Lightning Tensor device

The lightning.tensor device is a tensor network simulator, supporting both the Matrix Product State (MPS) and Exact Tensor Network (TN) methods. The device is built on top of the cutensornet library from the NVIDIA cuQuantum SDK, enabling GPU-accelerated simulation of quantum tensor network evolution. This device is designed to simulate large-scale quantum circuits using tensor networks. For small circuits, state-vector simulator plugins may be more suitable.

The lightning.tensor device defaults to the Matrix Product State (MPS) method, and can be loaded using:

import pennylane as qml
dev = qml.device("lightning.tensor", wires=100)

By default, the device approximates the quantum state using an MPS. The default setup for the MPS tensor network approximation is:

• max_bond_dim (maximum bond dimension) defaults to 128 .

• cutoff (singular value truncation threshold) defaults to 0 .

• cutoff_mode (singular value truncation mode) defaults to abs , considering the absolute values of the singular values; Alternatively, users can opt to set cutoff_mode to rel to consider the relative values of the singular values.

Note that cutensornet will automatically determine the reduced extent of the bond dimension based on the lowest among the multiple truncation cutoffs (max_bond_dim, cutoff-abs or cutoff-rel). For more details on how the cutoff works, please check the cuQuantum documentation.

Users also have the flexibility to customize MPS parameters according to their specific needs with:

import pennylane as qml

num_qubits = 100

device_kwargs_mps = {
    "max_bond_dim": 64,
    "cutoff": 1e-10,
    "cutoff_mode": "abs",
}

dev = qml.device("lightning.tensor", wires=num_qubits, method="mps", **device_kwargs_mps)

Users can also run the lightning.tensor device in the Exact Tensor Network mode by setting the method argument to "tn":

import pennylane as qml
dev = qml.device("lightning.tensor", wires=100, method="tn")

The lightning.tensor device dispatches all operations to be performed on a CUDA-capable GPU of generation SM 7.0 and greater (Volta and later). This device supports both exact and finite shots measurements. Currently, the supported differentiation methods are parameter-shift and finite-diff. Note that the MPS backend of lightning.tensor supports multi-wire gates via Matrix Product Operators (MPO).

The lightning.tensor device is designed for expectation value calculations. Measurements of probs() or state() return dense vectors of dimension \(2^{\text{n_qubits}}\), so they should only be used for small systems.

Note

Currently only single-wire Hermitian observables are supported. You can use pauli_decompose() on smaller matrices to obtain a compatible Pauli decomposition in the meantime.

The lightning.tensor device allows users to get quantum circuit gradients using the param_shift() method. This can be enabled at the PennyLane QNode level with:

@qml.qnode(dev, diff_method="parameter-shift")
def circuit(params):
    ...

Check out the Lightning-Tensor installation guide for more information.

Note that lightning.tensor cannot be cleaned up like other state-vector devices since the data is attached to the graph. It is recommended to create a new lightning.tensor device per circuit to ensure resources are correctly handled.

See also

DefaultTensor for a CPU only tensor network simulator device.

Operations and observables support

The lightning.tensor supports all gate operations supported by PennyLane, with the exception of StatePrep, which is not supported by the Exact Tensor Network method.

Supported operations:

BasisState	Prepares a single computational basis state.
BlockEncode	Construct a unitary \(U(A)\) such that an arbitrary matrix \(A\) is encoded in the top-left block.
CNOT	The controlled-NOT operator
ControlledPhaseShift	A qubit controlled phase shift.
ControlledQubitUnitary	Apply an arbitrary fixed unitary to wires with control from the control_wires.
CRot	The controlled-Rot operator
CRX	The controlled-RX operator
CRY	The controlled-RY operator
CRZ	The controlled-RZ operator
CSWAP	The controlled-swap operator
CY	The controlled-Y operator
CZ	The controlled-Z operator
DiagonalQubitUnitary	Apply an arbitrary diagonal unitary matrix with a dimension that is a power of two.
DoubleExcitation	Double excitation rotation.
DoubleExcitationMinus	Double excitation rotation with negative phase-shift outside the rotation subspace.
DoubleExcitationPlus	Double excitation rotation with positive phase-shift outside the rotation subspace.
ECR	An echoed RZX(\(\pi/2\)) gate.
GlobalPhase	A global phase operation that multiplies all components of the state by \(e^{-i \phi}\).
Hadamard	The Hadamard operator
Identity	The Identity operator
IsingXX	Ising XX coupling gate
IsingXY	Ising (XX + YY) coupling gate
IsingYY	Ising YY coupling gate
IsingZZ	Ising ZZ coupling gate
ISWAP	The i-swap operator
OrbitalRotation	Spin-adapted spatial orbital rotation.
PauliX	The Pauli X operator
PauliY	The Pauli Y operator
PauliZ	The Pauli Z operator
PhaseShift	Arbitrary single qubit local phase shift
PSWAP	Phase SWAP gate
QubitCarry	Apply the QubitCarry operation to four input wires.
QubitSum	Apply a QubitSum operation on three input wires.
QubitUnitary	Apply an arbitrary unitary matrix with a dimension that is a power of two.
Rot	Arbitrary single qubit rotation
RX	The single qubit X rotation
RY	The single qubit Y rotation
RZ	The single qubit Z rotation
S	The single-qubit phase gate
SingleExcitation	Single excitation rotation.
SingleExcitationMinus	Single excitation rotation with negative phase-shift outside the rotation subspace.
SingleExcitationPlus	Single excitation rotation with positive phase-shift outside the rotation subspace.
StatePrep	Prepare subsystems using the given ket vector in the computational basis.
SISWAP	The square root of i-swap operator.
SQISW	alias of SISWAP
SWAP	The swap operator
SX	The single-qubit Square-Root X operator.
T	The single-qubit T gate
Toffoli	Toffoli (controlled-controlled-X) gate.

Supported observables:

The lightning.tensor supports all observables supported by the Lightning state-vector simulators, besides SparseHamiltonian, Projector and limited support to Sum, Prod since lightning.tensor only supports 1-wire Hermitian observables.

Users cannot create a Sum observable or a Prod observable from Sum observables.

Exp	A symbolic operator representing the exponential of a operator.
Hadamard	The Hadamard operator
Hermitian	An arbitrary Hermitian observable.
Identity	The Identity operator
PauliX	The Pauli X operator
PauliY	The Pauli Y operator
PauliZ	The Pauli Z operator
Prod	Symbolic operator representing the product of operators.
SProd	Arithmetic operator representing the scalar product of an operator with the given scalar.
Sum	Symbolic operator representing the sum of operators.

Unsupported observables:

SparseHamiltonian	A Hamiltonian represented directly as a sparse matrix in Compressed Sparse Row (CSR) format.
Projector	Observable corresponding to the state projector \(P=\ket{\phi}\bra{\phi}\).

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