ZLAEV2(3) computes the eigendecomposition of a 2-by-2 Hermitian matrix [ A B ] [ CONJG(B) C ]

SYNOPSIS

SUBROUTINE ZLAEV2(
A, B, C, RT1, RT2, CS1, SN1 )

    
DOUBLE PRECISION CS1, RT1, RT2

    
COMPLEX*16 A, B, C, SN1

PURPOSE

ZLAEV2 computes the eigendecomposition of a 2-by-2 Hermitian matrix
   [  A         B  ]
   [  CONJG(B)  C  ]. On return, RT1 is the eigenvalue of larger absolute value, RT2 is the eigenvalue of smaller absolute value, and (CS1,SN1) is the unit right eigenvector for RT1, giving the decomposition
[ CS1 CONJG(SN1) ] [ A B ] [ CS1 -CONJG(SN1) ] = [ RT1 0 ] [-SN1 CS1 ] [ CONJG(B) C ] [ SN1 CS1 ] [ 0 RT2 ].

ARGUMENTS

A (input) COMPLEX*16
The (1,1) element of the 2-by-2 matrix.
B (input) COMPLEX*16
The (1,2) element and the conjugate of the (2,1) element of the 2-by-2 matrix.
C (input) COMPLEX*16
The (2,2) element of the 2-by-2 matrix.
RT1 (output) DOUBLE PRECISION
The eigenvalue of larger absolute value.
RT2 (output) DOUBLE PRECISION
The eigenvalue of smaller absolute value.
CS1 (output) DOUBLE PRECISION
SN1 (output) COMPLEX*16 The vector (CS1, SN1) is a unit right eigenvector for RT1.

FURTHER DETAILS

RT1 is accurate to a few ulps barring over/underflow.
RT2 may be inaccurate if there is massive cancellation in the determinant A*C-B*B; higher precision or correctly rounded or correctly truncated arithmetic would be needed to compute RT2 accurately in all cases.
CS1 and SN1 are accurate to a few ulps barring over/underflow. Overflow is possible only if RT1 is within a factor of 5 of overflow. Underflow is harmless if the input data is 0 or exceeds

   underflow_threshold / macheps.