diff --git a/.gitignore b/.gitignore
index 76429cb..48ee6f3 100644
--- a/.gitignore
+++ b/.gitignore
@@ -132,3 +132,4 @@ bigwig_loader/_version.py
 /example_data/bigwig
 /deleted
 .pfau.yml
+scratch/
diff --git a/bigwig_loader/__init__.py b/bigwig_loader/__init__.py
index 5300278..7e2ac57 100644
--- a/bigwig_loader/__init__.py
+++ b/bigwig_loader/__init__.py
@@ -14,12 +14,6 @@
 __email__ = ["joren.retel@pfizer.com"]
 
 logger = logging.getLogger("bigwig_loader")
-if not logger.hasHandlers():
-    handler = logging.StreamHandler()
-    formatter = logging.Formatter("[%(levelname)s] %(name)s: %(message)s")
-    handler.setFormatter(formatter)
-    logger.addHandler(handler)
-logger.setLevel(logging.WARNING)
 
 
 logger.warning(
diff --git a/bigwig_loader/bigwig.py b/bigwig_loader/bigwig.py
index f65ad75..55b6256 100644
--- a/bigwig_loader/bigwig.py
+++ b/bigwig_loader/bigwig.py
@@ -1,7 +1,5 @@
-import zlib
+import logging
 from pathlib import Path
-from random import sample
-from typing import BinaryIO
 from typing import Iterable
 from typing import Literal
 from typing import Optional
@@ -22,13 +20,15 @@
 from bigwig_loader.parser import ChromosomeTreeNode
 from bigwig_loader.parser import RTreeIndexHeader
 from bigwig_loader.parser import TotalSummary
-from bigwig_loader.parser import WIGSectionHeader
 from bigwig_loader.parser import ZoomHeader
 from bigwig_loader.parser import collect_leaf_nodes
 from bigwig_loader.store import BigWigStore
 from bigwig_loader.subtract_intervals import subtract_interval_dataframe
 from bigwig_loader.util import get_standard_chromosomes
 
+logger = logging.getLogger(__name__)
+logger.setLevel(logging.INFO)
+
 
 class BigWig:
     def __init__(
@@ -50,6 +50,24 @@ def __init__(
             self.id = id
             self.scale = scale
             self.bbi_header = BBIHeader.from_file(bigwig)
+
+            # Endianness check using BBI header magic
+            # UCSC BigWig spec: magic is 0x888FFC26
+            # Parser uses little-endian unpacking, so valid BigWig files will read as 0x888FFC26
+            # (the bytes in file are 26 FC 8F 88, which when read little-endian gives 0x888FFC26)
+            magic = self.bbi_header.magic
+            if magic == 0x888FFC26:
+                logger.debug(f"BBI header magic: {magic:#x} (valid BigWig file)")
+            elif magic == 0x26FC8F88:
+                # This would mean the file has bytes 88 8F FC 26, which is byte-swapped
+                logger.warning(
+                    f"BBI header magic: {magic:#x} (byte-swapped BigWig - may need big-endian parsing)"
+                )
+            else:
+                logger.warning(
+                    f"BBI header magic: {magic:#x} (unexpected value - not a valid BigWig file?)"
+                )
+
             self.zoom_headers = ZoomHeader.all(
                 bigwig, first_offset=64, n_zoom_levels=self.bbi_header.zoom_levels
             )
@@ -73,7 +91,7 @@ def __init__(
             )
 
             self.rtree_leaf_nodes = collect_leaf_nodes(file_object=bigwig, offset=None)
-            self.max_rows_per_chunk = self._guess_max_rows_per_chunk(bigwig)
+            self.max_rows_per_chunk = self.get_max_rows_per_chunk()
 
         self.chrom_to_chrom_id: dict[str, int] = {
             item.key: item.chrom_id for item in self.chromosome_head_node.items  # type: ignore
@@ -90,13 +108,28 @@ def run_indexing(self, chromosome_offsets: npt.NDArray[np.int64]) -> None:
         an index itself as well. But we prefer to recalculate
         an index here.
         """
-
         self.chromosome_offsets = chromosome_offsets
-        self.ncls_index, self.reference_data = self.build_ncls_index()
+        sorted_data = prepare_index_for_bigwig(
+            chromosome_offsets=chromosome_offsets,
+            rtree_leaf_nodes=self.rtree_leaf_nodes,
+        )
+        self.finalize_indexing(sorted_data)
+
+    def finalize_indexing(self, sorted_data: npt.NDArray[np.void]) -> None:
+        """
+        Finalize indexing by building NCLS from prepared data.
+        This should be called in the main thread/process.
+        """
+        self.reference_data = sorted_data
+        self.ncls_index = NCLS(
+            sorted_data["start_abs"],
+            sorted_data["end_abs"],
+            np.arange(len(sorted_data)),
+        )
         self.store = BigWigStore(
             self.path,
-            chunk_sizes=self.reference_data["data_size"],  # type: ignore
-            chunk_offsets=self.reference_data["data_offset"],  # type: ignore
+            chunk_sizes=sorted_data["data_size"],
+            chunk_offsets=sorted_data["data_offset"],
         )
 
     def chromosomes(
@@ -275,44 +308,6 @@ def get_batch_offsets_and_sizes_with_global_positions(
         )
         return self.store.get_offsets_and_sizes(np.sort(np.unique(right_index)))
 
-    def build_ncls_index(self) -> tuple[NCLS, npt.NDArray[np.void]]:
-        dtype = np.dtype(
-            [
-                ("start_chrom_ix", "u4"),
-                ("start_base", "u4"),
-                ("end_chrom_ix", "u4"),
-                ("end_base", "u4"),
-                ("data_offset", "u8"),
-                ("data_size", "u8"),
-                ("start_abs", "i8"),
-                ("end_abs", "i8"),
-            ]
-        )
-
-        data = np.empty(self.rtree_leaf_nodes.shape, dtype=dtype)
-        data["start_chrom_ix"] = self.rtree_leaf_nodes["start_chrom_ix"]  # type: ignore
-        data["start_base"] = self.rtree_leaf_nodes["start_base"]  # type: ignore
-        data["end_chrom_ix"] = self.rtree_leaf_nodes["end_chrom_ix"]  # type: ignore
-        data["end_base"] = self.rtree_leaf_nodes["end_base"]  # type: ignore
-        data["data_offset"] = self.rtree_leaf_nodes["data_offset"]  # type: ignore
-        data["data_size"] = self.rtree_leaf_nodes["data_size"]  # type: ignore
-        data["start_abs"] = self.make_positions_global(
-            self.rtree_leaf_nodes["start_chrom_ix"], self.rtree_leaf_nodes["start_base"]  # type: ignore
-        ).astype(np.int64)
-        data["end_abs"] = self.make_positions_global(
-            self.rtree_leaf_nodes["end_chrom_ix"], self.rtree_leaf_nodes["end_base"]  # type: ignore
-        ).astype(np.int64)
-
-        sort_indices = np.argsort(data["start_abs"])
-        sorted_data = data[sort_indices]
-
-        ncls = NCLS(
-            sorted_data["start_abs"],
-            sorted_data["end_abs"],
-            np.arange(len(sorted_data)),
-        )
-        return ncls, sorted_data
-
     def search_ncls(
         self, query_df: pd.DataFrame, use_key: bool = False
     ) -> tuple[npt.NDArray[np.int64], npt.NDArray[np.int64]]:
@@ -404,33 +399,75 @@ def _create_chrom_id_to_chrom_key(self) -> npt.NDArray[np.generic]:
             mapping[chrom_id] = key
         return mapping  # type: ignore
 
-    def _guess_max_rows_per_chunk(
-        self, file_object: BinaryIO, sample_size: int = 100
-    ) -> int:
+    def get_max_rows_per_chunk(self) -> int:
         """
-        Randomly samples some chunks and looks in the header
-        to see if in these chunks, the number of rows in the
-        decompressed data is always the same. This helps with
-        the ReferenceFileSystem.
+        Determines the maximum number of rows in any chunk.
+
+        Uses the BBI header's uncompress_buff_size as the authoritative source,
+        since this is the buffer size the file was created with and guarantees
+        all chunks can be decompressed into this space.
 
