diff --git a/.DS_Store b/.DS_Store
index 97f546b3..6fb74428 100644
Binary files a/.DS_Store and b/.DS_Store differ
diff --git a/poetry.lock b/poetry.lock
index 5a32d62a..68a340cc 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1,4 +1,4 @@
-# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand.
+# This file is automatically @generated by Poetry 1.8.5 and should not be changed by hand.
 
 [[package]]
 name = "aiosignal"
@@ -38,37 +38,34 @@ files = [
 
 [[package]]
 name = "asttokens"
-version = "2.4.1"
+version = "3.0.0"
 description = "Annotate AST trees with source code positions"
 optional = false
-python-versions = "*"
+python-versions = ">=3.8"
 files = [
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-    {file = "asttokens-2.4.1.tar.gz", hash = "sha256:b03869718ba9a6eb027e134bfdf69f38a236d681c83c160d510768af11254ba0"},
+    {file = "asttokens-3.0.0-py3-none-any.whl", hash = "sha256:e3078351a059199dd5138cb1c706e6430c05eff2ff136af5eb4790f9d28932e2"},
+    {file = "asttokens-3.0.0.tar.gz", hash = "sha256:0dcd8baa8d62b0c1d118b399b2ddba3c4aff271d0d7a9e0d4c1681c79035bbc7"},
 ]
 
-[package.dependencies]
-six = ">=1.12.0"
-
 [package.extras]
-astroid = ["astroid (>=1,<2)", "astroid (>=2,<4)"]
-test = ["astroid (>=1,<2)", "astroid (>=2,<4)", "pytest"]
+astroid = ["astroid (>=2,<4)"]
+test = ["astroid (>=2,<4)", "pytest", "pytest-cov", "pytest-xdist"]
 
 [[package]]
 name = "attrs"
-version = "24.2.0"
+version = "24.3.0"
 description = "Classes Without Boilerplate"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
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+    {file = "attrs-24.3.0-py3-none-any.whl", hash = "sha256:ac96cd038792094f438ad1f6ff80837353805ac950cd2aa0e0625ef19850c308"},
+    {file = "attrs-24.3.0.tar.gz", hash = "sha256:8f5c07333d543103541ba7be0e2ce16eeee8130cb0b3f9238ab904ce1e85baff"},
 ]
 
 [package.extras]
 benchmark = ["cloudpickle", "hypothesis", "mypy (>=1.11.1)", "pympler", "pytest (>=4.3.0)", "pytest-codspeed", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
 cov = ["cloudpickle", "coverage[toml] (>=5.3)", "hypothesis", "mypy (>=1.11.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
-dev = ["cloudpickle", "hypothesis", "mypy (>=1.11.1)", "pre-commit", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
+dev = ["cloudpickle", "hypothesis", "mypy (>=1.11.1)", "pre-commit-uv", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
 docs = ["cogapp", "furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier (<24.7)"]
 tests = ["cloudpickle", "hypothesis", "mypy (>=1.11.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
 tests-mypy = ["mypy (>=1.11.1)", "pytest-mypy-plugins"]
@@ -175,13 +172,13 @@ files = [
 
 [[package]]
 name = "certifi"
-version = "2024.8.30"
+version = "2024.12.14"
 description = "Python package for providing Mozilla's CA Bundle."
 optional = false
 python-versions = ">=3.6"
 files = [
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 ]
 
 [[package]]
@@ -404,13 +401,13 @@ contrib = ["autoray", "numba (>=0.53.0)", "opt-einsum", "ply (>=3.4)", "pylatex
 
 [[package]]
 name = "click"
-version = "8.1.7"
+version = "8.1.8"
 description = "Composable command line interface toolkit"
 optional = false
 python-versions = ">=3.7"
 files = [
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+    {file = "click-8.1.8-py3-none-any.whl", hash = "sha256:63c132bbbed01578a06712a2d1f497bb62d9c1c0d329b7903a866228027263b2"},
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 ]
 
