Merge branch 'master' into emery_haldane_models

.github/workflows/install_deps/action.yml

@@ -15,23 +15,23 @@ inputs:
   jax_version:
     description: The version of JAX to install for any job that requires JAX
     required: false
-    default: 0.4.23
+    default: '0.4.23'
   install_tensorflow:
     description: Indicate if TensorFlow should be installed or not
     required: false
     default: 'true'
   tensorflow_version:
     description: The version of TensorFlow to install for any job that requires TensorFlow
     required: false
-    default: 2.16.0
+    default: '2.16.0'
   install_pytorch:
     description: Indicate if PyTorch should be installed or not
     required: false
     default: 'true'
   pytorch_version:
     description: The version of PyTorch to install for any job that requires PyTorch
     required: false
-    default: 2.3.0
+    default: '2.3.0'
   install_pennylane_lightning_master:
     description: Indicate if PennyLane-Lightning should be installed from the master branch
     required: false

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

@@ -379,8 +379,7 @@ jobs:
       # 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_nightly: true
-      # using lightning master does not work for the tests with external libraries
-      install_pennylane_lightning_master: false
+      install_pennylane_lightning_master: true
       pytest_coverage_flags: ${{ inputs.pytest_coverage_flags }}
       pytest_markers: external
       additional_pip_packages: pyzx matplotlib stim quimb mitiq pennylane-qiskit ply
@@ -508,7 +507,7 @@ jobs:
     with:
       job_name: data-tests (${{ matrix.python-version }})
       branch: ${{ inputs.branch }}
-      coverage_artifact_name: data-coverage
+      coverage_artifact_name: data-coverage-${{ matrix.python-version }}
       python_version: ${{ matrix.python-version }}
       pipeline_mode: ${{ inputs.pipeline_mode }}
       install_jax: false

.github/workflows/tests-gpu.yml

@@ -15,7 +15,7 @@ concurrency:
   cancel-in-progress: true
 
 env:
-  TORCH_VERSION: 2.2.0
+  TORCH_VERSION: 2.3.0
 
 jobs:
   gpu-tests:

.gitignore

@@ -27,3 +27,5 @@ config.toml
 qml_debug.log
 datasets/*
 .benchmarks/*
+*.h5
+*.hdf5

Makefile

@@ -60,12 +60,10 @@ clean-docs:
 
 test:
 	$(PYTHON) $(TESTRUNNER)
-	$(PYTHON) $(PLUGIN_TESTRUNNER) --device=default.qubit.autograd
 
 coverage:
 	@echo "Generating coverage report..."
 	$(PYTHON) $(TESTRUNNER) $(COVERAGE)
-	$(PYTHON) $(PLUGIN_TESTRUNNER) --device=default.qubit.autograd $(COVERAGE) --cov-append
 
 .PHONY:format
 format:

doc/development/deprecations.rst

@@ -9,17 +9,18 @@ deprecations are listed below.
 Pending deprecations
 --------------------
 
-* All of the legacy devices (any with the name ``default.qubit.{autograd,torch,tf,jax,legacy}``) are deprecated. Use ``default.qubit`` instead,
-  as it supports backpropagation for the many backends the legacy devices support.
+* ``Device``, ``QubitDevice``, and ``QutritDevice`` will no longer be imported top level in v0.40.  They instead
+  we be available as ``qml.devices.LegacyDevice``, ``qml.devices.QubitDevice``, and ``qml.devices.QutritDevice``
+  respectively.
 
-  - Deprecated in v0.38
-  - Will be removed in v0.39
+  - Deprecated top level access in v0.39
+  - Top level access removed in v0.40
 
-* The logic for internally switching a device for a different backpropagation
-  compatible device is now deprecated, as it was in place for the deprecated ``default.qubit.legacy``.
+* `QNode.gradient_fn` is deprecated. Please use `QNode.diff_method` instead. `QNode.get_gradient_fn` can also be used to
+  process the diff method.
 
-  - Deprecated in v0.38
-  - Will be removed in v0.39  
+  - Deprecated in v0.39
+  - Will be removed in v0.40
 
 * The ``decomp_depth`` argument in ``qml.device`` is deprecated. 
 
