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João R.s. Leão - One of the best experts on this subject based on the ideXlab platform.

  • A Probabilistic Formulation for Empirical Population Synthesis: Sampling methods and tests
    Monthly Notices of the Royal Astronomical Society, 2001
    Co-Authors: Roberto Cid Fernandes, Laerte Sodré, Henrique R. Schmitt, João R.s. Leão
    Abstract:

    We present a Probabilistic Formulation of the classical problem of synthesizing spectral properties of a galaxy using a base of star clusters. The problem consists of estimating the population vector x, composed by the contributions of n_star base elements to the integrated spectrum of a galaxy, and the extinction A_V, given a set of absorption line equivalent widths and continuum colors. The formalism is applied to the n_star = 12 base defined by Schmidt etal and subsequently used in several studies. The 13-D parameter space is explored with a Markov chain Monte Carlo sampling scheme based on the Metropolis algorithm, which produces a smooth and efficient mapping of the P(x,A_V) probability distribution. This version of Empirical Population Synthesis is used to investigate the ability to recover the detailed history of star-formation and chemical evolution using this spectral base. This is studied as a function of (1) the magnitude of the measurement errors and (2) the set of observables used in the synthesis. Only for extremely high S/N all 12 base proportions can be accurately recovered, though the observables are very precisely reproduced for any S/N. Furthermore, the individual mean x components are biased in the sense that components which carry a large fraction of the light tend to share their contribution preferably among components of same age. This compensation effect is linked to noise-induced linear dependences in the base, which very effectively redistribute the likelihood in x-space. The age distribution, however, can be satisfactorily recovered for realistic data quality. (abridged)

  • a Probabilistic Formulation for empirical population synthesis sampling methods and tests
    Monthly Notices of the Royal Astronomical Society, 2001
    Co-Authors: Roberto Cid Fernandes, Laerte Sodré, Henrique R. Schmitt, João R.s. Leão
    Abstract:

    ABSTRA C T We revisit the classical problem of synthesizing spectral properties of a galaxy by using a base of star clusters, approaching it from a Probabilistic perspective. The problem consists of estimating the population vector x, composed by the contributions of nQ different base elements to the integrated spectrum of a galaxy, and the extinction AV, given a set of absorption line equivalent widths and continuum colours. The formalism is applied to the base of 12 elements defined by Schmidt et al. as corresponding to the principal components of the original base employed by Bica, and subsequently used in several studies of the stellar populations of galaxies. The exploration of the 13D parameter space is carried out with a Markov chain Monte Carlo sampling scheme, based on the Metropolis algorithm. This produces a smoother and more efficient mapping of the P(x,AV) probability distribution than the traditionally employed uniform-grid sampling. This new version of empirical population synthesis is used to investigate the ability to recover the detailed history of star formation and chemical evolution using this spectral base. This is studied as a function of (i) the magnitude of the measurement errors and (ii) the set of observables used in the synthesis. Extensive simulations with test galaxies are used for this purpose. The emphasis is put on the comparison of input parameters and the mean x and AV associated with the P(x,AV) distribution. It is found that only for extremely low errors [signalto-noise ratioOS=NU . 300 at 5870 A ˚ ] all 12 base proportions can be accurately recovered, though the observables are recovered very precisely for any S/N. Furthermore, the individual

Roberto Cid Fernandes - One of the best experts on this subject based on the ideXlab platform.

  • A Probabilistic Formulation for Empirical Population Synthesis: Sampling methods and tests
    Monthly Notices of the Royal Astronomical Society, 2001
    Co-Authors: Roberto Cid Fernandes, Laerte Sodré, Henrique R. Schmitt, João R.s. Leão
    Abstract:

    We present a Probabilistic Formulation of the classical problem of synthesizing spectral properties of a galaxy using a base of star clusters. The problem consists of estimating the population vector x, composed by the contributions of n_star base elements to the integrated spectrum of a galaxy, and the extinction A_V, given a set of absorption line equivalent widths and continuum colors. The formalism is applied to the n_star = 12 base defined by Schmidt etal and subsequently used in several studies. The 13-D parameter space is explored with a Markov chain Monte Carlo sampling scheme based on the Metropolis algorithm, which produces a smooth and efficient mapping of the P(x,A_V) probability distribution. This version of Empirical Population Synthesis is used to investigate the ability to recover the detailed history of star-formation and chemical evolution using this spectral base. This is studied as a function of (1) the magnitude of the measurement errors and (2) the set of observables used in the synthesis. Only for extremely high S/N all 12 base proportions can be accurately recovered, though the observables are very precisely reproduced for any S/N. Furthermore, the individual mean x components are biased in the sense that components which carry a large fraction of the light tend to share their contribution preferably among components of same age. This compensation effect is linked to noise-induced linear dependences in the base, which very effectively redistribute the likelihood in x-space. The age distribution, however, can be satisfactorily recovered for realistic data quality. (abridged)

