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<h3>Improvements 🛠</h3>

* The wires for the `default.tensor` device are selected at runtime if they are not provided by user.
[(#5744)](https://github.com/PennyLaneAI/pennylane/pull/5744)

* Added `packaging` in the required list of packages.
[(#5769)](https://github.com/PennyLaneAI/pennylane/pull/5769).

* Logging now allows for an easier opt-in across the stack, and also extends control support to `catalyst`.
[(#5528)](https://github.com/PennyLaneAI/pennylane/pull/5528).

* A number of templates have been updated to be valid pytrees and PennyLane operations.
[(#5698)](https://github.com/PennyLaneAI/pennylane/pull/5698)

* `ctrl` now works with tuple-valued `control_values` when applied to any already controlled operation.
[(#5725)](https://github.com/PennyLaneAI/pennylane/pull/5725)

* Add support for 3 new pytest markers: `unit`, `integration` and `system`.
[(#5517)](https://github.com/PennyLaneAI/pennylane/pull/5517)

* The sorting order of parameter-shift terms is now guaranteed to resolve ties in the absolute value with the sign of the shifts.
[(#5582)](https://github.com/PennyLaneAI/pennylane/pull/5582)

* Added compute_sparse_matrix for BasisStateProjector.
[(#5790)](https://github.com/PennyLaneAI/pennylane/pull/5790)

* `qml.transforms.split_non_commuting` can now handle circuits containing measurements of multi-term observables.
[(#5729)](https://github.com/PennyLaneAI/pennylane/pull/5729)

<h4>Mid-circuit measurements and dynamic circuits</h4>

* The `dynamic_one_shot` transform uses a single auxiliary tape with a shot vector and `default.qubit` implements the loop over shots with `jax.vmap`.
[(#5617)](https://github.com/PennyLaneAI/pennylane/pull/5617)

* The `dynamic_one_shot` transform can be compiled with `jax.jit`.
[(#5557)](https://github.com/PennyLaneAI/pennylane/pull/5557)

* When using `defer_measurements` with postselecting mid-circuit measurements, operations
that will never be active due to the postselected state are skipped in the transformed
quantum circuit. In addition, postselected controls are skipped, as they are evaluated
at transform time. This optimization feature can be turned off by setting `reduce_postselected=False`
[(#5558)](https://github.com/PennyLaneAI/pennylane/pull/5558)

Consider a simple circuit with three mid-circuit measurements, two of which are postselecting,
and a single gate conditioned on those measurements:

```python
@qml.qnode(qml.device("default.qubit"))
def node(x):
qml.RX(x, 0)
qml.RX(x, 1)
qml.RX(x, 2)
mcm0 = qml.measure(0, postselect=0, reset=False)
mcm1 = qml.measure(1, postselect=None, reset=True)
mcm2 = qml.measure(2, postselect=1, reset=False)
qml.cond(mcm0+mcm1+mcm2==1, qml.RX)(0.5, 3)
return qml.expval(qml.Z(0) @ qml.Z(3))
```

Without the new optimization, we obtain three gates, each controlled on the three measured
qubits. They correspond to the combinations of controls that satisfy the condition
`mcm0+mcm1+mcm2==1`:

```pycon
>>> print(qml.draw(qml.defer_measurements(node, reduce_postselected=False))(0.6))
0: ──RX(0.60)──|0⟩⟨0|─╭●─────────────────────────────────────────────┤ ╭<Z@Z>
1: ──RX(0.60)─────────│──╭●─╭X───────────────────────────────────────┤ │
2: ──RX(0.60)─────────│──│──│───|1⟩⟨1|─╭○────────╭○────────╭●────────┤ │
3: ───────────────────│──│──│──────────├RX(0.50)─├RX(0.50)─├RX(0.50)─┤ ╰<Z@Z>
4: ───────────────────╰X─│──│──────────├○────────├●────────├○────────┤
5: ──────────────────────╰X─╰●─────────╰●────────╰○────────╰○────────┤
```

If we do not explicitly deactivate the optimization, we obtain a much simpler circuit:

```pycon
>>> print(qml.draw(qml.defer_measurements(node))(0.6))
0: ──RX(0.60)──|0⟩⟨0|─╭●─────────────────┤ ╭<Z@Z>
1: ──RX(0.60)─────────│──╭●─╭X───────────┤ │
2: ──RX(0.60)─────────│──│──│───|1⟩⟨1|───┤ │
3: ───────────────────│──│──│──╭RX(0.50)─┤ ╰<Z@Z>
4: ───────────────────╰X─│──│──│─────────┤
5: ──────────────────────╰X─╰●─╰○────────┤
```

There is only one controlled gate with only one control wire.

