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

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

What a difference a term makes:the effect of educational attainment on marital outcomes in the UK

Abstract In the past, students in England and Wales born within the first 5 monthsof the academic year could leave school one term earlier than those born later inthe year. Focusing on women, those who were required to stay on an extra termmore frequently hold some academic qualification. Using having been required tostay on as an exogenous factor affecting academic attainment, we find that holding alow-level academic qualification has no effect on the probability of being currentlymarried for women aged 25 or above, but increases the probability of the husbandholding some academic qualification and being economically active.33 Halama