QDrift C API Implementation #15390
QDrift C API Implementation #15390
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…g, fixing an MSVC incompatibility
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…prox_real with Result
Cryoris
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Cryoris
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Thanks for the PR @Didgety, looks already good and I left some comments below. I think it would be good to separate the exposure of global_phase in a separate PR (including tests and a release note), if you'd like to do that.
| let rescaled_time = 2.0 * lambda / num_gates as f64 * time; | ||
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| // sample term indices (0..n_terms) | ||
| let sampled_indices: Vec<usize> = (0..num_gates).map(|_| dist.sample(&mut rng)).collect(); |
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Is it possible to write this and the following circuit constructor as single iteration and avoid the Vec creations? Possibly something along the lines of
let evos = (0..num_gates)
.map(|_| dist.sample(&mut rng))
.map(|i| {
// compute pauli_string, indices, theta
// call sparse_term_evolution directly
});
CircuitData::from_packed_operations(..., evos, ...)| pauli_strings.push(pauli_string); | ||
| pauli_indices.push(dense_indices); |
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I would expect we don't need to use "dense" indices and Paulis of size num_qubits but could just use a sparse format where we only store the non-identity Paulis and the corresponding indices, no?
| /// with a probability proportional to its weight. | ||
| /// Based on the work of Earl Campbell in Ref. [1]. | ||
| /// | ||
| /// # Parameters |
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Could you update this to doxygen style like the other C-facing functions? 🙂
| quantum circuits that approximate the time evolution under a given sparse | ||
| observable using the QDRIFT algorithm. For example:: | ||
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| #include <qiskit.h> |
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I think this needs to be captured in a .. code-block:: c. Afaik :: only works for Python
…ted to use sparse indices.
… sparse construction
4 participants
Summary
This pull request implements QDrift Trotterization within the C circuit library.
Details and comments
As part of the implementation, some things were made public:
pauli_evolutionmodule from the Rustcircuit_librarycrate, a type alias within that moduleInstruction, and a functionsparse_term_evolutionThe implementation was loosely based on the Python version, but is grounded in the mathematics from the paper: https://arxiv.org/abs/1811.08017
Tests were created for valid observables, invalid observables, gate count scaling, invalid repetitions, observables containing projectors, and global phase.