  • a Probabilistic Formulation for empirical population synthesis sampling methods and tests
    Monthly Notices of the Royal Astronomical Society, 2001
    Co-Authors: Roberto Cid Fernandes, Laerte Sodré, Henrique R. Schmitt, João R.s. Leão
    Abstract:

    ABSTRA C T We revisit the classical problem of synthesizing spectral properties of a galaxy by using a base of star clusters, approaching it from a Probabilistic perspective. The problem consists of estimating the population vector x, composed by the contributions of nQ different base elements to the integrated spectrum of a galaxy, and the extinction AV, given a set of absorption line equivalent widths and continuum colours. The formalism is applied to the base of 12 elements defined by Schmidt et al. as corresponding to the principal components of the original base employed by Bica, and subsequently used in several studies of the stellar populations of galaxies. The exploration of the 13D parameter space is carried out with a Markov chain Monte Carlo sampling scheme, based on the Metropolis algorithm. This produces a smoother and more efficient mapping of the P(x,AV) probability distribution than the traditionally employed uniform-grid sampling. This new version of empirical population synthesis is used to investigate the ability to recover the detailed history of star formation and chemical evolution using this spectral base. This is studied as a function of (i) the magnitude of the measurement errors and (ii) the set of observables used in the synthesis. Extensive simulations with test galaxies are used for this purpose. The emphasis is put on the comparison of input parameters and the mean x and AV associated with the P(x,AV) distribution. It is found that only for extremely low errors [signalto-noise ratioOS=NU . 300 at 5870 A ˚ ] all 12 base proportions can be accurately recovered, though the observables are recovered very precisely for any S/N. Furthermore, the individual

Henrique R. Schmitt - One of the best experts on this subject based on the ideXlab platform.

  • A Probabilistic Formulation for Empirical Population Synthesis: Sampling methods and tests
    Monthly Notices of the Royal Astronomical Society, 2001
    Co-Authors: Roberto Cid Fernandes, Laerte Sodré, Henrique R. Schmitt, João R.s. Leão
    Abstract:

    We present a Probabilistic Formulation of the classical problem of synthesizing spectral properties of a galaxy using a base of star clusters. The problem consists of estimating the population vector x, composed by the contributions of n_star base elements to the integrated spectrum of a galaxy, and the extinction A_V, given a set of absorption line equivalent widths and continuum colors. The formalism is applied to the n_star = 12 base defined by Schmidt etal and subsequently used in several studies. The 13-D parameter space is explored with a Markov chain Monte Carlo sampling scheme based on the Metropolis algorithm, which produces a smooth and efficient mapping of the P(x,A_V) probability distribution. This version of Empirical Population Synthesis is used to investigate the ability to recover the detailed history of star-formation and chemical evolution using this spectral base. This is studied as a function of (1) the magnitude of the measurement errors and (2) the set of observables used in the synthesis. Only for extremely high S/N all 12 base proportions can be accurately recovered, though the observables are very precisely reproduced for any S/N. Furthermore, the individual mean x components are biased in the sense that components which carry a large fraction of the light tend to share their contribution preferably among components of same age. This compensation effect is linked to noise-induced linear dependences in the base, which very effectively redistribute the likelihood in x-space. The age distribution, however, can be satisfactorily recovered for realistic data quality. (abridged)

  • a Probabilistic Formulation for empirical population synthesis sampling methods and tests
    Monthly Notices of the Royal Astronomical Society, 2001
    Co-Authors: Roberto Cid Fernandes, Laerte Sodré, Henrique R. Schmitt, João R.s. Leão
    Abstract:

    ABSTRA C T We revisit the classical problem of synthesizing spectral properties of a galaxy by using a base of star clusters, approaching it from a Probabilistic perspective. The problem consists of estimating the population vector x, composed by the contributions of nQ different base elements to the integrated spectrum of a galaxy, and the extinction AV, given a set of absorption line equivalent widths and continuum colours. The formalism is applied to the base of 12 elements defined by Schmidt et al. as corresponding to the principal components of the original base employed by Bica, and subsequently used in several studies of the stellar populations of galaxies. The exploration of the 13D parameter space is carried out with a Markov chain Monte Carlo sampling scheme, based on the Metropolis algorithm. This produces a smoother and more efficient mapping of the P(x,AV) probability distribution than the traditionally employed uniform-grid sampling. This new version of empirical population synthesis is used to investigate the ability to recover the detailed history of star formation and chemical evolution using this spectral base. This is studied as a function of (i) the magnitude of the measurement errors and (ii) the set of observables used in the synthesis. Extensive simulations with test galaxies are used for this purpose. The emphasis is put on the comparison of input parameters and the mean x and AV associated with the P(x,AV) distribution. It is found that only for extremely low errors [signalto-noise ratioOS=NU . 300 at 5870 A ˚ ] all 12 base proportions can be accurately recovered, though the observables are recovered very precisely for any S/N. Furthermore, the individual

Laerte Sodré - One of the best experts on this subject based on the ideXlab platform.

