API reference

Basis is an abstract type.

BasisSet(basis1, basis2, ...)

\[\{ \phi_1, \phi_2, \phi_3, \cdots \}\]

The basis set is the input for Rayleigh-Ritz method. You can define the basis set like this:

\[\begin{aligned} \phi_1(r) &= \exp(-13.00773 ~r^2), \\ \phi_2(r) &= \exp(-1.962079 ~r^2), \\ \phi_3(r) &= \exp(-0.444529 ~r^2), \\ \phi_4(r) &= \exp(-0.1219492 ~r^2). \end{aligned}\]

BS = BasisSet(
  SimpleGaussianBasis(13.00773),
  SimpleGaussianBasis(1.962079),
  SimpleGaussianBasis(0.444529),
  SimpleGaussianBasis(0.1219492),
)

ConstantPotential(constant=1)

\[+ c\]

ContractedBasis([c1, c2, ...], [basis1, basis2, ...])

\[\phi' = \sum_i c_i \phi_i\]

CoulombPotential(coefficient=1)

\[+ \frac{a}{r}\]

DeltaPotential(coefficient=1)

\[+ a δ(r)\]

ExponentialPotential(coefficient=1, exponent=1)

\[+ a \exp(- b r)\]

FiniteDifferenceMethod(Δr=0.1, rₘₐₓ=50.0, R=Δr:Δr:rₘₐₓ, l=0, direction=:c, solver=:LinearAlgebra)

FunctionPotential(f)

\[+ f(r)\]

GaussianBasis(a=1, l=0, m=0)

\[\phi_i(r, θ, φ) = N _{il} r^l \exp(-a_i r^2) Y_l^m(θ, φ)\]

GaussianPotential(coefficient=1, exponent=1)

\[+ a \exp(- b r^2)\]

GeometricBasisSet(basistype, r₁, rₙ, n; nₘᵢₙ=1, nₘₐₓ=n)

This is a basis set with exponentials generated by geometric(r₁, rₙ, n; nₘₐₓ=n, nₘᵢₙ=1). You can define the same basis set as Table A2 in E. Hiyama, M. Kamimura, Front. Phys. 13, 132106 (2018) like this:

\[ r_1 = 0.1, r_{n_\mathrm{max}} = 80.0, n_\mathrm{max} = 20.\]

BS = GeometricBasisSet(SimpleGaussianBasis, 0.1, 80.0, 20)

Hamiltonian(operator1, operator2, ...)

\[\hat{H} = \sum_i \hat{o}_i\]

The Hamiltonian is the input for each solver. This is an example for the non-relativistic Hamiltonian of hydrogen atom in atomic units:

\[\hat{H} = - \frac{1}{2} \nabla^2 - \frac{1}{r}\]

H = Hamiltonian(
  NonRelativisticKinetic(ℏ =1 , m = 1),
  CoulombPotential(coefficient = -1),
)

KineticTerm <: Operator is an abstract type.

Laplacian(coefficient=1)

\[+ a\nabla^2\]

LinearPotential(coefficient=1)

\[+ ar\]

NonRelativisticKinetic(ℏ=1, m=1)

\[-\frac{\hbar^2}{2m} \nabla^2\]

Operator is an abstract type.

PotentialTerm <: Operator is an abstract type.

PowerLawPotential(coefficient=1, exponent=1)

\[+ ar^n\]

PrimitiveBasis <: Basis is an abstract type.

RelativisticCorrection(c=1, m=1, n=2) The p^{2n} term of the Taylor expansion:

\[\begin{aligned} \sqrt{p^2 c^2 + m^2 c^4} =& m \times c^2 \\ &+ 1 / 2 / m \times p^2 (n=1) \\ &- 1 / 8 / m^3 / c^2 \times p^4 (n=2) \\ &+ 1 / 16 / m^5 / c^4 \times p^6 (n=3) \\ &- 5 / 128 / m^7 / c^6 \times p^8 (n=4) \\ &+ \cdots \end{aligned}\]

Use c = 137.035999177 (from 2022 CODATA) in the atomic units.

RelativisticKinetic(c=1, m=1)

\[\sqrt{p^2 c^2 + m^2 c^4} - m c^2\]

Use c = 137.035999177 (from 2022 CODATA) in the atomic units.

RestEnergy(c=1, m=1)

\[m c^2\]

Use c = 137.035999177 (from 2022 CODATA) in the atomic units.

