / 2.0),
sx * b, x * (2.0 / Global.SqrtThree * p.FirstSolutionDerivative + p.SecondSolutionDerivative / Math.PI) + b / sx / 2.0
));
}
// NR recommends against using the Ai' and Bi' expressions obtained from simply differentiating the Ai and Bi expressions
// They give instead expressions involving Bessel functions of different orders. But their reason is to avoid the cancellations
// among terms ~1/x that get large near x ~ 0, and their method would require two Bessel evaluations.
// Since we use the power series near x ~ 0, we avoid their cancelation problem and can get away with a single Bessel evaluation.
// It might appear that we can optimize by not computing both \sqrt{x} and x^{3/2} explicitly, but instead computing \sqrt{x} and
// then (\sqrt{x})^3. But the latter method looses accuracy, presumably because \sqrt{x} compresses range and cubing then expands
// it, skipping over the double that is actuall closest to x^{3/2}. So we compute both explicitly.
}
/// <summary>
/// Computes the regular Coulomb wave function.
/// </summary>
/// <param name="L">The angular momentum number, which must be non-negative.</param>
/// <param name="eta">The charge parameter, which can be postive or negative.</param>
/// <param name="rho">The radial distance parameter, which must be non-negative.</param>
/// <returns>The value of F<sub>L</sub>(η,ρ).</returns>
/// <remarks>
/// <para>For information on the Coulomb wave functions, see the remarks on <see cref="Coulomb" />.</para>
/// </remarks>
/// <exception cref="ArgumentOutOfRangeException"><paramref name="L"/> or <paramref name="rho"/> is negative.</exception>
/// <seealso cref="Coulomb"/>
/// <seealso cref="CoulombG"/>
/// <seealso href="http://en.wikipedia.org/wiki/Coulomb_wave_function" />
/// <seealso href="http://mathworld.wolfram.com/CoulombWaveFunction.html" />
public static double CoulombF(int L, double eta, double rho)
{
if (L < 0)
{
throw new ArgumentOutOfRangeException(nameof(L));
}
if (rho < 0)
{
throw new ArgumentOutOfRangeException(nameof(rho));
}
if ((rho < 4.0 + 2.0 * Math.Sqrt(L)) && (Math.Abs(rho * eta) < 8.0 + 4.0 * L))
{
// if rho and rho * eta are small enough, use the series expansion at the origin
double F, FP;
CoulombF_Series(L, eta, rho, out F, out FP);
return(F);
}
else if (rho > 32.0 + (L * L + eta * eta) / 2.0)
{
// if rho is large enrough, use the asymptotic expansion
SolutionPair s = Coulomb_Asymptotic(L, eta, rho);
return(s.FirstSolutionValue);
//double F, G;
//Coulomb_Asymptotic(L, eta, rho, out F, out G);
//return (F);
}
else
{
// transition region
if (rho >= CoulombTurningPoint(L, eta))
{
// beyond the turning point, use Steed's method
SolutionPair result = Coulomb_Steed(L, eta, rho);
return(result.FirstSolutionValue);
}
else
{
// inside the turning point, integrate out from the series limit
return(CoulombF_Integrate(L, eta, rho));
}
}
}
/// <summary>
/// Computes the Airy function of the second kind.
/// </summary>
/// <param name="x">The argument.</param>
/// <returns>The value Bi(x).</returns>
/// <remarks>
/// <para>For information on the Airy functions, see <see cref="AdvancedMath.Airy"/>.</para>
/// <para>While the notation Bi(x) was chosen simply as a natural complement to Ai(x), it has influenced the common
/// nomenclature for this function, which is now often called the "Bairy function".</para>
/// </remarks>
/// <seealso cref="AiryAi"/>
/// <seealso href="http://en.wikipedia.org/wiki/Airy_functions" />
public static double AiryBi(double x)
{
if (x <= -14.0)
{
return(Airy_Asymptotic_Negative(-x).SecondSolutionValue);
}
else if (x < -3.0)
{
// Get from Bessel functions.
double y = 2.0 / 3.0 * Math.Pow(-x, 3.0 / 2.0);
SolutionPair s = Bessel(1.0 / 3.0, y);
return(-Math.Sqrt(-x) / 2.0 * (s.FirstSolutionValue / Global.SqrtThree + s.SecondSolutionValue));
}
else if (x < 5.0)
{
// The Bi series is better than the Ai series for positive values, because it blows up rather than cancelling down.
// It's also slightly better for negative values, because a given number of oscillations occur further out.
return(AiryBi_Series(x));
}
else if (x < 14.0)
{
// Get from modified Bessel functions.
double y = 2.0 / 3.0 * Math.Pow(x, 3.0 / 2.0);
SolutionPair s = ModifiedBessel(1.0 / 3.0, y);
return(Math.Sqrt(x) * (2.0 / Global.SqrtThree * s.FirstSolutionValue + s.SecondSolutionValue / Math.PI));
}
else if (x < 108.0)
{
SolutionPair s = Airy_Asymptotic_Positive_Scaled(x, out double xi);
return(Math.Exp(xi) * s.SecondSolutionValue);
}
else if (x <= Double.PositiveInfinity)
{
return(Double.PositiveInfinity);
}
else
{
Debug.Assert(Double.IsNaN(x));
return(x);
}
}
// use Steed's method to compute F and G for a given L
// the method uses a real continued fraction (1 constraint), an imaginary continued fraction (2 constraints)
// and the Wronskian (4 constraints) to compute the 4 quantities F, F', G, G'
// it is reliable past the truning point, but becomes slow if used far past the turning point
// Solution (a la Barnett)
// F = s \left[ (f - p)^2 / q + q \right]^{-1/2}
// F' = f F
// G = g F \qquad g = (f - p) / q
// G' = (p g - q) F
private static SolutionPair Coulomb_Steed(double L, double eta, double rho)
{
// compute CF1 (F'/F)
double f = Coulomb_CF1(L, eta, rho, out int sign);
// compute CF2 ((G' + iF')/(G + i F))
Complex z = Coulomb_CF2(L, eta, rho);
double p = z.Re;
double q = z.Im;
// use CF1, CF2, and Wronskian (FG' - GF' = 1) to solve for F, F', G, G'
double g = (f - p) / q;
double F = sign / Math.Sqrt(g * g * q + q);
double FP = f * F;
double G = g * F;
double GP = (p * g - q) * F;
SolutionPair result = new SolutionPair(F, FP, G, GP);
return(result);
}
// Neuman series no good for computing K0; it relies on a near-perfect cancelation between the I0 term
// and the higher terms to achieve an exponentially supressed small value
#endif
/// <summary>
/// Computes the Airy function of the first kind.
/// </summary>
/// <param name="x">The argument.</param>
/// <returns>The value Ai(x).</returns>
/// <remarks>
/// <para>Airy functions are solutions to the Airy differential equation:</para>
/// <img src="../images/AiryODE.png" />
/// <para>The Airy functions appear in quantum mechanics in the semiclassical WKB solution to the wave functions in a potential.</para>
/// <para>For negative arguments, Ai(x) is oscilatory. For positive arguments, it decreases exponentially with increasing x.</para>
/// </remarks>
/// <seealso cref="AiryBi"/>
/// <seealso href="http://en.wikipedia.org/wiki/Airy_functions" />
public static double AiryAi(double x)
{
if (x < -3.0)
{
double y = 2.0 / 3.0 * Math.Pow(-x, 3.0 / 2.0);
SolutionPair s = Bessel(1.0 / 3.0, y);
return(Math.Sqrt(-x) / 2.0 * (s.FirstSolutionValue - s.SecondSolutionValue / Global.SqrtThree));
}
else if (x < 2.0)
{
// Close to the origin, use a power series.
