:orphan:

Release 0.40.0-dev (development release)

New features since last release

A DeviceCapabilities data class is defined to contain all capabilities of the device's execution interface (i.e. its implementation of Device.execute). A TOML file can be used to define the capabilities of a device, and it can be loaded into a DeviceCapabilities object. (#6407)
```
>>> from pennylane.devices.capabilities import load_toml_file, parse_toml_document, DeviceCapabilities
>>> document = load_toml_file("my_device.toml")
>>> capabilities = parse_toml_document(document)
>>> isinstance(capabilities, DeviceCapabilities)
True
```

New API for Qubit Mixed

Added qml.devices.qubit_mixed module for mixed-state qubit device support (#6379). This module introduces an apply_operation helper function that features:
- Two density matrix contraction methods using einsum and tensordot
- Optimized handling of special cases including: Diagonal operators, Identity operators, CX (controlled-X), Multi-controlled X gates, Grover operators
Added submodule 'initialize_state' featuring a create_initial_state function for initializing a density matrix from qml.StatePrep operations or qml.QubitDensityMatrix operations. (#6503)

Improvements 🛠

Added support for the wire_options dictionary to customize wire line formatting in qml.draw_mpl circuit visualizations, allowing global and per-wire customization with options like color, linestyle, and linewidth. (#6486)

Capturing and representing hybrid programs

jax.vmap can be captured with qml.capture.make_plxpr and is compatible with quantum circuits. (#6349)

Other Improvements

qml.BasisRotation template is now JIT compatible. (#6019)
The Jaxpr primitives for for_loop, while_loop and cond now store slices instead of numbers of args. (#6521)
Expand ExecutionConfig.gradient_method to store TransformDispatcher type. (#6455)

Breaking changes 💔

The qml.shadows.shadow_expval transform has been removed. Instead, please use the qml.shadow_expval measurement process. (#6530) (#6561)

Deprecations 👋

Documentation 📝

Add a warning message to Gradients and training documentation about ComplexWarnings (#6543)

Bug fixes 🐛

Fixed Identity.__repr__ to return correct wires list. (#6506)

Contributors ✍️

This release contains contributions from (in alphabetical order):

Shiwen An Astral Cai, Yushao Chen, Pietropaolo Frisoni, Andrija Paurevic, Justin Pickering