SimpleGaussianBasis(a=1)

Position-Space

\[\phi_i(\pmb{r}) = \exp(-a_i r^2)\]

Momentum-Space

\[\phi_{i}(\pmb{k}) = \frac{1}{(2a_i)^{\frac{3}{2}}} \exp(-k^2/4a_i)\]

Proof (Fourier Transform)

\[\begin{aligned} \phi_{n}(\pmb{k}) &= \frac{1}{\sqrt{2 \pi}^3} \int \phi_{n}(\pmb{r}) \mathrm{e}^{\mathrm{i} \pmb{k} \cdot \pmb{r}} \mathrm{d}\pmb{r} \\ &= \frac{1}{\sqrt{2 \pi}^3} \int \phi_{n}(\pmb{r}) \mathrm{e}^{\mathrm{i} \pmb{k} \cdot \pmb{r}} r^2 \sin (\theta) ~\mathrm{d}r \mathrm{d}\theta \mathrm{d} \varphi \\ &= \frac{1}{\sqrt{2 \pi}^3} \iiint \mathrm{e}^{-\alpha_i r^2} \sqrt{4\pi} Y_{00}(\hat{\pmb{r}}) \left[ 4 \pi \sum_{l'=0}^{\infty} \sum_{m=-l'}^{l'} \mathrm{i}^{l'} j_{l'}(pr) Y_{l'm'}(\hat{\pmb{k}}) Y_{l'm'}^*(\hat{\pmb{r}}) \right] r^2 \sin\theta~ \mathrm{d} r \mathrm{d} \theta \mathrm{d} \varphi \\ &= \frac{1}{\sqrt{2 \pi}^3} 4 \pi \sqrt{4\pi} \sum_{l'=0}^{\infty} \sum_{m=-l'}^{l'} \left[ \mathrm{i}^{l'} Y_{l'm'}(\hat{\pmb{k}}) \int_0^{2 \pi} \int_0^\pi Y_{00}(\hat{\pmb{r}}) Y_{l'm'}^*(\hat{\pmb{r}}) \sin (\theta)~ \mathrm{d} \theta \mathrm{d} \varphi \int_0^{\infty} j_{l'}(pr) \mathrm{e}^{-\alpha_i r^2} r^{2} \mathrm{d}r \right]\\ &= \frac{1}{\sqrt{2 \pi}^3} 4 \pi \sqrt{4\pi} \sum_{l'=0}^{\infty} \sum_{m=-l'}^{l'} \left[ \mathrm{i}^{l'} Y_{l'm'}(\hat{\pmb{k}}) \delta_{0l'} \delta_{0m'} \int_0^{\infty} j_{l'}(kr) \mathrm{e}^{-\alpha_i r^2} r^{2} \mathrm{d}r \right] \\ &= \frac{1}{\sqrt{2 \pi}^3} 4 \pi \sqrt{4\pi} \mathrm{i}^{0} Y_{00}(\hat{\pmb{k}}) \int_0^{\infty} j_{0}(kr) \mathrm{e}^{-\alpha_i r^2} r^{2} \mathrm{d}r \\ &= \frac{1}{2\pi\sqrt{2\pi}} 4 \pi \frac{\sqrt{4\pi}}{\sqrt{4\pi}} \sqrt{\frac{\pi}{2}} \sqrt{\frac{2}{\pi}} \int_0^{\infty} j_{0}(kr) \mathrm{e}^{-\alpha_i r^2} r^{2} ~\mathrm{d}r \\ &= \frac{1}{(2\alpha_i)^{\frac{3}{2}}} \mathrm{e}^{-\frac{k^2}{4 \alpha_i}} \end{aligned}\]

Formula

plane-wave expansion in spherical harmonics:

\[\mathrm{e}^{\mathrm{i} \pmb{k} \cdot \pmb{r}} = 4 \pi \sum_{l=0}^{\infty} \sum_{m=-l}^{l} \mathrm{i}^{l} j_{l}(pr) Y_{lm}(\hat{\pmb{k}}) Y_{lm}^*(\hat{\pmb{r}})\]

special case of spherical harmonics:

\[Y_{00}(\hat{\pmb{r}}) = \frac{1}{\sqrt{4\pi}}\]

orthonormality of spherical harmonics:

\[\int_0^{2\pi} \int_0^\pi Y_{lm}(\hat{\pmb{r}})^* Y_{l'm'}(\hat{\pmb{r}}) \sin(\theta) ~ \mathrm{d} \theta \mathrm{d} \varphi = \delta_{ll'} \delta_{mm'}\]

citation needed:

\[\sqrt{\frac{2}{\pi}} \int r^{l} j_l(kr) \mathrm{e}^{-\alpha r^2} r^{2} \mathrm{d} r = \frac{1}{(2\alpha)^{l+\frac{3}{2}}} k^l e^{-\frac{k^2}{4\alpha}}\]

