scirs2_integrate/specialized/quantum/
basis_sets.rs

1//! Advanced basis sets for quantum calculations
2//!
3//! This module provides various basis sets and basis set operations
4//! for quantum calculations and quantum chemistry applications.
5
6use crate::error::{IntegrateError, IntegrateResult as Result};
7use scirs2_core::ndarray::{Array1, Array2};
8use scirs2_core::numeric::Complex64;
9use std::collections::HashMap;
10
11/// Advanced basis sets for quantum calculations
12#[derive(Debug, Clone)]
13pub struct AdvancedBasisSets {
14    /// Number of basis functions
15    pub n_basis: usize,
16    /// Basis set type
17    pub basis_type: BasisSetType,
18    /// Basis function parameters
19    pub parameters: Vec<BasisParameter>,
20    /// Overlap matrix
21    pub overlap_matrix: Array2<f64>,
22}
23
24impl AdvancedBasisSets {
25    /// Create new advanced basis set
26    pub fn new(n_basis: usize, basistype: BasisSetType) -> Self {
27        let parameters = vec![BasisParameter::default(); n_basis];
28        let overlap_matrix = Array2::eye(n_basis);
29
30        Self {
31            n_basis,
32            basis_type: basistype,
33            parameters,
34            overlap_matrix,
35        }
36    }
37
38    /// Generate basis functions
39    pub fn generate_basis_functions(&self, coordinates: &Array2<f64>) -> Result<Array2<Complex64>> {
40        let n_points = coordinates.nrows();
41        let mut basis_functions = Array2::zeros((n_points, self.n_basis));
42
43        match self.basis_type {
44            BasisSetType::Gaussian => {
45                self.generate_gaussian_basis(coordinates, &mut basis_functions)?;
46            }
47            BasisSetType::SlaterType => {
48                self.generate_slater_basis(coordinates, &mut basis_functions)?;
49            }
50            BasisSetType::PlaneWave => {
51                self.generate_plane_wave_basis(coordinates, &mut basis_functions)?;
52            }
53            BasisSetType::Atomic => {
54                self.generate_atomic_basis(coordinates, &mut basis_functions)?;
55            }
56        }
57
58        Ok(basis_functions)
59    }
60
61    /// Generate Gaussian basis functions
62    fn generate_gaussian_basis(
63        &self,
64        coordinates: &Array2<f64>,
65        basis_functions: &mut Array2<Complex64>,
66    ) -> Result<()> {
67        for (i, param) in self.parameters.iter().enumerate() {
68            for (j, coord_row) in coordinates
69                .axis_iter(scirs2_core::ndarray::Axis(0))
70                .enumerate()
71            {
72                let x = coord_row[0];
73                let y = if coord_row.len() > 1 {
74                    coord_row[1]
75                } else {
76                    0.0
77                };
78                let z = if coord_row.len() > 2 {
79                    coord_row[2]
80                } else {
81                    0.0
82                };
83
84                let r_squared = (x - param.center_x).powi(2)
85                    + (y - param.center_y).powi(2)
86                    + (z - param.center_z).powi(2);
87
88                let gaussian = (-param.exponent * r_squared).exp();
89                basis_functions[[j, i]] = Complex64::new(gaussian * param.normalization, 0.0);
90            }
91        }
92
93        Ok(())
94    }
95
96    /// Generate Slater-type basis functions
97    fn generate_slater_basis(
98        &self,
99        coordinates: &Array2<f64>,
100        basis_functions: &mut Array2<Complex64>,
101    ) -> Result<()> {
102        for (i, param) in self.parameters.iter().enumerate() {
103            for (j, coord_row) in coordinates
104                .axis_iter(scirs2_core::ndarray::Axis(0))
105                .enumerate()
106            {
107                let x = coord_row[0];
108                let y = if coord_row.len() > 1 {
109                    coord_row[1]
110                } else {
111                    0.0
112                };
113                let z = if coord_row.len() > 2 {
114                    coord_row[2]
115                } else {
116                    0.0
117                };
118
119                let r = ((x - param.center_x).powi(2)
120                    + (y - param.center_y).powi(2)
121                    + (z - param.center_z).powi(2))
122                .sqrt();
123
124                let slater = r.powf(param.angular_momentum as f64) * (-param.exponent * r).exp();
125                basis_functions[[j, i]] = Complex64::new(slater * param.normalization, 0.0);
