From 322b143ca81ef6775bab12d7a7cbc51e6b21c48d Mon Sep 17 00:00:00 2001
From: "Samson Leong (wkstn)" <55839002+SSL32081@users.noreply.github.com>
Date: Sat, 11 Jul 2026 03:16:50 +0800
Subject: [PATCH 01/17] Remove redundant waveform mask

---
 src/jimgw/core/single_event/likelihood.py | 73 ++++++++---------------
 1 file changed, 26 insertions(+), 47 deletions(-)

diff --git a/src/jimgw/core/single_event/likelihood.py b/src/jimgw/core/single_event/likelihood.py
index 4d927000..7bceb61a 100644
--- a/src/jimgw/core/single_event/likelihood.py
+++ b/src/jimgw/core/single_event/likelihood.py
@@ -552,12 +552,12 @@ class HeterodynedTransientLikelihoodFD(SingleEventLikelihood):
     n_bins: int
     epsilon: float
     reference_parameters: dict
-    freq_grid_low: Float[Array, " n_bin"]
-    freq_grid_high: Float[Array, " n_bin"]
-    bin_widths: Float[Array, " n_bin"]
-    waveform_low_ref: dict[str, Complex[Array, " n_bin"]]
-    waveform_high_ref: dict[str, Complex[Array, " n_bin"]]
-    summary_data: dict[str, Complex[Array, "4 n_bin"]]
+    freq_grid_low: Float[Array, " n_bins"]
+    freq_grid_high: Float[Array, " n_bins"]
+    bin_widths: Float[Array, " n_bins"]
+    waveform_low_ref: dict[str, Complex[Array, " n_bins"]]
+    waveform_high_ref: dict[str, Complex[Array, " n_bins"]]
+    summary_data: dict[str, Complex[Array, "4 n_bins"]]
 
     def __init__(
         self,
@@ -690,34 +690,15 @@ def __init__(
                 )
                 n_bins = max(1, int(float(phase[-1]) / epsilon))
         assert isinstance(n_bins, int)
-        freq_grid, freq_grid_center = self._make_binning_scheme(
-            jnp.array(frequency_original), n_bins=n_bins
+        self.n_bins = n_bins
+        freq_grid = self._make_binning_scheme(
+            jnp.array(frequency_original), n_bins=self.n_bins
         )
+        self.bin_widths = self.freq_grid_high - self.freq_grid_low
         self.freq_grid_low = freq_grid[:-1]
         self.freq_grid_high = freq_grid[1:]
-
         h_sky = reference_waveform(frequency_original, self.reference_parameters)
 
-        h_amp = jnp.sum(
-            jnp.array([jnp.abs(h_sky[pol]) for pol in h_sky.keys()]), axis=0
-        )
-        f_valid = frequency_original[jnp.where(h_amp > 0)[0]]
-
-        valid_waveform_mask = jnp.where(
-            (self.freq_grid_high <= jnp.max(f_valid))
-            & (self.freq_grid_low >= jnp.min(f_valid))
-        )[0]
-        freq_grid_center = freq_grid_center[valid_waveform_mask]
-        self.freq_grid_low = self.freq_grid_low[valid_waveform_mask]
-        self.freq_grid_high = self.freq_grid_high[valid_waveform_mask]
-        self.n_bins = len(freq_grid_center)
-        self.bin_widths = self.freq_grid_high - self.freq_grid_low
-
-        # freq_grid is one cell longer than freq_grid_center/low/high
-        start_idx = valid_waveform_mask[0]
-        end_idx = valid_waveform_mask[-1] + 2
-        freq_grid = freq_grid[start_idx:end_idx]
-
         h_sky_low = reference_waveform(self.freq_grid_low, self.reference_parameters)
         h_sky_high = reference_waveform(self.freq_grid_high, self.reference_parameters)
 
@@ -737,8 +718,7 @@ def __init__(
                 waveform_ref,
                 detector.sliced_psd,
                 detector.sliced_frequencies,
-                freq_grid,
-                freq_grid_center,
+                freq_grid
             )
 
     def evaluate(self, params: dict[str, Float]) -> FloatScalar:
@@ -813,7 +793,7 @@ def _max_phase_diff(
 
         See also Eq.(7) in arXiv:2302.05333.
         """
-        gamma = jnp.array([-5 / 3, -2 / 3, 1.0, 5 / 3, 7 / 3])
+        gamma = jnp.array([-5., -2., 3., 5., 7.]) / 3
         freq_2D = jax.lax.broadcast_in_dim(freqs, (freqs.size, gamma.size), [0])
         f_star = jnp.where(gamma >= 0, f_high, f_low)
         summand = (freq_2D / f_star) ** gamma * jnp.sign(gamma)
@@ -825,7 +805,7 @@ def _make_binning_scheme(
         freqs: Float[Array, " n_freq"],
         n_bins: int,
         chi: float = 1.0,
-    ) -> tuple[Float[Array, " n_bins + 1"], Float[Array, " n_bins"]]:
+    ) -> Float[Array, " n_bins + 1"]:
         """Make ``n_bins`` frequency bins of equal phase change.
 
         ``n_bins`` must be a positive integer resolved by the caller
@@ -835,8 +815,7 @@ def _make_binning_scheme(
         total_phase = phase_diff_array[-1]
         phase_diff = jnp.linspace(0.0, total_phase, n_bins + 1)
         f_bins = interp1d(phase_diff_array, freqs)(phase_diff)
-        f_bins_center = (f_bins[:-1] + f_bins[1:]) / 2
-        return jnp.array(f_bins), jnp.array(f_bins_center)
+        return jnp.array(f_bins)
 
     @staticmethod
     def _compute_coefficients(
@@ -844,20 +823,23 @@ def _compute_coefficients(
         h_ref: Complex[Array, " n_freq"],
         psd: Complex[Array, " n_freq"],
         freqs: Float[Array, " n_freq"],
-        f_bins: Float[Array, " n_bin+1"],
-        f_bins_center: Float[Array, " n_bin"],
-    ) -> Complex[Array, "4 n_bin"]:
+        f_bins: Float[Array, " n_bins+1"]
+    ) -> Complex[Array, "4 n_bins"]:
         df = freqs[1] - freqs[0]
         data_prod = jnp.array(data * h_ref.conj()) / psd
         self_prod = jnp.array(h_ref * h_ref.conj()) / psd
 
-        freq_bins_left = f_bins[:-1]  # Shape: (n_bin)
-        freq_bins_right = f_bins[1:]  # Shape: (n_bin)
+        freq_bins_left = f_bins[:-1]  # Shape: (n_bins)
+        freq_bins_right = f_bins[1:]  # Shape: (n_bins)
+        freq_bins_center = (freq_bins_left + freq_bins_right) / 2  # Shape: (n_bins)
 
+        # Broadcasting for 2D frequencies
         freqs_broadcast = freqs[None, :]  # Shape: (1, n_freq)
-        left_bounds = freq_bins_left[:, None]  # Shpae: (n_bin, 1)
-        right_bounds = freq_bins_right[:, None]  # Shape: (n_bin, 1)
+        left_bounds = freq_bins_left[:, None]  # Shpae: (n_bins, 1)
+        right_bounds = freq_bins_right[:, None]  # Shape: (n_bins, 1)
+        freq_bins_center_broadcast = freq_bins_center[:, None]  # Shape: (n_bins, 1)
 
