diff --git a/qutil/signal_processing/fourier_space.py b/qutil/signal_processing/fourier_space.py
index 4b8b6eb0e5058ea34e0b1aab8f1949ec7de05ddf..ee69fa8d9d56ea8e949f78d925ba2d8afc1b6826 100644
--- a/qutil/signal_processing/fourier_space.py
+++ b/qutil/signal_processing/fourier_space.py
@@ -46,6 +46,7 @@ import numpy as np
 from qutil import math
 from qutil.caching import cache
 from qutil.functools import wraps
+from qutil.misc import deprecate_kwarg
 from qutil.signal_processing._common import _parse_filter_edges
 from qutil.typecheck import check_literals
 from scipy import integrate
@@ -113,7 +114,8 @@ def Id(x: _S, f: _T, *_, **__) -> Tuple[_S, _T]:
     return x, f
 
 
-def derivative(x, f, deriv_order: int = 0, overwrite_x: bool = False,
+@deprecate_kwarg('deriv_order', 'order')
+def derivative(x, f, order: int = 0, overwrite_x: bool = False,
                **_) -> Tuple[np.ndarray, np.ndarray]:
     r"""Compute the (anti-)derivative.
 
@@ -127,8 +129,8 @@ def derivative(x, f, deriv_order: int = 0, overwrite_x: bool = False,
             e^{i\omega t} \hat{f}(\omega)
 
     .. note::
-        For negative ``deriv_order`` (antiderivatives), the
-        zero-frequency component is set to zero (due to zero-division).
+        For negative ``order`` (antiderivatives), the zero-frequency
+        component is set to zero (due to zero-division).
 
     Parameters
     ----------
@@ -136,7 +138,7 @@ def derivative(x, f, deriv_order: int = 0, overwrite_x: bool = False,
         Target data.
     f : array_like
         Frequencies corresponding to the last axis of `x`.
-    deriv_order : int
+    order : int
         The order of the derivative. If negative, the antiderivative is
         computed (indefinite integral). Default: 0.
     overwrite_x : bool, default False
@@ -145,8 +147,8 @@ def derivative(x, f, deriv_order: int = 0, overwrite_x: bool = False,
     x = np.array(x, copy=not overwrite_x)
     f = np.asanyarray(f)
     with np.errstate(invalid='ignore', divide='ignore'):
-        x *= (2j*np.pi*f)**deriv_order
-    if deriv_order < 0:
+        x *= (2j*np.pi*f)**order
+    if order < 0:
         x[..., (f == 0).nonzero()] = 0
     return x, f