diff --git a/src/instrument/jonesmatrices.jl b/src/instrument/jonesmatrices.jl
index 9b88c911..2042b4c6 100644
--- a/src/instrument/jonesmatrices.jl
+++ b/src/instrument/jonesmatrices.jl
@@ -229,7 +229,7 @@ function forward_jones(v::AbstractJonesMatrix, xs::NamedTuple{N}) where {N}
     vs = map(eachindex(sm.times)) do index
         indices = map(x->getindex(x, index), bmaps)
         params = NamedTuple{N}(map(getindex, values(xs), values(indices)))
-        return jonesmatrix(v, params, indices, index)
+        return jonesmatrix(v, params, index, Val(1))
     end
     return SiteArray(vs, sm)
 end
diff --git a/src/posterior/abstract.jl b/src/posterior/abstract.jl
index 2e18b8d9..4566fbfa 100644
--- a/src/posterior/abstract.jl
+++ b/src/posterior/abstract.jl
@@ -52,7 +52,7 @@ instrumentmodel(d::AbstractVLBIPosterior) = getfield(d, :instrumentmodel)
 HypercubeTransform.dimension(d::AbstractVLBIPosterior) = length(d.prior)
 EnzymeRules.inactive(::typeof(instrumentmodel), args...) = nothing
 
-@noinline logprior_ref(d, x) = logprior(d, x[])
+# @noinline logprior_ref(d, x) = logprior(d, x[])
 
 # function ChainRulesCore.rrule(::typeof(logprior), d::AbstractVLBIPosterior, x)
 #     p = logprior(d, x)
@@ -68,18 +68,18 @@ EnzymeRules.inactive(::typeof(instrumentmodel), args...) = nothing
 #     return p, _logprior_pullback
 # end
 
-function _perturb(Δ, x::Union{NamedTuple, Tuple})
-    return map(x->_perturb(Δ, x), x)
-end
+# function _perturb(Δ, x::Union{NamedTuple, Tuple})
+#     return map(x->_perturb(Δ, x), x)
+# end
 
-function _perturb(Δ, x)
-    return Δ*x
-end
+# function _perturb(Δ, x)
+#     return Δ*x
+# end
 
-function _perturb(Δ, x::AbstractArray)
-    x .= Δ*x
-    return x
-end
+# function _perturb(Δ, x::AbstractArray)
+#     x .= Δ*x
+#     return x
+# end
 
 
 
diff --git a/test/Core/bayes.jl b/test/Core/bayes.jl
index 8d814557..fc51de7a 100644
--- a/test/Core/bayes.jl
+++ b/test/Core/bayes.jl
@@ -108,6 +108,16 @@ using Enzyme
         @test LogDensityProblems.capabilities(typeof(tpostc)) === LogDensityProblems.LogDensityOrder{0}()
     end
 
+    @testset "corr image prior" begin
+        cprior1 = corr_image_prior(g, 10.0; base=EMRF, order=1)
+        cprior2 = corr_image_prior(g, 10.0; base=EMRF, order=2)
+
+        @test cprior1 isa VLBIImagePriors.HierarchicalPrior
+        @test cprior2 isa VLBIImagePriors.HierarchicalPrior
+
+        bs = beamsize(dcoh)
+        @test corr_image_prior(g, bs).hyperprior == corr_image_prior(g, dcoh).hyperprior
+    end
 
 
 end
@@ -140,6 +150,7 @@ using FiniteDifferences
     post = VLBIPosterior(skym, intm_coh, coh)
     tpost = asflat(post)
     x = prior_sample(tpost)
+    fj = instrumentmodel(post, x)
     residual(post, Comrade.transform(tpost, x))
     gz = Enzyme.gradient(Enzyme.Reverse, Const(tpost), x)
     mfd = central_fdm(5,1)
diff --git a/test/Core/models.jl b/test/Core/models.jl
index 35651106..e7f7a80b 100644
--- a/test/Core/models.jl
+++ b/test/Core/models.jl
@@ -223,11 +223,19 @@ end
 
         intm = InstrumentModel(J, intprior)
         intm2 = InstrumentModel(J2, intprior)
+        intjg = InstrumentModel(JG, (;lg = ArrayPrior(IIDSitePrior(ScanSeg(), Normal(0.0, 0.1)))))
         show(IOBuffer(), MIME"text/plain"(), intm)
 
 
+
         ointm, printm = Comrade.set_array(intm, arrayconfig(dcoh))
         ointm2, printm2 = Comrade.set_array(intm2, arrayconfig(dcoh))
+        ointjg, printjg = Comrade.set_array(intjg, arrayconfig(dcoh))
+
+        x = rand(printjg)
+        fj = forward_jones(JG, x)
+        @test fj[1][1] == x.lg[1]
+
 
         Fpre = Comrade.preallocate_jones(F, arrayconfig(dcoh), CirBasis())
         Rpre = Comrade.preallocate_jones(JonesR(;add_fr=true), arrayconfig(dcoh), CirBasis())