+        # Shape: (n_bins, n_freq)
         mask = (freqs_broadcast >= left_bounds) & (freqs_broadcast < right_bounds)
         # The half-open interval [left, right) excludes any frequency that lands
         # exactly on the upper edge of the last bin (f_bins[-1]).  This happens
@@ -865,12 +847,9 @@ def _compute_coefficients(
         # frequency sample (common when the waveform reaches f_max).  Extend the
         # last row to a closed interval by OR-ing in the equality condition.
         mask = mask.at[-1].set(mask[-1] | (freqs == freq_bins_right[-1]))
-        # Shape: (n_bin, n_freq)
-
-        f_bins_center_broadcast = f_bins_center[:, None]  # Shape: (n_bin, 1)
-        freq_shift_matrix = (freqs_broadcast - f_bins_center_broadcast) * mask
+        freq_shift_matrix = (freqs_broadcast - freq_bins_center_broadcast) * mask
 
-        # The resultant arrays have shape (n_bin), the dimension with "n_freq" is summed over.
+        # The resultant arrays have shape (n_bins), the dimension with "n_freq" is summed over.
         summary_data = jnp.array(
             [
                 jnp.sum(data_prod[None, :] * mask, axis=1),  # A0

From 4cf526c24cbd25e1f9485b1e22f6d0c4cfb7dfe0 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Fri, 10 Jul 2026 19:32:26 +0000
Subject: [PATCH 02/17] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 src/jimgw/core/single_event/likelihood.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/src/jimgw/core/single_event/likelihood.py b/src/jimgw/core/single_event/likelihood.py
index 7bceb61a..b4cc276a 100644
--- a/src/jimgw/core/single_event/likelihood.py
+++ b/src/jimgw/core/single_event/likelihood.py
@@ -718,7 +718,7 @@ def __init__(
                 waveform_ref,
                 detector.sliced_psd,
                 detector.sliced_frequencies,
-                freq_grid
+                freq_grid,
             )
 
     def evaluate(self, params: dict[str, Float]) -> FloatScalar:
@@ -793,7 +793,7 @@ def _max_phase_diff(
 
         See also Eq.(7) in arXiv:2302.05333.
         """
-        gamma = jnp.array([-5., -2., 3., 5., 7.]) / 3
+        gamma = jnp.array([-5.0, -2.0, 3.0, 5.0, 7.0]) / 3
         freq_2D = jax.lax.broadcast_in_dim(freqs, (freqs.size, gamma.size), [0])
         f_star = jnp.where(gamma >= 0, f_high, f_low)
         summand = (freq_2D / f_star) ** gamma * jnp.sign(gamma)
@@ -823,7 +823,7 @@ def _compute_coefficients(
         h_ref: Complex[Array, " n_freq"],
         psd: Complex[Array, " n_freq"],
         freqs: Float[Array, " n_freq"],
-        f_bins: Float[Array, " n_bins+1"]
+        f_bins: Float[Array, " n_bins+1"],
     ) -> Complex[Array, "4 n_bins"]:
         df = freqs[1] - freqs[0]
         data_prod = jnp.array(data * h_ref.conj()) / psd

From 32cfc2ddc5eb509382f0a408f0688649170cd162 Mon Sep 17 00:00:00 2001
From: "Samson Leong (wkstn)" <55839002+SSL32081@users.noreply.github.com>
Date: Sat, 11 Jul 2026 03:45:53 +0800
Subject: [PATCH 03/17] Remove redundant variable definitions

---
 src/jimgw/core/single_event/likelihood.py | 16 ++++++----------
 1 file changed, 6 insertions(+), 10 deletions(-)

diff --git a/src/jimgw/core/single_event/likelihood.py b/src/jimgw/core/single_event/likelihood.py
index b4cc276a..e13ff9b0 100644
--- a/src/jimgw/core/single_event/likelihood.py
+++ b/src/jimgw/core/single_event/likelihood.py
@@ -829,25 +829,21 @@ def _compute_coefficients(
         data_prod = jnp.array(data * h_ref.conj()) / psd
         self_prod = jnp.array(h_ref * h_ref.conj()) / psd
 
-        freq_bins_left = f_bins[:-1]  # Shape: (n_bins)
-        freq_bins_right = f_bins[1:]  # Shape: (n_bins)
-        freq_bins_center = (freq_bins_left + freq_bins_right) / 2  # Shape: (n_bins)
-
         # Broadcasting for 2D frequencies
         freqs_broadcast = freqs[None, :]  # Shape: (1, n_freq)
-        left_bounds = freq_bins_left[:, None]  # Shpae: (n_bins, 1)
-        right_bounds = freq_bins_right[:, None]  # Shape: (n_bins, 1)
-        freq_bins_center_broadcast = freq_bins_center[:, None]  # Shape: (n_bins, 1)
+        freq_bins_left = f_bins[:-1][:, None]  # Shpae: (n_bins, 1)
+        freq_bins_right = f_bins[1:][:, None]  # Shape: (n_bins, 1)
+        freq_bins_center = (freq_bins_left + freq_bins_right) / 2
 
         # Shape: (n_bins, n_freq)
-        mask = (freqs_broadcast >= left_bounds) & (freqs_broadcast < right_bounds)
+        mask = (freqs_broadcast >= freq_bins_left) & (freqs_broadcast < freq_bins_right)
         # The half-open interval [left, right) excludes any frequency that lands
         # exactly on the upper edge of the last bin (f_bins[-1]).  This happens
         # whenever the interpolated bin edge coincides with the last discrete
         # frequency sample (common when the waveform reaches f_max).  Extend the
         # last row to a closed interval by OR-ing in the equality condition.
-        mask = mask.at[-1].set(mask[-1] | (freqs == freq_bins_right[-1]))
-        freq_shift_matrix = (freqs_broadcast - freq_bins_center_broadcast) * mask
+        mask = mask.at[-1].set(mask[-1] | (freqs == f_bins[-1]))
+        freq_shift_matrix = (freqs_broadcast - freq_bins_center) * mask
 
         # The resultant arrays have shape (n_bins), the dimension with "n_freq" is summed over.
         summary_data = jnp.array(

From 80468f3cb13fef919c845e0746744870e906f71e Mon Sep 17 00:00:00 2001
From: "Samson Leong (wkstn)" <55839002+SSL32081@users.noreply.github.com>
Date: Sat, 11 Jul 2026 03:48:34 +0800
Subject: [PATCH 04/17] Fix freq_grid reference before assignment

---
 src/jimgw/core/single_event/likelihood.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/jimgw/core/single_event/likelihood.py b/src/jimgw/core/single_event/likelihood.py
index e13ff9b0..126c7735 100644
--- a/src/jimgw/core/single_event/likelihood.py
+++ b/src/jimgw/core/single_event/likelihood.py
@@ -694,9 +694,9 @@ def __init__(
         freq_grid = self._make_binning_scheme(
             jnp.array(frequency_original), n_bins=self.n_bins
         )
-        self.bin_widths = self.freq_grid_high - self.freq_grid_low
         self.freq_grid_low = freq_grid[:-1]
         self.freq_grid_high = freq_grid[1:]
+        self.bin_widths = self.freq_grid_high - self.freq_grid_low
         h_sky = reference_waveform(frequency_original, self.reference_parameters)
 
         h_sky_low = reference_waveform(self.freq_grid_low, self.reference_parameters)

From cdd2b74f96e42854e07d7a8a2fac79f387c25ca8 Mon Sep 17 00:00:00 2001
From: "Samson Leong (wkstn)" <55839002+SSL32081@users.noreply.github.com>
Date: Sat, 11 Jul 2026 03:57:27 +0800
Subject: [PATCH 05/17] Passing detector object directly in
 compute_coefficients

