Final rc sync to master (PennyLaneAI#5970)

Co-authored-by: Jay Soni <jbsoni@uwaterloo.ca>
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: Yushao Chen (Jerry) <chenys13@outlook.com>
Co-authored-by: Christina Lee <chrissie.c.l@gmail.com>
Co-authored-by: Mudit Pandey <mudit.pandey@xanadu.ai>
Co-authored-by: Thomas R. Bromley <49409390+trbromley@users.noreply.github.com>
Co-authored-by: soranjh <40344468+soranjh@users.noreply.github.com>
Co-authored-by: Pietropaolo Frisoni <pietropaolo.frisoni@xanadu.ai>
Co-authored-by: Isaac De Vlugt <34751083+isaacdevlugt@users.noreply.github.com>
Co-authored-by: Vincent Michaud-Rioux <vincent.michaud-rioux@xanadu.ai>
Co-authored-by: lillian542 <38584660+lillian542@users.noreply.github.com>
Co-authored-by: Christina Lee <christina@xanadu.ai>
Co-authored-by: Diego <67476785+DSGuala@users.noreply.github.com>
Co-authored-by: trbromley <brotho02@gmail.com>
Co-authored-by: Korbinian Kottmann <43949391+Qottmann@users.noreply.github.com>
Co-authored-by: Diego <diego_guala@hotmail.com>
Co-authored-by: Cristian Emiliano Godinez Ramirez <57567043+EmilianoG-byte@users.noreply.github.com>
Co-authored-by: Ahmed Darwish <exclass9.24@gmail.com>

.github/stable/external.txt

@@ -117,8 +117,8 @@ packaging==24.1
 pandocfilters==1.5.1
 parso==0.8.4
 pathspec==0.12.1
-PennyLane-Catalyst==0.6.0
-PennyLane_Lightning==0.36.0
+PennyLane-Catalyst==0.7.0
+PennyLane_Lightning==0.37.0
 pexpect==4.9.0
 pillow==10.3.0
 platformdirs==4.2.2

.github/workflows/install_deps/action.yml

@@ -95,6 +95,11 @@ runs:
  python setup.py bdist_wheel
  pip install dist/PennyLane*.whl
 
+ - name: Install Catalyst
+ shell: bash
+ if: inputs.install_catalyst_after_pennylane == 'true'
+ run: pip install --upgrade pennylane-catalyst
+
  - name: Install PennyLane-Lightning master
  shell: bash
  if: inputs.install_pennylane_lightning_master == 'true'

.github/workflows/interface-unit-tests.yml

@@ -362,6 +362,10 @@ jobs:
  install_jax: true
  install_tensorflow: true
  install_pytorch: false
+ # This is required during the release process when the latest released version of
+ # catalyst requires the latest version of pennylane that is about to be released.
+ # Installing catalyst after pennylane to make sure that the latest catalyst is used.
+ install_catalyst_after_pennylane: true
  # using lightning master does not work for the tests with external libraries
  install_pennylane_lightning_master: false
  pytest_coverage_flags: ${{ inputs.pytest_coverage_flags }}

.github/workflows/unit-test.yml

@@ -59,6 +59,11 @@ on:
  required: false
  type: string
  default: ''
+ install_catalyst_after_pennylane:
+ description: Indicate if the latest Catalyst should be installed after PennyLane
+ required: false
+ type: boolean
+ default: false
  install_pennylane_lightning_master:
  description: Indicate if PennyLane-Lightning should be installed from the master branch
  required: false
@@ -147,6 +152,7 @@ jobs:
  install_tensorflow: ${{ inputs.install_tensorflow }}
  install_jax: ${{ inputs.install_jax }}
  additional_pip_packages: ${{ inputs.additional_pip_packages }}
+ install_catalyst_after_pennylane: ${{ inputs.install_catalyst_after_pennylane }}
  install_pennylane_lightning_master: ${{ inputs.install_pennylane_lightning_master }}
  requirements_file: ${{ inputs.requirements_file }}
 

doc/releases/changelog-0.37.0.md

@@ -4,8 +4,6 @@
 
 <h3>New features since last release</h3>
 
-<h4>Execute faster with Default Tensor 🔗</h4>
-
 <h4>Execute wide circuits with Default Tensor 🔗</h4>
 
