diff --git a/src/theory.jl b/src/theory.jl
index 36ed00d..5893e5f 100755
--- a/src/theory.jl
+++ b/src/theory.jl
@@ -3,8 +3,7 @@ function Theory(cosmology::Cosmology,
                 idx, files;
                 Nuisances=Dict(),
                 res_wl=350, res_gc=1000,
-                int_wl="linear", int_gc="linear",
-                smooth_gc=0)
+                int_wl="linear", int_gc="linear")
     
     nui_type =  eltype(valtype(Nuisances))
     if !(nui_type <: Float64) & (nui_type != Any)
@@ -26,8 +25,7 @@ function Theory(cosmology::Cosmology,
             dz = get(Nuisances, string(name, "_", "dz"), 0.0)
             tracer = NumberCountsTracer(cosmology, zs .+ dz, nz;
                                         b=b, res=res_gc, 
-                                        nz_interpolation=int_gc,
-                                        smooth=smooth_gc)
+                                        nz_interpolation=int_gc)
         elseif t_type == "galaxy_shear"
             zs_mean, nz_mean = files[string("nz_", name)]
             m = get(Nuisances, string(name, "_", "m"), 0.0)
diff --git a/src/tracers.jl b/src/tracers.jl
index 748f670..abcb98e 100755
--- a/src/tracers.jl
+++ b/src/tracers.jl
@@ -37,9 +37,6 @@ NumberCountsTracer(cosmo::Cosmology, z_n, nz;
     hz = Hmpc(cosmo, z_w)
     
     w_arr = @. (nz_w*hz/nz_norm)
-    if smooth != 0
-        w_arr = smooth_w_neighbors(w_arr, k=smooth)
-    end
     wint = linear_interpolation(chi, b .* w_arr, extrapolation_bc=0.0)
     F::Function = ℓ -> 1
     NumberCountsTracer(wint, F)
@@ -178,21 +175,3 @@ function nz_interpolate(z, nz, res; mode="linear")
         return z, nz
     end
 end
-
-function smooth_w_neighbors(arr; k::Int = 5)
-    N = length(arr)
-    neighbors = Vector{}(undef, N)  # Create an array to hold neighbor arrays
-
-    half_k = div(k, 2)  # This is 2 if k=5, so we look at two neighbors on each side
-
-    for i in 1:N
-        # Define the range around the current element, clamping to avoid out-of-bounds
-        start_idx = max(1, i - half_k)
-        end_idx = min(N, i + half_k)
-        
-        # Collect neighbors and assign to the current position
-        neighbors[i] = mean(arr[start_idx:end_idx])
-    end
-
-    return neighbors
-end