UniformGridPotential(R, V)

YukawaPotential(coefficient=1, exponent=1)

\[+ \frac{a}{r} \exp(- b r)\]

element(o::ConstantPotential, SGB1::SimpleGaussianBasis, SGB2::SimpleGaussianBasis)

\[\begin{aligned} \langle \phi_{i} | c | \phi_{j} \rangle &= c \langle \phi_{i} | \phi_{j} \rangle \\ &= c \iiint \phi_{i}^*(r) \phi_{j}(r) ~r^2 \sin\theta ~\mathrm{d}r \mathrm{d}\theta \mathrm{d}\varphi \\ &= c \int_0^{2\pi} \mathrm{d}\varphi \int_0^\pi \sin\theta ~\mathrm{d}\theta \int_0^\infty r^{2} \mathrm{e}^{-(\alpha_i + \alpha_j) r^2} ~\mathrm{d}r \\ &= c \times 2\pi \times 2 \times \frac{1!!}{2^{2}} \sqrt{\frac{\pi}{a^{3}}} \\ &= \underline{c \left( \frac{\pi}{\alpha_i + \alpha_j} \right)^{3/2}} \end{aligned}\]

Integral Formula:

\[\int_0^{\infty} r^{2n} \exp \left(-a r^2\right) ~\mathrm{d}r = \frac{(2n-1)!!}{2^{n+1}} \sqrt{\frac{\pi}{a^{2n+1}}}\]

element(o::CoulombPotential, SGB1::SimpleGaussianBasis, SGB2::SimpleGaussianBasis)

\[\begin{aligned} \langle \phi_{i} | \frac{1}{r} | \phi_{j} \rangle &= \iiint \phi_{i}^*(r) \times \frac{1}{r} \times \phi_{j}(r) ~r^2 \sin\theta ~\mathrm{d}r \mathrm{d}\theta \mathrm{d}\varphi \\ &= \int_0^{2\pi} \mathrm{d}\varphi \int_0^\pi \sin\theta ~\mathrm{d}\theta \int_0^\infty r \mathrm{e}^{-(\alpha_i + \alpha_j) r^2} ~\mathrm{d}r \\ &= 2\pi \times 2 \times \frac{0!}{2 (\alpha_i + \alpha_j)} \\ &= \underline{\frac{2\pi}{\alpha_i + \alpha_j}} \end{aligned}\]

Integral Formula:

\[\int_0^{\infty} r^{2n+1} \exp \left(-a r^2\right) ~\mathrm{d}r = \frac{n!}{2 a^{n+1}}\]

element(o::GaussianPotential, SGB1::SimpleGaussianBasis, SGB2::SimpleGaussianBasis)

\[\begin{aligned} \langle \phi_{i} | \exp(-br^2) | \phi_{j} \rangle &= \iiint \phi_{i}^*(r) \times \exp(-br^2) \times \phi_{j}(r) ~r^2 \sin\theta ~\mathrm{d}r \mathrm{d}\theta \mathrm{d}\varphi \\ &= \int_0^{2\pi} \mathrm{d}\varphi \int_0^\pi \sin\theta ~\mathrm{d}\theta \int_0^\infty r^2 \mathrm{e}^{-(b+\alpha_i + \alpha_j) r^2} ~\mathrm{d}r \\ &= 2\pi \times 2 \times \frac{1!!}{2^{2}} \sqrt{\frac{\pi}{(b + \alpha_i + \alpha_j)^{2\cdot1+1}}} \\ &= \underline{\left( \frac{\pi}{b + \alpha_i + \alpha_j} \right)^{3/2}} \end{aligned}\]

Integral Formula:

\[\int_0^{\infty} r^{2n} \exp \left(-a r^2\right) ~\mathrm{d}r = \frac{(2n-1)!!}{2^{n+1}} \sqrt{\frac{\pi}{a^{2n+1}}}\]

element(o::Hamiltonian, SGB1::SimpleGaussianBasis, SGB2::SimpleGaussianBasis)

\[\begin{aligned} H_{ij} &= \langle \phi_{i} | \hat{H} | \phi_{j} \rangle \\ &= \langle \phi_{i} | \sum_k \hat{o}_k | \phi_{j} \rangle \\ &= \sum_k \langle \phi_{i} | \hat{o}_k | \phi_{j} \rangle \\ \end{aligned}\]

element(o::LinearPotential, SGB1::SimpleGaussianBasis, SGB2::SimpleGaussianBasis)

\[\begin{aligned} \langle \phi_{i} | r | \phi_{j} \rangle &= \iiint \phi_{i}^*(r) \times r \times \phi_{j}(r) ~r^2 \sin\theta ~\mathrm{d}r \mathrm{d}\theta \mathrm{d}\varphi \\ &= \int_0^{2\pi} \mathrm{d}\varphi \int_0^\pi \sin\theta ~\mathrm{d}\theta \int_0^\infty r^3 \mathrm{e}^{-(\alpha_i + \alpha_j) r^2} ~\mathrm{d}r \\ &= 2\pi \times 2 \times \frac{1!}{2 (\alpha_i + \alpha_j)^{2}} \\ &= \underline{\frac{2\pi}{(\alpha_i + \alpha_j)^2}} \end{aligned}\]

