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Nov 19, 2025
Merged

Updates to account for changes in nda #18

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8 changes: 4 additions & 4 deletions c++/cppdlr/dlr_dyson.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -20,7 +20,7 @@
#include <cppdlr/dlr_imtime.hpp>
#include <cppdlr/dlr_kernels.hpp>

#include <nda/linalg/eigenelements.hpp>
#include <nda/linalg/eigh.hpp>
#include <type_traits>

namespace cppdlr {
Expand Down Expand Up @@ -86,7 +86,7 @@ namespace cppdlr {
* \note Hamiltonian must either be a symmetric matrix, a Hermitian matrix,
* or a real scalar.
*/
dyson_it(double beta, imtime_ops itops, Ht const &h, bool time_order) : dyson_it(beta, itops, h, 0, time_order){};
dyson_it(double beta, imtime_ops itops, Ht const &h, bool time_order) : dyson_it(beta, itops, h, 0, time_order) {};

/**
* @brief Solve Dyson equation for given self-energy
Expand Down Expand Up @@ -121,7 +121,7 @@ namespace cppdlr {
auto g = Tg(sig.shape()); // Declare Green's function
g = rhs; // Get right hand side of Dyson equation
auto g_rs = nda::matrix_view<nda::get_value_t<Tg>>(nda::reshape(g, norb, r * norb)); // Reshape g to be compatible w/ LAPACK
nda::lapack::getrs(sysmat, g_rs, ipiv); // Back solve
nda::lapack::getrs(sysmat, transpose(g_rs), ipiv); // Back solve
if constexpr (std::floating_point<Ht>) { // If h is scalar, g is scalar-valued
return g;
} else { // Otherwise, g is matrix-valued, and need to transpose some indices after solve to undo LAPACK formatting
Expand Down Expand Up @@ -181,7 +181,7 @@ namespace cppdlr {
int norb = h.shape(0);

// Diagonalize Hamiltonian
auto [eval, evec] = nda::linalg::eigenelements(h);
auto [eval, evec] = nda::linalg::eigh(h);

// Get free Green's function
auto g = nda::array<nda::get_value_t<Ht>, 3>(r, norb, norb);
Expand Down
22 changes: 13 additions & 9 deletions c++/cppdlr/dlr_imtime.hpp
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Expand Up @@ -580,11 +580,12 @@ namespace cppdlr {
fconv += matmul(cf2it, tmp2);

// Then precompose with DLR grid values to DLR coefficients matrix
if constexpr (nda::is_complex_v<S>) { // getrs requires matrix and rhs to have same value type
nda::lapack::getrs(transpose(it2cf.zlu), fconv, it2cf.piv); // Note: lapack effectively tranposes fconv by fortran reordering here
if constexpr (nda::is_complex_v<S>) { // getrs requires matrix and rhs to have same value type
nda::lapack::getrs(transpose(it2cf.zlu), transpose(fconv),
it2cf.piv); // Note: lapack effectively tranposes fconv by fortran reordering here
} else {
// getrs requires matrix and rhs to have same value type
nda::lapack::getrs(transpose(it2cf.lu), fconv, it2cf.piv);
nda::lapack::getrs(transpose(it2cf.lu), transpose(fconv), it2cf.piv);
}

fconv *= beta;
Expand Down Expand Up @@ -627,11 +628,12 @@ namespace cppdlr {
}

// Do the solve
if constexpr (nda::is_complex_v<S>) { // getrs requires matrix and rhs to have same value type
nda::lapack::getrs(transpose(it2cf.zlu), fconvtmp, it2cf.piv); // Note: lapack effectively tranposes fconv by fortran reordering here
if constexpr (nda::is_complex_v<S>) { // getrs requires matrix and rhs to have same value type
nda::lapack::getrs(transpose(it2cf.zlu), transpose(fconvtmp),
it2cf.piv); // Note: lapack effectively tranposes fconv by fortran reordering here
} else {
// getrs requires matrix and rhs to have same value type
nda::lapack::getrs(transpose(it2cf.lu), fconvtmp, it2cf.piv);
nda::lapack::getrs(transpose(it2cf.lu), transpose(fconvtmp), it2cf.piv);
}

// Transpose back
Expand Down Expand Up @@ -903,7 +905,7 @@ namespace cppdlr {
}

// Precompose with DLR values to coefficients matrix
nda::lapack::getrs(transpose(it2cf.lu), refl, it2cf.piv); // Lapack effectively transposes refl by fortran reordering here
nda::lapack::getrs(transpose(it2cf.lu), transpose(refl), it2cf.piv); // Lapack effectively transposes refl by fortran reordering here
}

private:
Expand Down Expand Up @@ -946,7 +948,7 @@ namespace cppdlr {
* @param[in] ar Archive to serialize into
*/
void serialize(auto &ar) const {
ar &lambda_ &r &dlr_rf &dlr_it &cf2it &it2cf.lu &it2cf.zlu &it2cf.piv &hilb &tcf2it &thilb &ttcf2it &ipmat &refl;
ar & lambda_ & r & dlr_rf & dlr_it & cf2it & it2cf.lu & it2cf.zlu & it2cf.piv & hilb & tcf2it & thilb & ttcf2it & ipmat & refl;
}

/**
Expand All @@ -956,7 +958,9 @@ namespace cppdlr {
*
* @param[in] ar Archive to deserialize from
*/
void deserialize(auto &ar) { ar &lambda_ &r &dlr_rf &dlr_it &cf2it &it2cf.lu &it2cf.zlu &it2cf.piv &hilb &tcf2it &thilb &ttcf2it &ipmat &refl; }
void deserialize(auto &ar) {
ar & lambda_ & r & dlr_rf & dlr_it & cf2it & it2cf.lu & it2cf.zlu & it2cf.piv & hilb & tcf2it & thilb & ttcf2it & ipmat & refl;
}

// -------------------- hdf5 -------------------

Expand Down
4 changes: 2 additions & 2 deletions test/c++/dyson_it.cpp
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Expand Up @@ -62,7 +62,7 @@ TEST(dyson_it, dyson_vs_ed_real) {
// Get random nxn Hamiltonian w/ eigenvalues in [-1 1]
auto a = nda::matrix<double>(nda::rand<double>(std::array<int, 2>({n, n}))); // Random matrix
a = (a + transpose(a)) / 2; // Make symmetric
auto [eval, u] = nda::linalg::eigenelements(a); // Random orthogonal matrix
auto [eval, u] = nda::linalg::eigh(a); // Random orthogonal matrix
eval = -1 + 2 * nda::rand<double>(std::array<int, 1>({n})); // Random eigenvalues in [-1,1]
auto h = matmul(matmul(u, nda::diag(eval)), transpose(conj(u))); // Random symmetric matrix

Expand Down Expand Up @@ -151,7 +151,7 @@ TEST(dyson_it, dyson_vs_ed_cmplx) {
// Get random nxn Hamiltonian w/ eigenvalues in [-1 1]
auto a = nda::matrix<dcomplex>(nda::rand<double>(std::array<int, 2>({n, n})) + 1i * nda::rand<double>(std::array<int, 2>({n, n}))); // Random matrix
a = (a + transpose(conj(a))) / 2; // Make Hermitian
auto [eval, u] = nda::linalg::eigenelements(a); // Random unitary matrix
auto [eval, u] = nda::linalg::eigh(a); // Random unitary matrix
eval = -1 + 2 * nda::rand<double>(std::array<int, 1>({n})); // Random eigenvalues in [-1,1]
auto h = matmul(matmul(u, nda::diag(eval)), transpose(conj(u))); // Random Hermitian matrix

Expand Down
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