// Convergence is slightly better for negative x than for positive, so we use it further out to the left of the origin.
return(AiryAi_Series(x));
// The definitions in terms of bessel functions becomes 0 X infinity at x=0, so we can't use them directly here anyway.
}
else
{
double y = 2.0 / 3.0 * Math.Pow(x, 3.0 / 2.0);
return(Math.Sqrt(x / 3.0) / Math.PI * ModifiedBesselK(1.0 / 3.0, y));
}
}
/// <summary>
/// Computes the Airy function of the first kind.
/// </summary>
/// <param name="x">The argument.</param>
/// <returns>The value Ai(x).</returns>
/// <remarks>
/// <para>For information on the Airy functions, see <see cref="AdvancedMath.Airy"/>.</para>
/// </remarks>
/// <seealso cref="AiryBi"/>
/// <seealso href="http://en.wikipedia.org/wiki/Airy_functions" />
public static double AiryAi(double x)
{
if (x <= -14.0)
{
return(Airy_Asymptotic_Negative(-x).FirstSolutionValue);
}
else if (x < -3.0)
{
double y = 2.0 / 3.0 * Math.Pow(-x, 3.0 / 2.0);
SolutionPair s = Bessel(1.0 / 3.0, y);
return(Math.Sqrt(-x) / 2.0 * (s.FirstSolutionValue - s.SecondSolutionValue / Global.SqrtThree));
}
else if (x < 2.0)
{
// Close to the origin, use a power series.
// Convergence is slightly better for negative x than for positive, so we use it further out to the left of the origin.
return(AiryAi_Series(x));
// The definitions in terms of bessel functions become 0 X infinity at x=0, so we can't use them directly here anyway.
}
else if (x < 14.0)
{
double y = 2.0 / 3.0 * Math.Pow(x, 3.0 / 2.0);
return(Math.Sqrt(x / 3.0) / Math.PI * ModifiedBesselK(1.0 / 3.0, y));
}
else if (x < 108.0)
{
SolutionPair s = Airy_Asymptotic_Positive_Scaled(x, out double xi);
return(Math.Exp(-xi) * s.FirstSolutionValue);
}
else if (x <= Double.PositiveInfinity)
{
return(0.0);
}
else
{
Debug.Assert(Double.IsNaN(x));
return(x);
}
}
// use Steed's method to compute F and G for a given L
// the method uses a real continued fraction (1 constraint), an imaginary continued fraction (2 constraints)
// and the Wronskian (4 constraints) to compute the 4 quantities F, F', G, G'
// it is reliable past the truning point, but becomes slow if used far past the turning point
private static SolutionPair Coulomb_Steed(double L, double eta, double rho)
{
// compute CF1 (F'/F)
int sign;
double f = Coulomb_CF1(L, eta, rho, out sign);
// compute CF2 ((G' + iF')/(G + i F))
Complex z = Coulomb_CF2(L, eta, rho);
double p = z.Re;
double q = z.Im;
// use CF1, CF2, and Wronskian (FG' - GF' = 1) to solve for F, F', G, G'
double g = (f - p) / q;
SolutionPair result = new SolutionPair();
result.FirstSolutionValue = sign / Math.Sqrt(g * g * q + q);
result.FirstSolutionDerivative = f * result.FirstSolutionValue;
result.SecondSolutionValue = g * result.FirstSolutionValue;
result.SecondSolutionDerivative = (p * g - q) * result.FirstSolutionValue;
return(result);
}
/// <summary>
/// Computes the Airy function of the second kind.
/// </summary>
/// <param name="x">The argument.</param>
/// <returns>The value Bi(x).</returns>
/// <remarks>
/// <para>For information on the Airy functions, see <see cref="AdvancedMath.Airy"/>.</para>
/// <para>While the notation Bi(x) was chosen simply as a natural complement to Ai(x), it has influenced the common
/// nomenclature for this function, which is now often called the "Bairy function".</para>
/// </remarks>
/// <seealso cref="AiryAi"/>
/// <seealso href="http://en.wikipedia.org/wiki/Airy_functions" />
public static double AiryBi(double x)
{
if (x < -3.0)
{
// Get from Bessel functions.
double y = 2.0 / 3.0 * Math.Pow(-x, 3.0 / 2.0);
SolutionPair s = Bessel(1.0 / 3.0, y);
return(-Math.Sqrt(-x) / 2.0 * (s.FirstSolutionValue / Global.SqrtThree + s.SecondSolutionValue));
}
else if (x < 5.0)
{
// The Bi series is better than the Ai series for positive values, because it blows up rather than cancelling down.
// It's also slightly better for negative values, because a given number of oscillations occur further out.
return(AiryBi_Series(x));
}
else
{
// Get from modified Bessel functions.
double y = 2.0 / 3.0 * Math.Pow(x, 3.0 / 2.0);
SolutionPair s = ModifiedBessel(1.0 / 3.0, y);
return(Math.Sqrt(x) * (2.0 / Global.SqrtThree * s.FirstSolutionValue + s.SecondSolutionValue / Math.PI));
}
}
/// <summary>
/// Computes the Airy function of the second kind.
/// </summary>
/// <param name="x">The argument.</param>
/// <returns>The value Bi(x).</returns>
/// <remarks>
/// <para>For information on the Airy functions, see <see cref="AdvancedMath.Airy"/>.</para>
/// <para>While the notation Bi(x) was chosen simply as a natural complement to Ai(x), it has influenced the common
/// nomenclature for this function, which is now often called the "Bairy function".</para>
/// </remarks>
/// <seealso cref="AiryAi"/>
/// <seealso href="http://en.wikipedia.org/wiki/Airy_functions" />
public static double AiryBi(double x)
{
if (x < -3.0)
{
// change to use a function that returns J and Y together
double y = 2.0 / 3.0 * Math.Pow(-x, 3.0 / 2.0);
double J = BesselJ(1.0 / 3.0, y);
double Y = BesselY(1.0 / 3.0, y);
return(-Math.Sqrt(-x) / 2.0 * (J / Global.SqrtThree + Y));
}
else if (x < 5.0)
{
// The Bi series is better than the Ai series for positive values, because it blows up rather than down.