Integral Formula:

\[\int_0^{\infty} r^{2n+1} \exp \left(-a r^2\right) ~\mathrm{d}r = \frac{n!}{2 a^{n+1}}\]

element(o::NonRelativisticKinetic, SGB1::SimpleGaussianBasis, SGB2::SimpleGaussianBasis)

Derivation (without Green's identity)

\[\begin{aligned} T_{ij} = \langle \phi_{i} | \hat{T} | \phi_{j} \rangle &= \iiint \mathrm{e}^{-\alpha_i r^2} \left[ -\frac{\hbar^2}{2\mu} \nabla^2 \right] \mathrm{e}^{-\alpha_j r^2} ~r^2 \sin\theta ~\mathrm{d}r \mathrm{d}\theta \mathrm{d}\varphi \\ &= -\frac{\hbar^2}{2\mu} \iiint \mathrm{e}^{-\alpha_i r^2} \left[ \nabla^2 \right] \mathrm{e}^{-\alpha_j r^2} ~r^2 \sin\theta ~\mathrm{d}r \mathrm{d}\theta \mathrm{d}\varphi \\ &= -\frac{\hbar^2}{2\mu} \iiint \mathrm{e}^{-\alpha_i r^2} \left[ -6\alpha_j + 4\alpha_j^2 r^2 \right] \mathrm{e}^{-\alpha_j r^2} ~r^2 \sin\theta ~\mathrm{d}r \mathrm{d}\theta \mathrm{d}\varphi \\ &= -\frac{\hbar^2}{2\mu} \iint \sin\theta ~\mathrm{d}\theta \mathrm{d}\varphi \int \left[ -6\alpha_j + 4\alpha_j^2 r^2 \right] r^2 \mathrm{e}^{-(\alpha_i + \alpha_j) r^2} ~\mathrm{d}r \\ &= -\frac{\hbar^2}{2\mu} \cdot 4\pi \left[ -6\alpha_j \mathrm{GGI}(2, \alpha_i + \alpha_j) +4\alpha_j^2 \mathrm{GGI}(4, \alpha_i + \alpha_j) \right] \\ &= -\frac{\hbar^2}{2\mu} \cdot 4\pi \left[ -6\alpha_j \frac{\Gamma\left( \frac{3}{2} \right)}{2 (\alpha_i + \alpha_j)^{\frac{3}{2}}} +4\alpha_j^2 \frac{\Gamma\left( \frac{5}{2} \right)}{2 (\alpha_i + \alpha_j)^{\frac{5}{2}}} \right] \\ &= -\frac{\hbar^2}{2\mu} \cdot 4\pi \left[ -6\alpha_j \frac{ \sqrt{\pi}/2}{2 (\alpha_i + \alpha_j)^{\frac{3}{2}}} +4\alpha_j^2 \frac{3\sqrt{\pi}/4}{2 (\alpha_i + \alpha_j)^{\frac{5}{2}}} \right] \\ &= -\frac{\hbar^2}{2\mu} \cdot 4\pi \left[ \frac{\alpha_j}{\alpha_i + \alpha_j} - 1 \right] \cdot 6 \alpha_j \cdot \frac{\sqrt{\pi}/2}{2 (\alpha_i + \alpha_j)^{\frac{3}{2}}} \\ &= -\frac{\hbar^2}{2\mu} \cdot 4\pi \left[ - \frac{\alpha_i}{\alpha_i + \alpha_j} \right] \cdot 6 \alpha_j \cdot \frac{\sqrt{\pi}/2}{2 (\alpha_i + \alpha_j)^{\frac{3}{2}}} \\ &= \underline{ \frac{\hbar^2}{2\mu} \cdot 6 \cdot \frac{\alpha_i \alpha_j \pi^{\frac{3}{2}}}{(\alpha_i + \alpha_j)^{\frac{5}{2}}} } \end{aligned}\]

