diff --git a/docs/source/conf.py b/docs/source/conf.py
index 5d6dfa444..0f515871f 100644
--- a/docs/source/conf.py
+++ b/docs/source/conf.py
@@ -124,6 +124,7 @@
     (r"py:.*", r".*numpy._typing._array_like._ScalarType_co.*"),
     (r"py:.*", r".*idex.l1a.TRIGGER_DESCRIPTION.*"),
     (r"py:.*", r".*idex.l1b.TriggerOrigin.*"),
+    (r"py:.*", r".*idex.l1b.EventMessage.*"),
     (r"py:.*", r".*idex.l2a.BaselineNoiseTime.*"),
     (r"py:.*", r".*PacketProperties"),
     (r"py:.*", r".*.spice.geometry.SpiceBody.*"),
diff --git a/imap_processing/cdf/config/imap_idex_global_cdf_attrs.yaml b/imap_processing/cdf/config/imap_idex_global_cdf_attrs.yaml
index a2ce61c7f..664e57adb 100644
--- a/imap_processing/cdf/config/imap_idex_global_cdf_attrs.yaml
+++ b/imap_processing/cdf/config/imap_idex_global_cdf_attrs.yaml
@@ -16,10 +16,10 @@ imap_idex_l1a_sci:
   Logical_source_description: IMAP Mission IDEX Instrument Level-1A Weekly Data.
 
 imap_idex_l1a_msg:
-   <<: *instrument_base
-   Data_type: L1A_MSG>Level-1A Event Message Data
-   Logical_source: imap_idex_l1a_msg
-   Logical_source_description: IMAP Mission IDEX Instrument Level-1A Event Message Data.
+  <<: *instrument_base
+  Data_type: L1A_MSG>Level-1A Event Message Data
+  Logical_source: imap_idex_l1a_msg
+  Logical_source_description: IMAP Mission IDEX Instrument Level-1A Event Message Data.
 
 imap_idex_l1a_catlst:
   <<: *instrument_base
@@ -34,10 +34,10 @@ imap_idex_l1b_sci:
   Logical_source_description: IMAP Mission IDEX Instrument Level-1B Weekly Data.
 
 imap_idex_l1b_msg:
-   <<: *instrument_base
-   Data_type: L1B_MSG>Level-1B Event Message Data
-   Logical_source: imap_idex_l1b_msg
-   Logical_source_description: IMAP Mission IDEX Instrument Level-1B Event Message Data.
+  <<: *instrument_base
+  Data_type: L1B_MSG>Level-1B Event Message Data
+  Logical_source: imap_idex_l1b_msg
+  Logical_source_description: IMAP Mission IDEX Instrument Level-1B Event Message Data.
 
 imap_idex_l1b_catlst:
   <<: *instrument_base
diff --git a/imap_processing/cdf/config/imap_idex_l1a_variable_attrs.yaml b/imap_processing/cdf/config/imap_idex_l1a_variable_attrs.yaml
index 4cf422b55..be5104ddc 100644
--- a/imap_processing/cdf/config/imap_idex_l1a_variable_attrs.yaml
+++ b/imap_processing/cdf/config/imap_idex_l1a_variable_attrs.yaml
@@ -199,6 +199,7 @@ shcoarse:
   FIELDNAM: Secondary header coarse time
   LABLAXIS: Packet Generation Time (Coarse)
   UNITS: seconds
+  FILLVAL: 4294967295
 
 shfine:
   <<: *trigger_base
@@ -207,6 +208,7 @@ shfine:
   VALIDMAX: *max_uint16
   LABLAXIS: Packet Generation Time (Fine)
   UNITS: seconds
+  FILLVAL: 65535
 
 messages:
   <<: *string_base
diff --git a/imap_processing/cdf/config/imap_idex_l1b_variable_attrs.yaml b/imap_processing/cdf/config/imap_idex_l1b_variable_attrs.yaml
index 0db4a6b75..e65b69da0 100644
--- a/imap_processing/cdf/config/imap_idex_l1b_variable_attrs.yaml
+++ b/imap_processing/cdf/config/imap_idex_l1b_variable_attrs.yaml
@@ -89,6 +89,28 @@ trigger_origin:
   FIELDNAM: Trigger Origin
   CATDESC: Trigger Origin of the event.
 