---
 src/jimgw/core/single_event/likelihood.py | 17 +++++++----------
 1 file changed, 7 insertions(+), 10 deletions(-)

diff --git a/src/jimgw/core/single_event/likelihood.py b/src/jimgw/core/single_event/likelihood.py
index 126c7735..446bee45 100644
--- a/src/jimgw/core/single_event/likelihood.py
+++ b/src/jimgw/core/single_event/likelihood.py
@@ -714,11 +714,7 @@ def __init__(
                 self.freq_grid_high, h_sky_high, self.reference_parameters
             )
             self.summary_data[detector.name] = self._compute_coefficients(
-                detector.sliced_fd_data,
-                waveform_ref,
-                detector.sliced_psd,
-                detector.sliced_frequencies,
-                freq_grid,
+                detector, waveform_ref, freq_grid,
             )
 
     def evaluate(self, params: dict[str, Float]) -> FloatScalar:
@@ -819,13 +815,14 @@ def _make_binning_scheme(
 
     @staticmethod
     def _compute_coefficients(
-        data: Complex[Array, " n_freq"],
+        detector: Detector,
         h_ref: Complex[Array, " n_freq"],
-        psd: Complex[Array, " n_freq"],
-        freqs: Float[Array, " n_freq"],
         f_bins: Float[Array, " n_bins+1"],
     ) -> Complex[Array, "4 n_bins"]:
-        df = freqs[1] - freqs[0]
+        data = detector.sliced_fd_data
+        psd = detector.sliced_psd
+        freqs = detector.sliced_frequencies
+
         data_prod = jnp.array(data * h_ref.conj()) / psd
         self_prod = jnp.array(h_ref * h_ref.conj()) / psd
 
@@ -855,7 +852,7 @@ def _compute_coefficients(
             ]
         )
 
-        return 4 * df * summary_data
+        return 4 / detector.duration * summary_data
 
     def maximize_likelihood(
         self,

From 869d3579b1c8af090e0f9ea4b4acebf91acacf54 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Fri, 10 Jul 2026 19:57:36 +0000
Subject: [PATCH 06/17] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 src/jimgw/core/single_event/likelihood.py | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/src/jimgw/core/single_event/likelihood.py b/src/jimgw/core/single_event/likelihood.py
index 446bee45..9f3005d6 100644
--- a/src/jimgw/core/single_event/likelihood.py
+++ b/src/jimgw/core/single_event/likelihood.py
@@ -714,7 +714,9 @@ def __init__(
                 self.freq_grid_high, h_sky_high, self.reference_parameters
             )
             self.summary_data[detector.name] = self._compute_coefficients(
-                detector, waveform_ref, freq_grid,
+                detector,
+                waveform_ref,
+                freq_grid,
             )
 
     def evaluate(self, params: dict[str, Float]) -> FloatScalar:

From b88ec6923ff092f8721fccf19f33553f047e3389 Mon Sep 17 00:00:00 2001
From: "Samson Leong (wkstn)" <55839002+SSL32081@users.noreply.github.com>
Date: Sat, 11 Jul 2026 04:02:08 +0800
Subject: [PATCH 07/17] Update likelihood test

---
 tests/unit/core/single_event/test_likelihood.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/tests/unit/core/single_event/test_likelihood.py b/tests/unit/core/single_event/test_likelihood.py
index 7a9ca2c9..8152f079 100644
--- a/tests/unit/core/single_event/test_likelihood.py
+++ b/tests/unit/core/single_event/test_likelihood.py
@@ -1178,8 +1178,9 @@ def test_low_frequency_reference_cutoff_does_not_reindex_summary_data(
         requested_n_bins = 32
 
         def fake_compute_coefficients(
-            likelihood, data, h_ref, psd, freqs, f_bins, f_bins_center
+            likelihood, detector, h_ref, f_bins
         ):
+            freqs = detector.sliced_frequencies
             freqs_broadcast = freqs[None, :]
             left_bounds = f_bins[:-1][:, None]
             right_bounds = f_bins[1:][:, None]
@@ -1187,9 +1188,8 @@ def fake_compute_coefficients(
             mask = (freqs_broadcast >= left_bounds) & (freqs_broadcast < right_bounds)
 
             n_freqs = len(freqs)
-            n_bins = len(f_bins_center)
+            n_bins = len(f_bins) - 1
             assert n_freqs > len(f_bins), f"{n_freqs = }, {len(f_bins) = }"
-            assert len(f_bins) == n_bins + 1, f"{len(f_bins) = }, {n_bins = }"
             assert likelihood.n_bins == n_bins, f"{likelihood.n_bins = }, {n_bins = }"
             assert n_bins < requested_n_bins
             assert freqs[0] == fmin

From d46118dceba9659c90bc6a7721ce4158fd2c94ea Mon Sep 17 00:00:00 2001
From: "Samson Leong (wkstn)" <55839002+SSL32081@users.noreply.github.com>
Date: Sat, 11 Jul 2026 15:19:08 +0800
Subject: [PATCH 08/17] Adding back frequency mask

---
 src/jimgw/core/single_event/likelihood.py     | 116 ++++++++++------
 .../unit/core/single_event/test_likelihood.py | 129 +++++++++---------
 2 files changed, 138 insertions(+), 107 deletions(-)

diff --git a/src/jimgw/core/single_event/likelihood.py b/src/jimgw/core/single_event/likelihood.py
index 9f3005d6..ca201250 100644
--- a/src/jimgw/core/single_event/likelihood.py
+++ b/src/jimgw/core/single_event/likelihood.py
@@ -7,7 +7,7 @@
 from jaxtyping import Array, Float, Complex
 from jimgw.typing import ComplexScalar, FloatLike, FloatScalar
 from scipy.interpolate import interp1d
-from evosax.algorithms import CMA_ES
+# from evosax.algorithms import CMA_ES
 from ripplegw.interfaces import Waveform
 
 from jimgw.core.utils import log_i0, round_up_to_power_of_two
@@ -552,12 +552,12 @@ class HeterodynedTransientLikelihoodFD(SingleEventLikelihood):
     n_bins: int
     epsilon: float
     reference_parameters: dict
-    freq_grid_low: Float[Array, " n_bins"]
-    freq_grid_high: Float[Array, " n_bins"]
-    bin_widths: Float[Array, " n_bins"]
-    waveform_low_ref: dict[str, Complex[Array, " n_bins"]]
-    waveform_high_ref: dict[str, Complex[Array, " n_bins"]]
-    summary_data: dict[str, Complex[Array, "4 n_bins"]]
+    freq_grid_low: Float[Array, " n_valid"]
+    freq_grid_high: Float[Array, " n_valid"]
+    bin_widths: Float[Array, " n_valid"]
+    waveform_low_ref: dict[str, Complex[Array, " n_valid"]]
+    waveform_high_ref: dict[str, Complex[Array, " n_valid"]]
+    summary_data: dict[str, Complex[Array, "4 n_valid"]]
 
     def __init__(
         self,
@@ -684,39 +684,37 @@ def __init__(
                     f"'epsilon' must be a positive number, got {epsilon!r}."
                 )
             else:
-                freqs_arr = jnp.array(frequency_original)
+                freqs_arr = self.frequencies
                 phase = HeterodynedTransientLikelihoodFD._max_phase_diff(
                     freqs_arr, freqs_arr[0], freqs_arr[-1]
                 )
                 n_bins = max(1, int(float(phase[-1]) / epsilon))
         assert isinstance(n_bins, int)
-        self.n_bins = n_bins
         freq_grid = self._make_binning_scheme(
-            jnp.array(frequency_original), n_bins=self.n_bins
+            self.frequencies, n_bins=n_bins
         )
-        self.freq_grid_low = freq_grid[:-1]
-        self.freq_grid_high = freq_grid[1:]
-        self.bin_widths = self.freq_grid_high - self.freq_grid_low
-        h_sky = reference_waveform(frequency_original, self.reference_parameters)
+        ref_hpc = reference_waveform(self.frequencies, self.reference_parameters)
+
+        masked_freq_grid = self._mask_and_set_frequency_arrays(ref_hpc, freq_grid)
 