 * A new `default.tensor` device is now available for performing
@@ -19,27 +17,41 @@
  [(#5795)](https://github.com/PennyLaneAI/pennylane/pull/5795)
 
  Either method can be selected when instantiating the `default.tensor` device by setting the
- `method` keyword argument to `"tn"` (tensor network) or `"mps"` (matrix product state). This
- device can simulate a large number of qubits. Take this example that
- simulates 1000 qubits with a shallow circuit in a few seconds!
+ `method` keyword argument to `"tn"` (tensor network) or `"mps"` (matrix product state).
+
+ There are
+ [several templates in PennyLane](https://docs.pennylane.ai/en/stable/introduction/templates.html#tensor-networks)
+ that are tensor-network focused, which are excellent candidates for the `"tn"` method for
+ `default.tensor`. The following example shows how a circuit comprising gates in a tree tensor
+ network architecture can be efficiently simulated using `method="tn"`.
 
  ```python
  import pennylane as qml
 
- num_qubits = 1000
- dev = qml.device("default.tensor", method="mps")
+ n_wires = 16
+ dev = qml.device("default.tensor", method="tn")
+
+ def block(weights, wires):
+ qml.CNOT(wires=[wires[0], wires[1]])
+ qml.RY(weights[0], wires=wires[0])
+ qml.RY(weights[1], wires=wires[1])
+
+ n_block_wires = 2
+ n_params_block = 2
+ n_blocks = qml.TTN.get_n_blocks(range(n_wires), n_block_wires)
+ template_weights = [[0.1, -0.3]] * n_blocks
 
  @qml.qnode(dev)
- def circuit():
- qml.Hadamard(0)
- for i in range(num_qubits - 1):
-  qml.CNOT([i, i + 1])
- return qml.expval(qml.Z(num_qubits - 1))
+ def circuit(template_weights):
+ for i in range(n_wires):
+  qml.Hadamard(i)
+ qml.TTN(range(n_wires), n_block_wires, block, n_params_block, template_weights)
+ return qml.expval(qml.Z(n_wires - 1))
  ```
 
  ```pycon
- >>> circuit()
- tensor(0., requires_grad=True)
+ >>> circuit(template_weights)
+ 0.3839174759751649
  ```
 
  For matrix product state simulations (`method="mps"`), we can make the execution be approximate by setting `max_bond_dim` (see the
@@ -215,18 +227,18 @@ via the `NoiseModel` class and an `add_noise` transform.
  For example, `qml.debug_tape()` returns the tape of the circuit, giving access to its operations and drawing:
 
  ```pycon
- (pldb): tape = qml.debug_tape()
- (pldb): print(tape.draw(wire_order=[0,1,2]))
+ [pldb] tape = qml.debug_tape()
+ [pldb] print(tape.draw(wire_order=[0,1,2]))
  0: ──H─╭●─┤ 
  2: ────╰X─┤ 
- (pldb): tape.operations
+ [pldb] tape.operations
  [Hadamard(wires=[0]), CNOT(wires=[0, 2])]
  ```
 
  While `qml.debug_state()` is equivalent to `qml.state()` and gives the current state:
 
  ```pycon
- (pldb): print(qml.debug_state())
+ [pldb] print(qml.debug_state())
  [0.70710678+0.j 0. +0.j 0. +0.j 0. +0.j
  1. +0.j 0.70710678+0.j 0. +0.j 0. +0.j]
  ```
@@ -238,9 +250,9 @@ via the `NoiseModel` class and an `add_noise` transform.
  Finally, to modify a circuit mid-run, simply call the desired PennyLane operations:
 