+pulser_on:
+  <<: *trigger_base
+  FIELDNAM: Pulser On
+  CATDESC: Pulser state flag derived from message events (0=off, 1=on).
+  LABLAXIS: Pulser On
+  FORMAT: I1
+  FILLVAL: 255
+  VAR_TYPE: support_data
+  VALIDMIN: 0
+  VALIDMAX: 1
+
+science_on:
+  <<: *trigger_base
+  FIELDNAM: Science On
+  CATDESC: Science acquisition state flag derived from message events (0=off, 1=on).
+  LABLAXIS: Science On
+  FORMAT: I1
+  FILLVAL: 255
+  VAR_TYPE: support_data
+  VALIDMIN: 0
+  VALIDMAX: 1
+
 tof_high:
   <<: *l1b_tof_base
   CATDESC: Time of flight waveform on the high-gain channel
diff --git a/imap_processing/cli.py b/imap_processing/cli.py
index 67b4a7372..68da35fdd 100644
--- a/imap_processing/cli.py
+++ b/imap_processing/cli.py
@@ -1040,10 +1040,11 @@ def do_processing(
             science_files = dependencies.get_file_paths(source="idex")
             datasets = PacketParser(science_files[0]).data
         elif self.data_level == "l1b":
-            if len(dependency_list) != 3:
+            n_expected_deps = 3 if self.descriptor == "sci-1week" else 1
+            if len(dependency_list) != n_expected_deps:
                 raise ValueError(
-                    f"Unexpected dependencies found for IDEX L1B:"
-                    f"{dependency_list}. Expected only three dependencies."
+                    f"Unexpected dependencies found for IDEX L1B {self.descriptor}:"
+                    f"{dependency_list}. Expected only {n_expected_deps} dependencies."
                 )
             # get CDF file
             science_files = dependencies.get_file_paths(source="idex")
@@ -1055,7 +1056,7 @@ def do_processing(
                 raise ValueError("No science files found for IDEX L1B processing.")
             latest_file = max(science_datasets, key=lambda ds: ds["epoch"].data[0])
             # process data
-            datasets = [idex_l1b(latest_file)]
+            datasets = [idex_l1b(latest_file, self.descriptor)]
         elif self.data_level == "l2a":
             if len(dependency_list) != 3:
                 raise ValueError(
diff --git a/imap_processing/idex/evt_msg_decode_utils.py b/imap_processing/idex/evt_msg_decode_utils.py
index c2e994840..ec3dff882 100644
--- a/imap_processing/idex/evt_msg_decode_utils.py
+++ b/imap_processing/idex/evt_msg_decode_utils.py
@@ -14,7 +14,7 @@ def render_event_template(
     Produce an event message string by replacing placeholders with parameter values.
 
     Example template:
-    "Event {p0} occurred with value {p1+2:dictName}"
+    "Event {p0} occurred with value {p1+2|dictName}"
 
     This would replace {p0} with the hex value of params[0], and replace {p1+2:dictName}
     with the combined hex value of params[1] and params[2] (treated as big-endian bytes)
diff --git a/imap_processing/idex/idex_constants.py b/imap_processing/idex/idex_constants.py
index 0f6d0e8f1..176971aea 100644
--- a/imap_processing/idex/idex_constants.py
+++ b/imap_processing/idex/idex_constants.py
@@ -88,11 +88,3 @@ class ConversionFactors(float, Enum):
 
 # Define the pointing reference frame for IDEX
 IDEX_EVENT_REFERENCE_FRAME = SpiceFrame.ECLIPJ2000
-
-
-class IDEXEvtAcquireCodes(IntEnum):
-    """Create ENUM for event message ints that signify science acquire events."""
-
-    ACQSETUP = 2
-    ACQ = 3
-    CHILL = 5
diff --git a/imap_processing/idex/idex_l1a.py b/imap_processing/idex/idex_l1a.py
index 4d6b06790..3cc053a67 100644
--- a/imap_processing/idex/idex_l1a.py
+++ b/imap_processing/idex/idex_l1a.py
@@ -135,12 +135,14 @@ def _create_evt_msg_data(self, data: xr.Dataset) -> xr.Dataset:
             data_vars={
                 "epoch": xr.DataArray(epoch, name="epoch", dims=["epoch"]),
                 "shfine": xr.DataArray(
-                    data["shfine"].data, dims=["epoch"], attrs=data["shfine"].attrs
+                    data["shfine"].data,
+                    dims=["epoch"],
+                    attrs=self.idex_attrs.get_variable_attributes("shfine"),
                 ),
                 "shcoarse": xr.DataArray(
                     data["shcoarse"].data,
                     dims=["epoch"],
-                    attrs=data["shcoarse"].attrs,
+                    attrs=self.idex_attrs.get_variable_attributes("shcoarse"),
                 ),
             },
             attrs=self.idex_attrs.get_global_attributes("imap_idex_l1a_msg"),
diff --git a/imap_processing/idex/idex_l1b.py b/imap_processing/idex/idex_l1b.py
index c271af1f8..b51a4a166 100644
--- a/imap_processing/idex/idex_l1b.py
+++ b/imap_processing/idex/idex_l1b.py
@@ -45,6 +45,19 @@
 logger = logging.getLogger(__name__)
 
