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JYU Condensed Matter Theory
usadelndsoc
Commits
4db599e4
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4db599e4
authored
2 years ago
by
patavirt
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doc/discretization.md
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4db599e4
...
...
@@ -20,14 +20,8 @@ and $h$ are the lattice spacings. See the figure below:

We choose $
`Q(j) = Q(\vec{r}_j)`
$ to be values of $
`Q`
$ at the lattice
sites. We define the Wilson link matrices
$
`U_{ij}
=U_{ji}^{-1}
=U(\vec{r}_{i},\vec{r}_{j})
=
\mathrm{Pexp}[i\int_{L(\vec{r}_i,\vec{r}_j)}d\vec{r}'\,\cdot\vec{\mathcal{A}}(\vec{r}')]
`
$
We choose $
`Q(j) = Q(\vec{r}_j)`
$ to be values of $
`Q`
$ at the lattice sites. We define the Wilson link matrices
$
`U_{ij} =U_{ji}^{-1} =U(\vec{r}_{i},\vec{r}_{j}) = \mathrm{Pexp}[i\int_{L(\vec{r}_i,\vec{r}_j)}d\vec{r}'\,\cdot\vec{\mathcal{A}}(\vec{r}')]`
$
where $
`L(\vec{r}_i,\vec{r}_j)`
$ is straight line from $
`\vec{r}_j`
$ to
$
`\vec{r}_i`
$ and $
`\mathrm{Pexp}`
$ is the path-ordered integral.
The neighbor cells of $
`j`
$ are $
`i\in{}\mathrm{neigh}(j)`
$
...
...
@@ -66,7 +60,7 @@ D
```
where $
`d`
$ is the space dimension.
Expanding in small $
h
$ we have
Expanding in small $
`h`
$ we have
```
math
S_2
\simeq
...
...
@@ -130,7 +124,7 @@ which then allows expressing $`F_{ij}`$ in terms of the link matrices.
## Hall term
When discretizing the $Q
\h
at{
\n
abla}_iQ
\h
at{
\n
abla}_jQ$ part, we can
When discretizing the $
`
Q\hat{\nabla}_iQ\hat{\nabla}_jQ
`
$ part, we can
consider a discrete derivative
```
math
D_{ij}
...
...
@@ -160,13 +154,13 @@ have
\mathrm{tr}
(U_{lk} U_{kj} - U_{li} U_{ij}) D_{ji} Q(i) D_{il}
```
So the structure is $
\f
rac{-i}{h^4}$ $
\t
imes$ (gauge factors for
counterclockwise loop $
-
$ return back clockwise) $
\t
imes$ $DQD$ for
three sites in counterclockwise order. Since only $Q(i)$, $Q(j)$,
$Q(l)$ appear here, one can also think of this as a plaquette corner
with $Q(i)$ being the corner.
So the structure is $
`
\frac{-i}{h^4}
`
$ $
`
\times
`
$ (gauge factors for
counterclockwise loop $
`-`
$ return back clockwise) $
`
\times
`
$ $
`
DQD
`
$ for
three sites in counterclockwise order. Since only $
`
Q(i)
`
$, $
`
Q(j)
`
$,
$
`
Q(l)
`
$ appear here, one can also think of this as a plaquette corner
with $
`
Q(i)
`
$ being the corner.
To do the sum over the $
\m
u$, $
\n
u$ indices, one can average over
To do the sum over the $
`
\mu
`
$, $
`
\nu
`
$ indices, one can average over
corners of the plaquettes as follows, which gives the final discretization
of the Hall term:
```
math
...
...
@@ -197,7 +191,7 @@ of the Hall term:
\Bigr)
\,,
```
where $
\m
athrm{plaqc}(i;jkl)$ are the plaquette corners. The last line
where $
`
\mathrm{plaqc}(i;jkl)
`
$ are the plaquette corners. The last line
follows with direct calculation, and considering the cyclic
permutations.
...
...
@@ -224,7 +218,7 @@ We can also calculate the matrix current $j\mapsto{}i$ between neighboring cells
]\rvert_{\xi=0}
```
%
where $T^a$ is an appropriate matrix generator, and the transformation
where $
`
T^a
`
$ is an appropriate matrix generator, and the transformation
is inserted only to one of the links.
The local gauge invariance now implies that there is an exact discrete
...
...
@@ -248,11 +242,13 @@ However, the definition of the matrix current is \emph{asymmetric}, so
that $
`J_{ij}\ne{}-J_{ji}`
$ as they differ by a quantity of order
$
`\mathcal{O}(h^2)`
$. The asymmetry arises when $
`T^a`
$ does not commute
with $
`U_{ij}`
$, so it is an issue only for the SU(2) component. The
problem is to some degree just in the interpretation of what $J_{ij}$
means: it is the incoming current measured at site $
`i`
$, whereas
problem is to some degree just in the interpretation of what $
`J_{ij}`
$
means:
It is the incoming current measured at site $
`i`
$, whereas
$
`J_{ji}`
$ is measured as site $
`j`
$. Since the parallel transport of
spin between these two locations can imply rotation due to the gauge
field, there's no reason why we should have $
`J_{ij}
=
-J_{ji}`
$, except
field, there's no reason why we should have $
`J_{ij}
=
-J_{ji}`
$, except
in the continuum limit where the two points become close to each
other.
...
...
@@ -261,10 +257,10 @@ other.
The above is sufficient for numerical implementation: it is not
necessary to find out the saddle point equation symbolically. It can
be deduced by parametrizing first so that $Q^2=1$ and then using
be deduced by parametrizing first so that $
`
Q^2=1
`
$ and then using
automatic differentiation (AD). Only a routine evaluating the value of
the action is then needed, in terms of the AD dual variables.
When looking for the saddle point in equilibrium, the problem becomes
even simpler; $
Q
$ has then additional restrictions, and we are looking
for the minimum of the free energy $
S
$.
even simpler; $
`Q`
$ has then additional restrictions, and we are looking
for the minimum of the free energy $
`S`
$.
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