-        h_sky_low = reference_waveform(self.freq_grid_low, self.reference_parameters)
-        h_sky_high = reference_waveform(self.freq_grid_high, self.reference_parameters)
+        hpc_low = reference_waveform(self.freq_grid_low, self.reference_parameters)
+        hpc_high = reference_waveform(self.freq_grid_high, self.reference_parameters)
 
         for i, detector in enumerate(self.detectors):
-            h_sky_ifo = {key: h_sky[key][self.frequency_masks[i]] for key in h_sky}
+            hpc_ifo = {key: ref_hpc[key][self.frequency_masks[i]] for key in ref_hpc}
             waveform_ref = detector.fd_response(
-                detector.sliced_frequencies, h_sky_ifo, self.reference_parameters
+                detector.sliced_frequencies, hpc_ifo, self.reference_parameters
             )
             self.waveform_low_ref[detector.name] = detector.fd_response(
-                self.freq_grid_low, h_sky_low, self.reference_parameters
+                self.freq_grid_low, hpc_low, self.reference_parameters
             )
             self.waveform_high_ref[detector.name] = detector.fd_response(
-                self.freq_grid_high, h_sky_high, self.reference_parameters
+                self.freq_grid_high, hpc_high, self.reference_parameters
             )
             self.summary_data[detector.name] = self._compute_coefficients(
                 detector,
                 waveform_ref,
-                freq_grid,
+                masked_freq_grid,
             )
 
     def evaluate(self, params: dict[str, Float]) -> FloatScalar:
@@ -772,6 +770,55 @@ def _likelihood(self, params: dict[str, Float]) -> FloatScalar:
 
         return log_likelihood
 
+    def _make_binning_scheme(
+        self,
+        freqs: Float[Array, " n_freq"],
+        n_bins: int,
+        chi: float = 1.0,
+    ) -> Float[Array, " n_bins + 1"]:
+        """Make ``n_bins`` frequency bins of equal phase change.
+
+        ``n_bins`` must be a positive integer resolved by the caller
+        (see :meth:`__init__`).
+        """
+        phase_diff_array = self._max_phase_diff(freqs, freqs[0], freqs[-1], chi=chi)
+        total_phase = phase_diff_array[-1]
+        phase_diff = jnp.linspace(0.0, total_phase, n_bins + 1)
+        f_bins = interp1d(phase_diff_array, freqs)(phase_diff)
+        return jnp.array(f_bins)
+
+    def _mask_and_set_frequency_arrays(
+        self, 
+        waveform: dict[str, Complex[Array, " n_freq"]], 
+        frequencies: Float[Array, " n_freq"]
+    ) -> Float[Array, " n_valid+1"]:
+        '''
+        Mask out trivial waveform pieces which are usually beyond merger frequency.
+
+        This is to avoid creating NaNs from 0/0 when computing the r0 and r1, 
+        where the ratios between waveforms are taken.
+
+        Remark:
+            The following operations change array shapes dynamically, which is 
+            not jittable. In the future, if jax.jit is preferable, this has to 
+            be scrapped, and then when computing the likelihood (inside _likelihood),
+            replace jnp.sum with jnp.nansum.
+            The current implementation has the advantage of greatly reducing memory
+            usage when the detector f_max is larger than merger frequency.
+        '''
+        h_amp = jnp.array([jnp.abs(p) for p in waveform.values()]).sum(axis=0)
+        _valid_frequencies = self.frequencies[h_amp > 0]
+        valid_mask = (frequencies >= _valid_frequencies[0]) & \
+            (frequencies <= _valid_frequencies[-1])
+
+        masked_frequencies = frequencies[valid_mask]
+        self.freq_grid_low = masked_frequencies[:-1]
+        self.freq_grid_high = masked_frequencies[1:]
+        self.nbins = len(masked_frequencies) - 1
+        self.bin_widths = self.freq_grid_high - self.freq_grid_low
+
+        return masked_frequencies
+
     @staticmethod
     def _max_phase_diff(
         freqs: Float[Array, " n_freq"],
@@ -798,29 +845,12 @@ def _max_phase_diff(
         dphi = 2 * jnp.pi * chi * jnp.sum(summand, axis=1)
         return dphi - dphi[0]
 
-    def _make_binning_scheme(
-        self,
-        freqs: Float[Array, " n_freq"],
-        n_bins: int,
-        chi: float = 1.0,
-    ) -> Float[Array, " n_bins + 1"]:
-        """Make ``n_bins`` frequency bins of equal phase change.
-
-        ``n_bins`` must be a positive integer resolved by the caller
-        (see :meth:`__init__`).
-        """
-        phase_diff_array = self._max_phase_diff(freqs, freqs[0], freqs[-1], chi=chi)
-        total_phase = phase_diff_array[-1]
-        phase_diff = jnp.linspace(0.0, total_phase, n_bins + 1)
-        f_bins = interp1d(phase_diff_array, freqs)(phase_diff)
-        return jnp.array(f_bins)
-
     @staticmethod
     def _compute_coefficients(
         detector: Detector,
         h_ref: Complex[Array, " n_freq"],
-        f_bins: Float[Array, " n_bins+1"],
-    ) -> Complex[Array, "4 n_bins"]:
+        f_bins: Float[Array, " n_valid+1"],
+    ) -> Complex[Array, "4 n_valid"]:
         data = detector.sliced_fd_data
         psd = detector.sliced_psd
         freqs = detector.sliced_frequencies
@@ -830,8 +860,8 @@ def _compute_coefficients(
 
         # Broadcasting for 2D frequencies
         freqs_broadcast = freqs[None, :]  # Shape: (1, n_freq)
-        freq_bins_left = f_bins[:-1][:, None]  # Shpae: (n_bins, 1)
-        freq_bins_right = f_bins[1:][:, None]  # Shape: (n_bins, 1)
+        freq_bins_left = self.freq_grid_low[:, None]  # Shpae: (n_bins, 1)
+        freq_bins_right = self.freq_grid_high[:, None]  # Shape: (n_bins, 1)
         freq_bins_center = (freq_bins_left + freq_bins_right) / 2
 
         # Shape: (n_bins, n_freq)
@@ -854,7 +884,7 @@ def _compute_coefficients(
             ]
         )
 
-        return 4 / detector.duration * summary_data
+        return 4 * summary_data / detector.duration
 
     def maximize_likelihood(
         self,
diff --git a/tests/unit/core/single_event/test_likelihood.py b/tests/unit/core/single_event/test_likelihood.py
index 8152f079..c37e7dae 100644
--- a/tests/unit/core/single_event/test_likelihood.py
+++ b/tests/unit/core/single_event/test_likelihood.py
@@ -1040,9 +1040,10 @@ def test_initialization_stores_attributes(self, detectors_and_waveform):
         assert hasattr(likelihood, "freq_grid_high")
         assert hasattr(likelihood, "bin_widths")
         for det in ifos:
-            assert det.name in likelihood.summary_data
-            assert det.name in likelihood.waveform_low_ref
-            assert det.name in likelihood.waveform_high_ref
+            for attr in ("summary_data", "waveform_low_ref", "waveform_high_ref"):
+                obj = getattr(likelihood, attr)
+                assert det.name in obj
+                assert jnp.isfinite(obj[det.name]).all()
 
     def test_no_reference_params_and_no_prior_raises(self, detectors_and_waveform):
         ifos, waveform, fmin, fmax, gps = detectors_and_waveform
@@ -1170,67 +1171,67 @@ def test_maximize_likelihood(self, detectors_and_waveform):
         assert jnp.isclose(float(base.evaluate(result)), ll_injected)
         common_keys_allclose(result, true_params)
 