 
+class EventMessage(Enum):
+    """Enum class for event messages."""
+
+    PULSER_ON = "SEQ success (len=0x0580, opCodeLCDictionary(enstim))"
+    PULSER_OFF = "SEQ success (len=0x0580, opCodeLCDictionary(susprel))"
+    SCIENCE_ON = (
+        "SCI state change: sciState16Dictionary(ACQSETUP) ==> sciState16Dictionary(ACQ)"
+    )
+    SCIENCE_OFF = (
+        "SCI state change: sciState16Dictionary(ACQ) ==> sciState16Dictionary(CHILL)"
+    )
+
+
 class TriggerOrigin(IntEnum):
     """Enum class for event trigger origins."""
 
@@ -104,9 +117,96 @@ def get_mode_label(mode: int, channel: str) -> str:
         return f"{channel.upper()}{TriggerMode(mode).name}"
 
 
-def idex_l1b(l1a_dataset: xr.Dataset) -> xr.Dataset:
+def idex_l1b(l1a_dataset: xr.Dataset, descriptor: str) -> xr.Dataset:
+    """
+    Process IDEX l1a data to create l1b data products based on the descriptor.
+
+    Parameters
+    ----------
+    l1a_dataset : xarray.Dataset
+        IDEX L1a dataset to process.
+    descriptor : str
+        Descriptor to determine the type of l1b processing to perform. E.g. "sci-1week"
+        or "msg".
+
+    Returns
+    -------
+    l1b_dataset : xarray.Dataset
+        The``xarray`` dataset containing the processed data and supporting metadata.
+    """
+    if descriptor.startswith("sci"):
+        return idex_l1b_science(l1a_dataset)
+    elif descriptor.startswith("msg"):
+        return idex_l1b_msg(l1a_dataset)
+    else:
+        raise ValueError(f"Unsupported descriptor: {descriptor}")
+
+
+def idex_l1b_msg(l1a_dataset: xr.Dataset) -> xr.Dataset:
+    """
+    Will process IDEX l1a msg data.
+
+    Parameters
+    ----------
+    l1a_dataset : xarray.Dataset
+        IDEX L1a dataset to process.
+
+    Returns
+    -------
+    l1b_dataset : xarray.Dataset
+        The``xarray`` dataset containing the msg housekeeping data and
+        supporting metadata.
+    """
+    logger.info(
+        f"Running IDEX L1B MSG processing on dataset: "
+        f"{l1a_dataset.attrs['Logical_source']}"
+    )
+    # create the attribute manager for this data level
+    idex_attrs = get_idex_attrs("l1b")
+    # set up a dataset with only epoch.
+    l1b_dataset = setup_dataset(l1a_dataset, [], idex_attrs, data_vars=None)
+    l1b_dataset.attrs = idex_attrs.get_global_attributes("imap_idex_l1b_msg")
+    # Compute science_on and pulser_on variables based on the event message. The
+    # "science_on" variable indicates when the science data collection is turned on or
+    # off and the "pulser_on" variable indicates when the pulser is turned on or off.
+    # The following logic is applied to determine the pulser_on status.
+    # enstim → set pulser_on = 1
+    # susprel AND the previous message was enstim → set pulser_on = 0
+    # susprel but previous message was NOT enstim → pulser_on stays whatever it was
+    l1a_messages = l1a_dataset.messages.values
+    # Set science_on to 1 when science is on and 0 when it is off. 255 otherwise.
+    science_on = np.where(l1a_messages == EventMessage.SCIENCE_ON.value, 1, 255)
+    science_on[l1a_messages == EventMessage.SCIENCE_OFF.value] = 0
+    # Find indices where there are consecutive PULSER_ON followed by PULSER_OFF
+    # messages. These are the only cases where we should set pulser_on to 1 and 0.
+    # Compare the messages by shifting the pulser off messages back by one and looking
+    # for matching overlaps.
+    consecutive_pulser_on_off = np.where(
+        (l1a_messages[:-1] == EventMessage.PULSER_ON.value)
+        & (l1a_messages[1:] == EventMessage.PULSER_OFF.value)
+    )[0]
+    pulser_on = np.full(len(l1a_messages), 255)  # initialize with 255 (unknown)
+    pulser_on[consecutive_pulser_on_off] = 1
+    pulser_on[consecutive_pulser_on_off + 1] = 0
+    l1b_dataset["pulser_on"] = xr.DataArray(
+        data=pulser_on,
+        dims="epoch",
+        name="pulser_on",
+        attrs=idex_attrs.get_variable_attributes("pulser_on"),
+    )
+    l1b_dataset["science_on"] = xr.DataArray(
+        data=science_on,
+        dims="epoch",
+        name="science_on",
+        attrs=idex_attrs.get_variable_attributes("science_on"),
+    )
+    logger.info("IDEX L1B MSG data processing completed.")
+    return l1b_dataset
+
+
+def idex_l1b_science(l1a_dataset: xr.Dataset) -> xr.Dataset:
     """
-    Will process IDEX l1a data to create l1b data products.
+    Will process IDEX l1a science data.
 
