• 제목/요약/키워드: ${\lambda}$-Robertson function

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CONVOLUTION PROPERTIES FOR ANALYTIC FUNCTIONS DEFINED BY q-DIFFERENCE OPERATOR

  • Cetinkaya, Asena;Sen, Arzu Yemisci;Polatoglu, Yasar
    • 호남수학학술지
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    • 제40권4호
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    • pp.681-689
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    • 2018
  • In this paper, we defined new subclasses of Spirallike and Robertson functions by using concept of q-derivative operator. We investigate convolution properties and coefficient estimates for both classes q-Spirallike and q-Robertson functions denoted by ${\mathcal{S}}^{\lambda}_q[A,\;B]$ and ${\mathcal{C}}^{\lambda}_q[A,\;B]$, respectively.

STATISTICAL PROPERTIES OF GRAVITATIONAL LENSING IN COSMOLOGICAL MODELS WITH COSMOLOGICAL CONSTANT

  • LEE HYUN-A;PARK MYEONG-GU
    • 천문학회지
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    • 제27권2호
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    • pp.103-117
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    • 1994
  • To extend the work of Gott, Park, and Lee (1989), statistical properties of gravitational lensing in a wide variety of cosmological models involving non-zero cosmological constant is investigated, using the redshifts of both lens and source and observed angular separation of images for gravitational lens systems. We assume singular isothermal sphere as lensing galaxy in homogenous and isotropic Friedmann­Lemaitre-Robertson- Walker universe, Schechter luminosity function, standard angular diameter distance formula and other galaxy parameters used in Fukugita and Turner (1991). To find the most adequate flat cosmological model and put a limit on the value of dimensionless cosmological constant $\lambda_0$, the mean value of the angular separation of images, probability distribution of angular separation and cumulative probability are calculated for given source and lens redshifts and compared with the observed values through several statistical methods. When there is no angular selection effect, models with highest value of $\lambda_0$ is preferred generally. When the angular selection effects are considered, the preferred model depends on the shape of the selection functions and statistical methods; yet, models with large $\lambda_0$ are preferred in general. However, the present data can not rule out any of the flat universe models with enough confidence. This approach can potentially select out best model. But at the moment, we need more data.

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