diff --git a/mrmustard/utils/settings.py b/mrmustard/utils/settings.py
index f1df34ee4..1f40736aa 100644
--- a/mrmustard/utils/settings.py
+++ b/mrmustard/utils/settings.py
@@ -114,6 +114,7 @@ def __init__(self):
         ]  # possible values for settings.PRECISION_BITS_HERMITE_POLY
 
     def _force_hbar(self, value):
+        r"can set the value of HBAR at any time. use with caution."
         self._hbar._value = value
 
     @property
diff --git a/tests/test_physics/test_fidelity.py b/tests/test_physics/test_fidelity.py
index a5c65ff4e..6ec830aa9 100644
--- a/tests/test_physics/test_fidelity.py
+++ b/tests/test_physics/test_fidelity.py
@@ -10,7 +10,6 @@
 from mrmustard.physics import gaussian as gp
 
 math = Math()
-hbar0 = settings.HBAR
 
 
 class TestGaussianStates:
@@ -79,7 +78,6 @@ def test_fidelity_coherent_state(self, num_modes, hbar):
     @pytest.mark.parametrize("r2", np.random.rand(3))
     def test_fidelity_squeezed_vacuum(self, r1, r2, hbar):
         """Tests fidelity between two squeezed states"""
-        hbar0 = settings.HBAR
         settings._force_hbar(hbar)
         cov1 = np.diag([np.exp(2 * r1), np.exp(-2 * r1)]) * hbar / 2
         cov2 = np.diag([np.exp(2 * r2), np.exp(-2 * r2)]) * hbar / 2
diff --git a/tests/test_physics/test_wigner.py b/tests/test_physics/test_wigner.py
index 02811e773..13cd63f5e 100644
--- a/tests/test_physics/test_wigner.py
+++ b/tests/test_physics/test_wigner.py
@@ -38,14 +38,6 @@
 # ~~~~~~~
 
 
-def reset_settings():
-    r"""Resets `Settings`"""
-    settings.AUTOCUTOFF_MAX_CUTOFF = autocutoff_max0
-    settings.AUTOCUTOFF_MIN_CUTOFF = autocutoff_min0
-    settings.DISCRETIZATION_METHOD = method0
-    settings._force_hbar(hbar0)
-
-
 def distance(W_mm, W_th):
     r"""Calculates the distance between the discretized Wigner functions W_mm (generated
     by `mrmustard`) and W_th (computed analytically) as the maximum of `|W_mm-W_th|/|W_th|`,
@@ -115,6 +107,15 @@ def generator(q, p, n):
 class TestWignerDiscretized:
     r"""Tests discretized Wigner functions (DWF) for various states"""
 
+    hbar0: float = settings.HBAR
+
+    def teardown_method(self, method):
+        r"""Resets `Settings`"""
+        settings.AUTOCUTOFF_MAX_CUTOFF = autocutoff_max0
+        settings.AUTOCUTOFF_MIN_CUTOFF = autocutoff_min0
+        settings.DISCRETIZATION_METHOD = method0
+        settings._force_hbar(self.hbar0)
+
     @pytest.mark.parametrize("method", ["iterative", "clenshaw"])
     @pytest.mark.parametrize("hbar", [1, 2])
     def test_cat_state(self, method, hbar):
@@ -136,8 +137,6 @@ def test_cat_state(self, method, hbar):
         assert np.allclose(q_mat.T, q_vec)
         assert np.allclose(p_mat, p_vec)
 
-        reset_settings()
-
     @pytest.mark.parametrize("alpha", [0 + 0j, 3 + 3j])
     @pytest.mark.parametrize("hbar", [2, 3])
     @pytest.mark.parametrize("method", ["iterative", "clenshaw"])
@@ -163,8 +162,6 @@ def test_coherent_state(self, alpha, hbar, method):
         assert np.allclose(q_mat.T, q_vec)
         assert np.allclose(p_mat, p_vec)
 
-        reset_settings()
-
     @pytest.mark.parametrize("n", [2, 6])
     @pytest.mark.parametrize("hbar", [2, 3])
     @pytest.mark.parametrize("method", ["iterative", "clenshaw"])
@@ -184,8 +181,6 @@ def test_fock_state(self, n, hbar, method):
         assert np.allclose(q_mat.T, q_vec)
         assert np.allclose(p_mat, p_vec)
 
-        reset_settings()
-
     @pytest.mark.parametrize("method", ["iterative", "clenshaw"])
     def test_squeezed_vacuum_both_method_succeed(self, method):
         r"""Tests DWF for a squeezed vacuum state with squeezing s=1.
@@ -207,8 +202,6 @@ def test_squeezed_vacuum_both_method_succeed(self, method):
         assert np.allclose(q_mat.T, q_vec)
         assert np.allclose(p_mat, p_vec)
 
-        reset_settings()
-
     @pytest.mark.parametrize("method", ["iterative", "clenshaw"])
     def test_squeezed_vacuum_iterative_fails(self, method):
         r"""Tests DWF for a squeezed vacuum state with squeezing s=2.
@@ -228,5 +221,3 @@ def test_squeezed_vacuum_iterative_fails(self, method):
 
         success = np.allclose(distance(W_mm, W_th), 0, atol=10**-1)
         assert success is False if method == "iterative" else True
-
-        reset_settings()