     Parameters
     ----------
diff --git a/imap_processing/idex/idex_l2b.py b/imap_processing/idex/idex_l2b.py
index 530bbd5bc..0fb193922 100644
--- a/imap_processing/idex/idex_l2b.py
+++ b/imap_processing/idex/idex_l2b.py
@@ -12,12 +12,13 @@
 
     l0_file = "imap_processing/tests/idex/imap_idex_l0_raw_20231218_v001.pkts"
     l0_file_hk = "imap_processing/tests/idex/imap_idex_l0_raw_20250108_v001.pkts"
-    l1a_data = PacketParser(l0_file).data[0]
-    evt_data = PacketParser(l0_file_hk).data[0]
-    l1a_data, l1a_evt_data, l1b_evt_data = PacketParser(l0_file)
-    l1b_data = idex_l1b(l1a_data)
+    l1a_data, _ = PacketParser(l0_file)
+    _, l1a_msg_data = PacketParser(l0_file_hk)
+    msg_data_l1b = idex_l1b(msg_data_l1a, "msg")
+    l1b_data = idex_l1b(l1a_data, "sci-1week")
+
     l1a_data = idex_l2a(l1b_data)
-    l2b_and_l2c_datasets = idex_l2b(l2a_data, [evt_data])
+    l2b_and_l2c_datasets = idex_l2b(l2a_data, [msg_data_l1b])
     write_cdf(l2b_and_l2c_datasets[0])
     write_cdf(l2b_and_l2c_datasets[1])
 """
@@ -38,7 +39,6 @@
     IDEX_EVENT_REFERENCE_FRAME,
     IDEX_SPACING_DEG,
     SECONDS_IN_DAY,
-    IDEXEvtAcquireCodes,
 )
 from imap_processing.idex.idex_utils import get_idex_attrs
 from imap_processing.spice.time import epoch_to_doy, et_to_datetime64, ttj2000ns_to_et
@@ -84,7 +84,7 @@
 
 
 def idex_l2b(
-    l2a_datasets: list[xr.Dataset], evt_datasets: list[xr.Dataset]
+    l2a_datasets: list[xr.Dataset], msg_data_l1b: list[xr.Dataset]
 ) -> list[xr.Dataset]:
     """
     Will process IDEX l2a data to create l2b and l2c data products.
@@ -96,8 +96,8 @@ def idex_l2b(
     ----------
     l2a_datasets : list[xarray.Dataset]
         IDEX L2a datasets to process.
-    evt_datasets : list[xarray.Dataset]
-        List of IDEX housekeeping event message datasets.
+    msg_data_l1b : list[xarray.Dataset]
+        List of IDEX L1B event message datasets.
 
     Returns
     -------
@@ -113,8 +113,9 @@ def idex_l2b(
     # create the attribute manager for this data level
     idex_l2b_attrs = get_idex_attrs("l2b")
     idex_l2c_attrs = get_idex_attrs("l2c")
-    evt_dataset = xr.concat(evt_datasets, dim="epoch")
-
+    msg_ds = (
+        xr.concat(msg_data_l1b, dim="epoch").sortby("epoch").drop_duplicates("epoch")
+    )
     # Concat all the l2a datasets together
     l2a_dataset = xr.concat(l2a_datasets, dim="epoch")
     epoch_doy = epoch_to_doy(l2a_dataset["epoch"].data)
@@ -130,10 +131,14 @@ def idex_l2b(
         counts_by_mass_map,
         daily_epoch,
     ) = compute_counts_by_charge_and_mass(l2a_dataset, epoch_doy_unique)
-    # Get science acquisition start and stop times
-    _, evt_time, evt_values = get_science_acquisition_timestamps(evt_dataset)
+    # Filter the message dataset to only include science acquisition on/off events.
+    # (ignore fill vals)
+    science_on_msg_ds = msg_ds.isel(epoch=np.isin(msg_ds.science_on, [0, 1]))
+    msg_time = science_on_msg_ds["epoch"].data
+    msg_values = science_on_msg_ds["science_on"].data
+
     # Get science acquisition percentage for each day
-    daily_on_percentage = get_science_acquisition_on_percentage(evt_time, evt_values)
+    daily_on_percentage = get_science_acquisition_on_percentage(msg_time, msg_values)
     (
         rate_by_charge,
         rate_by_mass,
@@ -164,7 +169,7 @@ def idex_l2b(
     common_vars = {
         "on_off_times": xr.DataArray(
             name="on_off_times",
-            data=evt_time,
+            data=msg_time,
             dims="on_off_times",
             attrs=idex_l2b_attrs.get_variable_attributes(
                 "on_off_times", check_schema=False
@@ -172,7 +177,7 @@ def idex_l2b(
         ),
         "on_off_events": xr.DataArray(
             name="on_off_events",
-            data=np.asarray(evt_values, dtype=np.uint8),
+            data=np.asarray(msg_values, dtype=np.uint8),
             dims="on_off_times",
             attrs=idex_l2b_attrs.get_variable_attributes(
                 "on_off_events", check_schema=False
@@ -589,79 +594,17 @@ def bin_spin_phases(spin_phases: xr.DataArray) -> np.ndarray:
     return np.asarray(bin_indices)
 
