Retrieving space-dependent polarization transformations via near-optimal quantum process tomography.

An optical waveplate rotating light polarization can be modeled as a single-qubit unitary operator. This analogy can be exploited to experimentally retrieve a polarization transformation within the paradigm of quantum process tomography. Standard approaches to tomographic problems rely on the maximum-likelihood estimation, providing the most likely transformation to yield the same outcomes as a set of experimental projective measurements.

A dataset for quantum circuit mapping.

Quantum computing is rapidly establishing itself as a new computing paradigm capable of obtaining advantages over its classical counterpart. However, a major limitation in the design of a quantum algorithm is related to the proper mapping of the corresponding circuit to a specific quantum processor so that the underlying physical constraints are satisfied. Moreover, current deterministic mapping algorithms suffer from high run times as the number of qubits to map increases.