From 1ad0eb3d36b672f5e050e58f0bd9af0363f6c0ac Mon Sep 17 00:00:00 2001
From: Pablo Andres-Martinez <104848389+PabloAndresCQ@users.noreply.github.com>
Date: Wed, 3 Apr 2024 17:09:11 +0100
Subject: [PATCH] [bugfix] Default value of chi causes an error when state is
 copied (#93)

* Now checking if chi is set to the default 'essentially unbounded' value; if so, do not raise error if non-default truncation fidelity is set.

* Adding a test of copy state using different configurations.
---
 .../cutensornet/structured_state/general.py   |  4 +-
 tests/test_structured_state.py                | 38 +++++++++++++++++++
 2 files changed, 41 insertions(+), 1 deletion(-)

diff --git a/pytket/extensions/cutensornet/structured_state/general.py b/pytket/extensions/cutensornet/structured_state/general.py
index 25d65876..fc862dc2 100644
--- a/pytket/extensions/cutensornet/structured_state/general.py
+++ b/pytket/extensions/cutensornet/structured_state/general.py
@@ -128,14 +128,16 @@ def __init__(
             ValueError: If the value of ``chi`` is set below 2.
             ValueError: If the value of ``truncation_fidelity`` is not in [0,1].
         """
+        _CHI_LIMIT = 2**60
         if (
             chi is not None
+            and chi < _CHI_LIMIT
             and truncation_fidelity is not None
             and truncation_fidelity != 1.0
         ):
             raise ValueError("Cannot fix both chi and truncation_fidelity.")
         if chi is None:
-            chi = 2**60  # In practice, this is like having it be unbounded
+            chi = _CHI_LIMIT  # In practice, this is like having it be unbounded
         if truncation_fidelity is None:
             truncation_fidelity = 1
 
diff --git a/tests/test_structured_state.py b/tests/test_structured_state.py
index 6a14a87a..5617ca44 100644
--- a/tests/test_structured_state.py
+++ b/tests/test_structured_state.py
@@ -51,6 +51,44 @@ def test_init() -> None:
         assert ttn_gate.is_valid()
 
 
+@pytest.mark.parametrize(
+    "algorithm",
+    [
+        SimulationAlgorithm.MPSxGate,
+        SimulationAlgorithm.MPSxMPO,
+        SimulationAlgorithm.TTNxGate,
+    ],
+)
+def test_copy(algorithm: SimulationAlgorithm) -> None:
+    simple_circ = Circuit(2).H(0).H(1).CX(0, 1)
+
+    with CuTensorNetHandle() as libhandle:
+
+        # Default config
+        cfg = Config()
+        state = simulate(libhandle, simple_circ, algorithm, cfg)
+        assert state.is_valid()
+        copy_state = state.copy()
+        assert copy_state.is_valid()
+        assert np.isclose(copy_state.vdot(state), 1.0, atol=cfg._atol)
+
+        # Bounded chi
+        cfg = Config(chi=8)
+        state = simulate(libhandle, simple_circ, algorithm, cfg)
+        assert state.is_valid()
+        copy_state = state.copy()
+        assert copy_state.is_valid()
+        assert np.isclose(copy_state.vdot(state), 1.0, atol=cfg._atol)
+
+        # Bounded truncation_fidelity
+        cfg = Config(truncation_fidelity=0.9999)
+        state = simulate(libhandle, simple_circ, algorithm, cfg)
+        assert state.is_valid()
+        copy_state = state.copy()
+        assert copy_state.is_valid()
+        assert np.isclose(copy_state.vdot(state), 1.0, atol=cfg._atol)
+
+
 def test_canonicalise_mps() -> None:
     cp.random.seed(1)
     circ = Circuit(5)