Derivation (with Green's identity)

\[\begin{aligned} T_{ij} = \langle \phi_{i} | \hat{T} | \phi_{j} \rangle &= \iiint \mathrm{e}^{-\alpha_i r^2} \left[ -\frac{\hbar^2}{2\mu} \nabla^2 \right] \mathrm{e}^{-\alpha_j r^2} ~r^2 \sin\theta ~\mathrm{d}r \mathrm{d}\theta \mathrm{d}\varphi \\ &= -\frac{\hbar^2}{2\mu} \iiint \mathrm{e}^{-\alpha_i r^2} \nabla^2 \mathrm{e}^{-\alpha_j r^2} ~r^2 \sin\theta ~\mathrm{d}r \mathrm{d}\theta \mathrm{d}\varphi \\ &= \frac{\hbar^2}{2\mu} \iiint \left[ \nabla \mathrm{e}^{-\alpha_i r^2} \right] \left[ \nabla \mathrm{e}^{-\alpha_j r^2} \right] ~r^2 \sin\theta ~\mathrm{d}r \mathrm{d}\theta \mathrm{d}\varphi \\ &= \frac{\hbar^2}{2\mu} \iiint \left[ -2 \alpha_i r \mathrm{e}^{-\alpha_i r^2} \right] \left[ -2 \alpha_j r \mathrm{e}^{-\alpha_j r^2} \right] ~r^2 \sin\theta ~\mathrm{d}r \mathrm{d}\theta \mathrm{d}\varphi \\ &= \frac{\hbar^2}{2\mu} \cdot 4 \alpha_i \alpha_j \iiint \left[ r \mathrm{e}^{-\alpha_i r^2} \right] \left[ r \mathrm{e}^{-\alpha_j r^2} \right] ~r^2 \sin\theta ~\mathrm{d}r \mathrm{d}\theta \mathrm{d}\varphi \\ &= \frac{\hbar^2}{2\mu} \cdot 4 \alpha_i \alpha_j \iint \sin\theta ~\mathrm{d}\theta \mathrm{d}\varphi \int r^4 \mathrm{e}^{- (\alpha_i + \alpha_j) r^2} ~\mathrm{d}r \\ &= \frac{\hbar^2}{2\mu} \cdot 4 \alpha_i \alpha_j \cdot 4 \pi \cdot \mathrm{GGI}(4, \alpha_i + \alpha_j) \\ &= \frac{\hbar^2}{2\mu} \cdot 4 \alpha_i \alpha_j \cdot 4 \pi \cdot \frac{\Gamma\left( \frac{5}{2} \right)}{2 (\alpha_i + \alpha_j)^{\frac{5}{2}}} \\ &= \frac{\hbar^2}{2\mu} \cdot 4 \alpha_i \alpha_j \cdot 4 \pi \cdot \frac{3\sqrt{\pi}/4}{2 (\alpha_i + \alpha_j)^{\frac{5}{2}}} \\ &= \underline{ \frac{\hbar^2}{2\mu} \cdot 6 \cdot \frac{\alpha_i \alpha_j \pi^{\frac{3}{2}}}{(\alpha_i + \alpha_j)^{\frac{5}{2}}} } \end{aligned}\]

Formula

Green's first identity:

\[\begin{aligned} \iiint_V f \pmb{\nabla}^2 g ~ \mathrm{d}V + \iiint_V \pmb{\nabla} f \cdot \pmb{\nabla} g ~ \mathrm{d}V = \iint_{\partial V} f \pmb{\nabla} g \cdot \pmb{n} ~ \mathrm{d}S \end{aligned}\]

generalized Gaussian integral:

\[\begin{aligned} \mathrm{GGI}(n,b) = \int_0^{\infty} x^{n} \exp \left(-b x^2\right) \mathrm{d}x = \frac{\Gamma\left( \frac{n+1}{2} \right)}{2 b^{\frac{n+1}{2}}} \end{aligned}\]

element(o::PowerLawPotential, SGB1::SimpleGaussianBasis, SGB2::SimpleGaussianBasis)

\[\begin{aligned} \langle \phi_{i} | r^n | \phi_{j} \rangle &= \iiint \phi_{i}^*(r) \times r^n \times \phi_{j}(r) ~r^2 \sin\theta ~\mathrm{d}r \mathrm{d}\theta \mathrm{d}\varphi \\ &= \int_0^{2\pi} \mathrm{d}\varphi \int_0^\pi \sin\theta ~\mathrm{d}\theta \int_0^\infty r^{n+2} \mathrm{e}^{-(\alpha_i + \alpha_j) r^2} ~\mathrm{d}r \\ &= 2\pi \times 2 \times \frac{\Gamma\left( \frac{n+3}{2} \right)}{2 (\alpha_i + \alpha_j)^{\frac{n+3}{2}}} \\ &= \underline{2\pi\frac{\Gamma\left( \frac{n+3}{2} \right)}{(\alpha_i + \alpha_j)^{\frac{n+3}{2}}}} \end{aligned}\]