* `qml.devices.LegacyDevice` is now an alias for `qml.Device`, so it is easier to distinguish it from
`qml.devices.Device`, which follows the new device API.
[(#5581)](https://github.com/PennyLaneAI/pennylane/pull/5581)

* The `dtype` for `eigvals` of `X`, `Y`, `Z` and `Hadamard` is changed from `int` to `float`, making them
consistent with the other observables. The `dtype` of the returned values when sampling these observables
(e.g. `qml.sample(X(0))`) is also changed to `float`.
[(#5607)](https://github.com/PennyLaneAI/pennylane/pull/5607)

* Sets up the framework for the development of an `assert_equal` function for testing operator comparison.
[(#5634)](https://github.com/PennyLaneAI/pennylane/pull/5634)

* `qml.sample` can now be used on Boolean values representing mid-circuit measurement results in
traced quantum functions. This feature is used with Catalyst to enable the pattern
`m = measure(0); qml.sample(m)`.
[(#5673)](https://github.com/PennyLaneAI/pennylane/pull/5673)

* PennyLane operators, measurements, and QNodes can now automatically be captured as instructions in JAXPR.
[(#5564)](https://github.com/PennyLaneAI/pennylane/pull/5564)
[(#5511)](https://github.com/PennyLaneAI/pennylane/pull/5511)
[(#5708)](https://github.com/PennyLaneAI/pennylane/pull/5708)
[(#5523)](https://github.com/PennyLaneAI/pennylane/pull/5523)

* The `decompose` transform has an `error` kwarg to specify the type of error that should be raised,
allowing error types to be more consistent with the context the `decompose` function is used in.
[(#5669)](https://github.com/PennyLaneAI/pennylane/pull/5669)

* The `qml.pytrees` module now has `flatten` and `unflatten` methods for serializing pytrees.
[(#5701)](https://github.com/PennyLaneAI/pennylane/pull/5701)

* Empty initialization of `PauliVSpace` is permitted.
[(#5675)](https://github.com/PennyLaneAI/pennylane/pull/5675)

* `QuantumScript` properties are only calculated when needed, instead of on initialization. This decreases the classical overhead by >20%.
`par_info`, `obs_sharing_wires`, and `obs_sharing_wires_id` are now public attributes.
[(#5696)](https://github.com/PennyLaneAI/pennylane/pull/5696)

* The `qml.qchem.Molecule` object is now the central object used by all qchem functions.
[(#5571)](https://github.com/PennyLaneAI/pennylane/pull/5571)

* The `qml.qchem.Molecule` class now supports Angstrom as a unit.
[(#5694)](https://github.com/PennyLaneAI/pennylane/pull/5694)

* The `qml.qchem.Molecule` class now supports open-shell systems.
[(#5655)](https://github.com/PennyLaneAI/pennylane/pull/5655)

* The `qml.qchem.molecular_hamiltonian` function now supports parity and Bravyi-Kitaev mappings.
[(#5657)](https://github.com/PennyLaneAI/pennylane/pull/5657/)

* The qchem docs are updated with the new qchem improvements.
[(#5758)](https://github.com/PennyLaneAI/pennylane/pull/5758/)
[(#5638)](https://github.com/PennyLaneAI/pennylane/pull/5638/)

* `StateMP.process_state` defines rules in `cast_to_complex` for complex casting, avoiding a superfluous state vector copy in Lightning simulations
[(#5995)](https://github.com/PennyLaneAI/pennylane/pull/5995)

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