Restricted Brueckner-orbital coupled cluster.

ebcc.opt.rbrueckner.BruecknerREBCC(cc, options=None, **kwargs)

Bases: BaseBruecknerEBCC

Restricted Brueckner-orbital coupled cluster.

Initialise the Brueckner EBCC object.

Parameters:
  • cc (BaseEBCC) –

    Parent EBCC object.

  • options (Optional[BaseOptions], default: None ) –

    Options for the EOM calculation.

  • **kwargs (Any, default: {} ) –

    Additional keyword arguments used to update options.
Source code in ebcc/opt/base.py 
def __init__(
    self,
    cc: BaseEBCC,
    options: Optional[BaseOptions] = None,
    **kwargs: Any,
) -> None:
    r"""Initialise the Brueckner EBCC object.

    Args:
        cc: Parent `EBCC` object.
        options: Options for the EOM calculation.
        **kwargs: Additional keyword arguments used to update `options`.
    """
    # Options:
    if options is None:
        options = self.Options()
    self.options = options
    for key, val in kwargs.items():
        setattr(self.options, key, val)

    # Parameters:
    self.cc = cc
    self.mf = cc.mf
    self.space = cc.space
    self.log = cc.log

    # Attributes:
    self.converged = False

    # Logging:
    init_logging(cc.log)
    cc.log.info(f"\n{ANSI.B}{ANSI.U}{self.name}{ANSI.R}")
    cc.log.debug(f"{ANSI.B}{'*' * len(self.name)}{ANSI.R}")
    cc.log.debug("")
    cc.log.info(f"{ANSI.B}Options{ANSI.R}:")
    cc.log.info(f" > e_tol:  {ANSI.y}{self.options.e_tol}{ANSI.R}")
    cc.log.info(f" > t_tol:  {ANSI.y}{self.options.t_tol}{ANSI.R}")
    cc.log.info(f" > max_iter:  {ANSI.y}{self.options.max_iter}{ANSI.R}")
    cc.log.info(f" > diis_space:  {ANSI.y}{self.options.diis_space}{ANSI.R}")
    cc.log.info(f" > diis_min_space:  {ANSI.y}{self.options.diis_min_space}{ANSI.R}")
    cc.log.info(f" > damping:  {ANSI.y}{self.options.damping}{ANSI.R}")
    cc.log.debug("")

ebcc.opt.rbrueckner.BruecknerREBCC.get_rotation_matrix(u_tot=None, damping=None, t1=None)

Update the rotation matrix.

Also returns the total rotation matrix.

Parameters:
  • u_tot (Optional[SpinArrayType], default: None ) –

    Total rotation matrix.

  • damping (Optional[BaseDamping], default: None ) –

    Damping object.

  • t1 (Optional[SpinArrayType], default: None ) –

    T1 amplitude.
Returns:
  • tuple[SpinArrayType, SpinArrayType] –

    Rotation matrix and total rotation matrix.
Source code in ebcc/opt/rbrueckner.py 
def get_rotation_matrix(
    self,
    u_tot: Optional[SpinArrayType] = None,
    damping: Optional[BaseDamping] = None,
    t1: Optional[SpinArrayType] = None,
) -> tuple[SpinArrayType, SpinArrayType]:
    """Update the rotation matrix.

    Also returns the total rotation matrix.

    Args:
        u_tot: Total rotation matrix.
        damping: Damping object.
        t1: T1 amplitude.

    Returns:
        Rotation matrix and total rotation matrix.
    """
    if t1 is None:
        t1 = self.cc.t1
    if u_tot is None:
        u_tot = np.eye(self.cc.space.ncorr, dtype=types[float])

    zocc = np.zeros((self.cc.space.ncocc, self.cc.space.ncocc))
    zvir = np.zeros((self.cc.space.ncvir, self.cc.space.ncvir))
    t1_block: NDArray[T] = np.block([[zocc, -t1], [np.transpose(t1), zvir]])

    u = scipy.linalg.expm(t1_block)

    u_tot = u_tot @ u
    if np.linalg.det(u_tot) < 0:
        u_tot = _put(u_tot, np.ix_(np.arange(u_tot.shape[0]), np.array([0])), -u_tot[:, 0])

    a: NDArray[T] = np.asarray(np.real(scipy.linalg.logm(u_tot)), dtype=types[float])
    if damping is not None:
        a = damping(a, error=t1)

    u_tot = scipy.linalg.expm(a)

    return u, u_tot

ebcc.opt.rbrueckner.BruecknerREBCC.transform_amplitudes(u, amplitudes=None)

Transform the amplitudes into the Brueckner orbital basis.

Parameters:
  • u (SpinArrayType) –

    Rotation matrix.

  • amplitudes (Optional[Namespace[SpinArrayType]], default: None ) –

    Cluster amplitudes.
Returns:
  • Namespace[SpinArrayType] –

    Transformed cluster amplitudes.
Source code in ebcc/opt/rbrueckner.py 
def transform_amplitudes(
    self, u: SpinArrayType, amplitudes: Optional[Namespace[SpinArrayType]] = None
) -> Namespace[SpinArrayType]:
    """Transform the amplitudes into the Brueckner orbital basis.