Integral Formula:

\[\int_0^{\infty} r^{n} \exp \left(-a r^2\right) ~\mathrm{d}r = \frac{\Gamma\left( \frac{n+1}{2} \right)}{2 a^{\frac{n+1}{2}}}\]

element(o::RestEnergy, SGB1::SimpleGaussianBasis, SGB2::SimpleGaussianBasis)

\[\begin{aligned} \langle \phi_{i} | mc^2 | \phi_{j} \rangle &= mc^2 \langle \phi_{i} | \phi_{j} \rangle \\ &= mc^2 \iiint \phi_{i}^*(r) \phi_{j}(r) ~r^2 \sin\theta ~\mathrm{d}r \mathrm{d}\theta \mathrm{d}\varphi \\ &= mc^2 \int_0^{2\pi} \mathrm{d}\varphi \int_0^\pi \sin\theta ~\mathrm{d}\theta \int_0^\infty r^{2} \mathrm{e}^{-(\alpha_i + \alpha_j) r^2} ~\mathrm{d}r \\ &= mc^2 \times 2\pi \times 2 \times \frac{1!!}{2^{2}} \sqrt{\frac{\pi}{a^{3}}} \\ &= \underline{mc^2 \left( \frac{\pi}{\alpha_i + \alpha_j} \right)^{3/2}} \end{aligned}\]

Integral Formula:

\[\int_0^{\infty} r^{2n} \exp \left(-a r^2\right) ~\mathrm{d}r = \frac{(2n-1)!!}{2^{n+1}} \sqrt{\frac{\pi}{a^{2n+1}}}\]

element(SGB1::SimpleGaussianBasis, SGB2::SimpleGaussianBasis)

\[\begin{aligned} S_{ij} = \langle \phi_{i} | \phi_{j} \rangle &= \int \phi_{i}^*(r) \phi_{j}(r) \mathrm{d} \pmb{r} \\ &= \iiint \mathrm{e}^{-\alpha_i r^2} \mathrm{e}^{-\alpha_j r^2} ~r^2 \sin\theta ~ \mathrm{d} r \mathrm{d} \theta \mathrm{d} \varphi \\ &= \int_0^{2\pi} \mathrm{d}\varphi \int_0^\pi \sin\theta ~\mathrm{d}\theta \int_0^\infty r^{2} \mathrm{e}^{-(\alpha_i + \alpha_j) r^2} ~\mathrm{d}r \\ &= 2\pi \times 2 \times \frac{1!!}{2^{2}} \sqrt{\frac{\pi}{a^{3}}} \\ &= \underline{\left( \frac{\pi}{\alpha_i + \alpha_j} \right)^{3/2}} \end{aligned}\]

Integral Formula:

\[\int_0^{\infty} r^{2n} \exp \left(-a r^2\right) ~\mathrm{d}r = \frac{(2n-1)!!}{2^{n+1}} \sqrt{\frac{\pi}{a^{2n+1}}}\]

element(o::Laplacian, SGB1::SimpleGaussianBasis, SGB2::SimpleGaussianBasis)

\[\begin{aligned} \langle \phi_{i} | \nabla^2 | \phi_{j} \rangle = \underline{ -6 \frac{\alpha_i \alpha_j \pi^{\frac{3}{2}}}{(\alpha_i + \alpha_j)^{\frac{5}{2}}} } \end{aligned}\]

geometric(r₁, rₙ, n::Int; nₘₐₓ::Int=n, nₘᵢₙ::Int=1)

Exponents of Gaussian basis functions are given by geometric progression:

\[\begin{aligned} & v_i = \frac{1}{r_i^2}, \\ & r_i = r_1 a^{i-1}. \end{aligned}\]

This function return array of $\nu_i$:

\[(r_1, r_{n}, n, n_\mathrm{max}) \mapsto (\nu_1, \nu_2, \cdots, \nu_{n-1}, \nu_n, \nu_{n+1}, \cdots, \nu_{n_\mathrm{max}})\]

Usually $n = n_\mathrm{max}$. Set $n<n_\mathrm{max}$ if you want to extend the geometric progression.