// It's also slightly better for negative values, because a given number of oscilations occur further out.
return(AiryBi_Series(x));
}
else
{
double y = 2.0 / 3.0 * Math.Pow(x, 3.0 / 2.0);
SolutionPair s = ModifiedBessel(1.0 / 3.0, y);
return(Math.Sqrt(x) * (2.0 / Global.SqrtThree * s.FirstSolutionValue + s.SecondSolutionValue / Math.PI));
}
}
// use Steed's method to compute F and G for a given L
// the method uses a real continued fraction (1 constraint), an imaginary continued fraction (2 constraints)
// and the Wronskian (4 constraints) to compute the 4 quantities F, F', G, G'
// it is reliable past the truning point, but becomes slow if used far past the turning point
private static SolutionPair Coulomb_Steed(double L, double eta, double rho)
{
// compute CF1 (F'/F)
int sign;
double f = Coulomb_CF1(L, eta, rho, out sign);
// compute CF2 ((G' + iF')/(G + i F))
Complex z = Coulomb_CF2(L, eta, rho);
double p = z.Re;
double q = z.Im;
// use CF1, CF2, and Wronskian (FG' - GF' = 1) to solve for F, F', G, G'
double g = (f - p) / q;
SolutionPair result = new SolutionPair();
result.FirstSolutionValue = sign / Math.Sqrt(g * g * q + q);
result.FirstSolutionDerivative = f * result.FirstSolutionValue;
result.SecondSolutionValue = g * result.FirstSolutionValue;
result.SecondSolutionDerivative = (p * g - q) * result.FirstSolutionValue;
return (result);
}
/// <summary>
/// Computes the irregular Coulomb wave function.
/// </summary>
/// <param name="L">The angular momentum number, which must be non-negative.</param>
/// <param name="eta">The charge parameter, which can be postive or negative.</param>
/// <param name="rho">The radial distance parameter, which must be non-negative.</param>
/// <returns>The value of G<sub>L</sub>(η,ρ).</returns>
/// <remarks>
/// <para>For information on the Coulomb wave functions, see the remarks on <see cref="Coulomb" />.</para>
/// </remarks>
/// <exception cref="ArgumentOutOfRangeException"><paramref name="L"/> or <paramref name="rho"/> is negative.</exception>
/// <seealso cref="Coulomb"/>
/// <seealso cref="CoulombF"/>
/// <seealso href="http://en.wikipedia.org/wiki/Coulomb_wave_function" />
/// <seealso href="http://mathworld.wolfram.com/CoulombWaveFunction.html" />
public static double CoulombG(int L, double eta, double rho)
{
if (L < 0)
{
throw new ArgumentOutOfRangeException(nameof(L));
}
if (rho < 0)
{
throw new ArgumentOutOfRangeException(nameof(rho));
}
if ((rho < 4.0) && Math.Abs(rho * eta) < 8.0)
{
// For small enough rho, use the power series for L=0, then recurse upward to desired L.
double F, FP, G, GP;
Coulomb_Zero_Series(eta, rho, out F, out FP, out G, out GP);
Coulomb_Recurse_Upward(0, L, eta, rho, ref G, ref GP);
return(G);
}
else if (rho > 32.0 + (L * L + eta * eta) / 2.0)
{
// For large enough rho, use the asymptotic series.
SolutionPair s = Coulomb_Asymptotic(L, eta, rho);
return(s.SecondSolutionValue);
}
else
{
// Transition region
if (rho >= CoulombTurningPoint(L, eta))
{
// Beyond the turning point, use Steed's method.
SolutionPair result = Coulomb_Steed(L, eta, rho);
return(result.SecondSolutionValue);
}
else
{
// we will start at L=0 (which has a smaller turning point radius) and recurse up to the desired L
// this is okay because G increasees with increasing L
double G, GP;
double rho0 = 2.0 * eta;
if (rho < rho0)
{
// if inside the turning point even for L=0, start at the turning point and integrate in
// this is okay becaue G increases with decraseing rho
// use Steed's method at the turning point
// for large enough eta, we could use the turning point expansion at L=0, but it contributes
// a lot of code for little overall performance increase so we have chosen not to
SolutionPair result = Coulomb_Steed(0, eta, 2.0 * eta);
G = result.SecondSolutionValue;
GP = result.SecondSolutionDerivative;
OdeResult r = FunctionMath.IntegrateConservativeOde(
(double x, double y) => (2.0 * eta / x - 1.0) * y,
rho0, G, GP, rho,
new OdeEvaluationSettings()
{
RelativePrecision = 2.5E-13,
AbsolutePrecision = 0.0,
EvaluationBudget = 8192 * 2
}
);
G = r.Y;
GP = r.YPrime;
/*
* BulrischStoerStoermerStepper s = new BulrischStoerStoermerStepper();
* s.RightHandSide = delegate(double x, double U) {
* return ((2.0 * eta / x - 1.0) * U);
* };
* s.X = 2.0 * eta;
* s.Y = G;
* s.YPrime = GP;
* s.DeltaX = 0.25;
* s.Accuracy = 2.5E-13;
* s.Integrate(rho);
*
* G = s.Y;
* GP = s.YPrime;
*/
}
else
{
// if beyond the turning point for L=0, just use Steeds method
SolutionPair result = Coulomb_Steed(0, eta, rho);
G = result.SecondSolutionValue;
GP = result.SecondSolutionDerivative;
}
// Recurse up to the desired L.
Coulomb_Recurse_Upward(0, L, eta, rho, ref G, ref GP);
return(G);
}
}
}
// **** Integer order Bessel functions ****
/// <summary>
/// Computes the regular Bessel function for integer orders.
/// </summary>
/// <param name="n">The order parameter.</param>
/// <param name="x">The argument.</param>
/// <returns>The value of J<sub>n</sub>(x).</returns>
/// <remarks>
/// <para>For information on the cylindrical Bessel functions, see <see cref="AdvancedMath.Bessel"/>.</para>
/// </remarks>
/// <seealso href="http://en.wikipedia.org/wiki/Bessel_function"/>
/// <seealso href="https://mathworld.wolfram.com/BesselFunctionoftheFirstKind.html"/>
public static double BesselJ(int n, double x)
{
// Relate negative n to positive n.
if (n < 0)
{
if ((n % 2) == 0)
{
return(BesselJ(-n, x));
}
else
{
return(-BesselJ(-n, x));
}
}
// Relate negative x to positive x.
if (x < 0)
{
if ((n % 2) == 0)
{
return(BesselJ(n, -x));
}
else
{
return(-BesselJ(n, -x));
}
}
if (x <= Math.Sqrt(2 * (n + 1)))
{
// If x is small enough, use the series.
// The transition point is chosen so that 2nd term cannot overwhelm 1st.
return(BesselJ_Series(n, x));
}
else if (x >= 32.0 + 0.5 * n * n)
{
// If x is large enough, use the asymptotic expansion.
return(Bessel_Asymptotic(n, x).FirstSolutionValue);
}
else if ((x > n) && (n > 32))
{
// We are in the transition region \sqrt{n} < x < n^2. If x > n we are still allowed to recurr upward,
// and as long as we can find an n below us for which x lies in the asymptotic region, we have a value
// to recur upward from. In general we expect this to be better than Miller's algorithm, because
// it will require fewer recurrance steps.
int m = (int)Math.Floor(Math.Sqrt(2.0 * (x - 32.0)));
Debug.Assert(m <= n);
SolutionPair s = Bessel_Asymptotic(m, x);
double J = s.FirstSolutionValue;
double JP = s.FirstSolutionDerivative;
Bessel_RecurrUpward(m, x, ref J, ref JP, n - m);
return(J);
}
else
{
// We are in the transition region; x is too large for the series but still less than n. In this region
// upward recurrance is unstable, since even a tiny mixture of the Y solution will come to dominate as n increases.
