Wolfram Language Paclet Repository
Community-contributed installable additions to the Wolfram Language
Wolfram`TensorNetworks`
MPSOverlap  |
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Details and Options
Examples
(6)
Scope
(4)
Self-overlap and squared norm
(1)
Self-overlap returns the squared 2-norm of the MPS:
In[1]:=
SeedRandom[42]
In[2]:=
mps=RandomTensorNetwork["MPS"[6,4,2]];
In[3]:=
{MPSOverlap[mps,mps],MPSNorm[mps]^2}
Out[4]=
{69.3437,69.3437}
The difference is zero to floating-point precision:
In[5]:=
Chop[MPSOverlap[mps,mps]-MPSNorm[mps]^2]
Out[6]=
0
Conjugate (Hermitian) symmetry
(1)
Normalized MPSs
(1)
Length mismatch
(1)
Applications
(1)
Properties & Relations
(1)
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Set a seed for reproducibility:
In[1]:=
SeedRandom[42]
Build a length-6, bond-4, physical-2 MPS:
In[2]:=
mps=RandomTensorNetwork["MPS"[6,4,2]];
Compute the squared norm of the state as the overlap with itself:
In[3]:=
MPSOverlap[mps,mps]
Out[3]=
69.3437
Build two independent MPSs and overlap them:
In[4]:=
mps1=RandomTensorNetwork["MPS"[6,4,2]];
In[5]:=
mps2=RandomTensorNetwork["MPS"[6,4,2]];
In[6]:=
MPSOverlap[mps1,mps2]
Out[6]=
5.42534
The overlap is Hermitian-symmetric in its two arguments:
In[7]:=
mps1=RandomTensorNetwork["MPS"[6,4,2]];mps2=RandomTensorNetwork["MPS"[6,4,2]];Conjugate[MPSOverlap[mps2,mps1]]
Out[7]=
5.42534
""