diff --git a/src/tensortrax/__about__.py b/src/tensortrax/__about__.py
index f88c25b..43ea437 100644
--- a/src/tensortrax/__about__.py
+++ b/src/tensortrax/__about__.py
@@ -2,4 +2,4 @@
 tensorTRAX: Math on (Hyper-Dual) Tensors with Trailing Axes.
 """
 
-__version__ = "0.22.0"
+__version__ = "0.23.0"
diff --git a/src/tensortrax/math/linalg/_linalg_tensor.py b/src/tensortrax/math/linalg/_linalg_tensor.py
index 9535f30..49911ec 100644
--- a/src/tensortrax/math/linalg/_linalg_tensor.py
+++ b/src/tensortrax/math/linalg/_linalg_tensor.py
@@ -126,27 +126,55 @@ def eigh(A, eps=np.sqrt(np.finfo(float).eps)):
 
     # alpha = [0, 1, 2]
     # beta = [(1, 2), (2, 0), (0, 1)]
-
     alpha = np.arange(dim)
     beta = [
         np.concatenate([np.arange(a + 1, dim), np.arange(a)]) for a in np.arange(dim)
     ]
 
     δN = []
+    ΔN = []
     for α in alpha:
         δNα = []
+        ΔNα = []
         for β in beta[α]:
             Mαβ = einsum("i...,j...->ij...", N[α], N[β])
             δAαβ = einsum("ij...,ij...->...", Mαβ, δ(A))
+            ΔAαβ = einsum("ij...,ij...->...", Mαβ, Δ(A))
             λαβ = λ[α] - λ[β]
             δNα.append(1 / λαβ * N[β] * δAαβ)
+            ΔNα.append(1 / λαβ * N[β] * ΔAαβ)
         δN.append(sum(δNα, axis=0))
+        ΔN.append(sum(ΔNα, axis=0))
+
+    ΔδN = []
+    for α in alpha:
+        ΔδNα = []
+        for β in beta[α]:
+            Mαβ = einsum("i...,j...->ij...", N[α], N[β])
+            δAαβ = einsum("ij...,ij...->...", Mαβ, δ(A))
+            ΔδAαβ = einsum("ij...,ij...->...", Mαβ, Δδ(A))
+            λαβ = λ[α] - λ[β]
+            Δλαβ = Δλ[α] - Δλ[β]
+            ΔδNα.append(
+                -(λαβ**-2) * Δλαβ * N[β] * δAαβ
+                + 1 / λαβ * ΔN[β] * δAαβ
+                + 1 / λαβ * N[β] * ΔδAαβ
+            )
+        ΔδN.append(sum(ΔδNα, axis=0))
 
     δM = einsum("ai...,aj...->aij...", δN, N) + einsum("ai...,aj...->aij...", N, δN)
+    ΔM = einsum("ai...,aj...->aij...", ΔN, N) + einsum("ai...,aj...->aij...", N, ΔN)
     Δδλ = einsum("aij...,ij...->a...", δM, Δ(A)) + einsum(
         "aij...,ij...->a...", M, Δδ(A)
     )
 
+    ΔδM = (
+        einsum("ai...,aj...->aij...", δN, ΔN)
+        + einsum("ai...,aj...->aij...", ΔN, δN)
+        + einsum("ai...,aj...->aij...", ΔδN, N)
+        + einsum("ai...,aj...->aij...", N, ΔδN)
+    )
+
     return (
         Tensor(
             x=λ,
@@ -158,8 +186,8 @@ def eigh(A, eps=np.sqrt(np.finfo(float).eps)):
         Tensor(
             x=M,
             δx=δM,
-            Δx=δM * np.nan,
-            Δδx=δM * np.nan,
+            Δx=ΔM,
+            Δδx=ΔδM,
             ntrax=A.ntrax,
         ),
     )