Source code for vibeqc.periodic_uks_multi_k_ewald

"""Phase 15c-3b: multi-k open-shell UKS SCF driver with composed
EWALD_3D Coulomb dispatch.

Open-shell DFT counterpart of:

  * :func:`run_uhf_periodic_multi_k_ewald3d` -- same per-spin
    DIIS / damping / orthogonalisation structure.
  * :func:`run_uks_periodic_gamma_ewald3d` -- Γ-only UKS Ewald
    (15c-3a).
  * :func:`run_rks_periodic_multi_k_ewald3d` -- multi-k closed-shell
    KS Ewald (15c-2).

Per SCF iteration:

    F_a(k) =  H_core(k) + Bloch_k[J(D_a + D_b, w) - K_HF(D_a)]
                       + Bloch_k[V_xc^a(g)]
    F_b(k) =  H_core(k) + Bloch_k[J(D_a + D_b, w) - K_HF(D_b)]
                       + Bloch_k[V_xc^b(g)]

with ``K_HF = c_full*K_full + c_sr*K_erfc(omega_screen)`` per the CAM
assembly of :func:`vibeqc.periodic_screened_exchange.resolve_periodic_exchange`
(pure DFT skips the K builds entirely; global hybrids keep the
full-range fraction; screened hybrids like hse06 ride the erfc arm;
LR-heavy range-separated functionals fail closed). The per-spin K
blocks come from ``build_jk_2e_real_space`` via
:func:`vibeqc.periodic_screened_exchange.build_exchange_blocks`
(mirrors the UHF multi-k pattern).

Density flow.  Multi-k carries proper LatticeMatrixSets
``D_a_real``, ``D_b_real`` (one-particle, no factor of 2). The
periodic UKS XC kernel :func:`build_xc_periodic_uks` consumes them
directly and returns LatticeMatrixSets ``V_xc^a(g)``, ``V_xc^b(g)``
which are Bloch-summed per k.

Energy formula (mirrors molecular UKS + the multi-k UHF Ewald
convention):

    E_elec  =  E_xc  +  S_k w_k . 1/2 Re tr[(D_a(k) + D_b(k)).H_core(k)]
                     +  S_k w_k . 1/2 Re tr[D_a(k).F_a^{HF}(k)]
                     +  S_k w_k . 1/2 Re tr[D_b(k).F_b^{HF}(k)]

where ``F_s^{HF}(k) = Bloch_k[J - a.K_s]`` is the Hartree-plus-HF
piece of F_s (V_xc reported through E_xc rather than a trace).

Scope.
  * Multi-k open-shell, ``multiplicity >= 1``; integer a/b occupations,
    or per-spin Fermi-Dirac fractional occupations via
    ``options.smearing_temperature`` (separate chemical potentials at
    fixed n_a / n_b; convergence on the free energy A = E - T.S).
  * Pure DFT, hybrid, and HF (a = 1, equivalent to UHF Ewald).
  * Per-spin Pulay DIIS with k-weighted Frobenius inner product.
  * Saunders-Hillier level shift via ``options.level_shift``.
  * Periodic Becke partition selectable via
    ``options.use_periodic_becke``.
  * <S^2> diagnostic on the Γ-block (or first) k-point -- same shortcut
    the multi-k UHF Ewald driver uses.
"""

from __future__ import annotations

import math
from dataclasses import dataclass, field
from typing import List, Optional, Sequence, Tuple, Union

import numpy as np

from ._vibeqc_core import (
    apply_level_shift_k,
    BasisSet,
    bloch_sum,
    BlochKMesh,
    build_grid,
    build_xc_periodic_uks,
    compute_kinetic_lattice,
    compute_nuclear_lattice,
    compute_overlap_lattice,
    CoulombMethod,
    Functional,
    InitialGuess,
    LatticeMatrixSet,
    LatticeSumOptions,
    LevelShiftDensity,
    nuclear_repulsion_per_cell,
    PeriodicKSOptions,
    PeriodicSystem,
    real_space_density_from_kpoints_fractional,
    SCFIteration,
    SpinlockMode,
)
from .ewald_j import auto_grid
from .guess import initial_densities_open_shell
from .mom import reorder_occupied_by_max_overlap as _mom_reorder
from .madelung import (
    madelung_energy_correction_for_lat as _madelung_energy_correction_for_lat,
)
from .periodic_fock_multi_k import (
    ewald_3d_j_blocks,
    make_ewald_3d_lattice_j_cache,
    make_slab_ewald_2d_lattice_j_cache,
    slab_ewald_2d_j_blocks,
)
from .periodic_grid import build_periodic_becke_grid
from .periodic_rhf_multi_k_ewald import (
    _canonical_orthogonalizer_complex,
    _damp_lattice_matrix,
    _diag_in_orth_basis,
    _g0_block,
    _MultiKPulayDIIS,
)
from .periodic_uhf_ewald import _spin_squared
from .periodic_screened_exchange import (
    PeriodicExchangeAssembly,
    build_exchange_blocks,
    resolve_periodic_exchange,
)
from .progress import ProgressLogger, resolve_progress
from .scf_divergence import check_scf_divergence
from .smearing.fermi_dirac import (
    fermi_dirac_occupations_per_k as _fermi_dirac_occupations_per_k,
)