         Args:
             file_object: BigWig file opened as bytes.
+            sample_size: Number of chunks to sample for verification.
         Returns:
-            Number of rows in a chunk
+            Maximum number of rows that could fit in the uncompressed buffer.
         """
-
-        rows_for_chunks = []
-
-        data_offsets = self.rtree_leaf_nodes["data_offset"]
-        data_sizes = self.rtree_leaf_nodes["data_size"]
-        if len(data_offsets) > sample_size:
-            sample_indices = sample(range(len(data_offsets)), sample_size)  # nosec
-            data_offsets = data_offsets[sample_indices]
-            data_sizes = data_sizes[sample_indices]
-
-        for data_offset, data_size in zip(data_offsets, data_sizes):
-            file_object.seek(data_offset, 0)  # type: ignore
-            decoded = zlib.decompress(file_object.read(data_size))  # type: ignore
-            header = WIGSectionHeader.from_bytes(decoded[:24])
-            rows_for_chunks.append(header.item_count)
-        return max(rows_for_chunks)
+        # The BBI header's uncompress_buff_size is the authoritative value
+        # It defines the maximum uncompressed size for any chunk in the file
+        # Each row is 12 bytes, plus 24-byte header
+        return (self.bbi_header.uncompress_buff_size - 24) // 12
+
+
+def prepare_index_for_bigwig(
+    chromosome_offsets: npt.NDArray[np.int64],
+    rtree_leaf_nodes: npt.NDArray[np.void],
+) -> npt.NDArray[np.generic]:
+    """
+    Standalone function for preparing index data in a separate process.
+    This can be pickled and run with ProcessPoolExecutor.
+
+    Args:
+        path: Path to bigwig file (for identification)
+        bigwig_id: ID of the bigwig file
+        chromosome_offsets: Offsets for converting local to global positions
+        rtree_leaf_nodes: The rtree leaf nodes from the bigwig file
+
+    Returns:
+        sorted data
+    """
+    dtype = np.dtype(
+        [
+            ("start_chrom_ix", "u4"),
+            ("start_base", "u4"),
+            ("end_chrom_ix", "u4"),
+            ("end_base", "u4"),
+            ("data_offset", "u8"),
+            ("data_size", "u8"),
+            ("start_abs", "i8"),
+            ("end_abs", "i8"),
+        ]
+    )
+
+    data = np.empty(rtree_leaf_nodes.shape, dtype=dtype)
+    data["start_chrom_ix"] = rtree_leaf_nodes["start_chrom_ix"]
+    data["start_base"] = rtree_leaf_nodes["start_base"]
+    data["end_chrom_ix"] = rtree_leaf_nodes["end_chrom_ix"]
+    data["end_base"] = rtree_leaf_nodes["end_base"]
+    data["data_offset"] = rtree_leaf_nodes["data_offset"]
+    data["data_size"] = rtree_leaf_nodes["data_size"]
+
+    # make_positions_global inline
+    data["start_abs"] = (
+        rtree_leaf_nodes["start_base"]
+        + chromosome_offsets[rtree_leaf_nodes["start_chrom_ix"]]
+    ).astype(np.int64)
+    data["end_abs"] = (
+        rtree_leaf_nodes["end_base"]
+        + chromosome_offsets[rtree_leaf_nodes["end_chrom_ix"]]
+    ).astype(np.int64)
+
+    sort_indices = np.argsort(data["start_abs"])
+    sorted_data = data[sort_indices]
+
+    return sorted_data
diff --git a/bigwig_loader/collection.py b/bigwig_loader/collection.py
index f117412..04192c4 100644
--- a/bigwig_loader/collection.py
+++ b/bigwig_loader/collection.py
@@ -1,4 +1,7 @@
 import logging
+import os
+from concurrent.futures import ProcessPoolExecutor
+from concurrent.futures import as_completed
 from functools import cached_property
 from pathlib import Path
 from typing import Any
@@ -14,6 +17,7 @@
 
 from bigwig_loader.batch_processor import BatchProcessor
 from bigwig_loader.bigwig import BigWig
+from bigwig_loader.bigwig import prepare_index_for_bigwig
 from bigwig_loader.decompressor import Decoder
 from bigwig_loader.memory_bank import MemoryBank
 from bigwig_loader.merge_intervals import merge_interval_dataframe
@@ -22,6 +26,8 @@
 from bigwig_loader.subtract_intervals import subtract_interval_dataframe
 from bigwig_loader.util import chromosome_sort
 
+logger = logging.getLogger(__name__)
+
 
 class BigWigCollection:
     """
@@ -47,7 +53,7 @@ def __init__(
         bigwig_path: Union[str, Sequence[str], Path, Sequence[Path]],
         file_extensions: Sequence[str] = (".bigWig", ".bw"),
         crawl: bool = True,
-        scale: Optional[dict[Union[str | Path], Any]] = None,
+        scale: Optional[dict[Union[str, Path], Any]] = None,
         first_n_files: Optional[int] = None,
         pinned_memory_size: int = 10000,
     ):
@@ -81,11 +87,49 @@ def __init__(
         self.run_indexing()
         self._batch_processor = None
 
-    def run_indexing(self) -> None:
-        for bigwig in self.bigwigs:
-            bigwig.run_indexing(
-                chromosome_offsets=self.local_chrom_ids_to_offset_matrix[bigwig.id]
-            )
+    def run_indexing(self, max_workers: Optional[int] = None) -> None:
+        """
+        Run indexing for all bigwig files in parallel using multiple CPUs.
+        """
+        n_bigwigs = len(self.bigwigs)
+        if n_bigwigs == 0:
+            return
+
+        if n_bigwigs <= 4 or max_workers == 1:
+            for bigwig in self.bigwigs:
+                bigwig.run_indexing(
+                    chromosome_offsets=self.local_chrom_ids_to_offset_matrix[bigwig.id]
+                )
+            return
+
+        if max_workers is None:
+            max_workers = min(os.cpu_count() or 4, n_bigwigs)
+
+        verbose = True  # logger.isEnabledFor(logging.INFO)
+
+        with ProcessPoolExecutor(max_workers=max_workers) as executor:
+            futures = {
+                executor.submit(
+                    prepare_index_for_bigwig,
+                    self.local_chrom_ids_to_offset_matrix[bigwig.id],
+                    bigwig.rtree_leaf_nodes,
+                ): bigwig
+                for bigwig in self.bigwigs
+            }
+
+            for i, future in enumerate(as_completed(futures), 1):
+                bigwig = futures[future]
+                sorted_data = future.result()
+                bigwig.chromosome_offsets = self.local_chrom_ids_to_offset_matrix[
+                    bigwig.id
+                ]
+                bigwig.finalize_indexing(sorted_data)
+
+                if verbose and (i % 100 == 0 or i == n_bigwigs):
+                    print(f"\rIndexed {i}/{n_bigwigs}", end="", flush=True)
+
+            if verbose:
+                print()
 
     def __len__(self) -> int:
         return len(self.bigwigs)
@@ -217,13 +261,11 @@ def intervals(
         Returns: pandas dataframe of intervals (chrom, start, end, value)
 
         """
-        logging.info("Collecting intervals from BigWig files.")
+        logger.info("Collecting intervals from BigWig files.")
         interval_for_all_bigwigs = []
         n_bigwigs = len(self.bigwigs)
         for i, bw in enumerate(self.bigwigs):
-            logging.info(
-                f"Getting intervals for BigWig file {i}/{n_bigwigs}: {bw.path}"
-            )
+            logger.info(f"Getting intervals for BigWig file {i}/{n_bigwigs}: {bw.path}")
             interval_for_all_bigwigs.append(
                 bw.intervals(
                     include_chromosomes=include_chromosomes,
@@ -244,14 +286,14 @@ def intervals(
             intervals["start"] = intervals["start"].values.clip(padding) - padding  # type: ignore
             intervals["end"] = intervals["end"].values + padding  # type: ignore
         if merge:
-            logging.info(
+            logger.info(
                 "Merging intervals from different BigWig Files into one interval list."
             )
             intervals = merge_interval_dataframe(
                 intervals, is_sorted=False, allow_gap=merge_allow_gap
             )
         if blacklist is not None:
-            logging.info("Subtracting blacklisted regions.")
+            logger.info("Subtracting blacklisted regions.")
             intervals = subtract_interval_dataframe(
                 intervals=intervals, blacklist=blacklist, buffer=blacklist_buffer
             )
@@ -375,7 +417,7 @@ def create_global_position_system(
             # exceeding this would be a problem as all the positions
             # in bigwig files are encoded in 32 bits. Making a global
             # base position that exceeds this number would be a problem.
-            logging.warning(
+            logger.warning(
                 "The sum of sizes of the chromosomes exceeds the size of uint32"
             )
         for bigwig in self.bigwigs:
diff --git a/bigwig_loader/decompressor.py b/bigwig_loader/decompressor.py
index 372048c..a09f3fe 100644
--- a/bigwig_loader/decompressor.py
+++ b/bigwig_loader/decompressor.py
@@ -8,6 +8,9 @@
 import numpy as np
 import numpy.typing as npt
 
+logger = logging.getLogger(__name__)
+logger.setLevel(logging.INFO)
+
 codec = numcodecs.registry.get_codec(
     {
         "id": "nvcomp_batch",
@@ -16,6 +19,20 @@
 )
 
 
+class DecompressionError(Exception):
+    """Raised when nvcomp decompression fails for one or more chunks."""
+
+    def __init__(
+        self,
+        message: str,
+        failed_bigwig_ids: Optional[np.ndarray] = None,
+        status_codes: Optional[np.ndarray] = None,
+    ):
+        super().__init__(message)
+        self.failed_bigwig_ids = failed_bigwig_ids
+        self.status_codes = status_codes
+
+
 class Decoder:
     # based on: `kvikio.nvcomp_codec.NvCompBatchCodec`
 