-    def test_low_frequency_reference_cutoff_does_not_reindex_summary_data(
-        self, detectors_and_waveform, monkeypatch
-    ):
-        ifos, waveform, fmin, fmax, gps = detectors_and_waveform
-        reference_fmin = 80.0
-        requested_n_bins = 32
-
-        def fake_compute_coefficients(
-            likelihood, detector, h_ref, f_bins
-        ):
-            freqs = detector.sliced_frequencies
-            freqs_broadcast = freqs[None, :]
-            left_bounds = f_bins[:-1][:, None]
-            right_bounds = f_bins[1:][:, None]
-
-            mask = (freqs_broadcast >= left_bounds) & (freqs_broadcast < right_bounds)
-
-            n_freqs = len(freqs)
-            n_bins = len(f_bins) - 1
-            assert n_freqs > len(f_bins), f"{n_freqs = }, {len(f_bins) = }"
-            assert likelihood.n_bins == n_bins, f"{likelihood.n_bins = }, {n_bins = }"
-            assert n_bins < requested_n_bins
-            assert freqs[0] == fmin
-            assert f_bins[0] >= reference_fmin
-            assert mask.shape == (n_bins, n_freqs), (
-                f"{mask.shape = }, expected: ({n_bins}, {n_freqs})"
-            )
-            coeffs = jnp.arange(n_bins, dtype=jnp.float64)
-            return jnp.array([coeffs + nn * 100 for nn in range(4)])
-
-        monkeypatch.setattr(
-            HeterodynedTransientLikelihoodFD,
-            "_compute_coefficients",
-            fake_compute_coefficients,
-        )
-
-        def reference_waveform(frequencies, params):
-            waveform_sky = waveform(frequencies, params)
-            mask = frequencies >= reference_fmin
-            return {
-                polarization: jnp.where(mask, strain, jnp.zeros_like(strain))
-                for polarization, strain in waveform_sky.items()
-            }
-
-        likelihood = HeterodynedTransientLikelihoodFD(
-            detectors=ifos,
-            waveform=waveform,
-            reference_waveform=reference_waveform,
-            f_min=fmin,
-            f_max=fmax,
-            trigger_time=gps,
-            n_bins=requested_n_bins,
-            reference_parameters=example_params(),
-        )
-        assert likelihood.n_bins < requested_n_bins
-        assert likelihood.freq_grid_low[0] >= reference_fmin
-
-        expected = jnp.arange(likelihood.n_bins, dtype=jnp.float64)
-        expected_arr = jnp.array([expected + nn * 100 for nn in range(4)])
-        for detector in ifos:
-            assert jnp.array_equal(likelihood.summary_data[detector.name], expected_arr)
+    # def test_low_frequency_reference_cutoff_does_not_reindex_summary_data(
+    #     self, detectors_and_waveform, monkeypatch
+    # ):
+    #     ifos, waveform, fmin, fmax, gps = detectors_and_waveform
+    #     reference_fmin = 80.0
+    #     requested_n_bins = 32
+
+    #     def fake_compute_coefficients(
+    #         likelihood, detector, h_ref, f_bins
+    #     ):
+    #         freqs = detector.sliced_frequencies
+    #         freqs_broadcast = freqs[None, :]
+    #         left_bounds = f_bins[:-1][:, None]
+    #         right_bounds = f_bins[1:][:, None]
+
+    #         mask = (freqs_broadcast >= left_bounds) & (freqs_broadcast < right_bounds)
+
+    #         n_freqs = len(freqs)
+    #         n_bins = len(f_bins) - 1
+    #         assert n_freqs > len(f_bins), f"{n_freqs = }, {len(f_bins) = }"
+    #         assert likelihood.n_bins == n_bins, f"{likelihood.n_bins = }, {n_bins = }"
+    #         assert n_bins <= requested_n_bins
+    #         assert freqs[0] == fmin
+    #         assert f_bins[0] >= reference_fmin
+    #         assert mask.shape == (n_bins, n_freqs), (
+    #             f"{mask.shape = }, expected: ({n_bins}, {n_freqs})"
+    #         )
+    #         coeffs = jnp.arange(n_bins, dtype=jnp.float64)
+    #         return jnp.array([coeffs + nn * 100 for nn in range(4)])
+
+    #     monkeypatch.setattr(
+    #         HeterodynedTransientLikelihoodFD,
+    #         "_compute_coefficients",
+    #         fake_compute_coefficients,
+    #     )
+
+    #     def reference_waveform(frequencies, params):
+    #         waveform_sky = waveform(frequencies, params)
+    #         mask = frequencies >= reference_fmin
+    #         return {
+    #             polarization: jnp.where(mask, strain, jnp.zeros_like(strain))
+    #             for polarization, strain in waveform_sky.items()
+    #         }
+
+    #     likelihood = HeterodynedTransientLikelihoodFD(
+    #         detectors=ifos,
+    #         waveform=waveform,
+    #         reference_waveform=reference_waveform,
+    #         f_min=fmin,
+    #         f_max=fmax,
+    #         trigger_time=gps,
+    #         n_bins=requested_n_bins,
+    #         reference_parameters=example_params(),
+    #     )
+    #     assert likelihood.n_bins < requested_n_bins
+    #     assert likelihood.freq_grid_low[0] >= reference_fmin
+
+    #     expected = jnp.arange(likelihood.n_bins, dtype=jnp.float64)
+    #     expected_arr = jnp.array([expected + nn * 100 for nn in range(4)])
+    #     for detector in ifos:
+    #         assert jnp.array_equal(likelihood.summary_data[detector.name], expected_arr)
 
     # ── Phase marginalization ──────────────────────────────────────────────────
 

From 2d34459eb2e4fc3fd16a0b63357f28616b474298 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Sat, 11 Jul 2026 07:19:22 +0000
Subject: [PATCH 09/17] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 src/jimgw/core/single_event/likelihood.py | 26 +++++++++++------------
 1 file changed, 13 insertions(+), 13 deletions(-)

diff --git a/src/jimgw/core/single_event/likelihood.py b/src/jimgw/core/single_event/likelihood.py
index ca201250..578f8d0f 100644
--- a/src/jimgw/core/single_event/likelihood.py
+++ b/src/jimgw/core/single_event/likelihood.py
@@ -7,6 +7,7 @@
 from jaxtyping import Array, Float, Complex
 from jimgw.typing import ComplexScalar, FloatLike, FloatScalar
 from scipy.interpolate import interp1d
+
 # from evosax.algorithms import CMA_ES
 from ripplegw.interfaces import Waveform
 
@@ -690,9 +691,7 @@ def __init__(
                 )
                 n_bins = max(1, int(float(phase[-1]) / epsilon))
         assert isinstance(n_bins, int)
-        freq_grid = self._make_binning_scheme(
-            self.frequencies, n_bins=n_bins
-        )
+        freq_grid = self._make_binning_scheme(self.frequencies, n_bins=n_bins)
         ref_hpc = reference_waveform(self.frequencies, self.reference_parameters)
 
         masked_freq_grid = self._mask_and_set_frequency_arrays(ref_hpc, freq_grid)
@@ -788,28 +787,29 @@ def _make_binning_scheme(
         return jnp.array(f_bins)
 
     def _mask_and_set_frequency_arrays(
-        self, 
-        waveform: dict[str, Complex[Array, " n_freq"]], 
-        frequencies: Float[Array, " n_freq"]
+        self,
+        waveform: dict[str, Complex[Array, " n_freq"]],
+        frequencies: Float[Array, " n_freq"],
     ) -> Float[Array, " n_valid+1"]:
-        '''
+        """
         Mask out trivial waveform pieces which are usually beyond merger frequency.
 
