Optimize lightning.tensor by adding direct MPS sites data set (#983)

**Context:**
Optimize `lightning.tensor` by adding direct MPS sites data set

**Description of the Change:**
Adding the `MPSPrep` gate to be able to pass an MPS directly to the
Tensor Network.
The `MPSPrep` gate frontend was developed on this
[PR](PennyLaneAI/pennylane#6431)

**Benefits:**
Avoid the decomposition from state vector to MPS sites which are
expensive and inefficient

**Possible Drawbacks:**

**Related GitHub Issues:**
[sc-74709]

---------

Co-authored-by: ringo-but-quantum <github-ringo-but-quantum@xanadu.ai>

Author: LuisAlfredoNu

.github/CHANGELOG.md

@@ -29,6 +29,9 @@
 
 ### Improvements
 
+* Optimize lightning.tensor by adding direct MPS sites data set with `qml.MPSPrep`.
+  [(#983)](https://github.com/PennyLaneAI/pennylane-lightning/pull/983)
+
 * Replace the `dummy_tensor_update` method with the `cutensornetStateCaptureMPS`API to ensure that further gates apply is allowed after the `cutensornetStateCompute` call.
   [(#1028)](https://github.com/PennyLaneAI/pennylane-lightning/pull/1028/)
 

pennylane_lightning/core/_version.py

@@ -16,4 +16,4 @@
    Version number (major.minor.patch[-label])
 """
 
-__version__ = "0.40.0-dev41"
+__version__ = "0.40.0-dev42"

pennylane_lightning/core/src/simulators/lightning_tensor/tncuda/TNCuda.hpp

@@ -60,32 +60,6 @@ class TNCuda : public TNCudaBase<PrecisionT, Derived> {
     using ComplexT = std::complex<PrecisionT>;
     using BaseType = TNCudaBase<PrecisionT, Derived>;
 
-  protected:
-    // Note both maxBondDim_ and bondDims_ are used for both MPS and Exact
-    // Tensor Network. Per Exact Tensor Network, maxBondDim_ is 1 and bondDims_
-    // is {1}. Per Exact Tensor Network, setting bondDims_ allows call to
-    // appendInitialMPSState_() to append the initial state to the Exact Tensor
-    // Network state.
-    const std::size_t
-        maxBondDim_; // maxBondDim_ default is 1 for Exact Tensor Network
-    const std::vector<std::size_t>
-        bondDims_; // bondDims_ default is {1} for Exact Tensor Network
-
-  private:
-    const std::vector<std::vector<std::size_t>> sitesModes_;
-    const std::vector<std::vector<std::size_t>> sitesExtents_;
-    const std::vector<std::vector<int64_t>> sitesExtents_int64_;
-
-    SharedCublasCaller cublascaller_;
-
-    std::shared_ptr<TNCudaGateCache<PrecisionT>> gate_cache_;
-    std::set<int64_t> gate_ids_;
-
-    std::vector<std::size_t> identiy_gate_ids_;
-
-    std::vector<TensorCuda<PrecisionT>> tensors_;
-    std::vector<TensorCuda<PrecisionT>> tensors_out_;
-
   public:
     TNCuda() = delete;
 
@@ -499,7 +473,27 @@ class TNCuda : public TNCudaBase<PrecisionT, Derived> {
                       projected_mode_values, numHyperSamples);
     }
 
+    /**
+     * @brief Get a const vector reference of sitesExtents_.
+     *
+     * @return const std::vector<std::vector<std::size_t>>
+     */
+    [[nodiscard]] auto getSitesExtents() const
+        -> const std::vector<std::vector<std::size_t>> & {
+        return sitesExtents_;
+    }
+
   protected:
+    // Note both maxBondDim_ and bondDims_ are used for both MPS and Exact
+    // Tensor Network. For Exact Tensor Network, maxBondDim_ is 1 and bondDims_
+    // is {1}. For Exact Tensor Network, setting bondDims_ allows call to
+    // appendInitialMPSState_() to append the initial state to the Exact Tensor
+    // Network state.
+    const std::size_t
+        maxBondDim_; // maxBondDim_ default is 1 for Exact Tensor Network
+    const std::vector<std::size_t>
+        bondDims_; // bondDims_ default is {1} for Exact Tensor Network
+
     /**
      * @brief Get a vector of pointers to tensor data of each site.
      *
@@ -578,6 +572,20 @@ class TNCuda : public TNCudaBase<PrecisionT, Derived> {
     }
 