@@ -51,7 +68,7 @@ def reserve_memory(self, num_chunks: int, generocity: float = 1.2) -> None:
 
         num_chunks = int(num_chunks * generocity)
 
-        logging.debug(f"Reserving memory for {num_chunks} chunks")
+        logger.debug(f"Reserving memory for {num_chunks} chunks")
 
         self.uncomp_chunks = [
             cp.empty(self.max_uncompressed_chunk_size, dtype=cp.uint8)
@@ -151,6 +168,27 @@ def decode(
             stream,
         )
 
+        failed_mask = statuses != 0
+        if failed_mask.any():
+            failed_statuses = statuses[failed_mask].get()
+            failed_bigwig_ids = (
+                bigwig_ids[failed_mask].get() if bigwig_ids is not None else None
+            )
+            unique_failed_bigwigs = (
+                np.unique(failed_bigwig_ids) if failed_bigwig_ids is not None else None
+            )
+
+            message = (
+                f"nvcomp decompression failed for {failed_mask.sum()} chunks. "
+                f"Status codes: {np.unique(failed_statuses).tolist()}"
+            )
+
+            raise DecompressionError(
+                message=message,
+                failed_bigwig_ids=unique_failed_bigwigs,
+                status_codes=failed_statuses,
+            )
+
         chrom_ids, start, end, value, n_rows_for_chunks = self.post_process(
             cp.concatenate(uncomp_chunks), bigwig_ids
         )
diff --git a/bigwig_loader/functional.py b/bigwig_loader/functional.py
index 4378f94..c9668ce 100644
--- a/bigwig_loader/functional.py
+++ b/bigwig_loader/functional.py
@@ -100,6 +100,11 @@ def load_and_decode(
         local_to_global=local_to_global,
     )
 
+    if stream is not None:
+        stream.synchronize()
+    else:
+        cp.cuda.Device().synchronize()
+
     start_data, end_data, value_data, bigwig_start_indices = decoder.decode_batch(
         bigwig_ids=bigwig_ids,
         comp_chunk_pointers=comp_chunk_pointers,
diff --git a/bigwig_loader/intervals_to_values.py b/bigwig_loader/intervals_to_values.py
index 72e5808..a8e958c 100644
--- a/bigwig_loader/intervals_to_values.py
+++ b/bigwig_loader/intervals_to_values.py
@@ -9,6 +9,8 @@
 from bigwig_loader.default_value import replace_out_tensor_if_needed
 from bigwig_loader.searchsorted import interval_searchsorted
 
+logger = logging.getLogger(__name__)
+
 CUDA_KERNEL_DIR = Path(__file__).parent.parent / "cuda_kernels"
 
 
@@ -153,9 +155,13 @@ def intervals_to_values(
 
     # Handle scaling factors - convert to float32 if provided
     if scaling_factors is not None:
-        scaling_factors = cp.ascontiguousarray(scaling_factors, dtype=cp.float32)
+        scaling_factors_arr = cp.ascontiguousarray(scaling_factors, dtype=cp.float32)
+        use_scaling_factors = True
     else:
-        scaling_factors = cp.asarray([], dtype=cp.float32)
+        scaling_factors_arr = cp.empty(
+            0, dtype=cp.float32
+        )  # Empty array, won't be accessed
+        use_scaling_factors = False
 
     cuda_kernel(
         (grid_size,),
@@ -170,16 +176,18 @@ def intervals_to_values(
             array_value,
             num_tracks,
             batch_size,
-            sequence_length,  # should really sequence length, not reduced sequence length
+            sequence_length,
             max_number_intervals,
             window_size,
             cp.float32(default_value),
             default_value_isnan,
-            scaling_factors,
+            scaling_factors_arr,
+            use_scaling_factors,
             out,
         ),
         dtype=dtype,
     )
+
     return out
 
 
diff --git a/bigwig_loader/memory_bank.py b/bigwig_loader/memory_bank.py
index bd484f6..729cb5a 100644
--- a/bigwig_loader/memory_bank.py
+++ b/bigwig_loader/memory_bank.py
@@ -5,6 +5,8 @@
 from kvikio.cufile import CuFile
 from kvikio.cufile import IOFuture
 
+logger = logging.getLogger(__name__)
+
 
 class MemoryBank:
     def __init__(self, nbytes: int = 10000, elastic: bool = True):
@@ -58,7 +60,7 @@ def increase_memory_size(self, new_size: int, generosity: float = 1.2) -> None:
         if new_size > self._gpu_byte_array.size:
             self.await_all_promises()
             new_size = int(new_size * generosity)
-            logging.debug(
+            logger.debug(
                 f"CuFileMemoryBank: Increasing size of cupy byte from {self._gpu_byte_array.size} to {new_size}"
             )
             new_mem = cp.empty(new_size, dtype=cp.uint8)
@@ -117,9 +119,6 @@ def add_many(
             offsets: byte offsets to starts of compressed chunks
             sizes: sizes of compressed chunks
             skip_bytes: skips this number of bytes from offset
-            increase_memory_size: whether to elastically increase the
-                size of the pinned memory if the new chunks don't
-                fit in anymore. (default: True)
 
         """
         new_size = self.compressed_chunk_offsets[-1] + sum(sizes)
diff --git a/bigwig_loader/searchsorted.py b/bigwig_loader/searchsorted.py
index 7151ed5..991109d 100644
--- a/bigwig_loader/searchsorted.py
+++ b/bigwig_loader/searchsorted.py
@@ -1,8 +1,12 @@
+import logging
 from typing import Literal
 
 import cupy as cp
 from cupy._sorting.search import _searchsorted_code
 
+logger = logging.getLogger(__name__)
+
+
 _preamble = """
 template<typename T>
 __device__ bool _isnan(T val) {
@@ -65,22 +69,55 @@ def searchsorted(
         absolute_indices: whether to give the indices with respect to the entire
             array (True) or for the subarrays (False).
     Returns:
-        And array of size n_subarrays x n_queries with insertion indices.
+        An array of size n_subarrays x n_queries with insertion indices.
 
     """
     start_indices, sizes = starts_and_sizes(start_indices, sizes)
 
     n_subarrays = len(sizes)
     n_queries = len(queries)
+
+    # If the array is empty, just return zeros
+    if len(array) == 0:
+        return cp.zeros((n_subarrays, n_queries), dtype=cp.uint32)
+
+    # The kernel has undefined behavior when n_bins=0 (accesses bins[-1])
+    # We mask empty subarrays, run the kernel with safe values, then fix results
+    empty_mask = sizes == 0
+    has_empty = bool(empty_mask.any())
+
+    if has_empty:
+        n_empty = int(empty_mask.sum())
+        logger.debug(f"searchsorted: {n_empty} empty subarrays detected, applying fix")
+        # Set empty subarrays to size=1 pointing to index 0
+        # This prevents the kernel from accessing bins[-1] (undefined behavior)
+        sizes = sizes.copy()
+        sizes[empty_mask] = 1
+
     idx = cp.arange(n_subarrays, dtype=queries.dtype)[:, cp.newaxis]
-    queries = queries[cp.newaxis, :]
+    queries_broadcast = queries[cp.newaxis, :]
     output = cp.zeros((n_subarrays, n_queries), dtype=cp.uint32)
 
     result = _searchsorted_kernel(
-        queries, idx, start_indices, sizes, array, side == "right", True, output
+        queries_broadcast,
+        idx,
+        start_indices,
+        sizes,
+        array,
+        side == "right",
+        True,
+        output,
     )
+
     if absolute_indices:
-        return result + start_indices[:, cp.newaxis]
+        result = result + start_indices[:, cp.newaxis]
+
+    # For empty subarrays, set result to 0
+    # This ensures found_starts == found_ends == 0 for empty tracks,
+    # so the interval processing loop does nothing (no intervals to process)
+    if has_empty:
+        result[empty_mask, :] = 0
+
     return result
 
 
@@ -96,7 +133,6 @@ def interval_searchsorted(
     """This is a convenience function that does searchsorted on both
     the start and end arrays and returns the results.
     """
-
     start_indices, sizes = starts_and_sizes(start_indices, sizes)
 