@@ -82,6 +83,23 @@ Other deprecations
 Completed deprecation cycles
 ----------------------------
 
+* All of the legacy devices (any with the name ``default.qubit.{autograd,torch,tf,jax,legacy}``) are removed. Use ``default.qubit`` instead,
+  as it supports backpropagation for the many backends the legacy devices support.
+
+  - Deprecated in v0.38
+  - Removed in v0.39
+
+* The logic for internally switching a device for a different backpropagation
+  compatible device is removed, as it was in place for removed ``default.qubit.legacy``.
+
+  - Deprecated in v0.38
+  - Removed in v0.39
+
+* `Operator.expand` is now removed. Use `qml.tape.QuantumScript(op.deocomposition())` instead.
+
+  - Deprecated in v0.38
+  - Removed in v0.39
+
 * The ``expansion_strategy`` attribute of ``qml.QNode`` is removed.
   Users should make use of ``qml.workflow.construct_batch``, should they require fine control over the output tape(s).
 

doc/development/guide/logging.rst

@@ -298,7 +298,7 @@ process, and surrounding operations:
 
    # Get logger for use by this script only.
    logger = logging.getLogger(__name__)
-   dev_name = "default.qubit.jax"
+   dev_name = "default.qubit"
    num_wires = 2
    num_shots = None
 

doc/development/release_notes.md

@@ -5,6 +5,8 @@ This page contains the release notes for PennyLane.
 
 .. mdinclude:: ../releases/changelog-dev.md
 
+.. mdinclude:: ../releases/changelog-0.38.1.md
+
 .. mdinclude:: ../releases/changelog-0.38.0.md
 
 .. mdinclude:: ../releases/changelog-0.37.0.md

doc/introduction/interfaces/jax.rst

@@ -54,7 +54,7 @@ a JAX-capable QNode in PennyLane. Simply specify the ``interface='jax'`` keyword
 
 .. code-block:: python
 
-    dev = qml.device('default.qubit.jax', wires=2)
+    dev = qml.device('default.qubit', wires=2)
 
     @qml.qnode(dev, interface='jax')
     def circuit1(phi, theta):
@@ -85,7 +85,7 @@ For example:
 
 .. code-block:: python
 
-    dev = qml.device('default.qubit.jax', wires=2)
+    dev = qml.device('default.qubit', wires=2)
 
     @qml.qnode(dev, interface='jax')
     def circuit3(phi, theta):
@@ -119,7 +119,7 @@ the ``@jax.jit`` decorator can be directly applied to the QNode.
 
 .. code-block:: python
 
-    dev = qml.device('default.qubit.jax', wires=2)
+    dev = qml.device('default.qubit', wires=2)
 
     @jax.jit  # QNode calls will now be jitted, and should run faster.
     @qml.qnode(dev, interface='jax')
@@ -176,7 +176,7 @@ Example:
 
         # Device construction should happen inside a `jax.jit` decorated
         # method when using a PRNGKey.
-        dev = qml.device('default.qubit.jax', wires=2, prng_key=key, shots=100)
+        dev = qml.device('default.qubit', wires=2, prng_key=key, shots=100)
 
 
         @qml.qnode(dev, interface='jax', diff_method=None)

doc/releases/changelog-0.38.0.md

@@ -1,6 +1,6 @@
 :orphan:
 
-# Release 0.38.0 (current release)
+# Release 0.38.0
 
 <h3>New features since last release</h3>
 

doc/releases/changelog-0.38.1.md

@@ -0,0 +1,14 @@
+:orphan:
+
+# Release 0.38.1 (current release)
+
+<h3>Bug fixes 🐛</h3>
+
+* Fix float-to-complex casting in various places across PennyLane.
+ [(#6260)](https://github.com/PennyLaneAI/pennylane/pull/6260)
+
+<h3>Contributors ✍️</h3>
+
+This release contains contributions from (in alphabetical order):
+
+Mudit Pandey

doc/releases/changelog-dev.md

@@ -9,16 +9,30 @@
   [(#6201)](https://github.com/PennyLaneAI/pennylane/pull/6201/)
 
