catalyst
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A JIT compiler for hybrid quantum programs in PennyLane
Currently compile driver always attempts to detect the entry point signature (see [getJITFunction](https://github.com/PennyLaneAI/catalyst/blob/2c77640cc5fbceeb88eeee541f1cc955774d791a/mlir/lib/Driver/CompilerDriver.cpp#L465)) and prints messages if it can't find one, which is is only relevant for IR string input....
* *Expected behavior:* In PL `qml.counts()` returns a dictionary. I would expect in catalyst to also return a dictionary. * *Actual behavior:* In Catalyst `qml.counts()` returns a tuple of arrays.
Devices have a short name, long name, and sometimes might even be different from their short name and long name. Right now depending on the implementation details, the qdevice_p primitive...
https://github.com/PennyLaneAI/pennylane/pull/5287 Superseded by: https://github.com/PennyLaneAI/pennylane/pull/5885
**Context:** Lowering of value_and_grad to MLIR is now supported when @qjit is used. **Description of the Change:** A new ValueAndGradOp was added and the existing BackpropOp was modified to return...
**Context:** We have a custom mutex that denotes current use of the Python interpreter (a shared resource among threads). This custom mutex may be replaced by the lock found in...
**Context:** **Description of the Change:** **Benefits:** **Possible Drawbacks:** **Related GitHub Issues:**
**Context:** **Description of the Change:** **Benefits:** **Possible Drawbacks:** **Related GitHub Issues:**
## Context Catalyst supports CUDA Quantum (CUDAQ) Interpreter as a simulator backend (`SoftwareQQPP)` by having a custom Jaxpr interpreter that translates the input program to CUDA Quantum Python API calls....