-        This is to avoid creating NaNs from 0/0 when computing the r0 and r1, 
+        This is to avoid creating NaNs from 0/0 when computing the r0 and r1,
         where the ratios between waveforms are taken.
 
         Remark:
-            The following operations change array shapes dynamically, which is 
-            not jittable. In the future, if jax.jit is preferable, this has to 
+            The following operations change array shapes dynamically, which is
+            not jittable. In the future, if jax.jit is preferable, this has to
             be scrapped, and then when computing the likelihood (inside _likelihood),
             replace jnp.sum with jnp.nansum.
             The current implementation has the advantage of greatly reducing memory
             usage when the detector f_max is larger than merger frequency.
-        '''
+        """
         h_amp = jnp.array([jnp.abs(p) for p in waveform.values()]).sum(axis=0)
         _valid_frequencies = self.frequencies[h_amp > 0]
-        valid_mask = (frequencies >= _valid_frequencies[0]) & \
-            (frequencies <= _valid_frequencies[-1])
+        valid_mask = (frequencies >= _valid_frequencies[0]) & (
+            frequencies <= _valid_frequencies[-1]
+        )
 
         masked_frequencies = frequencies[valid_mask]
         self.freq_grid_low = masked_frequencies[:-1]

From a730282abb6bca5c89d32fa4c673dd0cfa18e4bf Mon Sep 17 00:00:00 2001
From: "Samson Leong (wkstn)" <55839002+SSL32081@users.noreply.github.com>
Date: Sat, 11 Jul 2026 15:22:07 +0800
Subject: [PATCH 10/17] Fix merge conflict

---
 src/jimgw/core/single_event/likelihood.py | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/src/jimgw/core/single_event/likelihood.py b/src/jimgw/core/single_event/likelihood.py
index 578f8d0f..dba595fd 100644
--- a/src/jimgw/core/single_event/likelihood.py
+++ b/src/jimgw/core/single_event/likelihood.py
@@ -7,8 +7,7 @@
 from jaxtyping import Array, Float, Complex
 from jimgw.typing import ComplexScalar, FloatLike, FloatScalar
 from scipy.interpolate import interp1d
-
-# from evosax.algorithms import CMA_ES
+from evosax.algorithms import CMA_ES
 from ripplegw.interfaces import Waveform
 
 from jimgw.core.utils import log_i0, round_up_to_power_of_two

From f840eaf5c546913451648d73bda323aec5630791 Mon Sep 17 00:00:00 2001
From: "Samson Leong (wkstn)" <55839002+SSL32081@users.noreply.github.com>
Date: Sat, 11 Jul 2026 15:21:29 +0800
Subject: [PATCH 11/17] Minor order change

---
 src/jimgw/core/single_event/likelihood.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/jimgw/core/single_event/likelihood.py b/src/jimgw/core/single_event/likelihood.py
index dba595fd..d487ced2 100644
--- a/src/jimgw/core/single_event/likelihood.py
+++ b/src/jimgw/core/single_event/likelihood.py
@@ -883,7 +883,7 @@ def _compute_coefficients(
             ]
         )
 
-        return 4 * summary_data / detector.duration
+        return 4 / detector.duration * summary_data
 
     def maximize_likelihood(
         self,

From f2fd27c46180a03ae07286e34143776f8409a897 Mon Sep 17 00:00:00 2001
From: "Samson Leong (wkstn)" <55839002+SSL32081@users.noreply.github.com>
Date: Sat, 11 Jul 2026 15:26:08 +0800
Subject: [PATCH 12/17] Restore indices test in likelihood test

---
 src/jimgw/core/single_event/likelihood.py     |   8 +-
 .../unit/core/single_event/test_likelihood.py | 122 +++++++++---------
 2 files changed, 65 insertions(+), 65 deletions(-)

diff --git a/src/jimgw/core/single_event/likelihood.py b/src/jimgw/core/single_event/likelihood.py
index d487ced2..ac6b4ebb 100644
--- a/src/jimgw/core/single_event/likelihood.py
+++ b/src/jimgw/core/single_event/likelihood.py
@@ -859,11 +859,11 @@ def _compute_coefficients(
 
         # Broadcasting for 2D frequencies
         freqs_broadcast = freqs[None, :]  # Shape: (1, n_freq)
-        freq_bins_left = self.freq_grid_low[:, None]  # Shpae: (n_bins, 1)
-        freq_bins_right = self.freq_grid_high[:, None]  # Shape: (n_bins, 1)
+        freq_bins_left = self.freq_grid_low[:, None]  # Shpae: (n_valid, 1)
+        freq_bins_right = self.freq_grid_high[:, None]  # Shape: (n_valid, 1)
         freq_bins_center = (freq_bins_left + freq_bins_right) / 2
 
-        # Shape: (n_bins, n_freq)
+        # Shape: (n_valid, n_freq)
         mask = (freqs_broadcast >= freq_bins_left) & (freqs_broadcast < freq_bins_right)
         # The half-open interval [left, right) excludes any frequency that lands
         # exactly on the upper edge of the last bin (f_bins[-1]).  This happens
@@ -873,7 +873,7 @@ def _compute_coefficients(
         mask = mask.at[-1].set(mask[-1] | (freqs == f_bins[-1]))
         freq_shift_matrix = (freqs_broadcast - freq_bins_center) * mask
 
-        # The resultant arrays have shape (n_bins), the dimension with "n_freq" is summed over.
+        # The resultant arrays have shape (n_valid), the dimension with "n_freq" is summed over.
         summary_data = jnp.array(
             [
                 jnp.sum(data_prod[None, :] * mask, axis=1),  # A0
diff --git a/tests/unit/core/single_event/test_likelihood.py b/tests/unit/core/single_event/test_likelihood.py
index c37e7dae..f9e6ee01 100644
--- a/tests/unit/core/single_event/test_likelihood.py
+++ b/tests/unit/core/single_event/test_likelihood.py
@@ -1171,67 +1171,67 @@ def test_maximize_likelihood(self, detectors_and_waveform):
         assert jnp.isclose(float(base.evaluate(result)), ll_injected)
         common_keys_allclose(result, true_params)
 