126            }
127        }
128
129        Ok(())
130    }
131
132    /// Generate plane wave basis functions
133    fn generate_plane_wave_basis(
134        &self,
135        coordinates: &Array2<f64>,
136        basis_functions: &mut Array2<Complex64>,
137    ) -> Result<()> {
138        use scirs2_core::constants::PI;
139
140        for (i, param) in self.parameters.iter().enumerate() {
141            for (j, coord_row) in coordinates
142                .axis_iter(scirs2_core::ndarray::Axis(0))
143                .enumerate()
144            {
145                let x = coord_row[0];
146                let y = if coord_row.len() > 1 {
147                    coord_row[1]
148                } else {
149                    0.0
150                };
151                let z = if coord_row.len() > 2 {
152                    coord_row[2]
153                } else {
154                    0.0
155                };
156
157                let k_dot_r = param.kx * x + param.ky * y + param.kz * z;
158                let plane_wave = Complex64::new(
159                    (k_dot_r).cos() * param.normalization,
160                    (k_dot_r).sin() * param.normalization,
161                );
162                basis_functions[[j, i]] = plane_wave;
163            }
164        }
165
166        Ok(())
167    }
168
169    /// Generate atomic orbital basis functions
170    fn generate_atomic_basis(
171        &self,
172        coordinates: &Array2<f64>,
173        basis_functions: &mut Array2<Complex64>,
174    ) -> Result<()> {
175        // Simplified atomic orbital generation
176        for (i, param) in self.parameters.iter().enumerate() {
177            for (j, coord_row) in coordinates
178                .axis_iter(scirs2_core::ndarray::Axis(0))
179                .enumerate()
180            {
181                let x = coord_row[0];
182                let y = if coord_row.len() > 1 {
183                    coord_row[1]
184                } else {
185                    0.0
186                };
187                let z = if coord_row.len() > 2 {
188                    coord_row[2]
189                } else {
190                    0.0
191                };
192
193                let r = ((x - param.center_x).powi(2)
194                    + (y - param.center_y).powi(2)
195                    + (z - param.center_z).powi(2))
196                .sqrt();
197
198                // Simplified hydrogen-like orbital
199                let radial = r.powf(param.angular_momentum as f64) * (-param.exponent * r).exp();
200                let orbital = radial * param.normalization;
201                basis_functions[[j, i]] = Complex64::new(orbital, 0.0);
202            }
203        }
204
205        Ok(())
206    }
207
208    /// Calculate overlap matrix
209    pub fn calculate_overlap_matrix(&mut self, coordinates: &Array2<f64>) -> Result<()> {
210        let basis_functions = self.generate_basis_functions(coordinates)?;
211        let n_points = coordinates.nrows();
212
213        self.overlap_matrix = Array2::zeros((self.n_basis, self.n_basis));
214
215        for i in 0..self.n_basis {
216            for j in 0..self.n_basis {
217                let mut overlap = 0.0;
218                for k in 0..n_points {
219                    overlap += (basis_functions[[k, i]].conj() * basis_functions[[k, j]]).re;
220                }
221                self.overlap_matrix[[i, j]] = overlap;
222            }
223        }
224
225        Ok(())
226    }
227
228    /// Orthogonalize basis functions using Gram-Schmidt
229    pub fn orthogonalize_basis(&mut self) -> Result<()> {
230        // Apply Gram-Schmidt orthogonalization to basis parameters
231        for i in 1..self.n_basis {
232            for j in 0..i {
233                let overlap = self.overlap_matrix[[i, j]];
234                if overlap.abs() > 1e-12 {
235                    // Subtract projection
236                    let norm_j = self.overlap_matrix[[j, j]].sqrt();
237                    if norm_j > 1e-12 {
238                        let projection_coeff = overlap / norm_j;
239                        self.parameters[i].normalization -=
240                            projection_coeff * self.parameters[j].normalization;
241                    }
242                }
243            }
244        }
245
246        Ok(())
247    }
248
249    /// Transform basis functions
250    pub fn transform_basis(
251        &self,
