We read every piece of feedback, and take your input very seriously.
To see all available qualifiers, see our documentation.
There was an error while loading. Please reload this page.
random_itensor
random_mps
1 parent d7f7976 commit 5c3603fCopy full SHA for 5c3603f
Project.toml
@@ -1,7 +1,7 @@
1
name = "ITensorVisualizationBase"
2
uuid = "cd2553d2-8bef-4d93-8a38-c62f17d5ad23"
3
authors = ["Matthew Fishman <[email protected]> and contributors"]
4
-version = "0.1.10"
+version = "0.1.11"
5
6
[deps]
7
AbstractTrees = "1520ce14-60c1-5f80-bbc7-55ef81b5835c"
README.md
@@ -17,9 +17,9 @@ j = Index(10, "j")
17
k = Index(40, "k")
18
l = Index(40, "l")
19
m = Index(40, "m")
20
-A = randomITensor(i, j, k)
21
-B = randomITensor(i, j, l, m)
22
-C = randomITensor(k, l)
+A = random_itensor(i, j, k)
+B = random_itensor(i, j, l, m)
+C = random_itensor(k, l)
23
ABC = @visualize A * B * C
24
```
25
This will execute the contraction and output
examples/Project.toml
@@ -0,0 +1,12 @@
+[deps]
+GeometryBasics = "5c1252a2-5f33-56bf-86c9-59e7332b4326"
+Graphs = "86223c79-3864-5bf0-83f7-82e725a168b6"
+ITensorMPS = "0d1a4710-d33b-49a5-8f18-73bdf49b47e2"
+ITensorVisualizationBase = "cd2553d2-8bef-4d93-8a38-c62f17d5ad23"
+ITensors = "9136182c-28ba-11e9-034c-db9fb085ebd5"
+LayeredLayouts = "f4a74d36-062a-4d48-97cd-1356bad1de4e"
8
+NetworkLayout = "46757867-2c16-5918-afeb-47bfcb05e46a"
9
+
10
+[compat]
11
+ITensorMPS = "0.2.2"
12
+ITensors = "0.6.8"
examples/ex_dmrg.jl
@@ -14,11 +14,11 @@ x = Index([QN("Sz", 0) => 2]; tags="X")
14
y = Index([QN("Sz", 0) => 2]; tags="Y")
15
16
n = 2
-ψn1n2 = randomITensor(l⃗[n - 1], s⃗[n], s⃗[n + 1], l⃗[n + 1], dag(x), dag(y))
-hn1 = randomITensor(dag(h⃗[n - 1]), s⃗[n]', dag(s⃗[n]), h⃗[n], x, y)
-hn2 = randomITensor(dag(h⃗[n]), s⃗[n + 1]', dag(s⃗[n + 1]), h⃗[n + 1])
-ELn0 = randomITensor(l⃗[n - 1]', h⃗[n - 1], dag(l⃗[n - 1]))
-ERn2 = randomITensor(l⃗[n + 1]', dag(h⃗[n + 1]), dag(l⃗[n + 1]))
+ψn1n2 = random_itensor(l⃗[n - 1], s⃗[n], s⃗[n + 1], l⃗[n + 1], dag(x), dag(y))
+hn1 = random_itensor(dag(h⃗[n - 1]), s⃗[n]', dag(s⃗[n]), h⃗[n], x, y)
+hn2 = random_itensor(dag(h⃗[n]), s⃗[n + 1]', dag(s⃗[n + 1]), h⃗[n + 1])
+ELn0 = random_itensor(l⃗[n - 1]', h⃗[n - 1], dag(l⃗[n - 1]))
+ERn2 = random_itensor(l⃗[n + 1]', dag(h⃗[n + 1]), dag(l⃗[n + 1]))
edge_labels = (; plevs=true)
examples/ex_qn_mps.jl
@@ -3,7 +3,7 @@ using ITensorMPS
using ITensorVisualizationBase
s = siteinds("S=1/2", 5; conserve_qns=true)
-ψ = randomMPS(s, n -> isodd(n) ? "↑" : "↓"; linkdims=2)
+ψ = random_mps(s, n -> isodd(n) ? "↑" : "↓"; linkdims=2)
orthogonalize!(ψ, 2)
ψdag = prime(linkinds, dag(ψ))
tn = [ψ..., ψdag...]
examples/notest_ex_2d_circuit.jl
examples/notest_ex_qft_circuit.jl
test/Project.toml
@@ -2,7 +2,12 @@
GeometryBasics = "5c1252a2-5f33-56bf-86c9-59e7332b4326"
Graphs = "86223c79-3864-5bf0-83f7-82e725a168b6"
ITensorMPS = "0d1a4710-d33b-49a5-8f18-73bdf49b47e2"
ITensors = "9136182c-28ba-11e9-034c-db9fb085ebd5"
LayeredLayouts = "f4a74d36-062a-4d48-97cd-1356bad1de4e"
NetworkLayout = "46757867-2c16-5918-afeb-47bfcb05e46a"
Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
13
test/test_basics.jl
@@ -16,11 +16,11 @@ using Test
- ψn1n2 = randomITensor(l⃗[n - 1], s⃗[n], s⃗[n + 1], l⃗[n + 1], dag(x), dag(y))
- hn1 = randomITensor(dag(h⃗[n - 1]), s⃗[n]', dag(s⃗[n]), h⃗[n], x, y)
- hn2 = randomITensor(dag(h⃗[n]), s⃗[n + 1]', dag(s⃗[n + 1]), h⃗[n + 1])
- ELn0 = randomITensor(l⃗[n - 1]', h⃗[n - 1], dag(l⃗[n - 1]))
- ERn2 = randomITensor(l⃗[n + 1]', dag(h⃗[n + 1]), dag(l⃗[n + 1]))
+ ψn1n2 = random_itensor(l⃗[n - 1], s⃗[n], s⃗[n + 1], l⃗[n + 1], dag(x), dag(y))
+ hn1 = random_itensor(dag(h⃗[n - 1]), s⃗[n]', dag(s⃗[n]), h⃗[n], x, y)
+ hn2 = random_itensor(dag(h⃗[n]), s⃗[n + 1]', dag(s⃗[n + 1]), h⃗[n + 1])
+ ELn0 = random_itensor(l⃗[n - 1]', h⃗[n - 1], dag(l⃗[n - 1]))
+ ERn2 = random_itensor(l⃗[n + 1]', dag(h⃗[n + 1]), dag(l⃗[n + 1]))
tn = [ELn0, ψn1n2, hn1, hn2, ERn2]
26
0 commit comments