   private:
+    const std::vector<std::vector<std::size_t>> sitesModes_;
+    const std::vector<std::vector<std::size_t>> sitesExtents_;
+    const std::vector<std::vector<int64_t>> sitesExtents_int64_;
+
+    SharedCublasCaller cublascaller_;
+
+    std::shared_ptr<TNCudaGateCache<PrecisionT>> gate_cache_;
+    std::set<int64_t> gate_ids_;
+
+    std::vector<std::size_t> identiy_gate_ids_;
+
+    std::vector<TensorCuda<PrecisionT>> tensors_;
+    std::vector<TensorCuda<PrecisionT>> tensors_out_;
+
     /**
      * @brief Get accessor of a state tensor
      *

pennylane_lightning/core/src/simulators/lightning_tensor/tncuda/bindings/LTensorTNCudaBindings.hpp

@@ -33,13 +33,14 @@
 #include "TypeList.hpp"
 #include "Util.hpp"
 #include "cuda_helpers.hpp"
+#include "tncuda_helpers.hpp"
 
 /// @cond DEV
 namespace {
 using namespace Pennylane;
 using namespace Pennylane::Bindings;
 using namespace Pennylane::LightningGPU::Util;
-using Pennylane::LightningTensor::TNCuda::MPSTNCuda;
+using namespace Pennylane::LightningTensor::TNCuda::Util;
 } // namespace
 /// @endcond
 
@@ -137,6 +138,20 @@ void registerBackendClassSpecificBindingsMPS(PyClass &pyclass) {
         .def(
             "updateMPSSitesData",
             [](TensorNet &tensor_network, std::vector<np_arr_c> &tensors) {
+                // Extract the incoming MPS shape
+                std::vector<std::vector<std::size_t>> MPS_shape_source;
+                for (std::size_t idx = 0; idx < tensors.size(); idx++) {
+                    py::buffer_info numpyArrayInfo = tensors[idx].request();
+                    auto MPS_site_source_shape = numpyArrayInfo.shape;
+                    std::vector<std::size_t> MPS_site_source(
+                        MPS_site_source_shape.begin(),
+                        MPS_site_source_shape.end());
+                    MPS_shape_source.emplace_back(std::move(MPS_site_source));
+                }
+
+                const auto &MPS_shape_dest = tensor_network.getSitesExtents();
+                MPSShapeCheck(MPS_shape_dest, MPS_shape_source);
+
                 for (std::size_t idx = 0; idx < tensors.size(); idx++) {
                     py::buffer_info numpyArrayInfo = tensors[idx].request();
                     auto *data_ptr = static_cast<std::complex<PrecisionT> *>(

pennylane_lightning/core/src/simulators/lightning_tensor/tncuda/tests/Tests_MPSTNCuda.cpp

@@ -291,7 +291,7 @@ TEMPLATE_TEST_CASE("MPSTNCuda::getDataVector()", "[MPSTNCuda]", float, double) {
 
 TEMPLATE_TEST_CASE("MPOTNCuda::getBondDims()", "[MPOTNCuda]", float, double) {
     using cp_t = std::complex<TestType>;
-    SECTION("Check if bondDims is correctly set") {
+    SECTION("Check if bondDims is correct set") {
         const std::size_t num_qubits = 3;
         const std::size_t maxBondDim = 128;
         const DevTag<int> dev_tag{0, 0};
@@ -323,4 +323,64 @@ TEMPLATE_TEST_CASE("MPOTNCuda::getBondDims()", "[MPOTNCuda]", float, double) {
 