  ```pycon
- (pldb) qml.CNOT(wires=(0,2))
+ [pldb] qml.CNOT(wires=(0,2))
  CNOT(wires=[0, 2])
- (pldb): print(qml.debug_tape().draw(wire_order=[0,1,2]))
+ [pldb] print(qml.debug_tape().draw(wire_order=[0,1,2]))
  0: ──H─╭●─╭●─┤ 
  2: ────╰X─╰X─┤ 
  ```
@@ -340,10 +352,10 @@ Stay tuned for an in-depth demonstration on using this feature with real-world e
  ```
 
  ```pycon
- >>> print(pl_op)
- a⁺(0) a(2)
- >>> print(of_op_new)
- 1.0 [0^ 2]
+ >>> print(qml.draw(f, level="device")())
+ 0: ──RX(0.28)─╭●────╭X──RX(0.70)─╭●────╭X─┤ <X>
+ 1: ──RX(0.52)─╰X─╭●─│───RX(0.65)─╰X─╭●─│──┤ 
+ 2: ──RX(0.00)────╰X─╰●──RX(0.03)────╰X─╰●─┤ 
  ```
 
 <h3>Improvements 🛠</h3>
@@ -637,7 +649,8 @@ Stay tuned for an in-depth demonstration on using this feature with real-world e
  `base` properties.
  [(##5772)](https://github.com/PennyLaneAI/pennylane/pull/5772)
 
-<h4>Quantum chemistry</h4>
+* New dispatches for `qml.ops.Conditional` and `qml.MeasurementValue` have been added to `qml.equal`.
+ [(##5772)](https://github.com/PennyLaneAI/pennylane/pull/5772)
 
 * The `qml.snapshots` transform now supports arbitrary devices by running a separate tape for each snapshot 
  for unsupported devices.

pennylane/compiler/compiler.py

@@ -23,7 +23,7 @@
 
 from packaging.version import Version
 
-PL_CATALYST_MIN_VERSION = Version("0.6.0")
+PL_CATALYST_MIN_VERSION = Version("0.7.0")
 
 
 class CompileError(Exception):

pennylane/debugging/debugger.py

@@ -141,8 +141,6 @@ def breakpoint():
 
  .. seealso:: :doc:`/code/qml_debugging`
 
- .. seealso:: :doc:`/code/qml_debugging`
-
  **Example**
 
  Consider the following python script containing the quantum circuit with breakpoints.

setup.py

@@ -31,7 +31,7 @@
  "semantic-version>=2.7",
  "autoray>=0.6.11",
  "cachetools",
- "pennylane-lightning>=0.36",
+ "pennylane-lightning>=0.37",
  "requests",
  "typing_extensions",
  "packaging",

tests/test_compiler.py

@@ -249,7 +249,6 @@ def circuit(x: float):
  result_header = "func.func private @circuit(%arg0: tensor<f64>) -> tensor<f64>"
  assert result_header in mlir_str
 
- @pytest.mark.xfail(reason="supported once catalyst #768 is merged")
  def test_qjit_adjoint(self):
  """Test JIT compilation with adjoint support"""
  dev = qml.device("lightning.qubit", wires=2)
@@ -273,7 +272,6 @@ def func():
 
  assert jnp.allclose(workflow_cl(0.1, [1]), workflow_pl(0.1, [1]))
 
- @pytest.mark.xfail(reason="supported once catalyst #768 is merged")
  def test_qjit_adjoint_lazy(self):
  """Test that the lazy kwarg is supported."""
  dev = qml.device("lightning.qubit", wires=2)
@@ -732,7 +730,6 @@ def f(x):
 class TestCatalystSample:
  """Test qml.sample with Catalyst."""
 
- @pytest.mark.xfail(reason="requires simultaneous catalyst pr")
  def test_sample_measure(self):
  """Test that qml.sample can be used with catalyst.measure."""