 [package.dependencies]
@@ -613,97 +610,111 @@ tests = ["pytest", "pytest-cov", "pytest-xdist"]
 
 [[package]]
 name = "cytoolz"
-version = "1.0.0"
+version = "1.0.1"
 description = "Cython implementation of Toolz: High performance functional utilities"
 optional = false
 python-versions = ">=3.8"
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 [package.dependencies]
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 [[package]]
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 [[package]]
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+version = "2.21.1"
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 python-versions = "*"
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 [package.extras]
@@ -884,59 +899,61 @@ pyflakes = ">=2.4.0,<2.5.0"
 
 [[package]]
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+version = "4.55.3"
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 [[package]]
@@ -1327,32 +1359,32 @@ colors = ["colorama (>=0.4.6)"]
 
 [[package]]
 name = "jedi"
-version = "0.19.1"
+version = "0.19.2"
 description = "An autocompletion tool for Python that can be used for text editors."
 optional = false
 python-versions = ">=3.6"
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 ]
 
 [package.dependencies]
-parso = ">=0.8.3,<0.9.0"
+parso = ">=0.8.4,<0.9.0"
 
 [package.extras]
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 qa = ["flake8 (==5.0.4)", "mypy (==0.971)", "types-setuptools (==67.2.0.1)"]
-testing = ["Django", "attrs", "colorama", "docopt", "pytest (<7.0.0)"]
+testing = ["Django", "attrs", "colorama", "docopt", "pytest (<9.0.0)"]
 
 [[package]]
 name = "jinja2"
-version = "3.1.4"
+version = "3.1.5"
 description = "A very fast and expressive template engine."
 optional = false
 python-versions = ">=3.7"
 files = [
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 ]
 
 [package.dependencies]
@@ -2195,13 +2227,13 @@ files = [
 
 [[package]]
 name = "packaging"
-version = "24.1"
+version = "24.2"
 description = "Core utilities for Python packages"
 optional = false
 python-versions = ">=3.8"
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 ]
 
 [[package]]
@@ -2241,8 +2273,8 @@ files = [
 [package.dependencies]
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     {version = ">=1.23.2", markers = "python_version >= \"3.11\""},
+    {version = ">=1.21.0", markers = "python_version >= \"3.10\" and python_version < \"3.11\""},
 ]
 python-dateutil = ">=2.8.2"
 pytz = ">=2020.1"
@@ -2488,52 +2520,53 @@ wcwidth = "*"
 
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 python-versions = ">=3.8"
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 ]
 
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 description = "Cross-platform lib for process and system monitoring in Python."
 optional = false
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,>=2.7"
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 [package.extras]
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+test = ["pytest", "pytest-xdist", "setuptools"]
 
 [[package]]
 name = "ptyprocess"
@@ -2700,29 +2733,29 @@ files = [
 
 [[package]]
 name = "pywin32"
-version = "307"
+version = "308"
 description = "Python for Window Extensions"
 optional = false
 python-versions = "*"
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 [[package]]
@@ -3066,114 +3099,114 @@ use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"]
 
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 [package.dependencies]
@@ -3509,7 +3550,7 @@ aioodbc = ["aioodbc", "greenlet (!=0.4.17)"]
 aiosqlite = ["aiosqlite", "greenlet (!=0.4.17)", "typing_extensions (!=3.10.0.1)"]
 asyncio = ["greenlet (!=0.4.17)"]
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 mssql = ["pyodbc"]
 mssql-pymssql = ["pymssql"]
 mssql-pyodbc = ["pyodbc"]
@@ -3645,13 +3686,43 @@ widechars = ["wcwidth"]
 