252        transformation_matrix: &Array2<f64>,
253    ) -> Result<AdvancedBasisSets> {
254        if transformation_matrix.nrows() != self.n_basis
255            || transformation_matrix.ncols() != self.n_basis
256        {
257            return Err(IntegrateError::InvalidInput(
258                "Transformation matrix dimension mismatch".to_string(),
259            ));
260        }
261
262        let mut transformed_basis = self.clone();
263
264        // Apply transformation to basis parameters
265        for i in 0..self.n_basis {
266            let mut new_normalization = 0.0;
267            for j in 0..self.n_basis {
268                new_normalization +=
269                    transformation_matrix[[i, j]] * self.parameters[j].normalization;
270            }
271            transformed_basis.parameters[i].normalization = new_normalization;
272        }
273
274        // Transform overlap matrix
275        let overlap_transformed = transformation_matrix
276            .t()
277            .dot(&self.overlap_matrix)
278            .dot(transformation_matrix);
279        transformed_basis.overlap_matrix = overlap_transformed;
280
281        Ok(transformed_basis)
282    }
283}
284
285/// Types of basis sets
286#[derive(Debug, Clone, Copy)]
287pub enum BasisSetType {
288    /// Gaussian basis functions
289    Gaussian,
290    /// Slater-type orbitals
291    SlaterType,
292    /// Plane wave basis
293    PlaneWave,
294    /// Atomic orbital basis
295    Atomic,
296}
297
298/// Parameters for individual basis functions
299#[derive(Debug, Clone)]
300pub struct BasisParameter {
301    /// Exponent parameter
302    pub exponent: f64,
303    /// Normalization constant
304    pub normalization: f64,
305    /// Angular momentum quantum number
306    pub angular_momentum: i32,
307    /// Center coordinates
308    pub center_x: f64,
309    pub center_y: f64,
310    pub center_z: f64,
311    /// Wave vector components (for plane waves)
312    pub kx: f64,
313    pub ky: f64,
314    pub kz: f64,
315}
316
317impl Default for BasisParameter {
318    fn default() -> Self {
319        Self {
320            exponent: 1.0,
321            normalization: 1.0,
322            angular_momentum: 0,
323            center_x: 0.0,
324            center_y: 0.0,
325            center_z: 0.0,
326            kx: 0.0,
327            ky: 0.0,
328            kz: 0.0,
329        }
330    }
331}
332
333#[cfg(test)]
334mod tests {
335    use super::*;
336    use approx::assert_relative_eq;
337
338    #[test]
339    fn test_basis_set_creation() {
340        let basis = AdvancedBasisSets::new(5, BasisSetType::Gaussian);
341        assert_eq!(basis.n_basis, 5);
342        assert_eq!(basis.parameters.len(), 5);
343        assert_eq!(basis.overlap_matrix.nrows(), 5);
344        assert_eq!(basis.overlap_matrix.ncols(), 5);
345    }
346
347    #[test]
348    fn test_gaussian_basis_generation() {
349        let mut basis = AdvancedBasisSets::new(2, BasisSetType::Gaussian);
350
351        // Set up simple Gaussian parameters
352        basis.parameters[0].exponent = 1.0;
353        basis.parameters[0].normalization = 1.0;
354        basis.parameters[1].exponent = 2.0;
355        basis.parameters[1].normalization = 1.0;
356        basis.parameters[1].center_x = 1.0;
357
358        let coordinates =
359            Array2::from_shape_vec((3, 3), vec![0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.5, 0.5, 0.0])
360                .unwrap();
361
362        let basis_functions = basis.generate_basis_functions(&coordinates);
363        assert!(basis_functions.is_ok());
364
365        let functions = basis_functions.unwrap();
366        assert_eq!(functions.nrows(), 3);
367        assert_eq!(functions.ncols(), 2);
368    }
369
370    #[test]
371    fn test_overlap_matrix_calculation() {
372        let mut basis = AdvancedBasisSets::new(2, BasisSetType::Gaussian);
373
374        let coordinates = Array2::from_shape_vec(
375            (10, 3),
376            vec![
377                0.0, 0.0, 0.0, 0.1, 0.0, 0.0, 0.2, 0.0, 0.0, 0.3, 0.0, 0.0, 0.4, 0.0, 0.0, 0.5,
378                0.0, 0.0, 0.6, 0.0, 0.0, 0.7, 0.0, 0.0, 0.8, 0.0, 0.0, 0.9, 0.0, 0.0,
379            ],
380        )
381        .unwrap();
382
383        let result = basis.calculate_overlap_matrix(&coordinates);
384        assert!(result.is_ok());
385
386        // Diagonal elements should be positive
387        for i in 0..basis.n_basis {
388            assert!(basis.overlap_matrix[[i, i]] > 0.0);
389        }
390    }
391}