// Instead we will use Miller's algorithm: recurr downward from far above and use a sum rule to normalize the result
// The sum rule we will use is:
// \sum_{k=-\infty}^{\infty} J_{2k}(x) = J_0(x) + 2 J_2(x) + 2 J_4(x) + \cdots = 1
return(Bessel_Miller(n, -1, x).FirstSolutionValue);
//return (BesselJ_Miller(n, x));
}
}
/// <summary>
/// Computes the regular and irregular Coulomb wave functions and their derivatives.
/// </summary>
/// <param name="L">The angular momentum number, which must be non-negative.</param>
/// <param name="eta">The charge parameter, which can be postive or negative.</param>
/// <param name="rho">The radial distance parameter, which must be non-negative.</param>
/// <returns>The values of F, F', G, and G' for the given parameters.</returns>
/// <remarks>
/// <para>The Coulomb wave functions are the radial wave functions of a non-relativistic particle in a Coulomb
/// potential.</para>
/// <para>They satisfy the differential equation:</para>
/// <img src="../images/CoulombODE.png" />
/// <para>A repulsive potential is represented by η > 0, an attractive potential by η < 0.</para>
/// <para>F is oscilatory in the region beyond the classical turning point. In the quantum tunneling region inside
/// the classical turning point, F is exponentially supressed and vanishes at the origin, while G grows exponentially and
/// diverges at the origin.</para>
/// <para>Many numerical libraries compute Coulomb wave functions in the quantum tunneling region using a WKB approximation,
/// which accurately determine only the first handfull of digits; our library computes Coulomb wave functions even in this
/// computationaly difficult region to nearly full precision -- all but the last 3-4 digits can be trusted.</para>
/// <para>The irregular Coulomb wave functions G<sub>L</sub>(η,ρ) are the complementary independent solutions
/// of the same differential equation.</para>
/// </remarks>
/// <exception cref="ArgumentOutOfRangeException"><paramref name="L"/> or <paramref name="rho"/> is negative.</exception>
/// <seealso cref="CoulombF"/>
/// <seealso cref="CoulombG"/>
/// <seealso href="http://en.wikipedia.org/wiki/Coulomb_wave_function" />
/// <seealso href="http://mathworld.wolfram.com/CoulombWaveFunction.html" />
public static SolutionPair Coulomb(int L, double eta, double rho)
{
if (L < 0)
{
throw new ArgumentOutOfRangeException(nameof(L));
}
if (rho < 0)
{
throw new ArgumentOutOfRangeException(nameof(rho));
}
if (rho == 0.0)
{
if (L == 0)
{
double C = CoulombFactor(L, eta);
return(new SolutionPair(0.0, C, 1.0 / C, Double.NegativeInfinity));
}
else
{
return(new SolutionPair(0.0, 0.0, Double.PositiveInfinity, Double.NegativeInfinity));
}
}
else if ((rho < 4.0) && Math.Abs(rho * eta) < 8.0)
{
// Below the safe series radius for L=0, compute using the series
double F, FP, G, GP;
Coulomb_Zero_Series(eta, rho, out F, out FP, out G, out GP);
// For higher L, recurse G upward, but compute F via the direct series.
// G is safe to compute via recursion and F is not because G is increasing
// rapidly and F is decreasing rapidly with increasing L.
if (L > 0)
{
CoulombF_Series(L, eta, rho, out F, out FP);
Coulomb_Recurse_Upward(0, L, eta, rho, ref G, ref GP);
}
return(new SolutionPair(F, FP, G, GP));
}
else if (rho > 32.0 + (L * L + eta * eta) / 2.0)
{
return(Coulomb_Asymptotic(L, eta, rho));
}
else
{
double rho0 = CoulombTurningPoint(L, eta);
if (rho > rho0)
{
return(Coulomb_Steed(L, eta, rho));
}
else
{
// First F
double F, FP;
double rho1 = Math.Min(
4.0 + 2.0 * Math.Sqrt(L),
(8.0 + 4.0 * L) / Math.Abs(eta)
);
if (rho < rho1)
{
CoulombF_Series(L, eta, rho, out F, out FP);
}
else
{
CoulombF_Series(L, eta, rho1, out F, out FP);
OdeResult r = FunctionMath.IntegrateConservativeOde(
(double x, double y) => ((L * (L + 1) / x + 2.0 * eta) / x - 1.0) * y,
rho1, F, FP, rho,
new OdeEvaluationSettings()
{
RelativePrecision = 2.5E-13,
AbsolutePrecision = 0.0,
EvaluationBudget = 8192 * 2
}
);
F = r.Y;
FP = r.YPrime;
}
// Then G
double G, GP;
// For L = 0 the transition region is smaller, so we will determine G
// at L = 0, where non-integration methods apply over a larger region,
// and then recurse upward.
double rho2 = CoulombTurningPoint(0, eta);
if (rho > 32.0 + eta * eta / 2.0)
{
SolutionPair s = Coulomb_Asymptotic(0, eta, rho);
G = s.SecondSolutionValue;
GP = s.SecondSolutionDerivative;
}
else if (rho > rho2)
{
SolutionPair s = Coulomb_Steed(0, eta, rho);
G = s.SecondSolutionValue;
GP = s.SecondSolutionDerivative;
}
else
{
SolutionPair s = Coulomb_Steed(0, eta, rho2);
G = s.SecondSolutionValue;
GP = s.SecondSolutionDerivative;
// Integrate inward from turning point.
// G increases and F decreases in this direction, so this is stable.
OdeResult r = FunctionMath.IntegrateConservativeOde(
(double x, double y) => (2.0 * eta / x - 1.0) * y,
rho2, G, GP, rho,
new OdeEvaluationSettings()
{
RelativePrecision = 2.5E-13,
AbsolutePrecision = 0.0,
EvaluationBudget = 8192 * 2
}
);
G = r.Y;
GP = r.YPrime;
}
Coulomb_Recurse_Upward(0, L, eta, rho, ref G, ref GP);
return(new SolutionPair(F, FP, G, GP));
}
}
}
/// <summary>
/// Computes the regular Bessel function for real orders.
/// </summary>
/// <param name="nu">The order parameter.</param>
/// <param name="x">The argument, which must be non-negative.</param>
/// <returns>The value of J<sub>ν</sub>(x).</returns>
/// <remarks>
/// <para>For information on the cylindrical Bessel functions, see <see cref="AdvancedMath.Bessel"/>.</para>
/// </remarks>
/// <exception cref="ArgumentOutOfRangeException"><paramref name="x"/> is negative.</exception>
/// <seealso href="http://en.wikipedia.org/wiki/Bessel_function"/>
/// <seealso href="https://mathworld.wolfram.com/BesselFunctionoftheFirstKind.html"/>
public static double BesselJ(double nu, double x)
{
if (x < 0.0)
{
throw new ArgumentOutOfRangeException(nameof(x));
}
// Use reflection to turn negative orders into positive orders.
if (nu < 0.0)
{
double mu = -nu;
return(MoreMath.CosPi(mu) * BesselJ(mu, x) - MoreMath.SinPi(mu) * BesselY(mu, x));
}
if (x <= Math.Sqrt(2.0 * (nu + 1.0)))
{
// We are close enough to origin to use the series.
return(BesselJ_Series(nu, x));
}
else if (x >= 32.0 + 0.5 * nu * nu)
{
// We are far enough from origin to use the asymptotic expansion.