    Args:
        u: Rotation matrix.
        amplitudes: Cluster amplitudes.

    Returns:
        Transformed cluster amplitudes.
    """
    if not amplitudes:
        amplitudes = self.cc.amplitudes

    nocc = self.cc.space.ncocc
    ci = u[:nocc, :nocc]
    ca = u[nocc:, nocc:]

    # Transform T amplitudes:
    for name, key, n in self.cc.ansatz.fermionic_cluster_ranks(spin_type=self.spin_type):
        args: list[Union[SpinArrayType, tuple[int, ...]]] = [
            self.cc.amplitudes[name],
            tuple(range(n * 2)),
        ]
        for i in range(n):
            args += [ci, (i, i + n * 2)]
        for i in range(n):
            args += [ca, (i + n, i + n * 3)]
        args += [tuple(range(n * 2, n * 4))]
        self.cc.amplitudes[name] = util.einsum(*args)

    # Transform S amplitudes:
    for name, key, n in self.cc.ansatz.bosonic_cluster_ranks(spin_type=self.spin_type):
        raise util.ModelNotImplemented  # TODO

    # Transform U amplitudes:
    for name, key, nf, nb in self.cc.ansatz.coupling_cluster_ranks(spin_type=self.spin_type):
        raise util.ModelNotImplemented  # TODO

    return self.cc.amplitudes

ebcc.opt.rbrueckner.BruecknerREBCC.get_t1_norm(amplitudes=None)

Get the norm of the T1 amplitude.

Parameters:
  • amplitudes (Optional[Namespace[SpinArrayType]], default: None ) –

    Cluster amplitudes.
Returns:
  • T –

    Norm of the T1 amplitude.
Source code in ebcc/opt/rbrueckner.py 
def get_t1_norm(self, amplitudes: Optional[Namespace[SpinArrayType]] = None) -> T:
    """Get the norm of the T1 amplitude.

    Args:
        amplitudes: Cluster amplitudes.

    Returns:
        Norm of the T1 amplitude.
    """
    if not amplitudes:
        amplitudes = self.cc.amplitudes
    weight: T = np.linalg.norm(amplitudes["t1"])
    return weight

ebcc.opt.rbrueckner.BruecknerREBCC.mo_to_correlated(mo_coeff)

Transform the MO coefficients into the correlated basis.

Parameters:
  • mo_coeff (NDArray[T]) –

    MO coefficients.
Returns:
  • NDArray[T] –

    Correlated slice of MO coefficients.
Source code in ebcc/opt/rbrueckner.py 
def mo_to_correlated(self, mo_coeff: NDArray[T]) -> NDArray[T]:
    """Transform the MO coefficients into the correlated basis.

    Args:
        mo_coeff: MO coefficients.

    Returns:
        Correlated slice of MO coefficients.
    """
    return mo_coeff[:, self.cc.space.correlated]

ebcc.opt.rbrueckner.BruecknerREBCC.mo_update_correlated(mo_coeff, mo_coeff_corr)

Update the correlated slice of a set of MO coefficients.

Parameters:
  • mo_coeff (NDArray[T]) –

    MO coefficients.

  • mo_coeff_corr (NDArray[T]) –

    Correlated slice of MO coefficients.
Returns:
  • NDArray[T] –

    Updated MO coefficients.
Source code in ebcc/opt/rbrueckner.py 
def mo_update_correlated(self, mo_coeff: NDArray[T], mo_coeff_corr: NDArray[T]) -> NDArray[T]:
    """Update the correlated slice of a set of MO coefficients.

    Args:
        mo_coeff: MO coefficients.
        mo_coeff_corr: Correlated slice of MO coefficients.

    Returns:
        Updated MO coefficients.
    """
    mo_coeff = _put(
        mo_coeff,
        np.ix_(np.arange(mo_coeff.shape[0]), self.cc.space.correlated),  # type: ignore
        mo_coeff_corr,
    )
    return mo_coeff

ebcc.opt.rbrueckner.BruecknerREBCC.update_coefficients(u_tot, mo_coeff, mo_coeff_ref)

Update the MO coefficients.

Parameters:
  • u_tot (SpinArrayType) –

    Total rotation matrix.

  • mo_coeff (NDArray[T]) –

    New MO coefficients.

  • mo_coeff_ref (NDArray[T]) –

    Reference MO coefficients.
Returns:
  • NDArray[T] –

    Updated MO coefficients.
Source code in ebcc/opt/rbrueckner.py 
def update_coefficients(
    self, u_tot: SpinArrayType, mo_coeff: NDArray[T], mo_coeff_ref: NDArray[T]
) -> NDArray[T]:
    """Update the MO coefficients.

    Args:
        u_tot: Total rotation matrix.
        mo_coeff: New MO coefficients.
        mo_coeff_ref: Reference MO coefficients.

    Returns:
        Updated MO coefficients.
    """
    mo_coeff_new_corr = util.einsum("pi,ij->pj", mo_coeff_ref, u_tot)
    mo_coeff_new = self.mo_update_correlated(mo_coeff, mo_coeff_new_corr)
    return mo_coeff_new