         CHECK(bondDims == expected_bondDims);
     }
-}
+}
+
+TEMPLATE_TEST_CASE("MPSTNCuda::getSitesExtents()", "[MPSTNCuda]", float,
+                   double) {
+    SECTION("Check if sitesExtents retrun is correct with 3 qubits") {
+        const std::size_t num_qubits = 3;
+        const std::size_t maxBondDim = 128;
+        const DevTag<int> dev_tag{0, 0};
+
+        const std::vector<std::vector<std::size_t>> reference{
+            {{2, 2}, {2, 2, 2}, {2, 2}}};
+
+        MPSTNCuda<TestType> mps{num_qubits, maxBondDim, dev_tag};
+
+        const auto &sitesExtents = mps.getSitesExtents();
+
+        CHECK(reference == sitesExtents);
+    }
+
+    SECTION("Check if sitesExtents retrun is correct with 8 qubits") {
+        const std::size_t num_qubits = 8;
+        const std::size_t maxBondDim = 128;
+        const DevTag<int> dev_tag{0, 0};
+
+        const std::vector<std::vector<std::size_t>> reference{{{2, 2},
+                                                               {2, 2, 4},
+                                                               {4, 2, 8},
+                                                               {8, 2, 16},
+                                                               {16, 2, 8},
+                                                               {8, 2, 4},
+                                                               {4, 2, 2},
+                                                               {2, 2}}};
+
+        MPSTNCuda<TestType> mps{num_qubits, maxBondDim, dev_tag};
+
+        const auto &sitesExtents = mps.getSitesExtents();
+
+        CHECK(reference == sitesExtents);
+    }
+    SECTION("Check if sitesExtents retrun is correct with 8 qubits and "
+            "maxBondDim=8") {
+        const std::size_t num_qubits = 8;
+        const std::size_t maxBondDim = 8;
+        const DevTag<int> dev_tag{0, 0};
+
+        const std::vector<std::vector<std::size_t>> reference{{{2, 2},
+                                                               {2, 2, 4},
+                                                               {4, 2, 8},
+                                                               {8, 2, 8},
+                                                               {8, 2, 8},
+                                                               {8, 2, 4},
+                                                               {4, 2, 2},
+                                                               {2, 2}}};
+
+        MPSTNCuda<TestType> mps{num_qubits, maxBondDim, dev_tag};
+
+        const auto &sitesExtents = mps.getSitesExtents();
+
+        CHECK(reference == sitesExtents);
+    }
+}

pennylane_lightning/core/src/simulators/lightning_tensor/utils/tncuda_utils/tests/Test_TNCuda_utils.cpp

@@ -84,3 +84,52 @@ TEST_CASE("swap_op_wires_queue", "[TNCuda_utils]") {
         REQUIRE(swap_wires_queue[1] == swap_wires_queue_ref1);
     }
 }
+
+TEST_CASE("MPSShapeCheck", "[TNCuda_utils]") {
+    SECTION("Correct incoming MPS shape") {
+        std::vector<std::vector<std::size_t>> MPS_shape_dest{
+            {2, 2}, {2, 2, 4}, {4, 2, 2}, {2, 2}};
+
+        std::vector<std::vector<std::size_t>> MPS_shape_source{
+            {2, 2}, {2, 2, 4}, {4, 2, 2}, {2, 2}};
+
+        REQUIRE_NOTHROW(MPSShapeCheck(MPS_shape_dest, MPS_shape_source));
+    }
+
+    SECTION("Incorrect incoming MPS shape, bond dimension") {
+        std::vector<std::vector<std::size_t>> MPS_shape_dest{
+            {2, 2}, {2, 2, 4}, {4, 2, 2}, {2, 2}};
+
+        std::vector<std::vector<std::size_t>> incorrect_MPS_shape{
+            {2, 2}, {2, 2, 2}, {2, 2, 2}, {2, 2}};
+
+        REQUIRE_THROWS_WITH(
+            MPSShapeCheck(MPS_shape_dest, incorrect_MPS_shape),
+            Catch::Matchers::Contains("The incoming MPS does not have the "
+                                      "correct layout for lightning.tensor"));
+    }
+    SECTION("Incorrect incoming MPS shape, physical dimension") {
+        std::vector<std::vector<std::size_t>> MPS_shape_dest{
+            {2, 2}, {2, 2, 4}, {4, 2, 2}, {2, 2}};
+
+        std::vector<std::vector<std::size_t>> incorrect_shape{
+            {4, 2}, {2, 4, 4}, {4, 4, 2}, {2, 4}};
+
+        REQUIRE_THROWS_WITH(
+            MPSShapeCheck(MPS_shape_dest, incorrect_shape),
+            Catch::Matchers::Contains("The incoming MPS does not have the "
+                                      "correct layout for lightning.tensor"));
+    }
+    SECTION("Incorrect incoming MPS shape, number sites") {
+        std::vector<std::vector<std::size_t>> MPS_shape_dest{
+            {2, 2}, {2, 2, 4}, {4, 2, 2}, {2, 2}};
+
+        std::vector<std::vector<std::size_t>> incorrect_shape{
+            {2, 2}, {2, 2, 2}, {2, 2}};
+
+        REQUIRE_THROWS_WITH(
+            MPSShapeCheck(MPS_shape_dest, incorrect_shape),
+            Catch::Matchers::Contains("The incoming MPS does not have the "
+                                      "correct layout for lightning.tensor"));
+    }
+}