     # n_tracks x n_queries
@@ -107,6 +143,7 @@ def interval_searchsorted(
         side="right",
         absolute_indices=absolute_indices,
     )
+
     found_ends = searchsorted(
         array_start,
         queries=query_ends,
diff --git a/bigwig_loader/streamed_dataset.py b/bigwig_loader/streamed_dataset.py
index 1ddbb33..0113aff 100644
--- a/bigwig_loader/streamed_dataset.py
+++ b/bigwig_loader/streamed_dataset.py
@@ -1,5 +1,7 @@
+import logging
 import queue
 import threading
+import traceback
 from types import TracebackType
 from typing import Generator
 from typing import Iterable
@@ -13,9 +15,12 @@
 from bigwig_loader.batch_processor import BatchProcessor
 from bigwig_loader.batch_processor import PreprocessedReturnType
 from bigwig_loader.collection import BigWigCollection
+from bigwig_loader.decompressor import DecompressionError
 from bigwig_loader.default_value import replace_out_tensor_if_needed
 from bigwig_loader.intervals_to_values import intervals_to_values
 
+logger = logging.getLogger(__name__)
+
 InputBatchType = Batch | IntervalType
 
 
@@ -53,6 +58,8 @@ def batch_processor(self) -> BatchProcessor:
 
     def _worker(self) -> None:
         while self._wait_until_ready():
+            query_received = False
+            output_produced = False
             try:
                 # necessary because some other thread
                 # (for instance pytorch-lightning)
@@ -61,6 +68,7 @@ def _worker(self) -> None:
                 with cp.cuda.Device(self.stream.device_id):
                     with self.stream as stream:
                         query = self.input_queue.get(timeout=1)
+                        query_received = True
                         query = Batch.from_args(query)
                         result = self.batch_processor.preprocess(
                             chromosomes=query.chromosomes,
@@ -71,18 +79,43 @@ def _worker(self) -> None:
                         )
                         self.stream.synchronize()
                         self._put_output_queue(query, result)
-                        self.input_queue.task_done()
+                        output_produced = True
             except queue.Empty:
+                logger.debug(f"Queue Empty, batch_count: {self._batch_count}")
+            except DecompressionError as e:
+                if e.failed_bigwig_ids is None:
+                    logger.error(
+                        f"Decompression failed for some chunks. "
+                        f"Status codes: {set(e.status_codes.tolist()) if e.status_codes is not None else 'unknown'}"
+                    )
+
+                else:
+                    failed_paths = [
+                        str(self._collection.bigwigs[i].path)
+                        for i in e.failed_bigwig_ids
+                    ]
+                    logger.error(
+                        f"Decompression failed for {len(failed_paths)} file(s): {failed_paths}. "
+                        f"Status codes: {set(e.status_codes.tolist()) if e.status_codes is not None else 'unknown'}"
+                    )
+            except Exception as e:
+                logger.error(
+                    f"Worker {self.worker_id} encountered error processing batch: {e}\n"
+                    f"Traceback:\n{traceback.format_exc()}"
+                )
+            finally:
+                if query_received:
+                    self.input_queue.task_done()
+            if not output_produced:
                 self.ready.set()
-                continue
-            self._batch_count += 1
+
+            if output_produced:
+                self._batch_count += 1
 
     def _wait_until_ready(self) -> bool:
         while True:
             if self.stop_event.is_set():
                 return False
-            # returns True when ready event is set
-            # and false when the timeout is reached
             if self.ready.wait(timeout=1):
                 self.ready.clear()
                 return True
diff --git a/cuda_kernels/intervals_to_values_contiguous.cu b/cuda_kernels/intervals_to_values_contiguous.cu
index c4e699f..74caf72 100644
--- a/cuda_kernels/intervals_to_values_contiguous.cu
+++ b/cuda_kernels/intervals_to_values_contiguous.cu
@@ -31,12 +31,12 @@ void intervals_to_values_kernel(
         const int window_size,
         const float default_value,
         const bool default_value_isnan,
-        const float* scaling_factors,  // NEW: scaling factors array of length n_tracks
+        const float* scaling_factors,
+        const bool use_scaling_factors,
         T* out
 ) {
     int thread = blockIdx.x * blockDim.x + threadIdx.x;
 
-    // Same thread indexing as before
     int batch_index = thread % batch_size;
     int i = thread % (batch_size * n_tracks);
     int track_index = i / batch_size;
@@ -44,23 +44,25 @@ void intervals_to_values_kernel(
     if (window_size == 1) {
         int j = (thread / (batch_size * n_tracks)) % max_number_intervals;
 
-        int found_start_index = found_starts[i];
-        int found_end_index = found_ends[i];
-        int query_start = query_starts[batch_index];
-        int query_end = query_ends[batch_index];
+        unsigned int found_start_index = found_starts[i];
+        unsigned int found_end_index = found_ends[i];
+        unsigned int query_start = query_starts[batch_index];
+        unsigned int query_end = query_ends[batch_index];
 
-        int cursor = found_start_index + j;
+        unsigned int cursor = found_start_index + j;
 
         if (cursor < found_end_index) {
-            int interval_start = track_starts[cursor];
-            int interval_end = track_ends[cursor];
-            int start_index = max(interval_start - query_start, 0);
-            int end_index = min(interval_end, query_end) - query_start;
+            unsigned int interval_start = track_starts[cursor];
+            unsigned int interval_end = track_ends[cursor];
+
+            // Calculate indices - these are relative to query_start, so they fit in int
+            // Use signed arithmetic for the comparison with 0
+            int start_index = (interval_start > query_start) ? (int)(interval_start - query_start) : 0;
+            int end_index = (int)(min(interval_end, query_end) - query_start);
 
             float value = track_values[cursor];
 
-            // Apply scaling factor here
-            if (scaling_factors != nullptr) {
+            if (use_scaling_factors) {
                 value *= scaling_factors[track_index];
             }
 
@@ -73,12 +75,12 @@ void intervals_to_values_kernel(
             }
         }
     } else {
-        int found_start_index = found_starts[i];
-        int found_end_index = found_ends[i];
-        int query_start = query_starts[batch_index];
-        int query_end = query_ends[batch_index];
+        unsigned int found_start_index = found_starts[i];
+        unsigned int found_end_index = found_ends[i];
+        unsigned int query_start = query_starts[batch_index];
+        unsigned int query_end = query_ends[batch_index];
 
-        int cursor = found_start_index;
+        unsigned int cursor = found_start_index;
         int window_index = 0;
         float summation = 0.0f;
         int valid_count = 0;
@@ -89,11 +91,12 @@ void intervals_to_values_kernel(
             int window_start = window_index * window_size;
             int window_end = window_start + window_size;
 
-            int interval_start = track_starts[cursor];
-            int interval_end = track_ends[cursor];
+            unsigned int interval_start = track_starts[cursor];
+            unsigned int interval_end = track_ends[cursor];
 
-            int start_index = max(interval_start - query_start, 0);
-            int end_index = min(interval_end, query_end) - query_start;
+            // Calculate indices relative to query_start
+            int start_index = (interval_start > query_start) ? (int)(interval_start - query_start) : 0;
+            int end_index = (int)(min(interval_end, query_end) - query_start);
 
             if (start_index >= window_end) {
                 float final_value;
@@ -104,8 +107,7 @@ void intervals_to_values_kernel(
                     final_value = summation / window_size;
                 }
 
-                // Apply scaling factor
-                if (scaling_factors != nullptr) {
+                if (use_scaling_factors) {
                     final_value *= scaling_factors[track_index];
                 }
 
@@ -135,8 +137,7 @@ void intervals_to_values_kernel(
                     final_value = summation / window_size;
                 }
 
-                // Apply scaling factor
-                if (scaling_factors != nullptr) {
+                if (use_scaling_factors) {
                     final_value *= scaling_factors[track_index];
                 }
 
@@ -156,8 +157,6 @@ void intervals_to_values_kernel(
     }
 }
 
-// Update wrapper functions to include scaling_factors
-
 extern "C" __global__
 void intervals_to_values_float32(
         const unsigned int* query_starts,
@@ -175,6 +174,7 @@ void intervals_to_values_float32(
         const float default_value,
         const bool default_value_isnan,
         const float* scaling_factors,
+        const bool use_scaling_factors,
         float* out
 ) {
     intervals_to_values_kernel<float>(
@@ -182,7 +182,7 @@ void intervals_to_values_float32(
         track_starts, track_ends, track_values,
         n_tracks, batch_size, sequence_length, max_number_intervals,
         window_size, default_value, default_value_isnan,
-        scaling_factors, out
+        scaling_factors, use_scaling_factors, out
     );
 }
 
