2,254 research outputs found

    Quantum Bayes rule

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    We state a quantum version of Bayes's rule for statistical inference and give a simple general derivation within the framework of generalized measurements. The rule can be applied to measurements on N copies of a system if the initial state of the N copies is exchangeable. As an illustration, we apply the rule to N qubits. Finally, we show that quantum state estimates derived via the principle of maximum entropy are fundamentally different from those obtained via the quantum Bayes rule.Comment: REVTEX, 9 page

    Entanglement purification of unknown quantum states

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    A concern has been expressed that ``the Jaynes principle can produce fake entanglement'' [R. Horodecki et al., Phys. Rev. A {\bf 59}, 1799 (1999)]. In this paper we discuss the general problem of distilling maximally entangled states from NN copies of a bipartite quantum system about which only partial information is known, for instance in the form of a given expectation value. We point out that there is indeed a problem with applying the Jaynes principle of maximum entropy to more than one copy of a system, but the nature of this problem is classical and was discussed extensively by Jaynes. Under the additional assumption that the state ρ(N)\rho^{(N)} of the NN copies of the quantum system is exchangeable, one can write down a simple general expression for ρ(N)\rho^{(N)}. We show how to modify two standard entanglement purification protocols, one-way hashing and recurrence, so that they can be applied to exchangeable states. We thus give an explicit algorithm for distilling entanglement from an unknown or partially known quantum state.Comment: 20 pages RevTeX 3.0 + 1 figure (encapsulated Postscript) Submitted to Physical Review

    Role of phason-defects on the conductance of a 1-d quasicrystal

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    We have studied the influence of a particular kind of phason-defect on the Landauer resistance of a Fibonacci chain. Depending on parameters, we sometimes find the resistance to decrease upon introduction of defect or temperature, a behavior that also appears in real quasicrystalline materials. We demonstrate essential differences between a standard tight-binding model and a full continuous model. In the continuous case, we study the conductance in relation to the underlying chaotic map and its invariant. Close to conducting points, where the invariant vanishes, and in the majority of cases studied, the resistance is found to decrease upon introduction of a defect. Subtle interference effects between a sudden phason-change in the structure and the phase of the wavefunction are also found, and these give rise to resistive behaviors that produce exceedingly simple and regular patterns.Comment: 12 pages, special macros jnl.tex,reforder.tex, eqnorder.tex. arXiv admin note: original tex thoroughly broken, figures missing. Modified so that tex compiles, original renamed .tex.orig in source

    Length of the weaning period affects postweaning growth, health, and carcass merit of ranch-direct beef calves weaned during the fall

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    Bovine respiratory disease (BRD) is the most economically devastating feedlot disease. Risk factors associated with incidence of BRD include (1) stress associated with maternal separation, (2) stress associated with introduction to an unfamiliar environment, (3) poor intake associated with introduction of novel feedstuffs into the animal\u27s diet, (4) exposure to novel pathogens upon transport to a feeding facility and commingling with unfamiliar cattle, (5) inappropriately administered respiratory disease vaccination programs, and (6) poor response to respiratory disease vaccination programs. Management practices that are collectively referred to as preconditioning are thought to minimize damage to the beef carcass from the BRD complex. Preconditioning management reduces the aforementioned risk factors for respiratory disease by (1) using a relatively long ranch-of-origin weaning period following maternal separation, (2) exposing calves to concentrate-type feedstuffs, and (3) producing heightened resistance to respiratory disease-causing organisms through a preweaning vaccination program. The effectiveness of such programs for preserving animal performance is highly touted by certain segments of the beef industry. Ranch-of-origin weaning periods of up to 60 days are suggested for preconditioning beef calves prior to sale; however, optimal length of the ranch-of-origin weaning period has not been determined experimentally. The objective of this study was to test the validity of beef industry assumptions about appropriate length of ranch-of-origin weaning periods for calves aged 160 to 220 days and weaned during the fall