 
-def get_science_acquisition_timestamps(
-    evt_dataset: xr.Dataset,
-) -> tuple[np.ndarray, np.ndarray, np.ndarray]:
-    """
-    Get the science acquisition start and stop times and messages from the event data.
-
-    Parameters
-    ----------
-    evt_dataset : xarray.Dataset
-        Contains IDEX event message data.
-
-    Returns
-    -------
-    event_logs : np.ndarray
-        Array containing science acquisition start and stop events messages.
-    event_timestamps : np.ndarray
-        Array containing science acquisition start and stop timestamps.
-    event_values : np.ndarray
-        Array containing values indicating if the event is a start (1) or
-        stop (0).
-    """
-    # Sort the event dataset by the epoch time. Drop duplicates
-    evt_dataset = evt_dataset.sortby("epoch").drop_duplicates("epoch")
-    # First find indices of the state change events
-    sc_indices = np.where(evt_dataset["elid_evtpkt"].data == "SCI_STE")[0]
-    event_logs = []
-    event_timestamps = []
-    event_values = []
-    # Get the values of the state change events
-    val1 = (
-        evt_dataset["el1par_evtpkt"].data[sc_indices] << 8
-        | evt_dataset["el2par_evtpkt"].data[sc_indices]
-    )
-    val2 = (
-        evt_dataset["el3par_evtpkt"].data[sc_indices] << 8
-        | evt_dataset["el4par_evtpkt"].data[sc_indices]
-    )
-    epochs = evt_dataset["epoch"][sc_indices].data
-    # Now the state change values and check if it is either a science
-    # acquisition start or science acquisition stop event.
-    for v1, v2, epoch in zip(val1, val2, epochs, strict=False):
-        # An "acquire" start will have val1=ACQSETUP and val2=ACQ
-        # An "acquire" stop will have val1=ACQ and val2=CHILL
-        if (v1, v2) == (IDEXEvtAcquireCodes.ACQSETUP, IDEXEvtAcquireCodes.ACQ):
-            event_logs.append("SCI state change: ACQSETUP to ACQ")
-            event_timestamps.append(epoch)
-            event_values.append(1)
-        elif (v1, v2) == (IDEXEvtAcquireCodes.ACQ, IDEXEvtAcquireCodes.CHILL):
-            event_logs.append("SCI state change: ACQ to CHILL")
-            event_timestamps.append(epoch)
-            event_values.append(0)
-
-    logger.info(
-        f"Found science acquisition events: {event_logs} at times: {event_timestamps}"
-    )
-    return (
-        np.asarray(event_logs),
-        np.asarray(event_timestamps),
-        np.asarray(event_values),
-    )
-
-
 def get_science_acquisition_on_percentage(
-    evt_time: NDArray, evt_values: NDArray
+    msg_time: NDArray, msg_values: NDArray
 ) -> dict:
     """
     Calculate the percentage of time science acquisition was occurring for each day.
 
     Parameters
     ----------
-    evt_time : np.ndarray
+    msg_time : np.ndarray
         Array of timestamps for science acquisition start and stop events.
-    evt_values : np.ndarray
+    msg_values : np.ndarray
         Array of values indicating if the event is a start (1) or stop (0).
 