__all__ = [
    "PeriodicUKSMultiKEwaldResult",
    "run_uks_periodic_multi_k_ewald3d",
]


[docs] @dataclass class PeriodicUKSMultiKEwaldResult: """Result of :func:`run_uks_periodic_multi_k_ewald3d`.""" energy: float e_electronic: float e_nuclear: float e_xc: float e_coulomb: float e_hf_exchange: float n_iter: int converged: bool s_squared: float s_squared_ideal: float # a mo_energies_alpha: List[np.ndarray] mo_coeffs_alpha: List[np.ndarray] fock_alpha: List[np.ndarray] density_alpha: LatticeMatrixSet # b mo_energies_beta: List[np.ndarray] mo_coeffs_beta: List[np.ndarray] fock_beta: List[np.ndarray] density_beta: LatticeMatrixSet overlap: List[np.ndarray] hcore: List[np.ndarray] functional: str = "" scf_trace: List[SCFIteration] = field(default_factory=list) omega: float = 0.0 grid_shape: Tuple[int, int, int] = (0, 0, 0) # Smearing diagnostics (zero when smearing_temperature == 0). smearing_temperature: float = 0.0 fermi_level_alpha: float = 0.0 fermi_level_beta: float = 0.0 entropy: float = 0.0 free_energy: float = 0.0
def _build_uks_fock_2e_blocks_ewald3d( basis: BasisSet, system: PeriodicSystem, D_alpha_real: LatticeMatrixSet, D_beta_real: LatticeMatrixSet, omega: float, exx, lat_opts: LatticeSumOptions, grid_shape_t: Tuple[int, int, int], origin: Optional[Sequence[float]], spacing_bohr: float, j_cache=None, ) -> Tuple[List[np.ndarray], List[np.ndarray]]: """Per-cell F^{2e,s}(g) = J(D_total, w)(g) - K_HF(D_s)(g) blocks. Mirrors :func:`vibeqc.periodic_uhf_multi_k_ewald._build_uhf_fock_blocks_ewald3d` with the per-spin K generalised to the CAM assembly ``exx`` (:class:`vibeqc.periodic_screened_exchange.PeriodicExchangeAssembly`; ``None`` or a no-exchange assembly = pure DFT / J-only, K builds skipped -- saving the real-space 2e builds per Fock evaluation). ``j_cache`` is an optional :class:`EwaldJFTLatticeCache` reused across SCF iterations for the analytic-FT Hartree J; ``None`` rebuilds inline (unchanged one-shot behaviour).""" n_cells = len(D_alpha_real.cells) # D_total = D_a + D_b as a LatticeMatrixSet. D_total_real = compute_overlap_lattice(basis, system, lat_opts) for g in range(n_cells): D_total_real.set_block( g, np.asarray(D_alpha_real.blocks[g], dtype=float) + np.asarray(D_beta_real.blocks[g], dtype=float), ) if lat_opts.coulomb_method == CoulombMethod.SLAB_EWALD_2D: J_total_blocks = slab_ewald_2d_j_blocks( basis, system, D_total_real, float(omega), lattice_opts=lat_opts, j_cache=j_cache, ) else: # J(D_total) per cell via the shared EWALD_3D J-blocks helper # (analytic-FT default -- w-invariant, Bloch-sums to the Γ J at the # (1,1,1) mesh; FFT-Poisson split behind VIBEQC_J_EWALD3D_BACKEND=grid). J_total_blocks = ewald_3d_j_blocks( basis, system, D_total_real, float(omega), lattice_opts=lat_opts, grid_shape=grid_shape_t, origin=origin, spacing_bohr=spacing_bohr, j_cache=j_cache, ) if exx is None or not exx.needs_exchange: F_alpha_blocks: List[np.ndarray] = [] F_beta_blocks: List[np.ndarray] = [] for g in range(n_cells): J_total = np.asarray(J_total_blocks[g], dtype=float) F_alpha_blocks.append(J_total) F_beta_blocks.append(J_total) return F_alpha_blocks, F_beta_blocks # Hybrid path: per-spin coefficient-folded K blocks (full-range # and/or erfc-screened per the CAM assembly). Same builders + # omega convention as the Γ driver, so the (1,1,1) Bloch sum # matches it. Equality of the full-range routes is pinned in # tests/test_periodic_uhf_multi_k_ewald.py. K_alpha_blocks = build_exchange_blocks( basis, system, lat_opts, D_alpha_real, exx ) K_beta_blocks = build_exchange_blocks( basis, system, lat_opts, D_beta_real, exx ) F_alpha_blocks = [] F_beta_blocks = [] for g in range(n_cells): J_total = np.asarray(J_total_blocks[g], dtype=float) F_alpha_blocks.append(J_total - K_alpha_blocks[g]) F_beta_blocks.append(J_total - K_beta_blocks[g]) return F_alpha_blocks, F_beta_blocks def _bloch_sum_blocks( blocks: Sequence[np.ndarray], cells, k_cart: np.ndarray, ) -> np.ndarray: k = np.asarray(k_cart, dtype=float).reshape(3) F_k = np.zeros_like(blocks[0], dtype=complex) for g_idx, block in enumerate(blocks): R_g = np.asarray(cells[g_idx].r_cart, dtype=float) phase = np.exp(1j * float(np.dot(k, R_g))) F_k = F_k + phase * block return F_k def _bloch_sum_lms_at_k( lms: LatticeMatrixSet, k_cart: np.ndarray, ) -> np.ndarray: return np.asarray(bloch_sum(lms, np.asarray(k_cart, dtype=float).reshape(3))) def run_uks_periodic_multi_k_ewald3d( system: PeriodicSystem, basis: BasisSet, kmesh: BlochKMesh, options: Optional[PeriodicKSOptions] = None, *, omega: float = 0.0, grid_shape: Optional[Union[Tuple[int, int, int], int]] = None, origin: Optional[Sequence[float]] = None, spacing_bohr: float = 0.3, linear_dep_threshold: float = 1e-7, canonical_orth_normalize_diag_first: bool = True, auto_optimize_truncation: bool = True, progress: Union[bool, ProgressLogger, None] = None, verbose: Optional[int] = None, bz_integration: Optional[str] = None, ) -> PeriodicUKSMultiKEwaldResult: """Multi-k open-shell periodic Kohn-Sham SCF with EWALD_3D Coulomb. Parameters ---------- system, basis, kmesh Periodic system, AO basis, k-mesh. options Optional :class:`PeriodicKSOptions`. Reads ``functional``, ``grid``, ``use_periodic_becke``, ``becke_image_radius_bohr``, ``level_shift``, ``damping``, ``max_iter``, ``conv_tol_*``, ``diis_*``, ``initial_guess``, ``lattice_opts``. Positive ``smearing_temperature`` enables separate per-spin Fermi-Dirac occupations at fixed ``n_alpha`` / ``n_beta``. Returns ------- :class:`PeriodicUKSMultiKEwaldResult`. """ opts = options if options is not None else