A quantum neural network computes its own relative phase

Complete characterization of the state of a quantum system made up of subsystems requires determination of relative phase, because of interference effects between the subsystems. For a system of qubits used as a quantum computer this is especially vital, because the entanglement, which is the basis for the quantum advantage in computing, depends intricately on phase. We present here a first step towards that determination, in which we use a two-qubit quantum system as a quantum neural network, which is trained to compute and output its own relative phase

Floquet Analysis of Atom Optics Tunneling Experiments

Dynamical tunneling has been observed in atom optics experiments by two groups. We show that the experimental results are extremely well described by time-periodic Hamiltonians with momentum quantized in units of the atomic recoil. The observed tunneling has a well defined period when only two Floquet states dominate the dynamics. Beat frequencies are observed when three Floquet states dominate. We find frequencies which match those observed in both experiments. The dynamical origin of the dominant Floquet states is identified.Comment: Accepted in Physical Review

On the correction of anomalous phase oscillation in entanglement witnesses using quantum neural networks

Entanglement of a quantum system depends upon relative phase in complicated ways, which no single measurement can reflect. Because of this, entanglement witnesses are necessarily limited in applicability and/or utility. We propose here a solution to the problem using quantum neural networks. A quantum system contains the information of its entanglement; thus, if we are clever, we can extract that information efficiently. As proof of concept, we show how this can be done for the case of pure states of a two-qubit system, using an entanglement indicator corrected for the anomalous phase oscillation. Both the entanglement indicator and the phase correction are calculated by the quantum system itself acting as a neural network

Narrow structure in the coherent population trapping resonances in rubidium and Rayleigh scattering

The measurement of the coherent-population-trapping (CPT) resonances in uncoated Rb vacuum cells has shown that the shape of the resonances is different in different cells. In some cells the resonance has a complex shape - a narrow Lorentzian structure, which is not power broadened, superimposed on the power broadened CPT resonance. The results of the performed investigations on the fluorescence angular distribution are in agreement with the assumption that the narrow structure is a result of atom interaction with Rayleigh scattering light. The results are interesting for indication of the vacuum cleanness of the cells and building of magnetooptical sensors