     Returns
@@ -670,7 +613,7 @@ def get_science_acquisition_on_percentage(
         Percentages of time the instrument was in science acquisition mode for each day
          of year.
     """
-    if len(evt_time) == 0:
+    if len(msg_time) == 0:
         logger.warning(
             "No science acquisition events found in event dataset. Returning empty "
             "uptime percentages. All rate variables will be set to -1."
@@ -680,17 +623,17 @@ def get_science_acquisition_on_percentage(
     daily_totals: collections.defaultdict = defaultdict(timedelta)
     daily_on: collections.defaultdict = defaultdict(timedelta)
     # Convert epoch event times to datetime
-    dates = et_to_datetime64(ttj2000ns_to_et(evt_time)).astype(datetime)
+    dates = et_to_datetime64(ttj2000ns_to_et(msg_time)).astype(datetime)
     # Simulate an event at the start of the first day.
     start_of_first_day = dates[0].replace(hour=0, minute=0, second=0, microsecond=0)
     # Assume that the state at the start of the day is the opposite of what the first
     # state is.
-    state_at_start = 0 if evt_values[0] == 1 else 1
+    state_at_start = 0 if msg_values[0] == 1 else 1
     dates = np.insert(dates, 0, start_of_first_day)
-    evt_values = np.insert(evt_values, 0, state_at_start)
+    msg_values = np.insert(msg_values, 0, state_at_start)
     for i in range(len(dates)):
         start = dates[i]
-        state = evt_values[i]
+        state = msg_values[i]
         if i == len(dates) - 1:
             # If this is the last event, set the "end" value the end of the day.
             end = (start + timedelta(days=1)).replace(
diff --git a/imap_processing/tests/idex/conftest.py b/imap_processing/tests/idex/conftest.py
index 96f5c98b8..fbeb38e49 100644
--- a/imap_processing/tests/idex/conftest.py
+++ b/imap_processing/tests/idex/conftest.py
@@ -20,7 +20,7 @@
 L1B_EXAMPLE_FILE = TEST_DATA_PATH / "imap_idex_l1b_sci_20231218_v001.h5"
 
 L2A_CDF = TEST_DATA_PATH / "imap_idex_l2a_sci-1week_20251017_v001.cdf"
-L1B_MSG_CDF = TEST_DATA_PATH / "imap_idex_l1b_evt_20250108_v001.cdf"
+L1B_MSG_CDF = TEST_DATA_PATH / "imap_idex_l1b_msg_20250108_v001.cdf"
 
 pytestmark = pytest.mark.external_test_data
 
@@ -51,7 +51,7 @@ def decom_test_data_catlst() -> xr.Dataset:
 
 @pytest.fixture
 def decom_test_data_msg() -> xr.Dataset:
-    """``xarray`` dataset containing the raw and derived event log data.
+    """``xarray`` dataset containing the raw event message data.
 
     Returns
     -------
@@ -61,6 +61,18 @@ def decom_test_data_msg() -> xr.Dataset:
     return PacketParser(TEST_L0_FILE_MSG).data[0]
 
 
+@pytest.fixture
+def test_l1b_msg(decom_test_data_msg) -> xr.Dataset:
+    """``xarray`` dataset containing the l1b msg data.
+
+    Returns
+    -------
+    dataset : xarray.Dataset
+        ``xarray`` dataset containing the event log data.
+    """
+    return idex_l1b(decom_test_data_msg, "msg")
+
+
 @pytest.fixture
 def l1a_example_data(_download_test_data):
     """
@@ -112,7 +124,7 @@ def l1b_dataset(mock_get_spice_data, decom_test_data_sci: xr.Dataset) -> xr.Data
     """
 
     mock_get_spice_data.side_effect = get_spice_data_side_effect_func
-    dataset = idex_l1b(decom_test_data_sci)
+    dataset = idex_l1b(decom_test_data_sci, "sci-1week")
     return dataset
 
