diff -r 7ec1cfe19a24 -r a4137aedcb3a src/quadratic_dataterm.py
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/src/quadratic_dataterm.py	Thu Feb 26 09:32:12 2026 -0500
@@ -0,0 +1,53 @@
+import numpy as np
+from numpy.linalg import norm
+
+"""
+A quadratic data term
+"""
+
+
+class QuadraticDataTerm:
+    def __init__(self, opA, b, b_norm, xbound=None, λ=1.0):
+        self.opA = opA
+        self.b = b
+        self.b_norm = b_norm
+        self.xbound = xbound
+        self.λ = λ
+
+    def apply(self, x):
+        v = self.opA.apply(x) - self.b
+        return norm(v) ** 2 * (self.λ / 2)
+
+    def diff(self, x):
+        v = self.opA.apply(x) - self.b
+        j = self.λ * v
+        return self.opA.diff_adjdir(j, x)
+
+    def apply_and_diff(self, x):
+        v = self.opA.apply(x) - self.b
+        val = norm(v) ** 2 * (self.λ / 2)
+        j = self.λ * v
+        d = self.opA.diff_adjdir(j, x)
+        return (val, d)
+
+    def diff_lipschitz_factor(self, xbound=None):
+        if hasattr(self.opA, "opnorm"):
+            # Linear operator
+            return self.λ * self.opA.opnorm() ** 2
+        else:
+            raise Exception("diff_lipschitz_factor for non nonlinear operators")
+            # ‖∇A(x)^*∇F(A(x)) - ∇A(y)^*∇F(A(y))‖
+            # = ‖[∇A(x)^*-∇A(y)^*]∇F(A(x)) - ∇A(y)^*[A(y)-A(x)]‖
+            # ≤ L_{∇A(x)}(M_A+M_b) + M_{∇A(y)^*} L_A.
+            la = self.opA.lipschitz_factor()
+            ma = self.opA.bound(xbound=xbound)
+            mb = self.b.norm()
+            mda = self.opA.diff_bound(xbound=xbound)
+            lda = self.opA.diff_adj_lipschitz_factor()
+            return self.λ * (lda * (ma + mb) + mda * la)
+
+    # def diff_lipschitz_factor_pair(self, *args):
+    #     return self.diff_lipschitz_factor()
+
+    def diff_bound(self, xbound=None):
+        return self.λ * (self.opA.codomain_bound(xbound=xbound) + self.b_norm)