  • A Probabilistic Formulation for Empirical Population Synthesis: Sampling methods and tests
    Monthly Notices of the Royal Astronomical Society, 2001
    Co-Authors: Roberto Cid Fernandes, Laerte Sodré, Henrique R. Schmitt, João R.s. Leão
    Abstract:

    We present a Probabilistic Formulation of the classical problem of synthesizing spectral properties of a galaxy using a base of star clusters. The problem consists of estimating the population vector x, composed by the contributions of n_star base elements to the integrated spectrum of a galaxy, and the extinction A_V, given a set of absorption line equivalent widths and continuum colors. The formalism is applied to the n_star = 12 base defined by Schmidt etal and subsequently used in several studies. The 13-D parameter space is explored with a Markov chain Monte Carlo sampling scheme based on the Metropolis algorithm, which produces a smooth and efficient mapping of the P(x,A_V) probability distribution. This version of Empirical Population Synthesis is used to investigate the ability to recover the detailed history of star-formation and chemical evolution using this spectral base. This is studied as a function of (1) the magnitude of the measurement errors and (2) the set of observables used in the synthesis. Only for extremely high S/N all 12 base proportions can be accurately recovered, though the observables are very precisely reproduced for any S/N. Furthermore, the individual mean x components are biased in the sense that components which carry a large fraction of the light tend to share their contribution preferably among components of same age. This compensation effect is linked to noise-induced linear dependences in the base, which very effectively redistribute the likelihood in x-space. The age distribution, however, can be satisfactorily recovered for realistic data quality. (abridged)

  • a Probabilistic Formulation for empirical population synthesis sampling methods and tests
    Monthly Notices of the Royal Astronomical Society, 2001
    Co-Authors: Roberto Cid Fernandes, Laerte Sodré, Henrique R. Schmitt, João R.s. Leão
    Abstract:

    ABSTRA C T We revisit the classical problem of synthesizing spectral properties of a galaxy by using a base of star clusters, approaching it from a Probabilistic perspective. The problem consists of estimating the population vector x, composed by the contributions of nQ different base elements to the integrated spectrum of a galaxy, and the extinction AV, given a set of absorption line equivalent widths and continuum colours. The formalism is applied to the base of 12 elements defined by Schmidt et al. as corresponding to the principal components of the original base employed by Bica, and subsequently used in several studies of the stellar populations of galaxies. The exploration of the 13D parameter space is carried out with a Markov chain Monte Carlo sampling scheme, based on the Metropolis algorithm. This produces a smoother and more efficient mapping of the P(x,AV) probability distribution than the traditionally employed uniform-grid sampling. This new version of empirical population synthesis is used to investigate the ability to recover the detailed history of star formation and chemical evolution using this spectral base. This is studied as a function of (i) the magnitude of the measurement errors and (ii) the set of observables used in the synthesis. Extensive simulations with test galaxies are used for this purpose. The emphasis is put on the comparison of input parameters and the mean x and AV associated with the P(x,AV) distribution. It is found that only for extremely low errors [signalto-noise ratioOS=NU . 300 at 5870 A ˚ ] all 12 base proportions can be accurately recovered, though the observables are recovered very precisely for any S/N. Furthermore, the individual

Xuanlong Nguyen - One of the best experts on this subject based on the ideXlab platform.

  • sequential detection of multiple change points in networks a graphical model approach
    IEEE Transactions on Information Theory, 2013
    Co-Authors: Arash A Amini, Xuanlong Nguyen
    Abstract:

    We propose a Probabilistic Formulation that enables sequential detection of multiple change points in a network setting. We present a class of sequential detection rules for certain functionals of change points (minimum among a subset), and prove their asymptotic optimality in terms of expected detection delay. Drawing from graphical model formalism, the sequential detection rules can be implemented by a computationally efficient message-passing protocol which may scale up linearly in network size and in waiting time. The effectiveness of our inference algorithm is demonstrated by simulations.

  • ISIT - Message-passing sequential detection of multiple change points in networks
    2012 IEEE International Symposium on Information Theory Proceedings, 2012
    Co-Authors: Xuanlong Nguyen, Arash A Amini, Ram Rajagopal
    Abstract:

    We propose a Probabilistic Formulation that enables sequential detection of multiple change points in a network setting. We present a class of sequential detection rules for functionals of change points, and prove their asymptotic optimality properties in terms of expected detection delay time. Drawing from graphical model formalism, the sequential detection rules can be implemented by a computationally efficient message-passing protocol which may scale up linearly in network size and in waiting time. The effectiveness of our exact and approximate inference algorithms are demonstrated by simulations.