 
diff --git a/imap_processing/tests/idex/test_idex_l1b.py b/imap_processing/tests/idex/test_idex_l1b.py
index 2b95b28dc..21b482218 100644
--- a/imap_processing/tests/idex/test_idex_l1b.py
+++ b/imap_processing/tests/idex/test_idex_l1b.py
@@ -12,10 +12,12 @@
 from imap_processing.cdf.utils import write_cdf
 from imap_processing.idex.idex_l1b import (
     TRIGGER_LABELS,
+    EventMessage,
     TriggerOrigin,
     get_spice_data,
     get_trigger_mode_and_level,
     get_trigger_origin,
+    idex_l1b,
     unpack_instrument_settings,
 )
 from imap_processing.idex.idex_utils import get_idex_attrs
@@ -358,3 +360,46 @@ def test_validate_l1b_idex_data_variables(
                     decimal=4,
                     err_msg=warning,
                 )
+
+
+def test_l1b_msg_processing(decom_test_data_msg: xr.Dataset):
+    """Verify that the MSG data is being processed correctly in the l1b processing.
+
+    Parameters
+    ----------
+    decom_test_data_msg : xr.Dataset
+        A dataset containing the MSG data produced by the l1a processing.
+    """
+    msg_ds = decom_test_data_msg.copy()
+    # Set 2 consecutive events to have pulser on and pulser off
+    msg_ds.messages[2] = EventMessage.PULSER_ON.value
+    msg_ds.messages[3] = EventMessage.PULSER_OFF.value
+    # Set 2 to have a non-consecutive pulser on and pulser off to check that
+    # non-consecutive events are treated as non-valid pulser on and off events
+    msg_ds.messages[20] = EventMessage.PULSER_ON.value
+    msg_ds.messages[22] = EventMessage.PULSER_OFF.value
+    # Process the MSG data with the l1b function
+    test_l1b_msg = idex_l1b(msg_ds, "msg")
+    expected_vars = [
+        "epoch",
+        "pulser_on",
+        "science_on",
+    ]
+    for var in expected_vars:
+        assert var in test_l1b_msg, (
+            f"The variable '{var}' is missing from the MSG dataset."
+        )
+
+    # Check that the pulser_on variable is correct
+    expected_pulser_on = np.ones_like(test_l1b_msg["pulser_on"]) * 255
+    # The pulser_on variable should be 1 for the 2nd and 0 for the 3rd event, and
+    # 255 for all other events
+    expected_pulser_on[2] = 1
+    expected_pulser_on[3] = 0
+    np.testing.assert_array_equal(test_l1b_msg["pulser_on"].data, expected_pulser_on)
+    # Check that the science_on variable is correct
+    expected_science_on = np.ones_like(test_l1b_msg["pulser_on"]) * 255
+    # The science_on variable should be 1 for the 10th event and 0 for the 11th event
+    expected_science_on[10] = 1
+    expected_science_on[11] = 0
+    np.testing.assert_array_equal(test_l1b_msg["science_on"].data, expected_science_on)
diff --git a/imap_processing/tests/idex/test_idex_l2a.py b/imap_processing/tests/idex/test_idex_l2a.py
index 5b4517de8..9dd96feeb 100644
--- a/imap_processing/tests/idex/test_idex_l2a.py
+++ b/imap_processing/tests/idex/test_idex_l2a.py
@@ -49,7 +49,7 @@ def l2a_dataset(
         "imap_processing.idex.idex_l1b.get_spice_data",
         return_value={"spin_phase": spin_phase_angles},
     ):
-        dataset = idex_l2a(idex_l1b(decom_test_data_sci), ancillary_files)
+        dataset = idex_l2a(idex_l1b(decom_test_data_sci, "sci-1week"), ancillary_files)
     return dataset
 
 
diff --git a/imap_processing/tests/idex/test_idex_l2b.py b/imap_processing/tests/idex/test_idex_l2b.py
index 3a9605aa0..721c27452 100644
--- a/imap_processing/tests/idex/test_idex_l2b.py
+++ b/imap_processing/tests/idex/test_idex_l2b.py
@@ -1,13 +1,11 @@
 """Tests the L2b processing for IDEX data"""
 
-from unittest import mock
-
 import numpy as np
 import pytest
 import xarray as xr
 from numpy.testing import assert_array_equal
 
-from imap_processing.cdf.utils import load_cdf, write_cdf
+from imap_processing.cdf.utils import write_cdf
 from imap_processing.idex.idex_constants import (
     FG_TO_KG,
     IDEX_SPACING_DEG,
@@ -25,11 +23,10 @@
     get_science_acquisition_on_percentage,
     idex_l2b,
 )
-from imap_processing.tests.idex.conftest import L1B_MSG_CDF
 
 
 @pytest.fixture
-def l2b_and_l2c_datasets(l2a_dataset: xr.Dataset) -> list[xr.Dataset]:
+def l2b_and_l2c_datasets(l2a_dataset: xr.Dataset, test_l1b_msg) -> list[xr.Dataset]:
     """Return a ``xarray`` dataset containing test data.
 
     Returns
@@ -37,9 +34,8 @@ def l2b_and_l2c_datasets(l2a_dataset: xr.Dataset) -> list[xr.Dataset]:
     datasets : list[xr.Dataset]
         A list of ``xarray`` datasets containing the test data for L2B and L2C.
     """
-    l1b_msg_dataset = load_cdf(L1B_MSG_CDF)
     l1b_msg_dataset2 = (
-        l1b_msg_dataset.copy()
+        test_l1b_msg.copy()
     )  # Add a second dataset with different epoch values for testing
     l2a_dataset2 = (
         l2a_dataset.copy()
@@ -47,7 +43,7 @@ def l2b_and_l2c_datasets(l2a_dataset: xr.Dataset) -> list[xr.Dataset]:
     l1b_msg_dataset2["epoch"] = l1b_msg_dataset2["epoch"] + NANOSECONDS_IN_DAY
     l2a_dataset2["epoch"] = l2a_dataset2["epoch"] + NANOSECONDS_IN_DAY
     datasets = idex_l2b(
-        [l2a_dataset, l2a_dataset2], [l1b_msg_dataset, l1b_msg_dataset2]
+        [l2a_dataset, l2a_dataset2], [test_l1b_msg.copy(), l1b_msg_dataset2]
     )
     return datasets
 
