(s=1/2)-Heisenberg-chains N=5

N=2 and N=3 Heisenberg chains are to simple for spinpack, because spinpack uses symmetries and so matrix size becomes to one. Use minimum N=5 sites or switch off all symmetries to see the full base:

cd exe                      # execution path
gcc -lm -o m_1d ../m_1d.c   # compile model generation code for chains
./m_1d 5 > daten.def        # generate 5 side chain model

daten.i:
 verbose=33
 xout=3 99
 pew=2         # number of EWs for convergence proof 0..NEW-1
 nev=1         # number of lowest eigenvectors nev=0..NEV
 sym_ud= 0     # no up-down-symmetry (never used for odd N)
 sym_k= -9999
 param= 1.0, 0.0
 nud=0,5   # ddddd-subspace
 a0
 nud=5,0   # uuuuu-subspace (same as ddddd-subspace)
 a0
 nud=1,4   # udddd-subspace
 a0
 nud=2,3   # uuddd-subspace
 a0

make; ./spin

# matrix output? daten.i: verbose=67 # verbose=64+3=bit5+bit1+bit0 nud=1,5
 vvv&64: B=[    # B = basis space
   0 0x0f *q(   1)  # 0x0f hex means 01111 = udddd
   1 0x17 *q(   1)  # 0x17 hex means 10111 = duddd
   2 0x1b *q(   1)
   3 0x1d *q(   1)
   4 0x1e *q(   1)
vvv&64, output_H x_max=20 lines: # matrix entries (x, y, real, imag)
 addh(    0,    0, +1/4         ,+0           ):
 addh(    0,    1, +1/2         ,+0           ):
 addh(    0,    4, +1/2         ,+0           ):
 addh(    1,    1, +1/4         ,+0           ):
 addh(    1,    2, +1/2         ,+0           ):
 addh(    1,    0, +1/2         ,+0           ):
 addh(    2,    2, +1/4         ,+0           ):
 addh(    2,    3, +1/2         ,+0           ):
 addh(    2,    1, +1/2         ,+0           ):
 addh(    3,    3, +1/4         ,+0           ):
 addh(    3,    4, +1/2         ,+0           ):
 addh(    3,    2, +1/2         ,+0           ):
 addh(    4,    4, +1/4         ,+0           ):
 addh(    4,    3, +1/2         ,+0           ):
 addh(    4,    0, +1/2         ,+0           ):
# 1/4 * ((1 2 0 0 2)
#        (2 1 2 0 0)
#        (0 2 1 2 0)
#        (0 0 2 1 2)
#        (2 0 0 2 1))

results:
# nud=0,5 a4 eigenvals=  +1.25000000
# nud=1,4 a4 eigenvals=  -0.55901699  -0.55901699  +0.55901699  +0.55901699
#                        +1.25000000
# nud=2,3 a4 eigenvals=  -1.86803399  -1.86803399  -0.75000000  -0.55901699
#                        -0.55901699  +0.36803399  +0.36803399  +0.55901699
#                        +0.55901699  +1.25000000
#a4 sym_k= 0 0  eigenvals=  -0.75000000  +1.25000000
# a2:  -0.559016994374947 3e-10
# a0:  -0.55901699
 E0/N=  -0.11180340 E0/nw=  -0.05590170   
#! attention 2-fold degeneracy! ZiZj and other expectation values vary!
#   you have to build mean values
... ToDo