SolutionPair result = Bessel_Asymptotic(nu, x);
return(result.FirstSolutionValue);
}
else if (x >= nu)
{
// We are far enough from origin to evaluate CF2, so use Steed's method.
SolutionPair result = Bessel_Steed(nu, x);
return(result.FirstSolutionValue);
}
else
{
// We have x < nu, but x is still not small enough to use the series; this only occurs for nu >~ 6.
// To handle this case, compute J_{nu+1}/J_{nu}, recurse down to mu where mu ~ x < nu; use
// Steed's method to evaluate J_{mu} and re-normalize J_{nu}.
// for example, for mu = 16, x = 12, we can't evaluate CF2 because x < 16; so assume J_16=1, compute J_17 / J_16,
// and recurse down to J_11; since 12 > 11, we can compute CF2 and get J_11 and Y_11; comparing this
// with our value of J_11 gives the proper renormalization factor for J_16
int sign;
double r = nu / x - Bessel_CF1(nu, x, out sign);
double J = sign * Bessel_Tower_Start;
//double J = 1.0 * sign;
double JP = r * J;
double mu = nu;
while (mu > x)
{
double t = J;
J = mu / x * J + JP;
mu -= 1.0;
JP = mu / x * J - t;
// Not sure if this is really okay in all cases.
if (Double.IsInfinity(J))
{
return(0.0);
}
}
Complex z = Bessel_CF2(mu, x);
SolutionPair result = Bessel_Steed(JP / J, z, 2.0 / Math.PI / x, Math.Sign(J));
//SolutionPair result = Bessel_Steed(mu / x - Jp1 / J, z, 2.0 / Math.PI / x, Math.Sign(J));
return(result.FirstSolutionValue / J * Bessel_Tower_Start);
}
}
/// <summary>
/// Computes the irregual Bessel function for real orders.
/// </summary>
/// <param name="nu">The order parameter.</param>
/// <param name="x">The argument, which must be non-negative.</param>
/// <returns>The value of Y<sub>ν</sub>(x).</returns>
/// <remarks>
/// <para>For information on the cylindrical Bessel functions, see <see cref="AdvancedMath.Bessel"/>.</para>
/// </remarks>
/// <exception cref="ArgumentOutOfRangeException"><paramref name="x"/> is negative.</exception>
/// <seealso cref="Bessel"/>
/// <seealso href="http://en.wikipedia.org/wiki/Bessel_function"/>
/// <seealso href="https://mathworld.wolfram.com/BesselFunctionoftheSecondKind.html"/>
public static double BesselY(double nu, double x)
{
if (x < 0.0)
{
throw new ArgumentOutOfRangeException(nameof(x));
}
if (nu < 0.0)
{
return(MoreMath.CosPi(nu) * BesselY(-nu, x) - MoreMath.SinPi(nu) * BesselJ(-nu, x));
}
if (x == 0.0)
{
return(Double.NegativeInfinity);
}
else if (x >= 32.0 + nu * nu / 2.0)
{
// far from the origin, use the asymptotic expansion
SolutionPair result = Bessel_Asymptotic(nu, x);
return(result.SecondSolutionValue);
}
else if (x < 4.0)
{
// close to the origin, use the Temme series
double Y0, Y1;
if (nu <= 0.5)
{
BesselY_Series(nu, x, out Y0, out Y1);
return(Y0);
}
else if (nu <= 1.5)
{
BesselY_Series(nu - 1.0, x, out Y0, out Y1);
return(Y1);
}
else
{
// compute for mu -0.5 <= mu <= 0.5
double mu = nu - Math.Round(nu);
BesselY_Series(mu, x, out Y0, out Y1);
// recurr upward to nu
int n = ((int)Math.Round(nu - mu)) - 1;
for (int i = 0; i < n; i++)
{
// use recurrence on Y, Y':
// Y_{mu+1} = (2 mu/x) Y_{mu} - Y_{mu}
mu += 1.0;
double t = Y0;
Y0 = Y1;
Y1 = (2.0 * mu / x) * Y1 - t;
if (Double.IsNegativeInfinity(Y1))
{
break;
}
}
return(Y1);
}
}
else if (x > nu)
{
SolutionPair result = Bessel_Steed(nu, x);
return(result.SecondSolutionValue);
}
else
{
// we have 4 < x < nu; evaluate at mu~x and recurr upward to nu
// figure out mu
int n = (int)Math.Ceiling(nu - x);
double mu = nu - n;
// evaluate at mu
SolutionPair result = Bessel_Steed(mu, x);
double Y = result.SecondSolutionValue;
double YP = result.SecondSolutionDerivative;
// recurr upward to nu
Bessel_RecurrUpward(mu, x, ref Y, ref YP, n);
return(Y);
}
}
/// <summary>
/// Computes both solutions of the Bessel differential equation.
/// </summary>
/// <param name="nu">The order, which must be non-negative.</param>
/// <param name="x">The argument, which must be non-negative.</param>
/// <returns>The values of J<sub>nu</sub>(x), J'<sub>nu</sub>(x), Y<sub>nu</sub>(x), and Y'<sub>nu</sub>(x).</returns>
/// <remarks>
/// <para>Bessel functions often occur in the analysis of physical phenomena with cylindrical symmetry.
/// They satisfy the differential equation:</para>
/// <img src="../images/BesselODE.png" />
/// <para>Since this is a second order linear equation, it has two linearly independent solutions. The regular Bessel function
/// J<sub>ν</sub>(x), which is finite at the origin, and the irregular Bessel function Y<sub>ν</sub>(x), which diverges
/// at the origin. Far from the origin, both functions are oscilatory.</para>
/// <para>This method simultaneously computes both Bessel functions and their derivatives. If you need both J and Y, it is faster to call this method once than to call
/// <see cref="BesselJ(double,double)"/> and <see cref="BesselY(double,double)"/> seperately. If on, the other hand, you need only J or only Y, it is faster to
/// call the appropriate method to compute the one you need.</para>
/// </remarks>
/// <exception cref="ArgumentOutOfRangeException"><paramref name="nu"/> or <paramref name="x"/> is negative.</exception>
/// <seealso href="http://en.wikipedia.org/wiki/Bessel_function"/>
public static SolutionPair Bessel(double nu, double x)
{
if (nu < 0.0)
{
throw new ArgumentOutOfRangeException(nameof(nu));
}
if (x < 0.0)
{
throw new ArgumentOutOfRangeException(nameof(x));
}
if (x == 0.0)
{
return(Bessel_Zero(nu, +1));
}
else if (x < 4.0)
{
// Close to the origin, use the series for Y and J.
// The range does not grow with increasing order because our series for Y is only for small orders.
// for J, we can use the series directly
double J, JP;
BesselJ_Series(nu, x, out J, out JP);
// for Y, we only have a series for -0.5 < mu < 0.5, so pick an order in that range offset from our
// desired order by an integer number of recurrence steps. Evaluate at the mu order and recurr upward to nu.
double mu = nu - Math.Round(nu);
int n = (int)Math.Round(nu - mu);
double Y, YP1;
BesselY_Series(mu, x, out Y, out YP1);
double YP = (mu / x) * Y - YP1;
Bessel_RecurrUpward(mu, x, ref Y, ref YP, n);
// return J, J', Y, Y' in a solution pair
return(new SolutionPair(J, JP, Y, YP));
}
else if (x > 32.0 + nu * nu / 2.0)
{
// Far enough out, use the asymptotic series.
return(Bessel_Asymptotic(nu, x));
}
else if (x > nu)
{
// In the intermediate region, use Steed's method directly if x > nu.
return(Bessel_Steed(nu, x));
}
else
{
// If x < nu, we can't use Steed's method directly because CF2 does not converge.
