QSP iterative angle solver

[cvqmm]

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Context: QSP angle solver

Description of the Change: determine the QSP circuit angles through an iterative optimization procedure https://journals.aps.org/pra/abstract/10.1103/PhysRevA.103.042419

Benefits:

Possible Drawbacks:

Related GitHub Issues:

[cvqmm]

@KetpuntoG @AntonNI8 @DSGuala

[KetpuntoG]

Great! Thanks for working on it :)
Let me know if you have any question

[cvqmm]

Great! Thanks for working on it :) Let me know if you have any question

thx for the support.. just a couple:

• so you'll notice that I switched to random polynomials instead of hard coded coeffs for the tests.. the test that tests the complimentarity is falling short in terms of precision (~1e-5) instead (1e-7 which is the current atol) so idk how you/we want to resolve that (maybe reduce the atol)
• how to integrate jit: do I give the user the command to switch to jax use or do I do it under the hood by checking whether jax is installed and if it's the case switch from autograd to jax?

[KetpuntoG]

Great! Thanks for working on it :) Let me know if you have any question

thx for the support.. just a couple:

• so you'll notice that I switched to random polynomials instead of hard coded coeffs for the tests.. the test that tests the complimentarity is falling short in terms of precision (~1e-5) instead (1e-7 which is the current atol) so idk how you/we want to resolve that (maybe reduce the atol)
• how to integrate jit: do I give the user the command to switch to jax use or do I do it under the hood by checking whether jax is installed and if it's the case switch from autograd to jax?

• Let's reduce the atol to 1-e5 for the moment 👍
• Taking a look to the code, instead of using qml.numpy.____ you could use qml.math.___
  In that way the interface will be chosen based on the input of the function

Don't worry about jit integration. The code itself will not have jit. But it would be good to create a test to check that it will indeed work with jit. This is an example where jit is tested

[cvqmm]

Great! Thanks for working on it :) Let me know if you have any question

thx for the support.. just a couple:

• so you'll notice that I switched to random polynomials instead of hard coded coeffs for the tests.. the test that tests the complimentarity is falling short in terms of precision (~1e-5) instead (1e-7 which is the current atol) so idk how you/we want to resolve that (maybe reduce the atol)
• how to integrate jit: do I give the user the command to switch to jax use or do I do it under the hood by checking whether jax is installed and if it's the case switch from autograd to jax?

• Let's reduce the atol to 1-e5 for the moment 👍
• Taking a look to the code, instead of using qml.numpy.____ you could use qml.math.___
  In that way the interface will be chosen based on the input of the function

Don't worry about jit integration. The code itself will not have jit. But it would be good to create a test to check that it will indeed work with jit. This is an example where jit is tested

• So I replaced qml.numpy with qml.math as suggested.. I also added a customed decorator that will jit the adequate functions if jax is available (which will also carry the test in jax if it's available).. let me know what you think..

[DSGuala]

🚀 Thanks for opening this PR @cvqmm !