@@ -176,62 +172,35 @@ def test_bin_spin_phases_warning(caplog):
     ) in caplog.text
 
 
-# TODO uncomment tests below when the event message l1b products are ready
-# def test_science_acquisition_times(decom_test_data_msg: xr.Dataset):
-#     """Tests that the expected science acquisition times and messages are present.
-#
-#     Parameters
-#     ----------
-#     decom_test_data_msg : xr.Dataset
-#         A ``xarray`` dataset containing the test data
-#     """
-#     logs, times, vals = get_science_acquisition_timestamps(decom_test_data_msg)
-#     # For this example event message dataset we expect science acquisition events.
-#     assert len(logs) == 2
-#     assert len(times) == 2
-#     assert len(vals) == 2
-#     # The first event message is the start of the science acquisition.
-#     assert logs[0] == "SCI state change: ACQSETUP to ACQ"
-#     # The second event message is the end of the science acquisition.
-#     assert logs[1] == "SCI state change: ACQ to CHILL"
-#
-#     # assert the values are correct
-#     np.testing.assert_array_equal(vals, [1, 0])
-#
-#
-# def test_get_science_acquisition_on_percentage(decom_test_data_msg: xr.Dataset):
-#     """Test the function that calculates the percentage of uptime."""
-#     _, msg_time, msg_event = get_science_acquisition_timestamps(decom_test_data_msg)
-#     on_percentages = get_science_acquisition_on_percentage(msg_time, msg_event)
-#     # We expect 1 DOY and ~87% uptime for the science acquisition.
-#     assert len(on_percentages) == 1
-#     # The DOY should be 8 for this test dataset.
-#     assert on_percentages[8] < 1
-#
-#     msg_ds = decom_test_data_msg[1].copy()
-#     msg_ds_shifted = msg_ds.copy()
-#     msg_ds_shifted["epoch"] = msg_ds["epoch"] + NANOSECONDS_IN_DAY
-#     combined_ds = xr.concat([msg_ds, msg_ds_shifted], dim="epoch")
-#     # expect a second DOY.
-#     _, msg_time, msg_event = get_science_acquisition_timestamps(combined_ds)
-#     on_percentages = get_science_acquisition_on_percentage(msg_time, msg_event)
-#     # We expect 2 DOYs
-#     assert len(on_percentages) == 2
-#     # The uptime should be less than 1% for both
-#     assert on_percentages[8] < 1
-#     assert on_percentages[9] < 1  # The uptime should be less than 1%
-#
+def test_get_science_acquisition_on_percentage(test_l1b_msg: xr.Dataset):
+    """Test the function that calculates the percentage of uptime."""
+    test_l1b_msg = test_l1b_msg.isel(epoch=np.isin(test_l1b_msg.science_on, [0, 1]))
+    msg_time = test_l1b_msg.epoch.data
+    msg_event = test_l1b_msg.science_on.data
+    on_percentages = get_science_acquisition_on_percentage(msg_time, msg_event)
+    # We expect 1 DOY with less than 1% uptime for the science acquisition.
+    assert len(on_percentages) == 1
+    # The DOY should be 8 for this test dataset.
+    assert on_percentages[8] < 1
+
+    msg_ds = test_l1b_msg.copy()
+    msg_ds_shifted = msg_ds.copy()
+    msg_ds_shifted["epoch"] = msg_ds["epoch"] + NANOSECONDS_IN_DAY
+    combined_ds = xr.concat([msg_ds, msg_ds_shifted], dim="epoch")
+    # expect a second DOY.
+    msg_time = combined_ds.epoch.data
+    msg_event = combined_ds.science_on.data
+    on_percentages = get_science_acquisition_on_percentage(msg_time, msg_event)
+    # We expect 2 DOYs
+    assert len(on_percentages) == 2
+    # The uptime should be less than 1% for both
+    assert on_percentages[8] < 1
+    assert on_percentages[9] < 1  # The uptime should be less than 1%
 
 
 def test_get_science_acquisition_on_percentage_no_acquisition(caplog):
     """Test the function returns an empty dict when there is no science acquisition."""
-    with mock.patch(
-        "imap_processing.idex.idex_l2b.get_science_acquisition_timestamps",
-        return_value=([], [], []),
-    ):
-        on_percentages = get_science_acquisition_on_percentage(
-            np.array([]), np.array([])
-        )
+    on_percentages = get_science_acquisition_on_percentage(np.array([]), np.array([]))
     assert not on_percentages
     assert "No science acquisition events found" in caplog.text