// So pick a mu ~ x < nu, offset from nu by an integer; use Steed's method there,
// then recurr up to nu.
// this only occurs for 4 < x < nu, e.g. nu, x = 16, 8
int n = (int)Math.Ceiling(nu - x);
double mu = nu - n;
SolutionPair result = Bessel_Steed(mu, x);
double Y = result.SecondSolutionValue;
double YP = result.SecondSolutionDerivative;
Bessel_RecurrUpward(mu, x, ref Y, ref YP, n);
// being in a region with x < nu, we can evaluate CF1 to get J'/J
// this ratio, together with Y and Y' and the Wronskian, gives us J' and J seperately
int sign;
double r = nu / x - Bessel_CF1(nu, x, out sign);
double J = (2.0 / Math.PI / x) / (YP - r * Y);
double JP = r * J;
// return the result
return(new SolutionPair(J, JP, Y, YP));
}
}
// Hankel's asymptotic expansions for Bessel function (A&S 9.2)
// J = \sqrt{\frac{2}{\pi x}} \left[ P \cos\omega - Q \sin\omega \right]
// Y = \sqrt{\frac{2}{\pi x}} \left[ P \sin\omega + Q \cos\omega \right]
// where \omega = x - \left( \nu / 2 + 1 / 4 \right) \pi and \mu = 4 \nu^2 and
// P = 1 - \frac{(\mu-1)(\mu-9)}{2! (8x)^2} + \frac{(\mu-1)(\mu-9)(\mu-25)(\mu-49}{4! (8x)^4} + \cdots
// Q = \frac{(\mu-1)}{8x} - \frac{(\mu-1)(\mu-9)(\mu-25)}{3! (8x)^3} + \cdots
// Derivatives have similiar expressions
// J' = - \sqrt{\frac{2}{\pi x}} \left[ R \sin\omega + S \cos\omega \right]
// Y' = \sqrt{\frac{2}{\pi x}} \left[ R \cos\omega - S \sin\omega \right]
// where
// R = 1 - \frac{(\mu-1)(\mu+15)}{2! (8x)^2} + \cdots
// S = \frac{(\mu+3)}{8x} - \frac{(\mu-1)(\mu - 9)(\mu+35)}{3! (8x)^3} + \cdots
// For nu=0, this series converges to full precision in about 10 terms at x~100, and in about 25 terms even as low as x~25.
// It fails to converge to full precision for x <~ 25.
// Since the first correction term is ~ (4 \nu^2)^2 / (8 x)^2 ~ (\nu^2 / 2 x)^2, the minimum x should grow like \nu^2 / 2
private static SolutionPair Bessel_Asymptotic(double nu, double x)
{
Debug.Assert(nu >= 0.0);
Debug.Assert(x > 0.0);
// pre-compute factors of nu and x as they appear in the series
double mu = 4.0 * nu * nu;
double xx = 8.0 * x;
// initialize P and Q
double P = 1.0; double R = 1.0;
double Q = 0.0; double S = 0.0;
// k is the current term number, k2 is (2k - 1), and t is the value of the current term
int k = 0;
int k2 = -1;
double t = 1.0;
while (true)
{
double Q_old = Q; double P_old = P;
double R_old = R; double S_old = S;
k++; k2 += 2;
t /= k * xx;
S += (mu + k2 * (k2 + 2)) * t;
t *= (mu - k2 * k2);
Q += t;
k++; k2 += 2;
t /= -k * xx;
R += (mu + k2 * (k2 + 2)) * t;
t *= (mu - k2 * k2);
P += t;
if ((P == P_old) && (Q == Q_old) && (R == R_old) && (S == S_old))
{
break;
}
if (k > Global.SeriesMax)
{
throw new NonconvergenceException();
}
}
// The computation of \sin\omega and \cos\omega is fairly delicate. Since x is large,
// it's important to use MoreMath.Sin and MoreMath.Cos to ensure correctness for
// large arguments. Furthermore, since the shift by 1/2 ( \nu + 1/2) \pi is a
// multiple of \pi and could be dwarfed by or have significant cancellation with x,
// it's better to use the trig addition formulas to handle it seperately using
// SinPi and CosPi functions.
// This works well, but it took a long time to get to this.
double a = 0.5 * (nu + 0.5);
double sa = MoreMath.SinPi(a);
double ca = MoreMath.CosPi(a);
double sx = MoreMath.Sin(x);
double cx = MoreMath.Cos(x);
// It would be great to have a SinAndCos function so as not to do the range reduction twice.
double s1 = sx * ca - cx * sa;
double c1 = cx * ca + sx * sa;
// Assemble the solution
double N = Math.Sqrt(2.0 / Math.PI / x);
SolutionPair result = new SolutionPair(
N * (c1 * P - s1 * Q), -N * (R * s1 + S * c1),
N * (s1 * P + c1 * Q), N * (R * c1 - S * s1)
);
return(result);
}
/// <summary>
/// Computes the regular and irregular Coulomb wave functions and their derivatives.
/// </summary>
/// <param name="L">The angular momentum number, which must be non-negative.</param>
/// <param name="eta">The charge parameter, which can be positive or negative.</param>
/// <param name="rho">The radial distance parameter, which must be non-negative.</param>
/// <returns>The values of F, F', G, and G' for the given parameters.</returns>
/// <remarks>
/// <para>The Coulomb wave functions are the radial wave functions of a non-relativistic particle in a Coulomb
/// potential.</para>
/// <para>They satisfy the differential equation:</para>
/// <img src="../images/CoulombODE.png" />
/// <para>A repulsive potential is represented by η > 0, an attractive potential by η < 0.</para>
/// <para>F is oscillatory in the region beyond the classical turning point. In the quantum tunneling region inside
/// the classical turning point, F is exponentially suppressed and vanishes at the origin, while G grows exponentially and
/// diverges at the origin.</para>
/// <para>Many numerical libraries compute Coulomb wave functions in the quantum tunneling region using a WKB approximation,
/// which accurately determine only the first few decimal digits; our library computes Coulomb wave functions even in this
/// computationally difficult region to nearly full precision -- all but the last 4-5 decimal digits can be trusted.</para>
/// <para>The irregular Coulomb wave functions G<sub>L</sub>(η,ρ) are the complementary independent solutions
/// of the same differential equation.</para>
/// </remarks>
/// <exception cref="ArgumentOutOfRangeException"><paramref name="L"/> or <paramref name="rho"/> is negative.</exception>
/// <seealso cref="CoulombF"/>
/// <seealso cref="CoulombG"/>
/// <seealso href="http://en.wikipedia.org/wiki/Coulomb_wave_function" />
/// <seealso href="http://mathworld.wolfram.com/CoulombWaveFunction.html" />
public static SolutionPair Coulomb(int L, double eta, double rho)
{
if (L < 0)
{
throw new ArgumentOutOfRangeException(nameof(L));
}
if (rho < 0)
{
throw new ArgumentOutOfRangeException(nameof(rho));
}
if (rho == 0.0)
{
if (L == 0)
{
double C = CoulombFactor(L, eta);
return(new SolutionPair(0.0, C, 1.0 / C, Double.NegativeInfinity));
}
else
{
return(new SolutionPair(0.0, 0.0, Double.PositiveInfinity, Double.NegativeInfinity));
}
}
else if (rho <= Coulomb_Series_Limit(0, eta))
{
// Below the safe series radius for L=0, compute using the series.