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+    {file = "tomli-2.2.1-py3-none-any.whl", hash = "sha256:cb55c73c5f4408779d0cf3eef9f762b9c9f147a77de7b258bef0a5628adc85cc"},
+    {file = "tomli-2.2.1.tar.gz", hash = "sha256:cd45e1dc79c835ce60f7404ec8119f2eb06d38b1deba146f07ced3bbc44505ff"},
 ]
 
 [[package]]
@@ -3667,40 +3738,41 @@ files = [
 
 [[package]]
 name = "tornado"
-version = "6.4.1"
+version = "6.4.2"
 description = "Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "tornado-6.4.1-cp38-abi3-macosx_10_9_universal2.whl", hash = "sha256:163b0aafc8e23d8cdc3c9dfb24c5368af84a81e3364745ccb4427669bf84aec8"},
-    {file = "tornado-6.4.1-cp38-abi3-macosx_10_9_x86_64.whl", hash = "sha256:6d5ce3437e18a2b66fbadb183c1d3364fb03f2be71299e7d10dbeeb69f4b2a14"},
-    {file = "tornado-6.4.1-cp38-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e2e20b9113cd7293f164dc46fffb13535266e713cdb87bd2d15ddb336e96cfc4"},
-    {file = "tornado-6.4.1-cp38-abi3-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:8ae50a504a740365267b2a8d1a90c9fbc86b780a39170feca9bcc1787ff80842"},
-    {file = "tornado-6.4.1-cp38-abi3-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:613bf4ddf5c7a95509218b149b555621497a6cc0d46ac341b30bd9ec19eac7f3"},
-    {file = "tornado-6.4.1-cp38-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:25486eb223babe3eed4b8aecbac33b37e3dd6d776bc730ca14e1bf93888b979f"},
-    {file = "tornado-6.4.1-cp38-abi3-musllinux_1_2_i686.whl", hash = "sha256:454db8a7ecfcf2ff6042dde58404164d969b6f5d58b926da15e6b23817950fc4"},
-    {file = "tornado-6.4.1-cp38-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:a02a08cc7a9314b006f653ce40483b9b3c12cda222d6a46d4ac63bb6c9057698"},
-    {file = "tornado-6.4.1-cp38-abi3-win32.whl", hash = "sha256:d9a566c40b89757c9aa8e6f032bcdb8ca8795d7c1a9762910c722b1635c9de4d"},
-    {file = "tornado-6.4.1-cp38-abi3-win_amd64.whl", hash = "sha256:b24b8982ed444378d7f21d563f4180a2de31ced9d8d84443907a0a64da2072e7"},
-    {file = "tornado-6.4.1.tar.gz", hash = "sha256:92d3ab53183d8c50f8204a51e6f91d18a15d5ef261e84d452800d4ff6fc504e9"},
+    {file = "tornado-6.4.2-cp38-abi3-macosx_10_9_universal2.whl", hash = "sha256:e828cce1123e9e44ae2a50a9de3055497ab1d0aeb440c5ac23064d9e44880da1"},
+    {file = "tornado-6.4.2-cp38-abi3-macosx_10_9_x86_64.whl", hash = "sha256:072ce12ada169c5b00b7d92a99ba089447ccc993ea2143c9ede887e0937aa803"},
+    {file = "tornado-6.4.2-cp38-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1a017d239bd1bb0919f72af256a970624241f070496635784d9bf0db640d3fec"},
+    {file = "tornado-6.4.2-cp38-abi3-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:c36e62ce8f63409301537222faffcef7dfc5284f27eec227389f2ad11b09d946"},
+    {file = "tornado-6.4.2-cp38-abi3-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bca9eb02196e789c9cb5c3c7c0f04fb447dc2adffd95265b2c7223a8a615ccbf"},
+    {file = "tornado-6.4.2-cp38-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:304463bd0772442ff4d0f5149c6f1c2135a1fae045adf070821c6cdc76980634"},
+    {file = "tornado-6.4.2-cp38-abi3-musllinux_1_2_i686.whl", hash = "sha256:c82c46813ba483a385ab2a99caeaedf92585a1f90defb5693351fa7e4ea0bf73"},
+    {file = "tornado-6.4.2-cp38-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:932d195ca9015956fa502c6b56af9eb06106140d844a335590c1ec7f5277d10c"},
+    {file = "tornado-6.4.2-cp38-abi3-win32.whl", hash = "sha256:2876cef82e6c5978fde1e0d5b1f919d756968d5b4282418f3146b79b58556482"},
+    {file = "tornado-6.4.2-cp38-abi3-win_amd64.whl", hash = "sha256:908b71bf3ff37d81073356a5fadcc660eb10c1476ee6e2725588626ce7e5ca38"},
+    {file = "tornado-6.4.2.tar.gz", hash = "sha256:92bad5b4746e9879fd7bf1eb21dce4e3fc5128d71601f80005afa39237ad620b"},
 ]
 