-    # def test_low_frequency_reference_cutoff_does_not_reindex_summary_data(
-    #     self, detectors_and_waveform, monkeypatch
-    # ):
-    #     ifos, waveform, fmin, fmax, gps = detectors_and_waveform
-    #     reference_fmin = 80.0
-    #     requested_n_bins = 32
-
-    #     def fake_compute_coefficients(
-    #         likelihood, detector, h_ref, f_bins
-    #     ):
-    #         freqs = detector.sliced_frequencies
-    #         freqs_broadcast = freqs[None, :]
-    #         left_bounds = f_bins[:-1][:, None]
-    #         right_bounds = f_bins[1:][:, None]
-
-    #         mask = (freqs_broadcast >= left_bounds) & (freqs_broadcast < right_bounds)
-
-    #         n_freqs = len(freqs)
-    #         n_bins = len(f_bins) - 1
-    #         assert n_freqs > len(f_bins), f"{n_freqs = }, {len(f_bins) = }"
-    #         assert likelihood.n_bins == n_bins, f"{likelihood.n_bins = }, {n_bins = }"
-    #         assert n_bins <= requested_n_bins
-    #         assert freqs[0] == fmin
-    #         assert f_bins[0] >= reference_fmin
-    #         assert mask.shape == (n_bins, n_freqs), (
-    #             f"{mask.shape = }, expected: ({n_bins}, {n_freqs})"
-    #         )
-    #         coeffs = jnp.arange(n_bins, dtype=jnp.float64)
-    #         return jnp.array([coeffs + nn * 100 for nn in range(4)])
-
-    #     monkeypatch.setattr(
-    #         HeterodynedTransientLikelihoodFD,
-    #         "_compute_coefficients",
-    #         fake_compute_coefficients,
-    #     )
-
-    #     def reference_waveform(frequencies, params):
-    #         waveform_sky = waveform(frequencies, params)
-    #         mask = frequencies >= reference_fmin
-    #         return {
-    #             polarization: jnp.where(mask, strain, jnp.zeros_like(strain))
-    #             for polarization, strain in waveform_sky.items()
-    #         }
-
-    #     likelihood = HeterodynedTransientLikelihoodFD(
-    #         detectors=ifos,
-    #         waveform=waveform,
-    #         reference_waveform=reference_waveform,
-    #         f_min=fmin,
-    #         f_max=fmax,
-    #         trigger_time=gps,
-    #         n_bins=requested_n_bins,
-    #         reference_parameters=example_params(),
-    #     )
-    #     assert likelihood.n_bins < requested_n_bins
-    #     assert likelihood.freq_grid_low[0] >= reference_fmin
-
-    #     expected = jnp.arange(likelihood.n_bins, dtype=jnp.float64)
-    #     expected_arr = jnp.array([expected + nn * 100 for nn in range(4)])
-    #     for detector in ifos:
-    #         assert jnp.array_equal(likelihood.summary_data[detector.name], expected_arr)
+    def test_low_frequency_reference_cutoff_does_not_reindex_summary_data(
+        self, detectors_and_waveform, monkeypatch
+    ):
+        ifos, waveform, fmin, fmax, gps = detectors_and_waveform
+        reference_fmin = 80.0
+        requested_n_bins = 32
+
+        def fake_compute_coefficients(
+            likelihood, detector, h_ref, f_bins
+        ):
+            freqs = detector.sliced_frequencies
+            freqs_broadcast = freqs[None, :]
+            left_bounds = f_bins[:-1][:, None]
+            right_bounds = f_bins[1:][:, None]
+
+            mask = (freqs_broadcast >= left_bounds) & (freqs_broadcast < right_bounds)
+
+            n_freqs = len(freqs)
+            n_bins = len(f_bins) - 1
+            assert n_freqs > len(f_bins), f"{n_freqs = }, {len(f_bins) = }"
+            assert likelihood.n_bins == n_bins, f"{likelihood.n_bins = }, {n_bins = }"
+            assert n_bins <= requested_n_bins
+            assert freqs[0] == fmin
+            assert f_bins[0] >= reference_fmin
+            assert mask.shape == (n_bins, n_freqs), (
+                f"{mask.shape = }, expected: ({n_bins}, {n_freqs})"
+            )
+            coeffs = jnp.arange(n_bins, dtype=jnp.float64)
+            return jnp.array([coeffs + nn * 100 for nn in range(4)])
+
+        monkeypatch.setattr(
+            HeterodynedTransientLikelihoodFD,
+            "_compute_coefficients",
+            fake_compute_coefficients,
+        )
+
+        def reference_waveform(frequencies, params):
+            waveform_sky = waveform(frequencies, params)
+            mask = frequencies >= reference_fmin
+            return {
+                polarization: jnp.where(mask, strain, jnp.zeros_like(strain))
+                for polarization, strain in waveform_sky.items()
+            }
+
+        likelihood = HeterodynedTransientLikelihoodFD(
+            detectors=ifos,
+            waveform=waveform,
+            reference_waveform=reference_waveform,
+            f_min=fmin,
+            f_max=fmax,
+            trigger_time=gps,
+            n_bins=requested_n_bins,
+            reference_parameters=example_params(),
+        )
+        assert likelihood.n_bins < requested_n_bins
+        assert likelihood.freq_grid_low[0] >= reference_fmin
+
+        expected = jnp.arange(likelihood.n_bins, dtype=jnp.float64)
+        expected_arr = jnp.array([expected + nn * 100 for nn in range(4)])
+        for detector in ifos:
+            assert jnp.array_equal(likelihood.summary_data[detector.name], expected_arr)
 
     # ── Phase marginalization ──────────────────────────────────────────────────
 

From d9816c5dd6a00f23e6936f19e3a6f707181d51ec Mon Sep 17 00:00:00 2001
From: "Samson Leong (wkstn)" <55839002+SSL32081@users.noreply.github.com>
Date: Sat, 11 Jul 2026 15:38:39 +0800
Subject: [PATCH 13/17] Fix self reference in staticmethod

---
 src/jimgw/core/single_event/likelihood.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/src/jimgw/core/single_event/likelihood.py b/src/jimgw/core/single_event/likelihood.py
index ac6b4ebb..d6b9150c 100644
--- a/src/jimgw/core/single_event/likelihood.py
+++ b/src/jimgw/core/single_event/likelihood.py
@@ -859,8 +859,8 @@ def _compute_coefficients(
 
         # Broadcasting for 2D frequencies
         freqs_broadcast = freqs[None, :]  # Shape: (1, n_freq)
-        freq_bins_left = self.freq_grid_low[:, None]  # Shpae: (n_valid, 1)
-        freq_bins_right = self.freq_grid_high[:, None]  # Shape: (n_valid, 1)
+        freq_bins_left = freqs[:-1][:, None]  # Shpae: (n_valid, 1)
+        freq_bins_right = freqs[1:][:, None]  # Shape: (n_valid, 1)
         freq_bins_center = (freq_bins_left + freq_bins_right) / 2
 
         # Shape: (n_valid, n_freq)

From a0c0f1e3917f101e9a56e16fe7c65f45b8e84684 Mon Sep 17 00:00:00 2001
From: "Samson Leong (wkstn)" <55839002+SSL32081@users.noreply.github.com>
Date: Sat, 11 Jul 2026 15:39:49 +0800
Subject: [PATCH 14/17] Rename nbins to n_bins

---
 src/jimgw/core/single_event/likelihood.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/jimgw/core/single_event/likelihood.py b/src/jimgw/core/single_event/likelihood.py
index d6b9150c..b161ab81 100644
--- a/src/jimgw/core/single_event/likelihood.py
+++ b/src/jimgw/core/single_event/likelihood.py
@@ -813,7 +813,7 @@ def _mask_and_set_frequency_arrays(
         masked_frequencies = frequencies[valid_mask]
         self.freq_grid_low = masked_frequencies[:-1]
         self.freq_grid_high = masked_frequencies[1:]
-        self.nbins = len(masked_frequencies) - 1
+        self.n_bins = len(masked_frequencies) - 1
         self.bin_widths = self.freq_grid_high - self.freq_grid_low
 
         return masked_frequencies

From 270bd0808964cd79d7f047a0621dcaa8831fb2d5 Mon Sep 17 00:00:00 2001
From: "Samson Leong (wkstn)" <55839002+SSL32081@users.noreply.github.com>
Date: Sat, 11 Jul 2026 15:43:21 +0800
Subject: [PATCH 15/17] Minor syntax fixes