Coulomb_Zero_Series(eta, rho, out double F, out double FP, out double G, out double GP);
// For higher L, recurse G upward, but compute F via the direct series.
// G is safe to compute via recursion and F is not because G is increasing
// rapidly and F is decreasing rapidly with increasing L. Since the series
// for F was good for L = 0, it's certainly good for L > 0.
if (L > 0)
{
CoulombF_Series(L, eta, rho, out F, out FP);
double C = CoulombFactor(L, eta);
F *= C;
FP *= C;
Coulomb_Recurse_Upward(0, L, eta, rho, ref G, ref GP);
}
return(new SolutionPair(F, FP, G, GP));
}
else if (rho >= Coulomb_Asymptotic_Limit(L, eta))
{
return(Coulomb_Asymptotic(L, eta, rho));
}
else if (rho >= CoulombTurningPoint(L, eta))
{
return(Coulomb_Steed(L, eta, rho));
}
else
{
// This code is copied from CoulombG; factor it into a seperate method.
double G, GP;
if (rho >= Coulomb_Asymptotic_Limit(0, eta))
{
SolutionPair s = Coulomb_Asymptotic(0, eta, rho);
G = s.SecondSolutionValue;
GP = s.SecondSolutionDerivative;
}
else
{
double rho1 = CoulombTurningPoint(0, eta);
if (rho >= rho1)
{
SolutionPair s = Coulomb_Steed(0, eta, rho);
G = s.SecondSolutionValue;
GP = s.SecondSolutionDerivative;
}
else
{
SolutionPair s = Coulomb_Steed(0, eta, rho1);
G = s.SecondSolutionValue;
GP = s.SecondSolutionDerivative;
OdeResult r = FunctionMath.IntegrateConservativeOde(
(double x, double y) => (2.0 * eta / x - 1.0) * y,
rho1, G, GP, rho,
new OdeSettings()
{
RelativePrecision = 2.5E-13,
AbsolutePrecision = 0.0,
EvaluationBudget = 25000
}
);
G = r.Y;
GP = r.YPrime;
}
}
Coulomb_Recurse_Upward(0, L, eta, rho, ref G, ref GP);
// We can determine F and FP via CF1 and Wronskian, but if we are within
// series limit, it's likely a little faster and more accurate.
double F, FP;
if (rho < Coulomb_Series_Limit(L, eta))
{
CoulombF_Series(L, eta, rho, out F, out FP);
double C = CoulombFactor(L, eta);
F *= C;
FP *= C;
}
else
{
double f = Coulomb_CF1(L, eta, rho, out int _);
F = 1.0 / (f * G - GP);
FP = f * F;
}
return(new SolutionPair(F, FP, G, GP));
}
}
/// <summary>
/// Computes the irregular Coulomb wave function.
/// </summary>
/// <param name="L">The angular momentum number, which must be non-negative.</param>
/// <param name="eta">The charge parameter, which can be positive or negative.</param>
/// <param name="rho">The radial distance parameter, which must be non-negative.</param>
/// <returns>The value of G<sub>L</sub>(η,ρ).</returns>
/// <remarks>
/// <para>For information on the Coulomb wave functions, see the remarks on <see cref="Coulomb" />.</para>
/// </remarks>
/// <exception cref="ArgumentOutOfRangeException"><paramref name="L"/> or <paramref name="rho"/> is negative.</exception>
/// <seealso cref="Coulomb"/>
/// <seealso cref="CoulombF"/>
/// <seealso href="http://en.wikipedia.org/wiki/Coulomb_wave_function" />
/// <seealso href="http://mathworld.wolfram.com/CoulombWaveFunction.html" />
public static double CoulombG(int L, double eta, double rho)
{
if (L < 0)
{
throw new ArgumentOutOfRangeException(nameof(L));
}
if (rho < 0)
{
throw new ArgumentOutOfRangeException(nameof(rho));
}
if (rho <= Coulomb_Series_Limit(0, eta))
{
// For small enough rho, use the power series for L=0, then recurse upward to desired L.
Coulomb_Zero_Series(eta, rho, out double F, out double FP, out double G, out double GP);
Coulomb_Recurse_Upward(0, L, eta, rho, ref G, ref GP);
return(G);
}
else if (rho >= Coulomb_Asymptotic_Limit(L, eta))
{
// For large enough rho, use the asymptotic series.
SolutionPair s = Coulomb_Asymptotic(L, eta, rho);
return(s.SecondSolutionValue);
}
else if (rho >= CoulombTurningPoint(L, eta))
{
// Beyond the turning point, use Steed's method.
SolutionPair result = Coulomb_Steed(L, eta, rho);
return(result.SecondSolutionValue);
}
else
{
// We will start at L=0 (which has a smaller turning point radius) and recurse up to the desired L.
// This is okay because G increases with increasing L. We already know that we are beyond the L=0
// series limit; otherwise we would have taken the branch for it above. We might still be
// in the asymptotic region, in the Steed region, below the L=0 turning point (if \eta > 0).