PeriodicKSOptions() if getattr(opts, "initial_guess", None) == InitialGuess.READ: raise NotImplementedError( "periodic READ restart is Γ-point only: the QVF wavefunction.gto " "section stores real Γ MO coefficients, and a multi-k restart " "needs per-k complex Bloch coefficients (out of scope). Restart " "from a Γ calculation. See docs/roadmap.md Sec.G2." ) # SPINLOCK: this multi-k UKS driver implements PATTERN_HOLD (the AFM-seed # protection mode); SPIN_SCHEDULE's two-phase is Γ-Ewald-only in v1. from .spinlock_periodic import check_spinlock_support check_spinlock_support( opts, {SpinlockMode.PATTERN_HOLD}, "the multi-k UKS Ewald driver") smearing_T = float(getattr(opts, "smearing_temperature", 0.0)) if smearing_T < 0.0: raise ValueError( "run_uks_periodic_multi_k_ewald3d: smearing_temperature must be >= 0" ) # BZ-integration backend (opt-in). None / "smearing" keeps the temperature # path; "gilat" selects the Gilat-Raubenheimer net (computed per spin, # g=1.0) on the full or IBZ mesh. GR is T=0, so no finite smearing. if bz_integration not in (None, "smearing", "gilat"): raise ValueError( "run_uks_periodic_multi_k_ewald3d: bz_integration must be None, " f"'smearing', or 'gilat'; got {bz_integration!r}" ) use_gilat = bz_integration == "gilat" if use_gilat and smearing_T > 0.0: raise ValueError( "run_uks_periodic_multi_k_ewald3d: bz_integration='gilat' is a " "T=0 integrator; do not combine it with smearing_temperature > 0" ) # Finite-T smearing and GR both give fractional occupations -> the # fractional per-spin density path (vs integer Aufbau slicing). use_fractional_density = (smearing_T > 0.0) or use_gilat # Fermi-Dirac smearing is supported per spin (separate chemical # potentials at fixed n_alpha / n_beta, mirroring the BIPOLE UKS # driver); convergence then runs on the free energy A = E - T.S. lat_opts: LatticeSumOptions = opts.lattice_opts slab_mode = lat_opts.coulomb_method == CoulombMethod.SLAB_EWALD_2D if slab_mode and system.dim != 2: raise ValueError( "run_uks_periodic_multi_k_ewald3d: SLAB_EWALD_2D requires " f"dim == 2; got dim = {system.dim}" ) plog = resolve_progress(progress, verbose=verbose) # ---- Force EWALD_3D gauge (gauge consistency; handover F4 2026-06-01) ---- # This driver hard-codes the Hartree J to the Ewald-3D builder, so V_ne # (compute_nuclear_lattice_dispatch) and e_nuc (nuclear_repulsion_per_cell) # MUST share that gauge. Without the force, a default options object # (coulomb_method=DIRECT_TRUNCATED) makes nuclear_repulsion_per_cell return # the molecular 1/d sum and madelung_energy_correction_for_lat the bare-gauge # +a_M.Q_e^2/2L term; those only partially cancel (~0.74 mHa on H2/30-bohr), # so the SCF converged to a non-physical energy with no warning (CLAUDE.md # Sec.7). The RHF multi-k sibling already forces this (audit F1); extending it # here aligns e_nuclear with run_uks_periodic_gamma_ewald3d and zeroes the # now-redundant Madelung term (madelung_energy_correction_for_lat returns # 0.0 for EWALD_3D). # EWALD_3D V_ne (compute_nuclear_lattice_dispatch) is implemented only for # dim == 3 -- the 1D/2D Ewald variants raise (periodic_v_ne.py). So gate the # force on dim == 3; low-dim cells keep their DIRECT_TRUNCATED gauge (the # historical behaviour for these drivers on 1D/2D chains). if system.dim == 3 and lat_opts.coulomb_method != CoulombMethod.EWALD_3D: plog.info( "coulomb_method forced to EWALD_3D for gauge consistency " f"(was {lat_opts.coulomb_method!r}); this driver's Hartree J " "is Ewald-3D and V_ne / e_nuc must match" ) lat_opts.coulomb_method = CoulombMethod.EWALD_3D # w must match the nuclear Ewald a (auto-selected from # nuclear_cutoff_bohr in the C++ ewald engine) so the jellium # background terms cancel exactly. Mirrors the override block in # the sibling Ewald drivers (commit 49f8ae91 / 433d3543). The # driver kwarg ``omega`` is retained for signature parity but is # overridden here; users override via ``opts.ewald_omega``. _ewald_tol = getattr(opts, "ewald_tolerance", 1e-12) _cutoff = getattr(opts, "ewald_cutoff_bohr", lat_opts.nuclear_cutoff_bohr) if slab_mode: if omega <= 0.0: omega = float(getattr(lat_opts, "slab_ewald_alpha", 0.4)) if omega <= 0.0: omega = 0.4 lat_opts.slab_ewald_alpha = float(omega) elif omega <= 0.0: _user_omega = getattr(opts, "ewald_omega", None) if _user_omega is not None and float(_user_omega) > 0.0: omega = float(_user_omega) else: from .bipole_ext_el_pole import crystal_default_ewald_alpha V_cell = float(abs(np.linalg.det(np.asarray(system.lattice, dtype=float)))) omega = crystal_default_ewald_alpha(V_cell) lat = np.asarray(system.lattice, dtype=float) if slab_mode: grid_shape_t = (0, 0, 0) elif grid_shape is None: grid_shape_t = auto_grid(lat, spacing_bohr) elif isinstance(grid_shape, int): grid_shape_t = (grid_shape, grid_shape, grid_shape) else: grid_shape_t = tuple(int(x) for x in grid_shape) if slab_mode: plog.info( f"UKS multi-k SLAB_EWALD_2D / functional={opts.functional!r}, " f"alpha = {float(omega):.3f}" ) else: plog.info( f"UKS multi-k EWALD_3D / functional={opts.functional!r}, " f"omega = {float(omega):.3f}, " f"FFT grid {grid_shape_t[0]}x{grid_shape_t[1]}x{grid_shape_t[2]}" ) plog.info(f"basis: {basis.name} ({basis.nbasis} BFs / {basis.nshells} shells)") from .options_dump import dump_active_settings dump_active_settings( plog, [ ("PeriodicKSOptions", opts), ("LatticeSumOptions", lat_opts), ( "Driver kwargs", { "omega": float(omega), "grid_shape": grid_shape_t, "origin": origin, "spacing_bohr": float(spacing_bohr), "linear_dep_threshold": float(linear_dep_threshold), "canonical_orth_normalize_diag_first": canonical_orth_normalize_diag_first, "auto_optimize_truncation": auto_optimize_truncation, }, ), ], ) if