[dyn-alloc-base] Lightning dynamically allocate qubit memory

[josephleekl]

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---

Context:
This PR enables lightning devices to dynamically allocate memory for statevectors just before execution. The usual qml.device("lightning.x", wires=y) is still supported, but user can also not provide wires, i.e. qml.device("lightning.x"), and the qubits required for the statevector is provided by the circuit

Description of the Change:
For LQ/LK/LG - the state-vector is only created at the execute step, and not during device creation. For all devices, if wires is provided during device creation, this will be the number of wires allocated in the device state-vector/tensornet; otherwise, it will be determined from the circuit to be executed.

Benefits:

dev = qml.device("lightning.qubit")
@qml.qnode(dev)
def circuit():
    qml.Identity(wires=3)
    qml.Identity(wires=1)
    qml.Hadamard(wires=0)
    return qml.state()


@qml.qnode(dev)
def circuit1():
    qml.Identity(wires=1)
    qml.Hadamard(wires=0)
    return qml.state()

circuit()
> array([0.70710678+0.j, 0.70710678+0.j, 0.        +0.j, 0.        +0.j,
       0.        +0.j, 0.        +0.j, 0.        +0.j, 0.        +0.j])
 
circuit1()
> array([0.70710678+0.j, 0.        +0.j, 0.70710678+0.j, 0.        +0.j])

Possible Drawbacks:

Related GitHub Issues:

[sc-82702]

[codecov]

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 98.95%. Comparing base (c44508c) to head (5586c12).
Report is 1 commits behind head on master.

Additional details and impacted files

@@            Coverage Diff             @@
##           master    #1043      +/-   ##
==========================================
+ Coverage   98.04%   98.95%   +0.91%     
==========================================
  Files         233      266      +33     
  Lines       39556    44514    +4958     
==========================================
+ Hits        38782    44049    +5267     
+ Misses        774      465     -309     

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[AmintorDusko]

Nice job! A few comments and suggestions.

[AmintorDusko]

Thank you @josephleekl! Nice job!

[maliasadi]

Nice work @josephleekl! Just a few minor comments before merging the PR 🎉

[AmintorDusko]

Hey @josephleekl, super useful posting the links to the changes for each comment/suggestion. Much easier to follow, thank you! 🙏

[maliasadi]

Awesome! Happy to approve 🥳