double G, GP;
if (rho >= Coulomb_Asymptotic_Limit(0, eta))
{
SolutionPair s = Coulomb_Asymptotic(0, eta, rho);
G = s.SecondSolutionValue;
GP = s.SecondSolutionDerivative;
}
else
{
double rho1 = CoulombTurningPoint(0, eta);
if (rho >= rho1)
{
SolutionPair s = Coulomb_Steed(0, eta, rho);
G = s.SecondSolutionValue;
GP = s.SecondSolutionDerivative;
}
else
{
SolutionPair s = Coulomb_Steed(0, eta, rho1);
G = s.SecondSolutionValue;
GP = s.SecondSolutionDerivative;
OdeResult r = FunctionMath.IntegrateConservativeOde(
(double x, double y) => (2.0 * eta / x - 1.0) * y,
rho1, G, GP, rho,
new OdeSettings()
{
RelativePrecision = 2.5E-13,
AbsolutePrecision = 0.0,
EvaluationBudget = 25000
}
);
G = r.Y;
GP = r.YPrime;
}
}
Coulomb_Recurse_Upward(0, L, eta, rho, ref G, ref GP);
return(G);
}
}
// Hankel's asymptotic expansions for Bessel function (A&S 9.2)
// J = \sqrt{\frac{2}{\pi x}} \left[ P \cos\phi - Q \sin\phi \right]
// Y = \sqrt{\frac{2}{\pi x}} \left[ P \sin\phi + Q \cos\phi \right]
// where \phi = x - \left( \nu / 2 + 1 / 4 \right) \pi and \mu = 4 \nu^2 and
// P = 1 - \frac{(\mu-1)(\mu-9)}{2! (8x)^2} + \frac{(\mu-1)(\mu-9)(\mu-25)(\mu-49}{4! (8x)^4} + \cdots
// Q = \frac{(\mu-1)}{8x} - \frac{(\mu-1)(\mu-9)(\mu-25)}{3! (8x)^3} + \cdots
// Derivatives have similiar expressions
// J' = - \sqrt{\frac{2}{\pi x}} \left[ R \sin\phi + S \cos\phi \right]
// Y' = \sqrt{\frac{2}{\pi x}} \left[ R \cos\phi - S \sin\phi \right]
// where
// R = 1 - \frac{(\mu-1)(\mu+15)}{2! (8x)^2} + \cdots
// S = \frac{(\mu+3)}{8x} - \frac{(\mu-1)(\mu - 9)(\mu+35)}{3! (8x)^3} + \cdots
// For nu=0, this series converges to full precision in about 10 terms at x~100, and in about 25 terms even as low as x~25
// It fails to converge at all for lower x <~ 25
// Since the first correction term is ~ (4 \nu^2)^2 / (8 x)^2 ~ (\nu^2 / 2 x)^2, the minimum x should grow like \nu^2 / 2
private static SolutionPair Bessel_Asymptotic(double nu, double x)
{
// pre-compute factors of nu and x as they appear in the series
double mu = 4.0 * nu * nu;
double xx = 8.0 * x;
// initialize P and Q
double P = 1.0; double R = 1.0;
double Q = 0.0; double S = 0.0;
// k is the current term number, k2 is (2k - 1), and t is the value of the current term
int k = 0;
int k2 = -1;
double t = 1.0;
while (true) {
double Q_old = Q; double P_old = P;
double R_old = R; double S_old = S;
k++; k2 += 2;
t /= k * xx;
S += (mu + k2 * (k2 + 2)) * t;
t *= (mu - k2 * k2);
Q += t;
k++; k2 += 2;
t /= -k * xx;
R += (mu + k2 * (k2 + 2)) * t;
t *= (mu - k2 * k2);
P += t;
if ((P == P_old) && (Q == Q_old) && (R == R_old) && (S == S_old)) {
break;
}
if (k > Global.SeriesMax) throw new NonconvergenceException();
}
// We attempted to move to a single trig evaluation so as to avoid errors when the two terms nearly cancel,
// but this seemed to cause problems, perhaps because the arctan angle cannot be determined with sufficient
// resolution. Investigate further.
/*
double M = N * MoreMath.Hypot(Q, P);
double phi = Math.Atan2(Q, P);
SolutionPair result2 = new SolutionPair(
M * Cos(x + phi, -(nu + 0.5) / 4.0),
-N * (R * s + S * c),
M * Sin(x + phi, -(nu + 0.5) / 4.0),
N * (R * c - S * s)
);
*/
// Compute sin and cosine of x - (\nu + 1/2)(\pi / 2)
// Then we compute sine and cosine of (x1 - u1) with shift appropriate to (x0 - u0).
// For maximum accuracy, we first reduce x = (x_0 + x_1) (\pi / 2), where x_0 is an integer and -0.5 < x1 < 0.5
long x0; double x1;
RangeReduction.ReduceByPiHalves(x, out x0, out x1);
// Then we reduce (\nu + 1/2) = u_0 + u_1 where u_0 is an integer and -0.5 < u1 < 0.5
double u = nu + 0.5;
double ur = Math.Round(u);
long u0 = (long) ur;
double u1 = u - ur;
// FInally, we compute sine and cosine, having reduced the evaluation interval to -0.5 < \theta < 0.5
double s1 = RangeReduction.Sin(x0 - u0, x1 - u1);
double c1 = RangeReduction.Cos(x0 - u0, x1 - u1);
// Assemble the solution
double N = Math.Sqrt(2.0 / Math.PI / x);
SolutionPair result = new SolutionPair(
N * (c1 * P - s1 * Q), -N * (R * s1 + S * c1),
N * (s1 * P + c1 * Q), N * (R * c1 - S * s1)
);
return (result);
}
/// <summary>
/// Computes the irregular Coulomb wave function.
/// </summary>
/// <param name="L">The angular momentum number, which must be non-negative.</param>
/// <param name="eta">The charge parameter, which can be postive or negative.</param>
/// <param name="rho">The radial distance parameter, which must be non-negative.</param>
/// <returns>The value of G<sub>L</sub>(η,ρ).</returns>
/// <remarks>
/// <para>For information on the Coulomb wave functions, see the remarks on <see cref="CoulombF" />.</para>
/// </remarks>
/// <exception cref="ArgumentOutOfRangeException"><paramref name="L"/> or <paramref name="rho"/> is negative.</exception>
/// <seealso cref="CoulombF"/>
/// <seealso href="http://en.wikipedia.org/wiki/Coulomb_wave_function" />
/// <seealso href="http://mathworld.wolfram.com/CoulombWaveFunction.html" />
public static double CoulombG(int L, double eta, double rho)
{
if (L < 0)
{
throw new ArgumentOutOfRangeException("L");
}
if (rho < 0)
{
throw new ArgumentOutOfRangeException("rho");
}
if ((rho < 4.0) && Math.Abs(rho * eta) < 8.0)
{
// for small enough rho, use the power series for L=0, then recurse upward to desired L
double F, FP, G, GP;
Coulomb_Zero_Series(eta, rho, out F, out FP, out G, out GP);
Coulomb_Recurse_Upward(0, L, eta, rho, ref G, ref GP);
return(G);
}
else if (rho > 32.0 + (L * L + eta * eta) / 2.0)
{
// for large enough rho, use the asymptotic series
double F, G;
Coulomb_Asymptotic(L, eta, rho, out F, out G);
return(G);
}
else
{
// transition region
if (rho >= CoulombTurningPoint(L, eta))
{
// beyond the turning point, use Steed's method
SolutionPair result = Coulomb_Steed(L, eta, rho);
return(result.SecondSolutionValue);
}
else
{
// we will start at L=0 (which has a smaller turning point radius) and recurse up to the desired L
// this is okay because G increasees with increasing L
double G, GP;
if (rho < 2.0 * eta)
{
// if inside the turning point even for L=0, start at the turning point and integrate in
// this is okay becaue G increases with decraseing rho
// use Steed's method at the turning point
// for large enough eta, we could use the turning point expansion at L=0, but it contributes
// a lot of code for little overall performance increase so we have chosen not to
SolutionPair result;
//if (eta > 12.0) {
// result = Coulomb_Zero_Turning_Expansion(eta);
//} else {
result = Coulomb_Steed(0, eta, 2.0 * eta);
//}
G = result.SecondSolutionValue;
GP = result.SecondSolutionDerivative;
BulrischStoerStoermerStepper s = new BulrischStoerStoermerStepper();
s.RightHandSide = delegate(double x, double U) {
return((2.0 * eta / x - 1.0) * U);
};
s.X = 2.0 * eta;
s.Y = G;
s.YPrime = GP;
s.DeltaX = 0.25;
s.Accuracy = 2.5E-13;
s.Integrate(rho);
G = s.Y;
GP = s.YPrime;
}
else
{
// if beyond the turning point for L=0, just use Steeds method
SolutionPair result = Coulomb_Steed(0, eta, rho);
G = result.SecondSolutionValue;
GP = result.SecondSolutionDerivative;
}
// recurse up to desired L
Coulomb_Recurse_Upward(0, L, eta, rho, ref G, ref GP);
return(G);
}
}
}