@@ -203,6 +203,7 @@ void intervals_to_values_bfloat16(
         const float default_value,
         const bool default_value_isnan,
         const float* scaling_factors,
+        const bool use_scaling_factors,
         __nv_bfloat16* out
 ) {
     intervals_to_values_kernel<__nv_bfloat16>(
@@ -210,6 +211,6 @@ void intervals_to_values_bfloat16(
         track_starts, track_ends, track_values,
         n_tracks, batch_size, sequence_length, max_number_intervals,
         window_size, default_value, default_value_isnan,
-        scaling_factors, out
+        scaling_factors, use_scaling_factors, out
     );
 }
diff --git a/pixi.lock b/pixi.lock
index c69d9da..1b32325 100644
--- a/pixi.lock
+++ b/pixi.lock
@@ -11,78 +11,182 @@ environments:
     - https://pypi.org/simple
     packages:
       linux-64:
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/_libgcc_mutex-0.1-conda_forge.tar.bz2
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-2_gnu.tar.bz2
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-7_kmp_llvm.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/annotated-types-0.7.0-pyhd8ed1ab_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/attr-2.5.2-h39aace5_0.conda
+      - conda: https://conda.anaconda.org/dataloading/linux-64/bigwig-loader-0.3.1-py311h9bf148f_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/binutils_impl_linux-64-2.45-default_hfdba357_104.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/binutils_linux-64-2.45-default_h4852527_104.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/biopython-1.86-py311h49ec1c0_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-hda65f42_8.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2025.10.5-hbd8a1cb_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/cpython-3.11.14-py311hd8ed1ab_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-cccl_linux-64-12.8.90-ha770c72_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-crt-dev_linux-64-12.8.93-ha770c72_3.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/cuda-crt-tools-12.8.93-ha770c72_3.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/cuda-cudart-12.8.90-h5888daf_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/cuda-cudart-dev-12.8.90-h5888daf_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-cudart-dev_linux-64-12.8.90-h3f2d84a_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/cuda-cudart-static-12.8.90-h5888daf_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-cudart-static_linux-64-12.8.90-h3f2d84a_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-cudart_linux-64-12.8.90-h3f2d84a_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/cuda-cuobjdump-12.8.90-hbd13f7d_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/cuda-cupti-12.8.90-h5888daf_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-driver-dev_linux-64-12.8.90-h3f2d84a_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/cuda-nvcc-12.8.93-hcdd1206_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-nvcc-dev_linux-64-12.8.93-he91c749_3.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/cuda-nvcc-impl-12.8.93-h85509e4_3.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/cuda-nvcc-tools-12.8.93-he02047a_3.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/cuda-nvcc_linux-64-12.8.93-he0b4e1d_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/cuda-nvdisasm-12.8.90-hbd13f7d_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/cuda-nvrtc-12.8.93-h5888daf_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/cuda-nvtx-12.8.90-h5888daf_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-nvvm-dev_linux-64-12.8.93-ha770c72_3.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/cuda-nvvm-impl-12.8.93-he02047a_3.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/cuda-nvvm-tools-12.8.93-he02047a_3.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-version-12.8-h5d125a7_3.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/cudnn-9.10.2.21-hbcb9cd8_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/cupy-13.6.0-py311h72da3fd_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/cupy-core-13.6.0-py311he30c881_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/cython-3.2.2-py311h0daaf2c_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/deprecated-1.3.1-pyhd8ed1ab_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/donfig-0.8.1.post1-pyhd8ed1ab_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/fastrlock-0.8.3-py311hc665b79_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/filelock-3.20.0-pyhd8ed1ab_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/fsspec-2025.12.0-pyhd8ed1ab_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/gcc_impl_linux-64-14.3.0-h442bea5_14.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/gcc_linux-64-14.3.0-h298d278_14.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/gmp-6.3.0-hac33072_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/gmpy2-2.2.1-py311h92a432a_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/google-crc32c-1.7.1-py311h2702b87_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/gxx_impl_linux-64-14.3.0-h2185e75_14.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/gxx_linux-64-14.3.0-he6f32d1_14.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/icu-75.1-he02047a_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/ld_impl_linux-64-2.44-h1aa0949_5.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libblas-3.9.0-38_h4a7cf45_openblas.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libcblas-3.9.0-38_h0358290_openblas.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/importlib-metadata-8.7.0-pyhe01879c_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/jinja2-3.1.6-pyhcf101f3_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/kernel-headers_linux-64-4.18.0-he073ed8_8.conda
+      - conda: https://conda.anaconda.org/rapidsai/linux-64/kvikio-25.08.00-cuda12_py311_250806_2f72c39a.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/ld_impl_linux-64-2.45-default_hbd61a6d_104.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libabseil-20250127.1-cxx17_hbbce691_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libblas-3.9.0-37_h5875eb1_mkl.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libcap-2.77-h3ff7636_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libcblas-3.9.0-37_hfef963f_mkl.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libcrc32c-1.1.2-h9c3ff4c_0.tar.bz2
