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J. R. Fish

Researcher at Harvey Mudd College

Publications -  4
Citations -  435

J. R. Fish is an academic researcher from Harvey Mudd College. The author has contributed to research in topics: Stars & Planetary system. The author has an hindex of 3, co-authored 4 publications receiving 411 citations. Previous affiliations of J. R. Fish include Carnegie Institution for Science.

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Lithium abundances in nearby fgk dwarf and subgiant stars: internal destruction, galactic chemical evolution, and exoplanets

TL;DR: In this paper, the authors derived atmospheric parameters and lithium abundances for 671 stars and include their measurements in a literature compilation of 1381 dwarf and sub-giant stars, finding that most of the stars on the low A Li side of the desert have experienced a short-lived period of severe surface lithium destruction as main-sequence or subgiant star.
Journal ArticleDOI

Elemental abundance differences in the 16 Cygni binary system: A signature of gas giant planet formation?

TL;DR: In this article, the atmospheric parameters of the components of the 16-Cygni binary system, in which the secondary has a gas giant planet detected, are measured accurately using high-quality observational data.
Journal ArticleDOI

Lithium abundances in nearby FGK dwarf and subgiant stars: internal destruction, Galactic chemical evolution, and exoplanets

TL;DR: In this article, the authors derived atmospheric parameters and lithium abundances for 671 stars and include their measurements in a literature compilation of 1381 dwarf and subgiant stars, and found that most of the stars on the low A_Li side of the desert have experienced a short-lived period of severe surface lithium destruction as main-sequence or sub-giants.
Journal ArticleDOI

Elemental abundance differences in the 16 Cygni binary system: a signature of gas giant planet formation?

TL;DR: In this article, the atmospheric parameters of the components of the 16Cygni binary system, in which the secondary has a gas giant planet detected, are measured accurately using high quality observational data.