 [[package]]
 name = "tqdm"
-version = "4.66.5"
+version = "4.67.1"
 description = "Fast, Extensible Progress Meter"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "tqdm-4.66.5-py3-none-any.whl", hash = "sha256:90279a3770753eafc9194a0364852159802111925aa30eb3f9d85b0e805ac7cd"},
-    {file = "tqdm-4.66.5.tar.gz", hash = "sha256:e1020aef2e5096702d8a025ac7d16b1577279c9d63f8375b63083e9a5f0fcbad"},
+    {file = "tqdm-4.67.1-py3-none-any.whl", hash = "sha256:26445eca388f82e72884e0d580d5464cd801a3ea01e63e5601bdff9ba6a48de2"},
+    {file = "tqdm-4.67.1.tar.gz", hash = "sha256:f8aef9c52c08c13a65f30ea34f4e5aac3fd1a34959879d7e59e63027286627f2"},
 ]
 
 [package.dependencies]
 colorama = {version = "*", markers = "platform_system == \"Windows\""}
 
 [package.extras]
-dev = ["pytest (>=6)", "pytest-cov", "pytest-timeout", "pytest-xdist"]
+dev = ["nbval", "pytest (>=6)", "pytest-asyncio (>=0.24)", "pytest-cov", "pytest-timeout"]
+discord = ["requests"]
 notebook = ["ipywidgets (>=6)"]
 slack = ["slack-sdk"]
 telegram = ["requests"]
diff --git a/symmer/.DS_Store b/symmer/.DS_Store
index b80ade34..c0998b76 100644
Binary files a/symmer/.DS_Store and b/symmer/.DS_Store differ
diff --git a/symmer/utils.py b/symmer/utils.py
index c61c2b49..b6902b3f 100644
--- a/symmer/utils.py
+++ b/symmer/utils.py
@@ -224,77 +224,77 @@ def gram_schmidt_from_quantum_state(state:Union[np.array, list, QuantumState]) -
 