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libcublas-12.8.4.1-h9ab20c4_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libcudnn-9.10.2.21-hf7e9902_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libcudnn-dev-9.10.2.21-h58dd1b1_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libcudss-0.6.0.5-h58dd1b1_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libcufft-11.3.3.83-h5888daf_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libcufile-1.13.1.3-h628e99a_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libcufile-dev-1.13.1.3-h5888daf_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libcurand-10.3.9.90-h9ab20c4_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libcusolver-11.7.3.90-h9ab20c4_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libcusparse-12.5.8.93-h5888daf_1.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libffi-3.5.2-h9ec8514_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libgcc-15.2.0-h767d61c_7.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/libgcc-devel_linux-64-14.3.0-hf649bbc_114.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libgcc-ng-15.2.0-h69a702a_7.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libgfortran-15.2.0-h69a702a_7.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libgfortran5-15.2.0-hcd61629_7.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libgomp-15.2.0-h767d61c_7.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/liblapack-3.9.0-38_h47877c9_openblas.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libhwloc-2.12.1-default_h7f8ec31_1002.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libiconv-1.18-h3b78370_2.conda
+      - conda: https://conda.anaconda.org/rapidsai/linux-64/libkvikio-25.08.00-cuda12_9_250806_2f72c39a.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/liblapack-3.9.0-37_h5e43f62_mkl.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/liblzma-5.8.1-hb9d3cd8_2.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/liblzma-devel-5.8.1-hb9d3cd8_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libmagma-2.9.0-h19665d7_1.conda
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+  license_family: LGPL
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+  - libgcc >=14
+  - python >=3.11,<3.12.0a0
+  - python_abi 3.11.* *_cp311
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+  license_family: Apache
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   - setuptools ; extra == 'test'
   requires_python: '>=3.9'
+- conda: https://conda.anaconda.org/conda-forge/linux-64/gxx_impl_linux-64-14.3.0-h2185e75_14.conda
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+  - tzdata
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+  license_family: GPL
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   timestamp: 1759866571696
+- conda: https://conda.anaconda.org/conda-forge/linux-64/gxx_linux-64-14.3.0-he6f32d1_14.conda
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+  - gcc_linux-64 ==14.3.0 h298d278_14
+  - binutils_linux-64
+  - sysroot_linux-64
+  license: BSD-3-Clause
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+  - python
+  license: BSD-3-Clause
+  license_family: BSD
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+- conda: https://conda.anaconda.org/conda-forge/linux-64/ld_impl_linux-64-2.45-default_hbd61a6d_104.conda
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+  license_family: GPL
+  purls:
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-  - liblapacke 3.9.0   38*_openblas
-  - mkl <2026
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+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libblas-3.11.0-3_h51639a9_openblas.conda
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+  - mkl <2026
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+  - liblapack  3.11.0   3*_openblas
+  - libcblas   3.11.0   3*_openblas
+  license: BSD-3-Clause
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   timestamp: 1744577167992
+- conda: https://conda.anaconda.org/conda-forge/linux-64/libcap-2.77-h3ff7636_0.conda
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+  - attr >=2.5.2,<2.6.0a0
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+  license_family: BSD
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-  - liblapack  3.9.0   38*_openblas
-  - liblapacke 3.9.0   38*_openblas
-  license: BSD-3-Clause
-  license_family: BSD
-  purls:
-  - pkg:pypi/libcblas
-  size: 17503
-  timestamp: 1761680091587
+  timestamp: 1760212763579
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+  - blas 2.303   openblas
+  - liblapack  3.11.0   3*_openblas
+  license: BSD-3-Clause
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   timestamp: 1761680563279
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+  license_family: GPL
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   timestamp: 1753801238063
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 - conda: https://conda.anaconda.org/conda-forge/linux-64/libprotobuf-6.31.1-h49aed37_2.conda
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   timestamp: 1760550241203
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   timestamp: 1762299687230
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   license_family: MIT
   purls:
   - pkg:pypi/pydantic-core
-  size: 1952130
-  timestamp: 1762358856501
+  size: 1938184
+  timestamp: 1762988992467
 - pypi: https://files.pythonhosted.org/packages/c1/60/5d4751ba3f4a40a6891f24eec885f51afd78d208498268c734e256fb13c4/pydantic_settings-2.12.0-py3-none-any.whl
   name: pydantic-settings
   version: 2.12.0
@@ -4586,6 +5694,7 @@ packages:
   - python-dotenv >=0.21.0
   - typing-inspection >=0.4.0
   license: MIT
+  license_family: MIT
   purls:
   - pkg:pypi/pydantic-settings
   size: 43752
@@ -5094,6 +6203,15 @@ packages:
   - aiobotocore[awscli]>=2.5.4,<3.0.0 ; extra == 'awscli'
   - aiobotocore[boto3]>=2.5.4,<3.0.0 ; extra == 'boto3'
   requires_python: '>=3.9'
+- pypi: https://files.pythonhosted.org/packages/44/8c/04797ebb53748b4d594d4c334b2d9a99f2d2e06e19ad505f1313ca5d56eb/s3fs-2025.12.0-py3-none-any.whl
+  name: s3fs
+  version: 2025.12.0
+  sha256: 89d51e0744256baad7ae5410304a368ca195affd93a07795bc8ba9c00c9effbb
+  requires_dist:
+  - aiobotocore>=2.5.4,<3.0.0
+  - fsspec==2025.12.0
+  - aiohttp!=4.0.0a0,!=4.0.0a1
+  requires_python: '>=3.10'
 - pypi: https://files.pythonhosted.org/packages/48/f0/ae7ca09223a81a1d890b2557186ea015f6e0502e9b8cb8e1813f1d8cfa4e/s3transfer-0.14.0-py3-none-any.whl
   name: s3transfer
   version: 0.14.0
@@ -5102,6 +6220,14 @@ packages:
   - botocore>=1.37.4,<2.0a0
   - botocore[crt]>=1.37.4,<2.0a0 ; extra == 'crt'
   requires_python: '>=3.9'
+- pypi: https://files.pythonhosted.org/packages/5f/e1/5ef25f52973aa12a19cf4e1375d00932d7fb354ffd310487ba7d44225c1a/s3transfer-0.15.0-py3-none-any.whl
+  name: s3transfer
+  version: 0.15.0
+  sha256: 6f8bf5caa31a0865c4081186689db1b2534cef721d104eb26101de4b9d6a5852
+  requires_dist:
+  - botocore>=1.37.4,<2.0a0
+  - botocore[crt]>=1.37.4,<2.0a0 ; extra == 'crt'
+  requires_python: '>=3.9'
 - conda: https://conda.anaconda.org/conda-forge/noarch/setuptools-80.9.0-pyhff2d567_0.conda
   sha256: 972560fcf9657058e3e1f97186cc94389144b46dbdf58c807ce62e83f977e863
   md5: 4de79c071274a53dcaf2a8c749d1499e
@@ -5244,6 +6370,19 @@ packages:
   - python-multipart>=0.0.18 ; extra == 'full'
   - pyyaml ; extra == 'full'
   requires_python: '>=3.9'
+- pypi: https://files.pythonhosted.org/packages/d9/52/1064f510b141bd54025f9b55105e26d1fa970b9be67ad766380a3c9b74b0/starlette-0.50.0-py3-none-any.whl
+  name: starlette
+  version: 0.50.0
+  sha256: 9e5391843ec9b6e472eed1365a78c8098cfceb7a74bfd4d6b1c0c0095efb3bca
+  requires_dist:
+  - anyio>=3.6.2,<5
+  - typing-extensions>=4.10.0 ; python_full_version < '3.13'
+  - httpx>=0.27.0,<0.29.0 ; extra == 'full'
+  - itsdangerous ; extra == 'full'
+  - jinja2 ; extra == 'full'
+  - python-multipart>=0.0.18 ; extra == 'full'
+  - pyyaml ; extra == 'full'
+  requires_python: '>=3.10'
 - conda: https://conda.anaconda.org/conda-forge/noarch/sympy-1.14.0-pyh2585a3b_105.conda