 <h3>Improvements 🛠</h3>
+
+* PennyLane is now compatible with NumPy 2.0.
+  [(#6061)](https://github.com/PennyLaneAI/pennylane/pull/6061)
+  [(#6258)](https://github.com/PennyLaneAI/pennylane/pull/6258)
+
+* `qml.qchem.excitations` now optionally returns fermionic operators.
+  [(#6171)](https://github.com/PennyLaneAI/pennylane/pull/6171)
+
 * The `diagonalize_measurements` transform now uses a more efficient method of diagonalization 
   when possible, based on the `pauli_rep` of the relevant observables.
   [#6113](https://github.com/PennyLaneAI/pennylane/pull/6113/)
 
+* The `Hermitian` operator now has a `compute_sparse_matrix` implementation.
+  [(#6225)](https://github.com/PennyLaneAI/pennylane/pull/6225)
+
 <h4>Capturing and representing hybrid programs</h4>
 
-* Differentiation of hybrid programs via `qml.grad` can now be captured into plxpr.
-  When evaluating a captured `qml.grad` instruction, it will dispatch to `jax.grad`,
-  which differs from the Autograd implementation of `qml.grad` itself.
+* Differentiation of hybrid programs via `qml.grad` and `qml.jacobian` can now be captured
+  into plxpr. When evaluating a captured `qml.grad` (`qml.jacobian`) instruction, it will
+  dispatch to `jax.grad` (`jax.jacobian`), which differs from the Autograd implementation
+  without capture. Pytree inputs and outputs are supported.
   [(#6120)](https://github.com/PennyLaneAI/pennylane/pull/6120)
+  [(#6127)](https://github.com/PennyLaneAI/pennylane/pull/6127)
+  [(#6134)](https://github.com/PennyLaneAI/pennylane/pull/6134)
 
 * Improve unit testing for capturing of nested control flows.
   [(#6111)](https://github.com/PennyLaneAI/pennylane/pull/6111)
@@ -27,6 +41,9 @@
   `from pennylane.capture.primitives import *`.
   [(#6129)](https://github.com/PennyLaneAI/pennylane/pull/6129)
 
+* `FermiWord` and `FermiSentence` classes now have methods to compute adjoints.
+  [(#6166)](https://github.com/PennyLaneAI/pennylane/pull/6166)
+
 * The `SampleMP.process_samples` method is updated to support using JAX tracers
   for samples, allowing compatiblity with Catalyst workflows.
   [(#6211)](https://github.com/PennyLaneAI/pennylane/pull/6211)
@@ -38,14 +55,21 @@
   unique representation of the object.
   [(#6167)](https://github.com/PennyLaneAI/pennylane/pull/6167)
 
+* The `to_mat` methods for `FermiWord` and `FermiSentence` now optionally return
+  a sparse matrix.
+  [(#6173)](https://github.com/PennyLaneAI/pennylane/pull/6173)
 
 <h3>Breaking changes 💔</h3>
 
 * Remove support for Python 3.9.
   [(#6223)](https://github.com/PennyLaneAI/pennylane/pull/6223)
 
-* `DefaultQubitTF` is removed. Please use `default.qubit` for all interfaces.
+* `DefaultQubitTF`, `DefaultQubitTorch`, `DefaultQubitJax`, and `DefaultQubitAutograd` are removed.
+  Please use `default.qubit` for all interfaces.
   [(#6207)](https://github.com/PennyLaneAI/pennylane/pull/6207)
+  [(#6208)](https://github.com/PennyLaneAI/pennylane/pull/6208)
+  [(#6209)](https://github.com/PennyLaneAI/pennylane/pull/6209)
+  [(#6210)](https://github.com/PennyLaneAI/pennylane/pull/6210)
 
 * `expand_fn`, `max_expansion`, `override_shots`, and `device_batch_transform` are removed from the
   signature of `qml.execute`.
@@ -61,12 +85,27 @@
   Please use `qml.transforms.split_non_commuting` instead.
   [(#6204)](https://github.com/PennyLaneAI/pennylane/pull/6204)
 
+* `Operator.expand` is now removed. Use `qml.tape.QuantumScript(op.deocomposition())` instead.
+  [(#6227)](https://github.com/PennyLaneAI/pennylane/pull/6227)
+
+
 <h3>Deprecations 👋</h3>
 