Examples:

julia> ν = TwoBody.geometric(0.1, 10.0, 5)
5-element Vector{Float64}:
 100.0
  10.0
   0.9999999999999997
   0.09999999999999996
   0.009999999999999995

julia> ν = TwoBody.geometric(0.1, 10.0, 5, nₘₐₓ = 10)
10-element Vector{Float64}:
 100.0
  10.0
   0.9999999999999997
   0.09999999999999996
   0.009999999999999995
   0.0009999999999999994
   9.999999999999994e-5
   9.999999999999992e-6
   9.999999999999991e-7
   9.999999999999988e-8

matrix(basisset::BasisSet)

This function returns the overlap matrix $\pmb{S}$. The element is written as $S_{ij} = \langle \phi_{i} | \phi_{j} \rangle$.

matrix(hamiltonian::Hamiltonian, basisset::BasisSet)

This function returns the Hamiltonian matrix $\pmb{H}$. The element is written as $H_{ij} = \langle \phi_{i} | \hat{H} | \phi_{j} \rangle$.

matrix(o::Hamiltonian, method::FiniteDifferenceMethod)

The matrix for the Hamiltonian is a sum of matrices for each term,

\[\pmb{H} = \sum_i \pmb{O}_i.\]

matrix(o::NonRelativisticKinetic, method::FiniteDifferenceMethod)

We use the shorthand notation $\psi'(r) = \frac{\mathrm{d}\psi}{\mathrm{d}r}(r)$ and $\psi''(r) = \frac{\mathrm{d}^{2}\psi}{\mathrm{d}r^{2}}(r)$. For the uniform grid spacing ($r_{i+1} = r_{i} + \Delta r$), the finite difference for the first derivative,

\[\frac{\mathrm{d}\psi}{\mathrm{d}r}(r) = \frac{\psi(r+\Delta r) - \psi(r-\Delta r)}{2\Delta r} + O(\Delta r^{2})\]

is written as

\[\left(\begin{array}{ccccc} \psi'(r_1) \\ \psi'(r_2) \\ \psi'(r_3) \\ \psi'(r_4) \\ \vdots \end{array}\right) \simeq \frac{1}{2\Delta r} \left(\begin{array}{ccccc} 0 & 1 & 0 & 0 &\ldots \\ -1 & 0 & 1 & 0 &\ldots \\ 0 & -1 & 0 & 1 &\ldots \\ 0 & 0 & -1 & 0 &\ldots \\ \vdots & \vdots & \vdots & \vdots & \ddots \\ \end{array}\right) \left(\begin{array}{ccccccc} \psi(r_1) \\ \psi(r_2) \\ \psi(r_3) \\ \psi(r_4) \\ \vdots \end{array}\right),\]

and the finite difference for the second derivative,

\[\frac{\mathrm{d}^{2}}{\mathrm{d}r^{2}}(r) = \frac{\psi(r+\Delta r) - 2f(r) + \psi(r-\Delta r)}{\Delta r^{2}} + O(\Delta r^{2}).\]

is written as

\[\left(\begin{array}{ccccc} \psi''(r_1) \\ \psi''(r_2) \\ \psi''(r_3) \\ \psi''(r_4) \\ \vdots \end{array}\right) \simeq \frac{1}{\Delta r^2} \left(\begin{array}{ccccccc} -2 & 1 & 0 & 0 & \ldots \\ 1 & -2 & 1 & 0 & \ldots \\ 0 & 1 & -2 & 1 & \ldots \\ 0 & 0 & 1 & -2 & \ldots \\ \vdots & \vdots & \vdots & \vdots & \ddots \end{array}\right) \left(\begin{array}{ccccccc} \psi(r_1) \\ \psi(r_2) \\ \psi(r_3) \\ \psi(r_4) \\ \vdots \end{array}\right).\]

Similarly, the matrix for the kinetic energy,

\[\hat{T} = -\frac{\hbar^2}{2\mu} \left[ \frac{\partial^2}{\partial r^2} + \frac{2}{r} \frac{\partial}{\partial r} - \frac{l(l+1)}{r^2} \right]\]

is written as

\[\pmb{T} = - \frac{\hbar^2}{2\mu} \left[ \frac{1}{{\Delta r}^2} \left(\begin{array}{ccccccc} -2 & 1 & 0 & \ldots \\ 1 & -2 & 1 & \ldots \\ 0 & 1 & -2 & \ldots \\ \vdots & \vdots & \vdots & \ddots \\ \end{array}\right) + \left(\begin{array}{ccccccc} 2/r_1 & 0 & 0 & \ldots \\ 0 & 2/r_2 & 0 & \ldots \\ 0 & 0 & 2/r_3 & \ldots \\ \vdots & \vdots & \vdots & \ddots \\ \end{array}\right) \frac{1}{\Delta r} \left(\begin{array}{ccccccc} 0 & 1 & 0 & \ldots \\ -1 & 0 & 1 & \ldots \\ 0 & -1 & 0 & \ldots \\ \vdots & \vdots & \vdots & \ddots \\ \end{array}\right) - l(l+1) \left(\begin{array}{ccccccc} 1/{r_1}^2 & 0 & 0 & \ldots \\ 0 & 1/{r_2}^2 & 0 & \ldots \\ 0 & 0 & 1/{r_3}^2 & \ldots \\ \vdots & \vdots & \vdots & \ddots \\ \end{array}\right) \right].\]

matrix(operator::Operator, basisset::BasisSet)

This function is used for the expectation values and is not used in computing the Hamiltonian matrix.