plog.level >= 5: from .scf_log import format_basis_summary plog.write_raw(format_basis_summary(basis)) n_elec = int(system.n_electrons()) mult = int(system.multiplicity) if mult < 1: raise ValueError( f"run_uks_periodic_multi_k_ewald3d: multiplicity must be >= 1, got {mult}" ) if (n_elec + mult - 1) % 2 != 0 or (n_elec - mult + 1) % 2 != 0: raise ValueError( f"run_uks_periodic_multi_k_ewald3d: (n_electrons={n_elec}, " f"multiplicity={mult}) cannot be split into integer a/b." ) n_alpha = (n_elec + mult - 1) // 2 n_beta = (n_elec - mult + 1) // 2 # ---- Functional + DFT grid ------------------------------------------ func = Functional(opts.functional, 2) # spin-polarized # CAM exchange assembly (screened hybrids like hse06 ride the erfc # arm; LR-heavy RSH fails closed). omega_screen is unrelated to # this driver's ``omega`` (the Ewald split alpha). exx = resolve_periodic_exchange( func, where="run_uks_periodic_multi_k_ewald3d" ) if opts.use_periodic_becke: grid = build_periodic_becke_grid( system, grid_options=opts.grid, image_radius_bohr=float(opts.becke_image_radius_bohr), ) else: grid = build_grid(system.unit_cell_molecule(), opts.grid) k_points = list(kmesh.kpoints) weights = np.asarray(kmesh.weights, dtype=float) n_k = len(k_points) if n_k == 0: raise ValueError("kmesh has no k-points") if not np.isclose(weights.sum(), 1.0): raise ValueError(f"kmesh.weights must sum to 1; got {weights.sum():.6f}") plog.info( f"k-mesh: {n_k} k-point{'s' if n_k != 1 else ''}, " f"weights sum = {weights.sum():.4f}; " f"n_alpha = {n_alpha}, n_beta = {n_beta}" ) # ---- Auto-optimise lattice truncation (default ON) ------------------- if auto_optimize_truncation and lat_opts.coulomb_method == CoulombMethod.EWALD_3D: from .eigs_preflight import ( format_truncation_optimization_report, optimize_truncation, ) k_arr = [np.asarray(k, dtype=float) for k in k_points] opt_rep = optimize_truncation( system, basis, lattice_opts=lat_opts, k_points_cart=k_arr, ) if ( opt_rep.n_evaluations > 1 or opt_rep.optimized_lattice_opts.cutoff_bohr != lat_opts.cutoff_bohr ): plog.write_raw(format_truncation_optimization_report(opt_rep)) if not opt_rep.converged: plog.warn("auto_optimize_truncation did not converge.") lat_opts = opt_rep.optimized_lattice_opts with plog.stage( "integrals_lattice", detail=f"S/T/V at cutoff {lat_opts.cutoff_bohr:.2f} bohr" ): S_lat = compute_overlap_lattice(basis, system, lat_opts) T_lat = compute_kinetic_lattice(basis, system, lat_opts) if slab_mode: from .periodic_v_ne_slab import build_v_ne_slab_ewald_2d_k_cache slab_vne_cache = build_v_ne_slab_ewald_2d_k_cache( basis, system, lat_opts, alpha=float(omega), ) V_lat = None else: from .periodic_v_ne import compute_nuclear_lattice_dispatch V_lat = compute_nuclear_lattice_dispatch(basis, system, lat_opts) cells = list(S_lat.cells) n_cells = len(cells) S_k_list: List[np.ndarray] = [] Hcore_k_list: List[np.ndarray] = [] X_k_list: List[np.ndarray] = [] # Per-k linear-dependence preflight; see periodic_rhf_multi_k_ewald # for the rationale (Searle et al., ARCHER eCSE04-16, 2017). from .linear_dependence import scf_preflight_overlap_check for k_idx, k in enumerate(k_points): k_arr = np.asarray(k, dtype=float).reshape(3) S_k = np.asarray(bloch_sum(S_lat, k_arr)) T_k = np.asarray(bloch_sum(T_lat, k_arr)) if slab_mode: from .periodic_v_ne_slab import compute_v_ne_slab_ewald_2d_k_matrix V_k = compute_v_ne_slab_ewald_2d_k_matrix( basis, system, lat_opts, k_arr, alpha=float(omega), cache=slab_vne_cache, ) else: V_k = np.asarray(bloch_sum(V_lat, k_arr)) H_k = T_k + V_k S_k = 0.5 * (S_k + S_k.conj().T) H_k = 0.5 * (H_k + H_k.conj().T) scf_preflight_overlap_check( S_k, plog=plog, label=f"S(k={k_idx}, k_cart={k_arr.round(4).tolist()})", basis=basis, ) X_k, n_kept = _canonical_orthogonalizer_complex( S_k, linear_dep_threshold, normalize_diag_first=canonical_orth_normalize_diag_first, ) if max(n_alpha, n_beta) > n_kept: raise RuntimeError( f"run_uks_periodic_multi_k_ewald3d: orth dropped too many " f"directions (n_a={n_alpha}, n_b={n_beta}, " f"n_kept={n_kept}) at k = {k_arr}" ) S_k_list.append(S_k) Hcore_k_list.append(H_k) X_k_list.append(X_k) # T_lat / V_lat are folded into Hcore(k) in the per-k loop above and are # unused below; free the per-cell one-electron lattice integrals before # the SCF iterations (S_lat is still needed for its g0 block). del T_lat, V_lat e_nuc = float(nuclear_repulsion_per_cell(system, lat_opts)) # ---- Initial guess -------------------------------------------------- C_alpha_per_k: List[np.ndarray] = [] eps_alpha_per_k: List[np.ndarray] = [] C_beta_per_k: List[np.ndarray] = [] eps_beta_per_k: List[np.ndarray] = [] for H_k, X_k in zip(Hcore_k_list, X_k_list): C_a, eps_a = _diag_in_orth_basis(H_k, X_k) C_b, eps_b = _diag_in_orth_basis(H_k, X_k) C_alpha_per_k.append(C_a.astype(complex)) eps_alpha_per_k.append(eps_a) C_beta_per_k.append(C_b.astype(complex)) eps_beta_per_k.append(eps_b) def _integer_occupations(nbf: int, n_occ_each: int) -> List[np.ndarray]: occ_per_k = [] for _ in range(n_k): occ = np.zeros(nbf, dtype=float) occ[:n_occ_each] = 1.0 occ_per_k.append(occ) return occ_per_k def _occupations_per_spin( eps_spin_per_k: Sequence[np.ndarray], n_spin: int, ) -> Tuple[List[np.ndarray], float, float]: """Per-spin fractional occupations via Fermi-Dirac (mirrors the BIPOLE UKS driver): the closed-shell FD helper targets 2.n_spin electrons and returns