   sha256: 09d3b6ac51d437bc996ad006d9f749ca5c645c1900a854a6c8f193cbd13f03a8
   md5: 8c09fac3785696e1c477156192d64b91
@@ -5281,6 +6420,7 @@ packages:
   - libhwloc >=2.12.1,<2.12.2.0a0
   - libstdcxx >=14
   license: Apache-2.0
+  license_family: APACHE
   purls:
   - pkg:pypi/tbb
   size: 171868
@@ -5306,6 +6446,21 @@ packages:
   - pytest ; extra == 'tests'
   - pytest-cov ; extra == 'tests'
   requires_python: '>=3.10'
+- conda: https://conda.anaconda.org/conda-forge/linux-64/tk-8.6.13-noxft_ha0e22de_103.conda
+  sha256: 1544760538a40bcd8ace2b1d8ebe3eb5807ac268641f8acdc18c69c5ebfeaf64
+  md5: 86bc20552bf46075e3d92b67f089172d
+  depends:
+  - __glibc >=2.17,<3.0.a0
+  - libgcc >=13
+  - libzlib >=1.3.1,<2.0a0
+  constrains:
+  - xorg-libx11 >=1.8.12,<2.0a0
+  license: TCL
+  license_family: BSD
+  purls:
+  - pkg:pypi/tk
+  size: 3284905
+  timestamp: 1763054914403
 - conda: https://conda.anaconda.org/conda-forge/linux-64/tk-8.6.13-noxft_hd72426e_102.conda
   sha256: a84ff687119e6d8752346d1d408d5cf360dee0badd487a472aa8ddedfdc219e1
   md5: a0116df4f4ed05c303811a837d5b39d8
@@ -5331,6 +6486,18 @@ packages:
   - pkg:pypi/tk
   size: 3125538
   timestamp: 1748388189063
+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/tk-8.6.13-h892fb3f_3.conda
+  sha256: ad0c67cb03c163a109820dc9ecf77faf6ec7150e942d1e8bb13e5d39dc058ab7
+  md5: a73d54a5abba6543cb2f0af1bfbd6851
+  depends:
+  - __osx >=11.0
+  - libzlib >=1.3.1,<2.0a0
+  license: TCL
+  license_family: BSD
+  purls:
+  - pkg:pypi/tk
+  size: 3125484
+  timestamp: 1763055028377
 - pypi: https://files.pythonhosted.org/packages/86/7f/d8fffe6a7aefdb61bced88fcb5e280cfd71e08939da5894161bd71bea022/tomli-2.3.0-cp311-cp311-macosx_11_0_arm64.whl
   name: tomli
   version: 2.3.0
@@ -5404,9 +6571,9 @@ packages:
   requires_dist:
   - typing-extensions>=4.12.0
   requires_python: '>=3.9'
-- conda: https://conda.anaconda.org/conda-forge/noarch/typing-inspection-0.4.2-pyhd8ed1ab_0.conda
-  sha256: 8aaf69b828c2b94d0784f18f70f11aa032950d304e57e88467120b45c18c24fd
-  md5: 399701494e731ce73fdd86c185a3d1b4
+- conda: https://conda.anaconda.org/conda-forge/noarch/typing-inspection-0.4.2-pyhd8ed1ab_1.conda
+  sha256: 70db27de58a97aeb7ba7448366c9853f91b21137492e0b4430251a1870aa8ff4
+  md5: a0a4a3035667fc34f29bfbd5c190baa6
   depends:
   - python >=3.10
   - typing_extensions >=4.12.0
@@ -5414,8 +6581,8 @@ packages:
   license_family: MIT
   purls:
   - pkg:pypi/typing-inspection
-  size: 18799
-  timestamp: 1759301271883
+  size: 18923
+  timestamp: 1764158430324
 - conda: https://conda.anaconda.org/conda-forge/noarch/typing_extensions-4.15.0-pyhcf101f3_0.conda
   sha256: 032271135bca55aeb156cee361c81350c6f3fb203f57d024d7e5a1fc9ef18731
   md5: 0caa1af407ecff61170c9437a808404d
@@ -5467,9 +6634,41 @@ packages:
   - pydantic ; extra == 'dev-third-party'
   - pydantic-settings ; extra == 'dev-third-party'
   requires_python: '>=3.9'
-- conda: https://conda.anaconda.org/conda-forge/noarch/universal_pathlib-0.3.5-pyhd8ed1ab_0.conda
-  sha256: edc37177064cc052f3ba806a3e6ed11cc83013dc696ab1a37ee91485e0a251dd
-  md5: 65fe2f91dc8d539a3d36c5e60931ff5c
+- pypi: https://files.pythonhosted.org/packages/79/77/53c2d3a0413bc55b4c91067a0c41e55451be9b0784d204e4e46ce5abf668/universal_pathlib-0.3.7-py3-none-any.whl
+  name: universal-pathlib
+  version: 0.3.7
+  sha256: fb95117b20b5981f86ef9d887fddbf9c61d3596634ba42cccea444931d87c201
+  requires_dist:
+  - fsspec>=2024.5.0
+  - pathlib-abc>=0.5.1,<0.6.0
+  - pytest>=8 ; extra == 'tests'
+  - pytest-sugar>=0.9.7 ; extra == 'tests'
+  - pytest-cov>=4.1.0 ; extra == 'tests'
+  - pytest-mock>=3.12.0 ; extra == 'tests'
+  - pylint>=2.17.4 ; extra == 'tests'
+  - mypy>=1.10.0 ; extra == 'tests'
+  - pydantic>=2 ; extra == 'tests'
+  - pytest-mypy-plugins>=3.1.2 ; extra == 'tests'
+  - packaging ; extra == 'tests'
+  - mypy>=1.10.0 ; extra == 'typechecking'
+  - pytest-mypy-plugins>=3.1.2 ; extra == 'typechecking'
+  - fsspec[adl,gcs,github,http,s3,smb,ssh]>=2024.5.0 ; extra == 'dev'
+  - s3fs>=2024.5.0 ; extra == 'dev'
+  - gcsfs>=2024.5.0 ; extra == 'dev'
+  - adlfs>=2024 ; extra == 'dev'
+  - huggingface-hub ; extra == 'dev'
+  - webdav4[fsspec] ; extra == 'dev'
+  - moto[s3,server] ; extra == 'dev'
+  - wsgidav ; extra == 'dev'
+  - cheroot ; extra == 'dev'
+  - pyftpdlib ; extra == 'dev'
+  - typing-extensions ; python_full_version < '3.11' and extra == 'dev'
+  - pydantic ; extra == 'dev-third-party'
+  - pydantic-settings ; extra == 'dev-third-party'
+  requires_python: '>=3.9'
+- conda: https://conda.anaconda.org/conda-forge/noarch/universal_pathlib-0.3.7-pyhd8ed1ab_0.conda
+  sha256: c714a07cf0d559f0e1dfebff7804a39c3efa056c3edccc752e663d518fb1bad4
+  md5: a1e92d38a18ce0a2ab1f094fbbe3d3a0
   depends:
   - fsspec >=2024.5.0
   - pathlib-abc >=0.5.1,<0.6.0
@@ -5478,8 +6677,8 @@ packages:
   license_family: MIT
   purls:
   - pkg:pypi/universal-pathlib
-  size: 62292
-  timestamp: 1762676897088
+  size: 64604
+  timestamp: 1764747444832
 - pypi: https://files.pythonhosted.org/packages/a7/c2/fe1e52489ae3122415c51f387e221dd0773709bad6c6cdaa599e8a2c5185/urllib3-2.5.0-py3-none-any.whl
   name: urllib3
   version: 2.5.0
@@ -5686,17 +6885,50 @@ packages:
   - pkg:pypi/zarr
   size: 290974
   timestamp: 1758255670714
-- conda: https://conda.anaconda.org/conda-forge/noarch/zipp-3.23.0-pyhd8ed1ab_0.conda
-  sha256: 7560d21e1b021fd40b65bfb72f67945a3fcb83d78ad7ccf37b8b3165ec3b68ad
-  md5: df5e78d904988eb55042c0c97446079f
+- conda: https://conda.anaconda.org/conda-forge/noarch/zarr-3.1.5-pyhcf101f3_0.conda
+  sha256: c36bec7d02d2f227409fcc4cf586cf3a658af068b58374de7f8f2d0b5c1c84f9
+  md5: c1844a94b2be61bb03bbb71574a0abfc
   depends:
-  - python >=3.9
+  - python >=3.11
+  - packaging >=22.0
+  - numpy >=1.26
+  - numcodecs >=0.14
+  - typing_extensions >=4.9
+  - donfig >=0.8
+  - google-crc32c >=1.5
+  - python
+  constrains:
+  - fsspec >=2023.10.0
+  - obstore >=0.5.1
+  license: MIT
+  license_family: MIT
+  purls:
+  - pkg:pypi/zarr
+  size: 305998
+  timestamp: 1763742695201
+- conda: https://conda.anaconda.org/conda-forge/noarch/zipp-3.23.0-pyhcf101f3_1.conda
+  sha256: b4533f7d9efc976511a73ef7d4a2473406d7f4c750884be8e8620b0ce70f4dae
+  md5: 30cd29cb87d819caead4d55184c1d115
+  depends:
+  - python >=3.10
+  - python
   license: MIT
   license_family: MIT
   purls:
   - pkg:pypi/zipp
-  size: 22963
-  timestamp: 1749421737203
+  size: 24194
+  timestamp: 1764460141901
+- conda: https://conda.anaconda.org/conda-forge/linux-64/zstd-1.5.7-hb78ec9c_6.conda
+  sha256: 68f0206ca6e98fea941e5717cec780ed2873ffabc0e1ed34428c061e2c6268c7
+  md5: 4a13eeac0b5c8e5b8ab496e6c4ddd829
+  depends:
+  - __glibc >=2.17,<3.0.a0
+  - libzlib >=1.3.1,<2.0a0
+  license: BSD-3-Clause
+  purls:
+  - pkg:pypi/zstd
+  size: 601375
+  timestamp: 1764777111296
 - conda: https://conda.anaconda.org/conda-forge/linux-64/zstd-1.5.7-hb8e6e7a_2.conda
   sha256: a4166e3d8ff4e35932510aaff7aa90772f84b4d07e9f6f83c614cba7ceefe0eb
   md5: 6432cb5d4ac0046c3ac0a8a0f95842f9
diff --git a/tests/test_searchsorted.py b/tests/test_searchsorted.py
index 619ca21..860025a 100644
--- a/tests/test_searchsorted.py
+++ b/tests/test_searchsorted.py
@@ -1,6 +1,7 @@
 import cupy as cp
 import pytest
 