     return M
 
-def get_sparse_matrix_large_pauliwordop(P_op: PauliwordOp) -> csr_matrix:
-    """
-    In order to build the sparse matrix (e.g. above 18 qubits), this function goes through each pauli term
-    divides into two equally sized tensor products finds the sparse matrix of those and then does a sparse
-    kron product to get the large matrix.
-
-    TODO:  Could also add how many chunks to split problem into (e.g. three/four/... tensor products).
-
-    Args:
-        P_op (PauliwordOp): Pauli operator to convert into sparse matrix
-    Returns:
-        mat (csr_matrix): sparse matrix of P_op
-    """
-    nq = P_op.n_qubits
-    if nq<16:
-        mat = P_op.to_sparse_matrix
-    else:
-        # n_cpus = mp.cpu_count()
-        # P_op_chunks_inds = np.rint(np.linspace(0, P_op.n_terms, min(n_cpus, P_op.n_terms))).astype(set).astype(int)
-        #
-        # # miss zero index out (as emtpy list)
-        # P_op_chunks = [P_op[P_op_chunks_inds[ind_i]: P_op_chunks_inds[ind_i+1]] for ind_i, _ in enumerate(P_op_chunks_inds[1:])]
-        # with mp.Pool(n_cpus) as pool:
-        #     tracker = pool.map(_get_sparse_matrix_large_pauliwordop, P_op_chunks)
-
-        # plus one below due to indexing (actual number of chunks ignores this value)
-        n_chunks = os.cpu_count()
-        if (n_chunks<=1) or (P_op.n_terms<=1):
-            # no multiprocessing possible
-            mat = get(_get_sparse_matrix_large_pauliwordop.remote(P_op))
-        else:
-            # plus one below due to indexing (actual number of chunks ignores this value)
-            n_chunks += 1
-            P_op_chunks_inds = np.rint(np.linspace(0, P_op.n_terms, min(n_chunks, P_op.n_terms+1))).astype(set).astype(int)
-            P_op_chunks = [P_op[P_op_chunks_inds[ind_i]: P_op_chunks_inds[ind_i + 1]] for ind_i, _ in
-                           enumerate(P_op_chunks_inds[1:])]
-            tracker = np.array(get(
-                [_get_sparse_matrix_large_pauliwordop.remote(op) for op in P_op_chunks]))
-            mat = reduce(lambda x, y: x + y, tracker)
-
-    return mat
-
-@remote(num_cpus=os.cpu_count(),
-            runtime_env={
-                "env_vars": {
-                    "NUMBA_NUM_THREADS": os.getenv("NUMBA_NUM_THREADS"),
-                    # "OMP_NUM_THREADS": str(os.cpu_count()),
-                    "OMP_NUM_THREADS": os.getenv("NUMBA_NUM_THREADS"),
-                    "NUMEXPR_MAX_THREADS": str(os.cpu_count())
-                }
-            }
-            )
-def _get_sparse_matrix_large_pauliwordop(P_op: PauliwordOp) -> csr_matrix:
-    """
-    """
-    nq = P_op.n_qubits
-    mat = csr_matrix(([], ([],[])), shape=(2**nq,2**nq))
-    for op in P_op:
-        left_tensor = np.hstack((op.X_block[:, :nq // 2],
-                                 op.Z_block[:, :nq // 2]))
-        left_coeff = op.coeff_vec
-
-        right_tensor = np.hstack((op.X_block[:, nq // 2:],
-                                  op.Z_block[:, nq // 2:]))
-        right_coeff = np.array([1])
-
-        mat += sparse_kron(PauliwordOp(left_tensor, left_coeff).to_sparse_matrix,
-                           PauliwordOp(right_tensor, right_coeff).to_sparse_matrix,
-                           format='csr')  # setting format makes this faster!
-
-    return mat
+# def get_sparse_matrix_large_pauliwordop(P_op: PauliwordOp) -> csr_matrix:
+#     """
+#     In order to build the sparse matrix (e.g. above 18 qubits), this function goes through each pauli term
+#     divides into two equally sized tensor products finds the sparse matrix of those and then does a sparse
+#     kron product to get the large matrix.
+
+#     TODO:  Could also add how many chunks to split problem into (e.g. three/four/... tensor products).
+
+#     Args:
+#         P_op (PauliwordOp): Pauli operator to convert into sparse matrix
+#     Returns:
+#         mat (csr_matrix): sparse matrix of P_op
+#     """
+#     nq = P_op.n_qubits
+#     if nq<16:
+#         mat = P_op.to_sparse_matrix
+#     else:
+#         # n_cpus = mp.cpu_count()
+#         # P_op_chunks_inds = np.rint(np.linspace(0, P_op.n_terms, min(n_cpus, P_op.n_terms))).astype(set).astype(int)
+#         #
+#         # # miss zero index out (as emtpy list)
+#         # P_op_chunks = [P_op[P_op_chunks_inds[ind_i]: P_op_chunks_inds[ind_i+1]] for ind_i, _ in enumerate(P_op_chunks_inds[1:])]
+#         # with mp.Pool(n_cpus) as pool:
+#         #     tracker = pool.map(_get_sparse_matrix_large_pauliwordop, P_op_chunks)
+
+#         # plus one below due to indexing (actual number of chunks ignores this value)
+#         n_chunks = os.cpu_count()
+#         if (n_chunks<=1) or (P_op.n_terms<=1):
+#             # no multiprocessing possible
+#             mat = get(_get_sparse_matrix_large_pauliwordop.remote(P_op))
+#         else:
+#             # plus one below due to indexing (actual number of chunks ignores this value)
+#             n_chunks += 1
+#             P_op_chunks_inds = np.rint(np.linspace(0, P_op.n_terms, min(n_chunks, P_op.n_terms+1))).astype(set).astype(int)
+#             P_op_chunks = [P_op[P_op_chunks_inds[ind_i]: P_op_chunks_inds[ind_i + 1]] for ind_i, _ in
+#                            enumerate(P_op_chunks_inds[1:])]
+#             tracker = np.array(get(
+#                 [_get_sparse_matrix_large_pauliwordop.remote(op) for op in P_op_chunks]))
+#             mat = reduce(lambda x, y: x + y, tracker)
+
+#     return mat
+
+# @remote(num_cpus=os.cpu_count(),
+#             runtime_env={
+#                 "env_vars": {
+#                     "NUMBA_NUM_THREADS": os.getenv("NUMBA_NUM_THREADS"),
+#                     # "OMP_NUM_THREADS": str(os.cpu_count()),
+#                     "OMP_NUM_THREADS": os.getenv("NUMBA_NUM_THREADS"),
+#                     "NUMEXPR_MAX_THREADS": str(os.cpu_count())
+#                 }
+#             }
+#             )
+# def _get_sparse_matrix_large_pauliwordop(P_op: PauliwordOp) -> csr_matrix:
+#     """
+#     """
+#     nq = P_op.n_qubits
+#     mat = csr_matrix(([], ([],[])), shape=(2**nq,2**nq))
+#     for op in P_op:
+#         left_tensor = np.hstack((op.X_block[:, :nq // 2],
+#                                  op.Z_block[:, :nq // 2]))
+#         left_coeff = op.coeff_vec
+
+#         right_tensor = np.hstack((op.X_block[:, nq // 2:],
+#                                   op.Z_block[:, nq // 2:]))
+#         right_coeff = np.array([1])
+
+#         mat += sparse_kron(PauliwordOp(left_tensor, left_coeff).to_sparse_matrix,
+#                            PauliwordOp(right_tensor, right_coeff).to_sparse_matrix,
+#                            format='csr')  # setting format makes this faster!
+
+#     return mat
 