occupations in [0, 2]; halving gives the single-spin occupations in [0, 1] at the same per-spin chemical potential, and the entropy halves with them. Returns (occ_per_k, mu_spin, entropy_spin).""" nbf = eps_spin_per_k[0].shape[0] if eps_spin_per_k else 0 if use_gilat and n_spin > 0: # Gilat-Raubenheimer net for this spin channel (g=1.0, n_spin # electrons; sharp Fermi surface -> entropy 0). Handles full or # IBZ meshes via the shared auto-dispatch entry point. from .bz_integration import gilat_occupations_for_kmesh occ_gr, ef_gr = gilat_occupations_for_kmesh( system, kmesh, eps_spin_per_k, float(n_spin), spin_degeneracy=1.0 ) return occ_gr, float(ef_gr), 0.0 if smearing_T <= 0.0 or n_spin == 0: return _integer_occupations(nbf, n_spin), 0.0, 0.0 occ_double, mu, entropy_double = _fermi_dirac_occupations_per_k( eps_spin_per_k, weights, float(2 * n_spin), smearing_T, ) occ = [np.asarray(o, dtype=float) * 0.5 for o in occ_double] return occ, float(mu), float(entropy_double) * 0.5 def _spin_density(C_per_k_local, occ_per_k_local): """One-particle (no factor 2) real-space spin density via the C++ fractional-occupation builder. Mirrors the UHF multi-k Ewald driver convention.""" return real_space_density_from_kpoints_fractional( C_per_k_local, occ_per_k_local, kmesh, cells, ) occ_alpha_per_k, mu_alpha, entropy_alpha = _occupations_per_spin( eps_alpha_per_k, n_alpha ) occ_beta_per_k, mu_beta, entropy_beta = _occupations_per_spin( eps_beta_per_k, n_beta ) entropy = entropy_alpha + entropy_beta D_alpha_real = _spin_density(C_alpha_per_k, occ_alpha_per_k) D_beta_real = _spin_density(C_beta_per_k, occ_beta_per_k) # Density-mode guesses: overwrite per-spin densities at g=0 with # the engine output (proportional spin split -- matches molecular # UHF behaviour). Closed-shell-like cases (n_a == n_b) reduce to # the even split that this driver previously used inline. guess = getattr(opts, "initial_guess", InitialGuess.HCORE) seed_guess = InitialGuess.SAD if guess == InitialGuess.PATOM else guess split = initial_densities_open_shell( system.unit_cell_molecule(), basis, n_alpha, n_beta, seed_guess, is_periodic=True, periodic_system=system, lattice_opts=lat_opts, # ATOMSPIN: per-atom +1/-1/0 seed -> broken-symmetry g=0 density # (Bloch-sums to a broken-symmetry D(k)). Empty/None = symmetric. atomic_spins=getattr(opts, "atomic_spins", None) or None, ) if split is not None: plog.info(f"initial guess: {guess.name} (spin-split density via GuessEngine)") D_a_sad, D_b_sad = split zero_block = np.zeros_like(D_a_sad, dtype=float) for g_idx in range(len(D_alpha_real.cells)): is_g0 = (D_alpha_real.cells[g_idx].index == np.array([0, 0, 0])).all() D_alpha_real.set_block(g_idx, D_a_sad if is_g0 else zero_block) D_beta_real.set_block(g_idx, D_b_sad if is_g0 else zero_block) else: plog.info( f"initial guess: {guess.name} " "(Hcore-diagonalise at each k, spin-degenerate)" ) # Cache the iteration-invariant per-cell Hartree-J machinery once. PATOM # consumes the same cache for its one HF-like in-field step before SCF. if slab_mode: j_cache = make_slab_ewald_2d_lattice_j_cache( basis, system, D_alpha_real.cells, lattice_opts=lat_opts, alpha=float(omega), ) else: j_cache = make_ewald_3d_lattice_j_cache( basis, system, D_alpha_real.cells, lattice_opts=lat_opts, ) if guess == InitialGuess.PATOM: plog.info("initial guess: PATOM (SAD + one periodic in-field step)") F_alpha_blocks, F_beta_blocks = _build_uks_fock_2e_blocks_ewald3d( basis, system, D_alpha_real, D_beta_real, omega, # PATOM seed uses one full-HF in-field step regardless of # the functional (same convention as the Γ driver). PeriodicExchangeAssembly(1.0, 0.0, 0.0), lat_opts, grid_shape_t, origin, spacing_bohr, j_cache=j_cache, ) C_alpha_per_k = [] eps_alpha_per_k = [] C_beta_per_k = [] eps_beta_per_k = [] for k_idx, k_cart in enumerate(k_points): F_a = _bloch_sum_blocks(F_alpha_blocks, cells, np.asarray(k_cart)) F_b = _bloch_sum_blocks(F_beta_blocks, cells, np.asarray(k_cart)) C_a, eps_a = _diag_in_orth_basis( F_a + Hcore_k_list[k_idx], X_k_list[k_idx], ) C_b, eps_b = _diag_in_orth_basis( F_b + Hcore_k_list[k_idx], X_k_list[k_idx], ) C_alpha_per_k.append(C_a) eps_alpha_per_k.append(eps_a) C_beta_per_k.append(C_b) eps_beta_per_k.append(eps_b) occ_alpha_per_k, mu_alpha, entropy_alpha = _occupations_per_spin( eps_alpha_per_k, n_alpha ) occ_beta_per_k, mu_beta, entropy_beta = _occupations_per_spin( eps_beta_per_k, n_beta ) entropy = entropy_alpha + entropy_beta D_alpha_real = _spin_density(C_alpha_per_k, occ_alpha_per_k) D_beta_real = _spin_density(C_beta_per_k, occ_beta_per_k) D_alpha_prev: Optional[LatticeMatrixSet] = None D_beta_prev: Optional[LatticeMatrixSet] = None damping = float(opts.damping) if not (0.0 <= damping < 1.0): raise ValueError( f"run_uks_periodic_multi_k_ewald3d: damping must be in " f"[0, 1); got {damping}" ) use_diis = bool(opts.use_diis) diis_start_iter = int(opts.diis_start_iter) # Single spin-coupled Pulay history over the concatenated a + b # per-k block lists (one coefficient set extrapolates both spins; # see the _AcceleratorState note in periodic_scf_accelerators.py). diis = ( _MultiKPulayDIIS(max_subspace=int(opts.diis_subspace_size)) if use_diis else None ) level_shift = float(getattr(opts, "level_shift", 0.0)) # SPINLOCK PATTERN_HOLD (open-shell magnetic convergence): hold the seeded # broken-symmetry occupied subspace per-k per-spin by maximum overlap (MOM) # with the previous cycle for the first ``spinlock_iterations`` cycles, then # release to aufbau -- protecting an ATOMSPIN seed from collapsing to the # symmetric solution on the multi-k path. Aufbau-mode only; skipped under # fractional smearing. (SPIN_SCHEDULE is handled as a two-phase run by # run_periodic_job, which restarts the released phase from the locked one.) spinlock_mode = getattr(opts, "spinlock_mode", SpinlockMode.OFF) spinlock_iterations = int(getattr(opts, "spinlock_iterations", 0)) _pattern_hold = ( spinlock_mode == SpinlockMode.PATTERN_HOLD and spinlock_iterations > 0 and smearing_T == 0.0 ) # Previous-cycle occupied MOs per k per spin, for the MOM hold. C_alpha_occ_prev: List[Optional[np.ndarray]] = [None] * n_k C_beta_occ_prev: List[Optional[np.ndarray]] = [None] * n_k # Phase C1c -- quadratic SCF fallback (per-spin per-k Newton step). quadratic_fallback_iter = int(getattr(opts, "quadratic_fallback_iter", 0)) quadratic_fallback_shift = float(getattr(opts, "quadratic_fallback_shift", 0.1)) quadratic_fallback_max_step = float( getattr(opts, "quadratic_fallback_max_step", 0.1) ) # ---- SCF loop ------------------------------------------------------- scf_trace: List[SCFIteration] = [] E_prev = 0.0 F_alpha_k_list: List[np.ndarray] = [np.zeros_like(H) for H in Hcore_k_list] F_beta_k_list: List[np.ndarray] = [np.zeros_like(H) for H in Hcore_k_list] F_HF_alpha_k_list: List[np.ndarray] = list(F_alpha_k_list) F_HF_beta_k_list: List[np.ndarray] = list(F_beta_k_list) E_xc = 0.0 E_coulomb_per_cell = 0.0 E_hf_K_per_cell = 0.0 scf_label = "SLAB_EWALD_2D" if slab_mode else "EWALD_3D" plog.banner(f"SCF (UKS multi-k {opts.functional!r}, {scf_label})") plog.info(" iter energy (Ha) dE ||[F,DS]|| DIIS") converged = False iter_idx = 0 for iter_idx in range(1, int(opts.max_iter) + 1): # SPINLOCK PATTERN_HOLD: DIIS is suspended (no history recorded, no # extrapolation, damping stays live) while the hold is active. Fock # extrapolation across held-window iterates steers the SCF toward the # symmetric attractor by continuous orbital rotation -- a collapse the # occupation-selecting MOM hold cannot see -- and poisons the # post-release history with out-of-basin iterates. The history starts # fresh at release. hold_active = _pattern_hold and iter_idx <= spinlock_iterations diis_active = use_diis and iter_idx >= diis_start_iter and not hold_active if iter_idx > 1 and damping > 0.0 and not diis_active: D_alpha_used = _damp_lattice_matrix( D_alpha_real, D_alpha_prev, damping, ) D_beta_used = _damp_lattice_matrix( D_beta_real, D_beta_prev, damping, ) else: D_alpha_used = D_alpha_real D_beta_used = D_beta_real # Per-spin 2e Fock blocks F^{2e,s}(g) = J(D_total) - K_HF(D_s). F_HF_alpha_blocks, F_HF_beta_blocks = _build_uks_fock_2e_blocks_ewald3d( basis, system, D_alpha_used, D_beta_used, omega, exx, lat_opts, grid_shape_t, origin, spacing_bohr, j_cache=j_cache, ) # Periodic UKS XC: V_xc^s(g) lattice + scalar E_xc. xc = build_xc_periodic_uks( basis, system, grid, func, D_alpha_used, D_beta_used, lat_opts, ) E_xc = float(xc.e_xc) # Bloch-sum F^{2e,s}(g) and V_xc^s(g) at every k, add Hcore(k). F_alpha_k_list = [] F_beta_k_list = [] F_HF_alpha_k_list = [] F_HF_beta_k_list = [] for k_idx, k_cart in enumerate(k_points): k_arr = np.asarray(k_cart) F_HF_a_k = _bloch_sum_blocks(F_HF_alpha_blocks, cells, k_arr) F_HF_b_k = _bloch_sum_blocks(F_HF_beta_blocks, cells, k_arr) V_xc_a_k = _bloch_sum_lms_at_k(xc.V_alpha, k_arr) V_xc_b_k = _bloch_sum_lms_at_k(xc.V_beta, k_arr) F_a = Hcore_k_list[k_idx] + F_HF_a_k + V_xc_a_k F_b = Hcore_k_list[k_idx] + F_HF_b_k + V_xc_b_k F_a = 0.5 * (F_a + F_a.conj().T) F_b = 0.5 * (F_b + F_b.conj().T) F_alpha_k_list.append(F_a) F_beta_k_list.append(F_b) F_HF_alpha_k_list.append(F_HF_a_k) F_HF_beta_k_list.append(F_HF_b_k) # Energy + per-k errors. # E_elec = E_xc + S_k w_k [1/2 Re tr((D_a + D_b).H_k) # + 1/2 Re tr(D_a(k).F_HF_a(k)) # + 1/2 Re tr(D_b(k).F_HF_b(k))] E_core_trace = 0.0 E_HF_alpha_trace = 0.0 E_HF_beta_trace = 0.0 grad_norm_sum = 0.0 error_alpha_k_list: List[np.ndarray] = [] error_beta_k_list: List[np.ndarray] = [] for idx in range(n_k): C_a = C_alpha_per_k[idx] C_b = C_beta_per_k[idx] if use_fractional_density: D_a_k = (C_a * occ_alpha_per_k[idx]) @ C_a.conj().T D_b_k = (C_b * occ_beta_per_k[idx]) @ C_b.conj().T else: C_a_occ = C_a[:, :n_alpha] if n_alpha > 0 else C_a[:, :0] C_b_occ = C_b[:, :n_beta] if n_beta > 0 else C_b[:, :0] D_a_k = C_a_occ @ C_a_occ.conj().T D_b_k = C_b_occ @ C_b_occ.conj().T H_k = Hcore_k_list[idx] F_a_k = F_alpha_k_list[idx] F_b_k = F_beta_k_list[idx] F_HF_a_k = F_HF_alpha_k_list[idx] F_HF_b_k = F_HF_beta_k_list[idx] w = float(weights[idx]) # NOTE: prefactor is 1.0 (not 1/2) because the per-spin # contribution below uses F_HF_s (Hartree + scaled-K only, # no Hcore). Compare the multi-k UHF Ewald driver, which # uses 1/2 on Hcore *and* uses the full F (Hcore included) # inside the per-spin terms -- equivalent total. E_core_trace += w * np.real(np.trace((D_a_k + D_b_k) @ H_k)) E_HF_alpha_trace += w * 0.5 * np.real(np.trace(D_a_k @ F_HF_a_k)) E_HF_beta_trace += w * 0.5 * np.real(np.trace(D_b_k @ F_HF_b_k)) S_k = S_k_list[idx] FDS_a = F_a_k @ D_a_k @ S_k FDS_b = F_b_k @ D_b_k @ S_k err_a = FDS_a - FDS_a.conj().T err_b = FDS_b - FDS_b.conj().T error_alpha_k_list.append(err_a) error_beta_k_list.append(err_b) grad_norm_sum += w * float( np.sqrt(np.linalg.norm(err_a) ** 2 + np.linalg.norm(err_b) ** 2) ) E_elec = ( E_xc + float(E_core_trace) + float(E_HF_alpha_trace) + float(E_HF_beta_trace) ) # Madelung-leak correction (v0.6.1). For UKS, total density # is D_a + D_b at the unit cell. _D_g0 = np.asarray(_g0_block(D_alpha_real)) + np.asarray(_g0_block(D_beta_real)) _S_g0 = np.asarray(_g0_block(S_lat)) E_madelung_fix = ( 0.0 if slab_mode else _madelung_energy_correction_for_lat(_D_g0, _S_g0, system, lat_opts) ) E_total = E_elec + e_nuc + E_madelung_fix # Free-energy formulation: with smearing the variational # quantity is A = E - T*S (per-spin entropies summed); dE and # the convergence check run on A so fractional occupations # can't oscillate the bare energy below the tolerance. free_energy = E_total - smearing_T * entropy dE = free_energy - E_prev # Divergence detection (v0.6.2). check_scf_divergence( "run_uks_periodic_multi_k_ewald3d", iter_idx, E_total, grad_norm_sum, dE, ) diis_sub = 0 if diis is not None: diis_sub = max(diis_sub, diis.subspace_size) scf_trace.append( SCFIteration( iter=iter_idx, energy=float(E_total), delta_e=float(dE if iter_idx > 1 else 0.0), grad_norm=float(grad_norm_sum), diis_subspace=diis_sub, ) ) plog.iteration( iter_idx, energy=float(E_total), dE=float(dE if iter_idx > 1 else 0.0), grad=float(grad_norm_sum), diis=diis_sub, ) converged = ( iter_idx > 1 and abs(dE) < float(opts.conv_tol_energy) and grad_norm_sum < float(opts.conv_tol_grad) ) # Phase C1c gate. in_quadratic_phase = ( quadratic_fallback_iter > 0 and iter_idx > quadratic_fallback_iter ) new_C_alpha: List[np.ndarray] = [] new_eps_alpha: List[np.ndarray] = [] new_C_beta: List[np.ndarray] = [] new_eps_beta: List[np.ndarray] = [] if in_quadratic_phase: from .quadratic_scf import quadratic_step for idx in range(n_k): C_a, eps_a = quadratic_step( F_alpha_k_list[idx], C_alpha_per_k[idx], eps_alpha_per_k[idx], n_alpha, shift=quadratic_fallback_shift, max_step=quadratic_fallback_max_step, ) C_b, eps_b = quadratic_step( F_beta_k_list[idx], C_beta_per_k[idx], eps_beta_per_k[idx], n_beta, shift=quadratic_fallback_shift, max_step=quadratic_fallback_max_step, ) new_C_alpha.append(C_a) new_eps_alpha.append(eps_a) new_C_beta.append(C_b) new_eps_beta.append(eps_b) else: # Spin-coupled DIIS extrapolation: one history over the # concatenated a + b per-k block lists with duplicated # k-weights, one coefficient set applied to both spins. # Skipped entirely (not even recorded) while the PATTERN_HOLD # window is active; see the hold_active note at the loop head. if diis is not None and not hold_active: F_ex = diis.extrapolate( list(F_alpha_k_list) + list(F_beta_k_list), list(error_alpha_k_list) + list(error_beta_k_list), list(weights) + list(weights), ) if diis_active: F_alpha_k_list = F_ex[:n_k] F_beta_k_list = F_ex[n_k:] # Saunders-Hillier level shift per spin per k, through the shared # Hermitian operator. D_a_k / D_b_k are *spin* densities built # from the occupied MOs, so they are idempotent in the S(k) metric # and the weight is 1, not the closed-shell ½. Guarded so the per-k # projectors are not even built on an unshifted cycle. if level_shift != 0.0: for idx in range(n_k): S_k = S_k_list[idx] C_a = C_alpha_per_k[idx] C_b = C_beta_per_k[idx] C_a_occ = C_a[:, :n_alpha] if n_alpha > 0 else C_a[:, :0] C_b_occ = C_b[:, :n_beta] if n_beta > 0 else C_b[:, :0] D_a_k = C_a_occ @ C_a_occ.conj().T D_b_k = C_b_occ @ C_b_occ.conj().T F_alpha_k_list[idx] = apply_level_shift_k( F_alpha_k_list[idx], S_k, D_a_k, level_shift, LevelShiftDensity.SPIN) F_beta_k_list[idx] = apply_level_shift_k( F_beta_k_list[idx], S_k, D_b_k, level_shift, LevelShiftDensity.SPIN) # Diagonalize per spin per k. for idx in range(n_k): C_a, eps_a = _diag_in_orth_basis( F_alpha_k_list[idx], X_k_list[idx], ) C_b, eps_b = _diag_in_orth_basis( F_beta_k_list[idx], X_k_list[idx], ) new_C_alpha.append(C_a) new_eps_alpha.append(eps_a) new_C_beta.append(C_b) new_eps_beta.append(eps_b) # SPINLOCK PATTERN_HOLD: for cycles 2..spinlock_iterations, reorder the # freshly diagonalised MOs per k per spin so the occupied subspace most # overlapping the previous cycle's occupied set comes first (MOM); the # column-order aufbau fill below then picks up the held broken-symmetry # pattern instead of pure-aufbau, protecting an ATOMSPIN seed. iter 1 # sets the pattern by aufbau (no previous MOs yet). if _pattern_hold and 1 < iter_idx <= spinlock_iterations: for idx in range(n_k): if n_alpha > 0 and C_alpha_occ_prev[idx] is not None: new_C_alpha[idx], new_eps_alpha[idx] = _mom_reorder( new_C_alpha[idx], new_eps_alpha[idx], S_k_list[idx], C_alpha_occ_prev[idx], n_alpha) if n_beta > 0 and C_beta_occ_prev[idx] is not None: new_C_beta[idx], new_eps_beta[idx] = _mom_reorder( new_C_beta[idx], new_eps_beta[idx], S_k_list[idx], C_beta_occ_prev[idx], n_beta) # Record this cycle's occupied MOs for the next cycle's MOM hold. if _pattern_hold and iter_idx <= spinlock_iterations: for idx in range(n_k): C_alpha_occ_prev[idx] = ( new_C_alpha[idx][:, :n_alpha].copy() if n_alpha > 0 else None) C_beta_occ_prev[idx] = ( new_C_beta[idx][:, :n_beta].copy() if n_beta > 0 else None) C_alpha_per_k = new_C_alpha eps_alpha_per_k = new_eps_alpha C_beta_per_k = new_C_beta eps_beta_per_k = new_eps_beta occ_alpha_per_k, mu_alpha, entropy_alpha = _occupations_per_spin( eps_alpha_per_k, n_alpha ) occ_beta_per_k, mu_beta, entropy_beta = _occupations_per_spin( eps_beta_per_k, n_beta ) entropy = entropy_alpha + entropy_beta D_alpha_new = _spin_density(C_alpha_per_k, occ_alpha_per_k) D_beta_new = _spin_density(C_beta_per_k, occ_beta_per_k) D_alpha_prev = D_alpha_used D_beta_prev = D_beta_used D_alpha_real = D_alpha_new D_beta_real = D_beta_new E_prev = free_energy if converged: break # ---- Final pass on converged D's ------------------------------------ if converged: F_HF_alpha_blocks, F_HF_beta_blocks = _build_uks_fock_2e_blocks_ewald3d( basis, system, D_alpha_real, D_beta_real, omega, exx, lat_opts, grid_shape_t, origin, spacing_bohr, j_cache=j_cache, ) # J-only per-spin pair for reporting. if exx.needs_exchange: J_only_alpha_blocks, J_only_beta_blocks = _build_uks_fock_2e_blocks_ewald3d( basis, system, D_alpha_real, D_beta_real, omega, None, lat_opts, grid_shape_t, origin, spacing_bohr, j_cache=j_cache, ) else: J_only_alpha_blocks = F_HF_alpha_blocks J_only_beta_blocks = F_HF_beta_blocks xc = build_xc_periodic_uks( basis, system, grid, func, D_alpha_real, D_beta_real, lat_opts, ) E_xc = float(xc.e_xc) F_alpha_k_list = [] F_beta_k_list = [] F_HF_alpha_k_list = [] F_HF_beta_k_list = [] J_only_alpha_k_list: List[np.ndarray] = [] J_only_beta_k_list: List[np.ndarray] = [] for k_idx, k_cart in enumerate(k_points): k_arr = np.asarray(k_cart) F_HF_a_k = _bloch_sum_blocks(F_HF_alpha_blocks, cells, k_arr) F_HF_b_k = _bloch_sum_blocks(F_HF_beta_blocks, cells, k_arr) V_xc_a_k = _bloch_sum_lms_at_k(xc.V_alpha, k_arr) V_xc_b_k = _bloch_sum_lms_at_k(xc.V_beta, k_arr) F_alpha_k_list.append( 0.5 * ( (Hcore_k_list[k_idx] + F_HF_a_k + V_xc_a_k) + (Hcore_k_list[k_idx] + F_HF_a_k + V_xc_a_k).conj().T ) ) F_beta_k_list.append( 0.5 * ( (Hcore_k_list[k_idx] + F_HF_b_k + V_xc_b_k) + (Hcore_k_list[k_idx] + F_HF_b_k + V_xc_b_k).conj().T ) ) F_HF_alpha_k_list.append(F_HF_a_k) F_HF_beta_k_list.append(F_HF_b_k) J_only_alpha_k_list.append( _bloch_sum_blocks(J_only_alpha_blocks, cells, k_arr) ) J_only_beta_k_list.append( _bloch_sum_blocks(J_only_beta_blocks, cells, k_arr) ) final_C_alpha: List[np.ndarray] = [] final_C_beta: List[np.ndarray] = [] final_eps_alpha: List[np.ndarray] = [] final_eps_beta: List[np.ndarray] = [] E_core_trace = 0.0 E_HF_alpha_trace = 0.0 E_HF_beta_trace = 0.0 E_J_alpha_trace = 0.0 E_J_beta_trace = 0.0 for idx in range(n_k): C_a, eps_a = _diag_in_orth_basis( F_alpha_k_list[idx], X_k_list[idx], ) C_b, eps_b = _diag_in_orth_basis( F_beta_k_list[idx], X_k_list[idx], ) # If the SCF converged while the PATTERN_HOLD window was still # active, the converged state is the MOM-held occupied set, which # need not be aufbau in its own Fock. Re-select by max overlap # with the held pattern so the reported energy / <S^2> / MOs # describe the state the SCF actually converged to (an aufbau # slice here would silently swap to a different state). if _pattern_hold and iter_idx <= spinlock_iterations: if n_alpha > 0 and C_alpha_occ_prev[idx] is not None: C_a, eps_a = _mom_reorder( C_a, eps_a, S_k_list[idx], C_alpha_occ_prev[idx], n_alpha) if n_beta > 0 and C_beta_occ_prev[idx] is not None: C_b, eps_b = _mom_reorder( C_b, eps_b, S_k_list[idx], C_beta_occ_prev[idx], n_beta) final_C_alpha.append(C_a) final_C_beta.append(C_b) final_eps_alpha.append(eps_a) final_eps_beta.append(eps_b) C_a_occ = C_a[:, :n_alpha] if n_alpha > 0 else C_a[:, :0] C_b_occ = C_b[:, :n_beta] if n_beta > 0 else C_b[:, :0] D_a_k = C_a_occ @ C_a_occ.conj().T D_b_k = C_b_occ @ C_b_occ.conj().T w = float(weights[idx]) E_core_trace += w * np.real(np.trace((D_a_k + D_b_k) @ Hcore_k_list[idx])) E_HF_alpha_trace += ( w * 0.5 * np.real(np.trace(D_a_k @ F_HF_alpha_k_list[idx])) ) E_HF_beta_trace += ( w * 0.5 * np.real(np.trace(D_b_k @ F_HF_beta_k_list[idx])) ) E_J_alpha_trace += ( w * 0.5 * np.real(np.trace(D_a_k @ J_only_alpha_k_list[idx])) ) E_J_beta_trace += ( w * 0.5 * np.real(np.trace(D_b_k @ J_only_beta_k_list[idx])) ) C_alpha_per_k = final_C_alpha C_beta_per_k = final_C_beta eps_alpha_per_k = final_eps_alpha eps_beta_per_k = final_eps_beta E_elec = ( E_xc + float(E_core_trace) + float(E_HF_alpha_trace) + float(E_HF_beta_trace) ) # Madelung-leak correction (v0.6.1). _D_g0_f = np.asarray(_g0_block(D_alpha_real)) + np.asarray( _g0_block(D_beta_real) ) _S_g0_f = np.asarray(_g0_block(S_lat)) E_madelung_fix = ( 0.0 if slab_mode else _madelung_energy_correction_for_lat(_D_g0_f, _S_g0_f, system, lat_opts) ) E_total = float(E_elec) + e_nuc + E_madelung_fix E_coulomb_per_cell = float(E_J_alpha_trace + E_J_beta_trace) # tr(D.F_HF) = tr(D.J) - a.tr(D.K) (with the 1/2 prefactor inside # E_HF_*_trace), so HF_total - J_total = -a . 1/2 tr(D.K). E_hf_K_per_cell = float( (E_HF_alpha_trace - E_J_alpha_trace) + (E_HF_beta_trace - E_J_beta_trace) ) # <S^2> from the Γ-block (or first) k-point -- same shortcut as # multi-k UHF Ewald. if n_alpha == 0 or n_beta == 0: s2 = 0.25 * (n_alpha - n_beta) * (n_alpha - n_beta + 2) + n_beta else: k0_idx = 0 for i, k in enumerate(k_points): if np.allclose(np.asarray(k), 0.0): k0_idx = i break S_real = np.real(S_k_list[k0_idx]) s2 = _spin_squared( n_alpha, n_beta, np.real(C_alpha_per_k[k0_idx]), np.real(C_beta_per_k[k0_idx]), S_real, ) plog.converged(n_iter=iter_idx, energy=E_total, converged=converged) return PeriodicUKSMultiKEwaldResult( energy=E_total, e_electronic=float(E_elec), e_nuclear=e_nuc, e_xc=float(E_xc), e_coulomb=float(E_coulomb_per_cell), e_hf_exchange=float(E_hf_K_per_cell), n_iter=iter_idx, converged=converged, s_squared=float(s2), s_squared_ideal=0.25 * (mult - 1) * (mult + 1), mo_energies_alpha=eps_alpha_per_k, mo_coeffs_alpha=C_alpha_per_k, fock_alpha=F_alpha_k_list, density_alpha=D_alpha_real, mo_energies_beta=eps_beta_per_k, mo_coeffs_beta=C_beta_per_k, fock_beta=F_beta_k_list, density_beta=D_beta_real, overlap=S_k_list, hcore=Hcore_k_list, functional=str(opts.functional), scf_trace=scf_trace, omega=float(omega), grid_shape=grid_shape_t, smearing_temperature=float(smearing_T), fermi_level_alpha=float(mu_alpha), fermi_level_beta=float(mu_beta), entropy=float(entropy), free_energy=float(E_total - smearing_T * entropy), )