    Mid-infrared plasmons in scaled graphene nanostructures

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    Plasmonics takes advantage of the collective response of electrons to electromagnetic waves, enabling dramatic scaling of optical devices beyond the diffraction limit. Here, we demonstrate the mid-infrared (4 to 15 microns) plasmons in deeply scaled graphene nanostructures down to 50 nm, more than 100 times smaller than the on-resonance light wavelength in free space. We reveal, for the first time, the crucial damping channels of graphene plasmons via its intrinsic optical phonons and scattering from the edges. A plasmon lifetime of 20 femto-seconds and smaller is observed, when damping through the emission of an optical phonon is allowed. Furthermore, the surface polar phonons in SiO2 substrate underneath the graphene nanostructures lead to a significantly modified plasmon dispersion and damping, in contrast to a non-polar diamond-like-carbon (DLC) substrate. Much reduced damping is realized when the plasmon resonance frequencies are close to the polar phonon frequencies. Our study paves the way for applications of graphene in plasmonic waveguides, modulators and detectors in an unprecedentedly broad wavelength range from sub-terahertz to mid-infrared.Comment: submitte

    Proximity induced metal/insulator transition in YBa2Cu3O7/La2/3Ca1/3MnO3Y Ba_2 Cu_3 O_7 / La_{2/3} Ca_{1/3} Mn O_3 superlattices

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    The far-infrared dielectric response of superlattices (SL) composed of superconducting YBa2_{2}Cu3_{3}O7_{7} (YBCO) and ferromagnetic La0.67_{0.67}% Ca0.33_{0.33}MnO3_{3} (LCMO) has been investigated by ellipsometry. A drastic decrease of the free carrier response is observed which involves an unusually large length scale of dcrit^{crit}\approx 20 nm in YBCO and dcrit^{crit}\approx 10 nm in LCMO. A corresponding suppression of metallicity is not observed in SLs where LCMO is replaced by the paramagnetic metal LaNiO3_{3}. Our data suggest that either a long range charge transfer from the YBCO to the LCMO layers or alternatively a strong coupling of the charge carriers to the different and competitive kind of magnetic correlations in the LCMO and YBCO layers are at the heart of the observed metal/insulator transition. The low free carrier response observed in the far-infrared dielectric response of the magnetic superconductor RuSr2_{2}GdCu2_{2}O8_{8} is possibly related to this effect

    Post-Newtonian expansions for perfect fluids

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    We prove the existence of a large class of dynamical solutions to the Einstein-Euler equations that have a first post-Newtonian expansion. The results here are based on the elliptic-hyperbolic formulation of the Einstein-Euler equations used in \cite{Oli06}, which contains a singular parameter \ep = v_T/c, where vTv_T is a characteristic velocity associated with the fluid and cc is the speed of light. As in \cite{Oli06}, energy estimates on weighted Sobolev spaces are used to analyze the behavior of solutions to the Einstein-Euler equations in the limit \ep\searrow 0, and to demonstrate the validity of the first post-Newtonian expansion as an approximation

    Deep Neural Networks for Energy and Position Reconstruction in EXO-200

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    We apply deep neural networks (DNN) to data from the EXO-200 experiment. In the studied cases, the DNN is able to reconstruct the relevant parameters - total energy and position - directly from raw digitized waveforms, with minimal exceptions. For the first time, the developed algorithms are evaluated on real detector calibration data. The accuracy of reconstruction either reaches or exceeds what was achieved by the conventional approaches developed by EXO-200 over the course of the experiment. Most existing DNN approaches to event reconstruction and classification in particle physics are trained on Monte Carlo simulated events. Such algorithms are inherently limited by the accuracy of the simulation. We describe a unique approach that, in an experiment such as EXO-200, allows to successfully perform certain reconstruction and analysis tasks by training the network on waveforms from experimental data, either reducing or eliminating the reliance on the Monte Carlo.Comment: Accepted version. 33 pages, 28 figure

    Measurement of the Spectral Shape of the beta-decay of 137Xe to the Ground State of 137Cs in EXO-200 and Comparison with Theory

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    We report on a comparison between the theoretically predicted and experimentally measured spectra of the first-forbidden non-unique β\beta-decay transition ^{137}\textrm{Xe}(7/2^-)\to\,^{137}\textrm{Cs}(7/2^+). The experimental data were acquired by the EXO-200 experiment during a deployment of an AmBe neutron source. The ultra-low background environment of EXO-200, together with dedicated source deployment and analysis procedures, allowed for collection of a pure sample of the decays, with an estimated signal-to-background ratio of more than 99-to-1 in the energy range from 1075 to 4175 keV. In addition to providing a rare and accurate measurement of the first-forbidden non-unique β\beta-decay shape, this work constitutes a novel test of the calculated electron spectral shapes in the context of the reactor antineutrino anomaly and spectral bump.Comment: Version as accepted by PR
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