diff --git a/Project.toml b/Project.toml
index 098ca029..37ac3b15 100644
--- a/Project.toml
+++ b/Project.toml
@@ -1,7 +1,7 @@
 name = "ITensorNetworks"
 uuid = "2919e153-833c-4bdc-8836-1ea460a35fc7"
 authors = ["Matthew Fishman <mfishman@flatironinstitute.org>, Joseph Tindall <jtindall@flatironinstitute.org> and contributors"]
-version = "0.13.10"
+version = "0.13.11"
 
 [deps]
 AbstractTrees = "1520ce14-60c1-5f80-bbc7-55ef81b5835c"
diff --git a/src/formnetworks/bilinearformnetwork.jl b/src/formnetworks/bilinearformnetwork.jl
index f0796937..7d662162 100644
--- a/src/formnetworks/bilinearformnetwork.jl
+++ b/src/formnetworks/bilinearformnetwork.jl
@@ -53,12 +53,14 @@ function Base.copy(blf::BilinearFormNetwork)
   )
 end
 
-function itensor_identity_map(i_pairs::Vector)
+function itensor_identity_map(elt::Type, i_pairs::Vector)
   return prod(i_pairs; init=ITensor(one(Bool))) do i_pair
-    return denseblocks(delta(last(i_pair), dag(first(i_pair))))
+    return denseblocks(delta(elt, last(i_pair), dag(first(i_pair))))
   end
 end
 
+itensor_identity_map(i_pairs::Vector) = itensor_identity_map(Float64, i_pairs)
+
 function BilinearFormNetwork(
   bra::AbstractITensorNetwork,
   ket::AbstractITensorNetwork;
@@ -72,7 +74,7 @@ function BilinearFormNetwork(
   operator_inds = union_all_inds(s, s_mapped)
 
   O = ITensorNetwork(operator_inds; link_space) do v
-    return inds -> itensor_identity_map(s[v] .=> s_mapped[v])
+    return inds -> itensor_identity_map(scalartype(ket), s[v] .=> s_mapped[v])
   end
   return BilinearFormNetwork(O, bra, ket; dual_site_index_map, kwargs...)
 end
diff --git a/src/specialitensornetworks.jl b/src/specialitensornetworks.jl
index f0c4f26f..ba6f196d 100644
--- a/src/specialitensornetworks.jl
+++ b/src/specialitensornetworks.jl
@@ -29,8 +29,10 @@ end
 """
 Build an ITensor network on a graph specified by the inds network s. Bond_dim is given by link_space and entries are randomised (normal distribution, mean 0 std 1)
 """
-function random_tensornetwork(rng::AbstractRNG, eltype::Type, s::IndsNetwork; kwargs...)
-  return ITensorNetwork(s; kwargs...) do v
+function random_tensornetwork(
+  rng::AbstractRNG, eltype::Type, s::IndsNetwork; link_space=1, kwargs...
+)
+  return ITensorNetwork(s; link_space, kwargs...) do v
     return inds -> itensor(randn(rng, eltype, dim.(inds)...), inds)
   end
 end