+from bigwig_loader.searchsorted import interval_searchsorted
 from bigwig_loader.searchsorted import searchsorted
 
 
@@ -86,3 +87,298 @@ def test_searchsorted_right_absolute(test_data) -> None:
     )
     expected = cp.asarray([[1, 1, 2], [8, 9, 10], [17, 19, 21], [25, 25, 25]])
     assert (output == expected).all()
+
+
+# ========== Tests for empty subarrays ==========
+
+
+@pytest.fixture
+def test_data_with_empty_subarrays():
+    """Test data where some subarrays are empty (size=0)."""
+    intervals_track1 = [5, 10, 12, 18]
+    # track2 is empty
+    intervals_track3 = [1, 2, 3, 4, 5]
+    # track4 is empty
+    intervals_track5 = [100, 200]
+
+    array = cp.asarray(
+        intervals_track1 + intervals_track3 + intervals_track5,
+        dtype=cp.uint32,
+    )
+    queries = cp.asarray([7, 9, 11], dtype=cp.uint32)
+    sizes = cp.asarray(
+        [
+            len(intervals_track1),  # 4
+            0,  # empty
+            len(intervals_track3),  # 5
+            0,  # empty
+            len(intervals_track5),  # 2
+        ],
+        dtype=cp.uint32,
+    )
+    return array, queries, sizes
+
+
+def test_searchsorted_with_empty_subarrays_left_absolute(
+    test_data_with_empty_subarrays,
+) -> None:
+    """Empty subarrays should return 0 (no valid indices)."""
+    array, queries, sizes = test_data_with_empty_subarrays
+    output = searchsorted(
+        array=array, queries=queries, sizes=sizes, side="left", absolute_indices=True
+    )
+
+    # Track 0: [5, 10, 12, 18], queries [7, 9, 11] -> left indices [1, 1, 2] + start 0 = [1, 1, 2]
+    # Track 1: empty -> [0, 0, 0]
+    # Track 2: [1, 2, 3, 4, 5], queries [7, 9, 11] -> all past end -> [5, 5, 5] + start 4 = [9, 9, 9]
+    # Track 3: empty -> [0, 0, 0]
+    # Track 4: [100, 200], queries [7, 9, 11] -> all before start -> [0, 0, 0] + start 9 = [9, 9, 9]
+
+    expected = cp.asarray(
+        [
+            [1, 1, 2],  # track 0
+            [0, 0, 0],  # track 1 (empty)
+            [9, 9, 9],  # track 2
+            [0, 0, 0],  # track 3 (empty)
+            [9, 9, 9],  # track 4
+        ],
+        dtype=cp.uint32,
+    )
+
+    assert (
+        output == expected
+    ).all(), f"Expected:\n{expected.get()}\nGot:\n{output.get()}"
+
+
+def test_searchsorted_with_empty_subarrays_right_absolute(
+    test_data_with_empty_subarrays,
+) -> None:
+    """Empty subarrays should return 0 (no valid indices)."""
+    array, queries, sizes = test_data_with_empty_subarrays
+    output = searchsorted(
+        array=array, queries=queries, sizes=sizes, side="right", absolute_indices=True
+    )
+
+    # Track 0: [5, 10, 12, 18], queries [7, 9, 11] -> right indices [1, 1, 2] + start 0 = [1, 1, 2]
+    # Track 1: empty -> [0, 0, 0]
+    # Track 2: [1, 2, 3, 4, 5], queries [7, 9, 11] -> all past end -> [5, 5, 5] + start 4 = [9, 9, 9]
+    # Track 3: empty -> [0, 0, 0]
+    # Track 4: [100, 200], queries [7, 9, 11] -> all before start -> [0, 0, 0] + start 9 = [9, 9, 9]
+
+    expected = cp.asarray(
+        [
+            [1, 1, 2],  # track 0
+            [0, 0, 0],  # track 1 (empty)
+            [9, 9, 9],  # track 2
+            [0, 0, 0],  # track 3 (empty)
+            [9, 9, 9],  # track 4
+        ],
+        dtype=cp.uint32,
+    )
+
+    assert (
+        output == expected
+    ).all(), f"Expected:\n{expected.get()}\nGot:\n{output.get()}"
+
+
+def test_searchsorted_with_empty_subarrays_relative(
+    test_data_with_empty_subarrays,
+) -> None:
+    """Empty subarrays should return 0 in relative indices too."""
+    array, queries, sizes = test_data_with_empty_subarrays
+    output = searchsorted(
+        array=array, queries=queries, sizes=sizes, side="left", absolute_indices=False
+    )
+
+    # Track 1 and 3 are empty, should return 0
+    assert (
+        output[1, :] == 0
+    ).all(), f"Empty track 1 should have all zeros, got {output[1].get()}"
+    assert (
+        output[3, :] == 0
+    ).all(), f"Empty track 3 should have all zeros, got {output[3].get()}"
+
+
+def test_searchsorted_all_empty_subarrays() -> None:
+    """Test when ALL subarrays are empty."""
+    array = cp.asarray([], dtype=cp.uint32)
+    queries = cp.asarray([7, 9, 11], dtype=cp.uint32)
+    sizes = cp.asarray([0, 0, 0], dtype=cp.uint32)
+
+    output = searchsorted(
+        array=array, queries=queries, sizes=sizes, side="left", absolute_indices=True
+    )
+
+    expected = cp.zeros((3, 3), dtype=cp.uint32)
+    assert (output == expected).all(), f"Expected all zeros, got:\n{output.get()}"
+
+
+def test_searchsorted_single_empty_subarray() -> None:
+    """Test with a single empty subarray."""
+    array = cp.asarray([], dtype=cp.uint32)
+    queries = cp.asarray([1, 2, 3], dtype=cp.uint32)
+    sizes = cp.asarray([0], dtype=cp.uint32)
+
+    output = searchsorted(
+        array=array, queries=queries, sizes=sizes, side="right", absolute_indices=True
+    )
+
+    expected = cp.zeros((1, 3), dtype=cp.uint32)
+    assert (output == expected).all()
+
+
+def test_searchsorted_empty_subarray_at_start() -> None:
+    """Test with empty subarray at the beginning."""
+    array = cp.asarray([10, 20, 30], dtype=cp.uint32)
+    queries = cp.asarray([15, 25], dtype=cp.uint32)
+    sizes = cp.asarray([0, 3], dtype=cp.uint32)  # First empty, second has 3 elements
+
+    output = searchsorted(
+        array=array, queries=queries, sizes=sizes, side="left", absolute_indices=True
+    )
+
+    # Track 0: empty -> [0, 0]
+    # Track 1: [10, 20, 30], queries [15, 25] -> [1, 2] + start 0 = [1, 2]
+    expected = cp.asarray(
+        [
+            [0, 0],  # empty track
+            [1, 2],  # normal track
+        ],
+        dtype=cp.uint32,
+    )
+
+    assert (
+        output == expected
+    ).all(), f"Expected:\n{expected.get()}\nGot:\n{output.get()}"
+
+
+def test_searchsorted_empty_subarray_at_end() -> None:
+    """Test with empty subarray at the end."""
+    array = cp.asarray([10, 20, 30], dtype=cp.uint32)
+    queries = cp.asarray([15, 25], dtype=cp.uint32)
+    sizes = cp.asarray([3, 0], dtype=cp.uint32)  # First has 3 elements, second empty
+
+    output = searchsorted(
+        array=array, queries=queries, sizes=sizes, side="left", absolute_indices=True
+    )
+
+    # Track 0: [10, 20, 30], queries [15, 25] -> [1, 2] + start 0 = [1, 2]
+    # Track 1: empty -> [0, 0]
+    expected = cp.asarray(
+        [
+            [1, 2],  # normal track
+            [0, 0],  # empty track
+        ],
+        dtype=cp.uint32,
+    )
+
+    assert (
+        output == expected
+    ).all(), f"Expected:\n{expected.get()}\nGot:\n{output.get()}"
+
+
+# ========== Tests for interval_searchsorted with empty subarrays ==========
+
+
+def test_interval_searchsorted_with_empty_subarrays() -> None:
+    """Test interval_searchsorted with some empty tracks."""
+    # Intervals: track 0 has data, track 1 is empty, track 2 has data
+    # Track 0: intervals [10-20], [30-40], [50-60]
+    # Track 1: empty
+    # Track 2: intervals [100-110], [120-130]
+
+    array_start = cp.asarray([10, 30, 50, 100, 120], dtype=cp.uint32)
+    array_end = cp.asarray([20, 40, 60, 110, 130], dtype=cp.uint32)
+
+    query_starts = cp.asarray([35], dtype=cp.uint32)  # Query region 35-45
+    query_ends = cp.asarray([45], dtype=cp.uint32)
+
+    sizes = cp.asarray([3, 0, 2], dtype=cp.uint32)  # Track 1 is empty
+
+    found_starts, found_ends = interval_searchsorted(
+        array_start, array_end, query_starts, query_ends, sizes=sizes
+    )
+
+    # For track 1 (empty), found_starts and found_ends should both be 0
+    # This ensures the interval loop does nothing
+    assert (
+        found_starts[1, 0] == 0
+    ), f"Empty track found_starts should be 0, got {found_starts[1, 0]}"
+    assert (
+        found_ends[1, 0] == 0
+    ), f"Empty track found_ends should be 0, got {found_ends[1, 0]}"
+
+    # For empty tracks, found_starts should equal found_ends (empty range)
+    assert (
+        found_starts[1, 0] == found_ends[1, 0]
+    ), "Empty track should have found_starts == found_ends"
+
+
+def test_interval_searchsorted_empty_tracks_no_intervals_to_process() -> None:
+    """Verify that empty tracks result in no intervals being selected."""
+    # All empty tracks
+    array_start = cp.asarray([], dtype=cp.uint32)
+    array_end = cp.asarray([], dtype=cp.uint32)
+
+    query_starts = cp.asarray([100, 200], dtype=cp.uint32)
+    query_ends = cp.asarray([150, 250], dtype=cp.uint32)
+
+    sizes = cp.asarray([0, 0, 0], dtype=cp.uint32)  # 3 empty tracks
+
+    found_starts, found_ends = interval_searchsorted(
+        array_start, array_end, query_starts, query_ends, sizes=sizes
+    )
+
+    # All should be zero
+    assert (
+        found_starts == 0
+    ).all(), f"All found_starts should be 0, got:\n{found_starts.get()}"
+    assert (
+        found_ends == 0
+    ).all(), f"All found_ends should be 0, got:\n{found_ends.get()}"
+
+    # Verify shape is correct
+    assert found_starts.shape == (
+        3,
+        2,
+    ), f"Expected shape (3, 2), got {found_starts.shape}"
+    assert found_ends.shape == (3, 2), f"Expected shape (3, 2), got {found_ends.shape}"
+
+
+def test_interval_searchsorted_mixed_empty_and_nonempty() -> None:
+    """Test with a realistic mix of empty and non-empty tracks."""
+    # Simulating 5 tracks where tracks 1 and 3 have no data for this chromosome
+    # Track 0: 2 intervals
+    # Track 1: empty
+    # Track 2: 3 intervals
+    # Track 3: empty
+    # Track 4: 1 interval
+
+    array_start = cp.asarray([10, 50, 100, 150, 200, 300], dtype=cp.uint32)
+    array_end = cp.asarray([20, 60, 120, 180, 220, 350], dtype=cp.uint32)
+
+    query_starts = cp.asarray([15], dtype=cp.uint32)
+    query_ends = cp.asarray([160], dtype=cp.uint32)
+
+    sizes = cp.asarray([2, 0, 3, 0, 1], dtype=cp.uint32)
+
+    found_starts, found_ends = interval_searchsorted(
+        array_start, array_end, query_starts, query_ends, sizes=sizes
+    )
+
+    # Verify empty tracks have found_starts == found_ends == 0
+    assert (
+        found_starts[1, 0] == 0 and found_ends[1, 0] == 0
+    ), "Track 1 (empty) should have zeros"
+    assert (
+        found_starts[3, 0] == 0 and found_ends[3, 0] == 0
+    ), "Track 3 (empty) should have zeros"
+
+    # Verify non-empty tracks have valid ranges (found_starts <= found_ends for non-empty results)
+    # or found_starts > found_ends for regions with no overlapping intervals
+    for i in [0, 2, 4]:
+        start = int(found_starts[i, 0])
+        end = int(found_ends[i, 0])
+        # Either valid range or empty range, but not garbage values
+        assert start < 1000000, f"Track {i} found_starts looks like garbage: {start}"
+        assert end < 1000000, f"Track {i} found_ends looks like garbage: {end}"