Informational completeness of continuous-variable measurements

We justify that homodyne tomography turns out to be informationally complete when the number of independent quadrature measurements is equal to the dimension of the density matrix in the Fock representation. Using this as our thread, we examine the completeness of other schemes, when continuous-variable observations are truncated to discrete finite-dimensional subspaces.Comment: To appear in Phys. Rev.

Optimal measurements for quantum spatial superresolution

We construct optimal measurements, achieving the ultimate precision predicted by quantum theory, for the simultaneous estimation of centroid, separation, and relative intensities of two incoherent point sources using a linear optical system. We discuss the physical feasibility of the scheme, which could pave the way for future practical implementations of quantum inspired imaging.Comment: 7 pages. 3 color figures. Title change

Efficient algorithm for optimizing data pattern tomography

We give a detailed account of an efficient search algorithm for the data pattern tomography proposed by J. Rehacek, D. Mogilevtsev, and Z. Hradil [Phys. Rev. Lett.~\textbf{105}, 010402 (2010)], where the quantum state of a system is reconstructed without a priori knowledge about the measuring setup. The method is especially suited for experiments involving complex detectors, which are difficult to calibrate and characterize. We illustrate the approach with the case study of the homodyne detection of a nonclassical photon state.Comment: 5 pages, 5 eps-color figure

Anchors for the Cosmic Distance Scale: the Cepheid QZ Normae in the Open Cluster NGC 6067

Cepheids are key to establishing the cosmic distance scale. Therefore it's important to assess the viability of QZ Nor, V340 Nor, and GU Nor as calibrators for Leavitt's law via their purported membership in the open cluster NGC 6067. The following suite of evidence confirms that QZ Nor and V340 Nor are members of NGC 6067, whereas GU Nor likely lies in the foreground: (i) existing radial velocities for QZ Nor and V340 Nor agree with that established for the cluster (-39.4+-1.2 km/s) to within 1 km/s, whereas GU Nor exhibits a markedly smaller value; (ii) a steep velocity-distance gradient characterizes the sight-line toward NGC 6067, thus implying that objects sharing common velocities are nearly equidistant; (iii) a radial profile constructed for NGC 6067 indicates that QZ Nor is within the cluster bounds, despite being 20' from the cluster center; (iv) new BVJH photometry for NGC 6067 confirms the cluster lies d=1.75+-0.10 kpc distant, a result that matches Wesenheit distances computed for QZ Nor/V340 Nor using the Benedict et al. (2007, HST parallaxes) calibration. QZ Nor is a cluster Cepheid that should be employed as a calibrator for the cosmic distance scale.Comment: To appear in ApS

Developing collaborative partnerships with culturally and linguistically diverse families during the IEP process

Family participation in the special education process has been federally mandated for 40 years, and educators recognize that effective collaboration with their students’ families leads to improved academic and social outcomes for students. However, while some family-school relationships are positive and collaborative, many are not, particularly for culturally and linguistically diverse (CLD) families. This article provides practice guidelines based in research for teachers who seek to improve their practices when working with CLD families who have children served by special education

Analysis of Deterioration in a Plasma Focus Device

Indexación: Scopus.The Plasma Focus (PF) is a kind of dense transient plasmas in with high-pulsed voltage. To produce devices for eld application it is necessary to obtain PF equipment able to operate for a long period of time. Thus, a reliability analysis is indispensable. In this work a reliability analysis program for plasma focus devices is presented. The program considers a criticality analysis using Failure Modes and Effects Criticality Analysis (FMECA) to identify the most important failure modes of the system. Said failure modes are studied operating the Plasma Focus for many cycles, obtaining from them the characteristic curves of V(t) and İ(t). Feature Extraction (FE) techniques are applied to obtain a list of parameters that correlate to the degrading process. Furthermore, Machine Learning tools are used to learn from the obtained data, linking the changes in these parameters during its life cycle to the decay of the system in hope for future implementation of a predictive maintenance system and a reference for data analysis and prediction in PFs. The study was applied to a portable plasma focus device operated at 2 joules of stored energy. © Published under licence by IOP Publishing Ltd.The work is supported by IAEA CRP contract 20370 and by grant ACT-1115, CONICYT, Chile.https://iopscience.iop.org/article/10.1088/1742-6596/1043/1/01204

Neural-network quantum state tomography

We revisit the application of neural networks techniques to quantum state tomography. We confirm that the positivity constraint can be successfully implemented with trained networks that convert outputs from standard feed-forward neural networks to valid descriptions of quantum states. Any standard neural-network architecture can be adapted with our method. Our results open possibilities to use state-of-the-art deep-learning methods for quantum state reconstruction under various types of noise.Comment: 8 pages, 4 color figures. Comments are most welcom