This function returns the matrix corresponding to the operator in the given basis set. The element is written as $O_{ij} = \langle \phi_{i} | \hat{o} | \phi_{j} \rangle$.

matrix(o::RestEnergy, method::FiniteDifferenceMethod)

The matrix for the rest energy $mc^2$ is a diagonal matrix,

\[mc^2 \left(\begin{array}{ccccccc} 1 & 0 & 0 & \ldots \\ 0 & 1 & 0 & \ldots \\ 0 & 0 & 1 & \ldots \\ \vdots & \vdots & \vdots & \ddots \\ \end{array}\right).\]

matrix(o::PotentialTerm, method::FiniteDifferenceMethod)

The matrix for the potential energy $V(r)$ is a diagonal matrix,

\[\pmb{V} = \left(\begin{array}{ccccccc} V(r_1) & 0 & 0 & \ldots \\ 0 & V(r_2) & 0 & \ldots \\ 0 & 0 & V(r_3) & \ldots \\ \vdots & \vdots & \vdots & \ddots \\ \end{array}\right).\]

function optimize(hamiltonian::Hamiltonian, basisset::BasisSet; perturbation=Hamiltonian(), info=4, progress=true, optimizer=Optim.NelderMead(), options...)

This function minimizes the energy by changing the exponents of the basis functions using Optim.jl.

\[\frac{\partial E}{\partial a_i} = 0\]

optimize(hamiltonian::Hamiltonian, basis::Basis; perturbation=Hamiltonian(), info=4, optimizer=Optim.NelderMead())

This a optimizer for 1-basis calculations. This function returns optimize(hamiltonian, BasisSet(basis); perturbation=perturbation, info=info, progress=progress, optimizer=optimizer, options...).

optimize(hamiltonian::Hamiltonian, basisset::GeometricBasisSet; perturbation=Hamiltonian(), info=4, optimizer=Optim.NelderMead())

This function minimizes the energy by optimizing $r_1$ and $r_n$ using Optim.jl.

\[\frac{\partial E}{\partial r_1} = \frac{\partial E}{\partial r_n} = 0\]

solve(hamiltonian::Hamiltonian, wavefunction::Function, method::FiniteDifferenceMethod, info=4, nₘₐₓ=4)

solve(hamiltonian::Hamiltonian, basisset::BasisSet)

This function returns the eigenvalues $E$ and eigenvectors $\pmb{c}$ for

\[\pmb{H} \pmb{c} = E \pmb{S} \pmb{c}.\]

The Hamiltonian matrix is defined as $H_{ij} = \langle \phi_{i} | \hat{H} | \phi_{j} \rangle$. The overlap matrix is defined as $S_{ij} = \langle \phi_{i} | \phi_{j} \rangle$.

solve(hamiltonian::Hamiltonian, basis::Basis; perturbation=Hamiltonian(), info=4)

This a solver for 1-basis calculations. This function returns solve(hamiltonian, BasisSet(basis); perturbation=perturbation, info=info).

solve(hamiltonian::Hamiltonian, method::FiniteDifferenceMethod; perturbation=Hamiltonian(), info=4, nₘₐₓ=4)

This method solve the eigenvalue problem for the Hamiltonian discretized as a sparse matrix with finite difference approximation,

\[\pmb{H} \pmb{\psi} = E \pmb{\psi}.\]

The eigenvalue $E$ is an approximation of the exact energy and the eigenvector $\pmb{\psi}$ is a vector of the approximated values of the exact wavefunction $\psi(r)$ on points of the grid,

\[\pmb{\psi} = \left(\begin{array}{c} \psi(r_1) \\ \psi(r_2) \\ \psi(r_3) \\ \vdots \\ \end{array}\right).\]

solve(hamiltonian::Hamiltonian, basisset::GeometricBasisSet; perturbation=Hamiltonian(), info=4)

This function is a wrapper for solve(hamiltonian::Hamiltonian, basisset::BasisSet, ...).