[ITensors] Fix eigen_perturbation rank

src/tensor_operations/matrix_decomposition.jl

@@ -781,13 +781,19 @@ function factorize(
   Lis = commoninds(A, indices(Linds...))
   Ris = uniqueinds(A, Lis)
   dL, dR = dim(Lis), dim(Ris)
-  # maxdim is forced to be at most the max given SVD
-  if isnothing(maxdim)
-    maxdim = min(dL, dR)
+  if isnothing(eigen_perturbation)
+    # maxdim is forced to be at most the max given SVD
+    if isnothing(maxdim)
+      maxdim = min(dL, dR)
+    end
+    maxdim = min(maxdim, min(dL, dR))
+  else
+    if isnothing(maxdim)
+      maxdim = max(dL, dR)
+    end
+    maxdim = min(maxdim, max(dL, dR))
   end
-  maxdim = min(maxdim, min(dL, dR))
   might_truncate = !isnothing(cutoff) || maxdim < min(dL, dR)
-
   if isnothing(which_decomp)
     if !might_truncate && ortho != "none"
       which_decomp = "qr"

test/base/test_decomp.jl

@@ -136,6 +136,25 @@ end
     )
   end
 
+  @testset "factorize with eigen_perturbation dimensions" begin
+    elt = Float64
+    di = 10
+    dj = 5
+    maxdim = di - 1
+    i = Index(di, "i")
+    j = Index(dj, "j")
+    a = randomITensor(elt, i, j)
+    δ = randomITensor(elt, i, j)
+    δ² = prime(δ, i) * dag(δ)
+    a² = prime(a, i) * dag(a)
+    x, y = factorize(a, i; ortho="left", which_decomp="eigen", maxdim)
+    l = commonind(x, y)
+    @test dim(l) == dj
+    xδ, yδ = factorize(a, i; ortho="left", which_decomp="eigen", eigen_perturbation=δ², maxdim)
+    lδ = commonind(xδ, yδ)
+    @test dim(lδ) == maxdim
+  end
+
   @testset "QR/RQ/QL/LQ decomp on MPS dense $elt tensor with all possible collections on Q/R/L" for ninds in
                                                                                                     [
       0, 1, 2, 3