1,491 research outputs found

    Fluctuation properties of laser light after interaction with an atomic system: comparison between two-level and multilevel atomic transitions

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    The complex internal atomic structure involved in radiative transitions has an effect on the spectrum of fluctuations (noise) of the transmitted light. A degenerate transition has different properties in this respect than a pure two-level transition. We investigate these variations by studying a certain transition between two degenerate atomic levels for different choices of the polarization state of the driving laser. For circular polarization, corresponding to the textbook two-level atom case, the optical spectrum shows the characteristic Mollow triplet for strong laser drive, while the corresponding noise spectrum exhibits squeezing in some frequency ranges. For a linearly polarized drive, corresponding to the case of a multilevel system, additional features appear in both optical and noise spectra. These differences are more pronounced in the regime of a weakly driven transition: whereas the two-level case essentially exhibits elastic scattering, the multilevel case has extra noise terms related to spontaneous Raman transitions. We also discuss the possibility to experimentally observe these predicted differences for the commonly encountered case where the laser drive has excess noise in its phase quadrature.Comment: New version. Accepted for publication in Physical Review

    Dynamics of a stored Zeeman coherence grating in an external magnetic field

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    We investigate the evolution of a Zeeman coherence grating induced in a cold atomic cesium sample in the presence of an external magnetic field. The gratings are created in a three-beam light storage configuration using two quasi-collinear writing laser pulses and reading with a counterpropagating pulse after a variable time delay. The phase conjugated pulse arising from the atomic sample is monitored. Collapses and revivals of the retrieved pulse are observed for different polarizations of the laser beams and for different directions of the applied magnetic field. While magnetic field inhomogeneities are responsible for the decay of the coherent atomic response, a five-fold increase in the coherence decay time, with respect to no applied magnetic field, is obtained for an appropriate choice of the direction of the applied magnetic field. A simplified theoretical model illustrates the role of the magnetic field mean and its inhomogeneity on the collective atomic response.Comment: To appear in J. Phys.

    Polarization squeezing of light by single passage through an atomic vapor

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    We have studied relative-intensity fluctuations for a variable set of orthogonal elliptic polarization components of a linearly polarized laser beam traversing a resonant 87^{87}Rb vapor cell. Significant polarization squeezing at the threshold level (-3dB) required for the implementation of several continuous variables quantum protocols was observed. The extreme simplicity of the setup, based on standard polarization components, makes it particularly convenient for quantum information applications.Comment: Revised version. Minor changes. four pages, three figure

    Spectroscopic observation of the rotational Doppler effect

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    We report on the first spectroscopic observation of the rotational Doppler shift associated with light beams carrying orbital angular momentum. The effect is evidenced as the broadening of a Hanle/EIT coherence resonance on Rb vapor when the two incident Laguerre-Gaussian laser beams have opposite topological charges. The observations closely agree with theoretical predictions.Comment: Submited to Physical Review Lette

    Hybrid-adaptive differential evolution with decay function (HyDE-DF) applied to the 100-digit challenge competition on single objective numerical optimization

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    In this paper, a hybrid-adaptive differential evolution with a decay function (HyDE-DF)1 is proposed for numerical function optimization. The proposed HyDE-DF is applied to the 100-Digit Challenge in a set of 10 benchmark functions. Results show that HyDE-DF can achieve a 93/100 score, proving its effectiveness for numerical optimization.This research has received funding from FEDER funds through the Operational Programme for Competitiveness and Internationalization (COMPETE 2020), under Project POCI-01-0145-FEDER-028983; by National Funds through the FCT Portuguese Foundation for Science and Technology, under Projects PTDC/EEI-EEE/28983/2017 (CENERGETIC).info:eu-repo/semantics/publishedVersio

    Polarization dependence of four-wave mixing in a degenerate two-level system

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    Nearly degenerate four-wave mixing (NDFWM) within a closed degenerate two-level atomic transition is theoretically and experimentally examined. Using the model presented by A. Lezama et al [Phys. Rev. A 61, 013801 (2000)] the NDFWM spectra corresponding to different pump and probe polarization cases are calculated and discussed. The calculated spectra are compared to the observation of NDFWM within the 6S1/2(F=4)6P3/2(F=5)6S_{1/2}(F=4)\to 6P_{3/2}(F=5) transition of cesium in a phase conjugation experiment using magneto optically cooled atomsComment: 10 pages, 13 figures; submitted to Phys. Rev.

    Partial replay of long-running applications

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    Bugs in deployed software can be extremely difficult to track down. Invasive logging techniques, such as logging all non-deterministic inputs, can incur substantial runtime overheads. This paper shows how symbolic analysis can be used to re-create path equivalent executions for very long running programs such as databases and web servers. The goal is to help developers debug such long-running programs by allowing them to walk through an execution of the last few requests or transactions leading up to an error. The challenge is to provide this functionality without the high runtime overheads associated with traditional replay techniques based on input logging or memory snapshots. Our approach achieves this by recording a small amount of information about program execution, such as the direction of branches taken, and then using symbolic analysis to reconstruct the execution of the last few inputs processed by the application, as well as the state of memory before these inputs were executed. We implemented our technique in a new tool called bbr. In this paper, we show that it can be used to replay bugs in long-running single-threaded programs starting from the middle of an execution. We show that bbr incurs low recording overhead (avg. of 10%) during program execution, which is much less than existing replay schemes. We also show that it can reproduce real bugs from web servers, database systems, and other common utilities

    Safety-Aware Apprenticeship Learning

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    Apprenticeship learning (AL) is a kind of Learning from Demonstration techniques where the reward function of a Markov Decision Process (MDP) is unknown to the learning agent and the agent has to derive a good policy by observing an expert's demonstrations. In this paper, we study the problem of how to make AL algorithms inherently safe while still meeting its learning objective. We consider a setting where the unknown reward function is assumed to be a linear combination of a set of state features, and the safety property is specified in Probabilistic Computation Tree Logic (PCTL). By embedding probabilistic model checking inside AL, we propose a novel counterexample-guided approach that can ensure safety while retaining performance of the learnt policy. We demonstrate the effectiveness of our approach on several challenging AL scenarios where safety is essential.Comment: Accepted by International Conference on Computer Aided Verification (CAV) 201

    Learning Bidding Strategies in Local Electricity Markets using Ant Colony optimization

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    Local energy markets (LM) are attracting significant interest due to their potential of balancing generation and consumption and supporting the adoption of distributed renewable sources at the distribution level. Besides, LMs aim at increasing the participation of small end-users in energy transactions, setting the stage for transactive energy systems. In this work, we explore the use of ant colony optimization (ACO) for learning bidding strategies under a bi-level optimization framework that arises when trading energy in an LM. We performed an empirical analysis of the impact of ACO parameters have in the learning process and the obtained profits of agents. After that, we analyze and compare ACO performance against an evolutionary algorithm under a realistic case study with nine agents trading energy in the day-ahead LM. Results suggest that ACO can be efficient for strategic learning of agents, providing solutions in which all agents can improve their profits. Overall, it is shown the advantages that an LM can bring to market participants, thereby increasing the tolerable penetration of renewable resources and facilitating the energy transition.This work has received funding from the European Union's Horizon 2020 research and innovation programme under project DOMINOES (grant agreement No 771066) and CENERGETIC (POCI-01-0145- FEDER-028983 and PTDC/EEI-EEE/28983/2017), from FEDER Funds through COMPETE program and from National Funds through (FCT) under the project UIDB/00760/2020, and grants CEECIND/02814/2017, CEECIND/02887/2017, SFRH/BD/133086/2017.info:eu-repo/semantics/publishedVersio
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