 
 def matrix_allclose(A: Union[csr_matrix, np.array], B:Union[csr_matrix, np.array], tol:int = 1e-15) -> bool:
diff --git a/tests/.DS_Store b/tests/.DS_Store
index 1ebd65c9..4129e175 100644
Binary files a/tests/.DS_Store and b/tests/.DS_Store differ
diff --git a/tests/test_symmer_utils.py b/tests/test_symmer_utils.py
index e714dc45..e8615291 100644
--- a/tests/test_symmer_utils.py
+++ b/tests/test_symmer_utils.py
@@ -1,7 +1,7 @@
 from symmer.operators import PauliwordOp, QuantumState
 from symmer.utils import (exact_gs_energy, random_anitcomm_2n_1_PauliwordOp,
                           tensor_list, gram_schmidt_from_quantum_state, product_list,
-                          get_sparse_matrix_large_pauliwordop, matrix_allclose)
+                          matrix_allclose)
 import numpy as np
 from openfermion import QubitOperator
 
@@ -445,38 +445,38 @@ def test_gram_schmidt_from_quantum_state_numpy_array():
     assert np.allclose(U_gram[:, 0], psi_norm), 'first column of U_gram not correct'
     assert np.allclose(U_gram @ U_gram.conj().T, np.eye(2 ** nq)), 'U_gram not unitary'
 
-def test_get_sparse_matrix_large_pauliwordop():
-    for nq in range(2,6):
-        n_terms = 10*nq
-        random_P = PauliwordOp.random(nq, n_terms)
-        sparse_mat = get_sparse_matrix_large_pauliwordop(random_P)
-        assert np.allclose(random_P.to_sparse_matrix.toarray(),
-                           sparse_mat.toarray())
-
-def test_matrix_allclose_sparse():
-    for nq in range(2,6):
-        n_terms = 10*nq
-        random_P = PauliwordOp.random(nq, n_terms)
-        sparse_mat = get_sparse_matrix_large_pauliwordop(random_P)
-        assert matrix_allclose(random_P.to_sparse_matrix,
-                           sparse_mat)
-
-    # assert false output
-    Pop_XI= PauliwordOp.from_list(['XI']).to_sparse_matrix
-    Pop_ZI = PauliwordOp.from_list(['ZI']).to_sparse_matrix
-    assert not matrix_allclose(Pop_XI,
-                           Pop_ZI)
-
-def test_matrix_allclose_dense():
-    for nq in range(2,6):
-        n_terms = 10*nq
-        random_P = PauliwordOp.random(nq, n_terms)
-        sparse_mat = get_sparse_matrix_large_pauliwordop(random_P)
-        assert matrix_allclose(random_P.to_sparse_matrix.toarray(),
-                           sparse_mat.toarray())
-
-    # assert false output
-    Pop_XI= PauliwordOp.from_list(['XI']).to_sparse_matrix
-    Pop_ZI = PauliwordOp.from_list(['ZI']).to_sparse_matrix
-    assert not matrix_allclose(Pop_XI.toarray(),
-                           Pop_ZI.toarray())
\ No newline at end of file
+# def test_get_sparse_matrix_large_pauliwordop():
+#     for nq in range(2,6):
+#         n_terms = 10*nq
+#         random_P = PauliwordOp.random(nq, n_terms)
+#         sparse_mat = get_sparse_matrix_large_pauliwordop(random_P)
+#         assert np.allclose(random_P.to_sparse_matrix.toarray(),
+#                            sparse_mat.toarray())
+
+# def test_matrix_allclose_sparse():
+#     for nq in range(2,6):
+#         n_terms = 10*nq
+#         random_P = PauliwordOp.random(nq, n_terms)
+#         sparse_mat = get_sparse_matrix_large_pauliwordop(random_P)
+#         assert matrix_allclose(random_P.to_sparse_matrix,
+#                            sparse_mat)
+
+#     # assert false output
+#     Pop_XI= PauliwordOp.from_list(['XI']).to_sparse_matrix
+#     Pop_ZI = PauliwordOp.from_list(['ZI']).to_sparse_matrix
+#     assert not matrix_allclose(Pop_XI,
+#                            Pop_ZI)
+
+# def test_matrix_allclose_dense():
+#     for nq in range(2,6):
+#         n_terms = 10*nq
+#         random_P = PauliwordOp.random(nq, n_terms)
+#         sparse_mat = get_sparse_matrix_large_pauliwordop(random_P)
+#         assert matrix_allclose(random_P.to_sparse_matrix.toarray(),
+#                            sparse_mat.toarray())
+
+#     # assert false output
+#     Pop_XI= PauliwordOp.from_list(['XI']).to_sparse_matrix
+#     Pop_ZI = PauliwordOp.from_list(['ZI']).to_sparse_matrix
+#     assert not matrix_allclose(Pop_XI.toarray(),
+#                            Pop_ZI.toarray())
\ No newline at end of file