pennylane_lightning/core/src/simulators/lightning_tensor/utils/tncuda_utils/tncuda_helpers.hpp

@@ -194,4 +194,19 @@ inline auto create_swap_wire_pair_queue(const std::vector<std::size_t> &wires)
     return {local_wires, swap_wires_queue};
 }
 
+/**
+ * @brief Check if the provided MPS has the correct dimension for C++
+ * backend.
+ *
+ * @param MPS_shape_dest Dimension list of destination MPS.
+ * @param MPS_shape_source Dimension list of incoming MPS.
+ */
+inline void
+MPSShapeCheck(const std::vector<std::vector<std::size_t>> &MPS_shape_dest,
+              const std::vector<std::vector<std::size_t>> &MPS_shape_source) {
+    PL_ABORT_IF_NOT(MPS_shape_dest == MPS_shape_source,
+                    "The incoming MPS does not have the correct layout for "
+                    "lightning.tensor.")
+}
+
 } // namespace Pennylane::LightningTensor::TNCuda::Util

pennylane_lightning/core/src/utils/Util.hpp

@@ -592,4 +592,5 @@ bool areVecsDisjoint(const std::vector<T> &v1, const std::vector<T> &v2) {
     }
     return true;
 }
+
 } // namespace Pennylane::Util

pennylane_lightning/lightning_tensor/_tensornet.py

@@ -28,7 +28,7 @@
 
 import numpy as np
 import pennylane as qml
-from pennylane import BasisState, DeviceError, StatePrep
+from pennylane import BasisState, DeviceError, MPSPrep, StatePrep
 from pennylane.ops.op_math import Adjoint
 from pennylane.tape import QuantumScript
 from pennylane.wires import Wires
@@ -433,17 +433,24 @@ def apply_operations(self, operations):
         # State preparation is currently done in Python
         if operations:  # make sure operations[0] exists
             if isinstance(operations[0], StatePrep):
-                if self.method == "tn":
-                    raise DeviceError("Exact Tensor Network does not support StatePrep")
-
                 if self.method == "mps":
                     self._apply_state_vector(
                         operations[0].parameters[0].copy(), operations[0].wires
                     )
                     operations = operations[1:]
+                if self.method == "tn":
+                    raise DeviceError("Exact Tensor Network does not support StatePrep")
             elif isinstance(operations[0], BasisState):
                 self._apply_basis_state(operations[0].parameters[0], operations[0].wires)
                 operations = operations[1:]
+            elif isinstance(operations[0], MPSPrep):
+                if self.method == "mps":
+                    mps = operations[0].mps
+                    self._tensornet.updateMPSSitesData(mps)
+                    operations = operations[1:]
+
+                if self.method == "tn":
+                    raise DeviceError("Exact Tensor Network does not support MPSPrep")
 
         self._apply_lightning(operations)
 

pennylane_lightning/lightning_tensor/lightning_tensor.py

@@ -71,6 +71,7 @@
     {
         "Identity",
         "BasisState",
+        "MPSPrep",
         "QubitUnitary",
         "ControlledQubitUnitary",
         "DiagonalQubitUnitary",
@@ -169,6 +170,9 @@ def stopping_condition(op: Operator) -> bool:
     if isinstance(op, qml.ControlledQubitUnitary):
         return True
 
+    if isinstance(op, qml.MPSPrep):
+        return True
+
     return op.has_matrix and op.name in _operations