---
 src/jimgw/core/single_event/likelihood.py | 5 ++---
 1 file changed, 2 insertions(+), 3 deletions(-)

diff --git a/src/jimgw/core/single_event/likelihood.py b/src/jimgw/core/single_event/likelihood.py
index b161ab81..8a630763 100644
--- a/src/jimgw/core/single_event/likelihood.py
+++ b/src/jimgw/core/single_event/likelihood.py
@@ -665,7 +665,6 @@ def __init__(
         self.waveform_high_ref = {}
         self.summary_data = {}
 
-        frequency_original = self.frequencies
         if n_bins is not None:
             if epsilon is not None:
                 raise ValueError(
@@ -691,8 +690,8 @@ def __init__(
                 n_bins = max(1, int(float(phase[-1]) / epsilon))
         assert isinstance(n_bins, int)
         freq_grid = self._make_binning_scheme(self.frequencies, n_bins=n_bins)
-        ref_hpc = reference_waveform(self.frequencies, self.reference_parameters)
 
+        ref_hpc = reference_waveform(self.frequencies, self.reference_parameters)
         masked_freq_grid = self._mask_and_set_frequency_arrays(ref_hpc, freq_grid)
 
         hpc_low = reference_waveform(self.freq_grid_low, self.reference_parameters)
@@ -773,7 +772,7 @@ def _make_binning_scheme(
         freqs: Float[Array, " n_freq"],
         n_bins: int,
         chi: float = 1.0,
-    ) -> Float[Array, " n_bins + 1"]:
+    ) -> Float[Array, " n_bins+1"]:
         """Make ``n_bins`` frequency bins of equal phase change.
 
         ``n_bins`` must be a positive integer resolved by the caller

From 1f22d81e9a522f340f7bc4ec4a3852f5e9d53c16 Mon Sep 17 00:00:00 2001
From: "Samson Leong (wkstn)" <55839002+SSL32081@users.noreply.github.com>
Date: Sat, 11 Jul 2026 21:53:08 +0800
Subject: [PATCH 16/17] Fix freq_bins in compute coefficients

---
 src/jimgw/core/single_event/likelihood.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/src/jimgw/core/single_event/likelihood.py b/src/jimgw/core/single_event/likelihood.py
index 8a630763..d5b9b9a2 100644
--- a/src/jimgw/core/single_event/likelihood.py
+++ b/src/jimgw/core/single_event/likelihood.py
@@ -858,8 +858,8 @@ def _compute_coefficients(
 
         # Broadcasting for 2D frequencies
         freqs_broadcast = freqs[None, :]  # Shape: (1, n_freq)
-        freq_bins_left = freqs[:-1][:, None]  # Shpae: (n_valid, 1)
-        freq_bins_right = freqs[1:][:, None]  # Shape: (n_valid, 1)
+        freq_bins_left = f_bins[:-1][:, None]  # Shpae: (n_valid, 1)
+        freq_bins_right = f_bins[1:][:, None]  # Shape: (n_valid, 1)
         freq_bins_center = (freq_bins_left + freq_bins_right) / 2
 
         # Shape: (n_valid, n_freq)

From 6ebfcfd655286509781ac9f6d04fe4f15f3b3d10 Mon Sep 17 00:00:00 2001
From: Thomas Ng <thomas.ng@nikhef.nl>
Date: Mon, 13 Jul 2026 12:42:10 +0200
Subject: [PATCH 17/17] Update lockfile

---
 uv.lock | 382 ++++++++++++++++++++++++++++----------------------------
 1 file changed, 191 insertions(+), 191 deletions(-)

diff --git a/uv.lock b/uv.lock
index 15659089..21a6ff0b 100644
--- a/uv.lock
+++ b/uv.lock
@@ -95,11 +95,11 @@ wheels = [
 
 [[package]]
 name = "astropy-iers-data"
-version = "0.2026.7.6.1.1.20"
+version = "0.2026.7.13.0.54.2"
 source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/7f/e3/d32d2401c53fa1aaf118c963c51c4eb9cd10d074a72a52430904dc8ef46e/astropy_iers_data-0.2026.7.6.1.1.20.tar.gz", hash = "sha256:bc38de235802c9f006c8a04693706e2adcc9e7ac1cbf415dc042b5f0ac14f1f3", size = 1939850, upload-time = "2026-07-06T01:02:02.379Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/b7/f2/8e52b70264edc5664c069939224405c6e9085fa3388403b8313303a62b82/astropy_iers_data-0.2026.7.13.0.54.2.tar.gz", hash = "sha256:d86e32e95e98a86f83b5b073627442924a0f45cf61a7828da4f565a17d726c2f", size = 1941259, upload-time = "2026-07-13T00:54:51.205Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/8c/a3/1d816863674c610234afef9a444d4eb562689a3fa1a872ac5687b4e0eac4/astropy_iers_data-0.2026.7.6.1.1.20-py3-none-any.whl", hash = "sha256:7aa50fa7f6d13258357d1e17fa97f3a8c2f04b9a7429d056e986a91cc46576a0", size = 1994649, upload-time = "2026-07-06T01:02:00.977Z" },
+    { url = "https://files.pythonhosted.org/packages/7b/54/121240c06fff63d358f2a96187e927d05628fdf933a84246151954e95c7a/astropy_iers_data-0.2026.7.13.0.54.2-py3-none-any.whl", hash = "sha256:0f0b22f43d0917d78382f35ef13acd72600752d65289a3f91e39ea67653264cd", size = 1996278, upload-time = "2026-07-13T00:54:49.386Z" },
 ]
 
 [[package]]
@@ -197,8 +197,8 @@ wheels = [
 
 [[package]]
 name = "blackjax"
-version = "1.6.dev120+g8bf703f4a"
-source = { git = "https://github.com/blackjax-devs/blackjax.git#8bf703f4a2407151ad9d76212f4e68d9c95f6544" }
+version = "1.7.dev9+gdbe43b69e"
+source = { git = "https://github.com/blackjax-devs/blackjax.git#dbe43b69e28d6f81c04718eb2d6b72de4d961bac" }
 dependencies = [
     { name = "jax" },
     { name = "jaxlib" },
@@ -535,86 +535,86 @@ wheels = [
 
 [[package]]
 name = "coverage"
-version = "7.15.0"
-source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/cc/8b/adeb62ea8951f13c4c7fef2e7a85e1a06b499c8d8237ea589d496029e53f/coverage-7.15.0.tar.gz", hash = "sha256:9ac3fe7a1435986463eaa8ee253ae2f2a268709ba4ae5c7dd1f52a05391ad78f", size = 925362, upload-time = "2026-07-02T13:10:50.535Z" }
-wheels = [
-    { url = "https://files.pythonhosted.org/packages/ae/23/82e910835ef4b8391047025e1d53aa48d66029f444eb8b25373c849bf503/coverage-7.15.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:003fff99412ea848c0aaebcc78ed2b6ce7d8a1227ed17e68470672770b78a02a", size = 220662, upload-time = "2026-07-02T13:08:39.205Z" },
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