+* `Device`, `QubitDevice`, and `QutritDevice` will no longer be accessible via top-level import in v0.40.
+  They will still be accessible as `qml.devices.LegacyDevice`, `qml.devices.QubitDevice`, and `qml.devices.QutritDevice`
+  respectively.
+  [(#6238)](https://github.com/PennyLaneAI/pennylane/pull/6238/)
+
+* `QNode.gradient_fn` is deprecated. Please use `QNode.diff_method` and `QNode.get_gradient_fn` instead.
+  [(#6244)](https://github.com/PennyLaneAI/pennylane/pull/6244)
+
 <h3>Documentation 📝</h3>
 
 <h3>Bug fixes 🐛</h3>
 
+* Fix a bug where zero-valued JVPs were calculated wrongly in the presence of shot vectors.
+  [(#6219)](https://github.com/PennyLaneAI/pennylane/pull/6219)
+
 * Fix `qml.PrepSelPrep` template to work with `torch`:
   [(#6191)](https://github.com/PennyLaneAI/pennylane/pull/6191)
 
@@ -75,15 +114,33 @@
 
 * The ``qml.QSVT`` template now orders the ``projector`` wires first and the ``UA`` wires second, which is the expected order of the decomposition.
   [(#6212)](https://github.com/PennyLaneAI/pennylane/pull/6212)
+
+* The ``qml.Qubitization`` template now orders the ``control`` wires first and the ``hamiltonian`` wires second, which is the expected according to other templates.
+  [(#6229)](https://github.com/PennyLaneAI/pennylane/pull/6229)
+
+* The ``qml.FABLE`` template now returns the correct value when JIT is enabled.
+  [(#6263)](https://github.com/PennyLaneAI/pennylane/pull/6263)
+
+* Fixes a bug where a circuit using the `autograd` interface sometimes returns nested values that are not of the `autograd` interface.
+  [(#6225)](https://github.com/PennyLaneAI/pennylane/pull/6225)
+
+* Fixes a bug where a simple circuit with no parameters or only builtin/numpy arrays as parameters returns autograd tensors.
+  [(#6225)](https://github.com/PennyLaneAI/pennylane/pull/6225)
 
-* <h3>Contributors ✍️</h3>
+<h3>Contributors ✍️</h3>
 
 This release contains contributions from (in alphabetical order):
 
 Guillermo Alonso,
 Utkarsh Azad,
+<<<<<<< emery_haldane_models
 Diksha Dhawan
+=======
+Astral Cai,
+>>>>>>> master
 Lillian M. A. Frederiksen,
+Pietropaolo Frisoni,
+Emiliano Godinez,
 Christina Lee,
 William Maxwell,
 Lee J. O'Riordan,

pennylane/__init__.py

@@ -16,8 +16,6 @@
 PennyLane can be directly imported.
 """
 
-import numpy as _np
-
 
 from pennylane.boolean_fn import BooleanFn
 import pennylane.numpy
@@ -180,13 +178,30 @@ def __getattr__(name):
     if name == "plugin_devices":
         return pennylane.devices.device_constructor.plugin_devices
 
+    from warnings import warn  # pylint: disable=import-outside-toplevel
+
     if name == "QubitDevice":
+        warn(
+            "QubitDevice will no longer be accessible top level. Please access "
+            " the class as pennylane.devices.QubitDevice",
+            PennyLaneDeprecationWarning,
+        )
         return pennylane.devices._qubit_device.QubitDevice  # pylint:disable=protected-access
 
     if name == "QutritDevice":
+        warn(
+            "QutritDevice will no longer be accessible top level. Please access "
+            " the class as pennylane.devices.QutritDevice",
+            PennyLaneDeprecationWarning,
+        )
         return pennylane.devices._qutrit_device.QutritDevice  # pylint:disable=protected-access
 
     if name == "Device":
+        warn(
+            "Device will no longer be accessible top level. Please access "
+            " the class as pennylane.devices.LegacyDevice",
+            PennyLaneDeprecationWarning,
+        )
         return pennylane.devices._legacy_device.Device  # pylint:disable=protected-access
 
     raise AttributeError(f"module 'pennylane' has no attribute '{name}'")