diff --git a/pancax/domains/base.py b/pancax/domains/base.py
index fc10077..1c248a8 100644
--- a/pancax/domains/base.py
+++ b/pancax/domains/base.py
@@ -21,7 +21,6 @@ class BaseDomain(eqx.Module):
     mesh: Mesh
     coords: Float[Array, "nn nd"]
     times: Union[Float[Array, "nt"], Float[Array, "nn 1"]]
-    dt: float  # TODO assumes times were generated with linspace
 
     def __init__(
         self, mesh_file: str, times: Float[Array, "nt"],
@@ -49,17 +48,7 @@ def __init__(
                 if times[i] >= times[i + 1]:
                     raise SimulationTimesNotStrictlyIncreasingException()
 
-            if len(times) > 1:
-                dt = times[1] - times[0]
-            else:
-                print(
-                    "WARNING: setting dt = 0. since this is a \
-                    static problem. Is this what you want?"
-                )
-                dt = 0.0
-
             self.mesh_file = mesh_file
             self.mesh = mesh
             self.coords = jnp.array(mesh.coords)
             self.times = times
-            self.dt = dt
diff --git a/pancax/loss_functions/weak_form_loss_functions.py b/pancax/loss_functions/weak_form_loss_functions.py
index 3e24954..6445254 100644
--- a/pancax/loss_functions/weak_form_loss_functions.py
+++ b/pancax/loss_functions/weak_form_loss_functions.py
@@ -173,34 +173,6 @@ class PathDependentEnergyLoss(PhysicsLossFunction):
     def __init__(self, weight: Optional[float] = 1.0) -> None:
         self.weight = weight
 
-    def __call__old(self, params, problem):
-        field, physics, state = params
-
-        ne = problem.domain.conns.shape[0]
-        nq = len(problem.domain.fspace.quadrature_rule)
-
-        def _vmap_func(n):
-            return problem.physics.constitutive_model.\
-                initial_state()
-
-        state_old = vmap(vmap(_vmap_func))(
-            jnp.zeros((ne, nq))
-        )
-
-        # TODO not adaptive
-        # dumb implementation below
-        dt = problem.times[1] - problem.times[0]
-        pi = 0.0
-        for n in range(problem.times.shape[0]):
-            t = problem.times[n]
-            pi_t, state_new = self.load_step(params, problem, t, dt, state_old)
-
-            state_old = state_new
-            pi = pi + pi_t
-
-        loss = pi
-        return self.weight * loss, dict(energy=pi)
-
     def __call__(self, params, problem):
 
         ne = problem.domain.conns.shape[0]