122 research outputs found

    Pattern Count on Multiply Restricted Permutations

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    Previous work has studied the pattern count on singly restricted permutations. In this work, we focus on patterns of length 3 in multiply restricted permutations, especially for double and triple pattern-avoiding permutations. We derive explicit formulae or generating functions for various occurrences of length 3 patterns on multiply restricted permutations, as well as some combinatorial interpretations for non-trivial pattern relationships.Comment: 23 pages, 2 figure

    Mixed Statistics on 01-Fillings of Moon Polyominoes

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    We establish a stronger symmetry between the numbers of northeast and southeast chains in the context of 01-fillings of moon polyominoes. Let \M be a moon polyomino with nn rows and mm columns. Consider all the 01-fillings of \M in which every row has at most one 1. We introduce four mixed statistics with respect to a bipartition of rows or columns of \M. More precisely, let S{1,2,...,n}S \subseteq \{1,2,..., n\} and R(S)\mathcal{R}(S) be the union of rows whose indices are in SS. For any filling MM, the top-mixed (resp. bottom-mixed) statistic α(S;M)\alpha(S; M) (resp. β(S;M)\beta(S; M)) is the sum of the number of northeast chains whose top (resp. bottom) cell is in R(S)\mathcal{R}(S), together with the number of southeast chains whose top (resp. bottom) cell is in the complement of R(S)\mathcal{R}(S). Similarly, we define the left-mixed and right-mixed statistics γ(T;M)\gamma(T; M) and δ(T;M)\delta(T; M), where TT is a subset of the column index set {1,2,...,m}\{1,2,..., m\}. Let λ(A;M)\lambda(A; M) be any of these four statistics α(S;M)\alpha(S; M), β(S;M)\beta(S; M), γ(T;M)\gamma(T; M) and δ(T;M)\delta(T; M), we show that the joint distribution of the pair (λ(A;M),λ(Aˉ;M))(\lambda(A; M), \lambda(\bar A; M)) is symmetric and independent of the subsets S,TS, T. In particular, the pair of statistics (λ(A;M),λ(Aˉ;M))(\lambda(A;M), \lambda(\bar A; M)) is equidistributed with (\se(M),\ne(M)), where \se(M) and (M)\ne(M) are the numbers of southeast chains and northeast chains of MM, respectively.Comment: 20 pages, 6 figure

    Mixed Statistics on 01-Fillings of Moon Polyominoes

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    Sloan Digital Sky Survey IV: Mapping the Milky Way, Nearby Galaxies, and the Distant Universe

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    We describe the Sloan Digital Sky Survey IV (SDSS-IV), a project encompassing three major spectroscopic programs. The Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2) is observing hundreds of thousands of Milky Way stars at high resolution and high signal-to-noise ratios in the near-infrared. The Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey is obtaining spatially resolved spectroscopy for thousands of nearby galaxies (median z0.03z\sim 0.03). The extended Baryon Oscillation Spectroscopic Survey (eBOSS) is mapping the galaxy, quasar, and neutral gas distributions between z0.6z\sim 0.6 and 3.5 to constrain cosmology using baryon acoustic oscillations, redshift space distortions, and the shape of the power spectrum. Within eBOSS, we are conducting two major subprograms: the SPectroscopic IDentification of eROSITA Sources (SPIDERS), investigating X-ray AGNs and galaxies in X-ray clusters, and the Time Domain Spectroscopic Survey (TDSS), obtaining spectra of variable sources. All programs use the 2.5 m Sloan Foundation Telescope at the Apache Point Observatory; observations there began in Summer 2014. APOGEE-2 also operates a second near-infrared spectrograph at the 2.5 m du Pont Telescope at Las Campanas Observatory, with observations beginning in early 2017. Observations at both facilities are scheduled to continue through 2020. In keeping with previous SDSS policy, SDSS-IV provides regularly scheduled public data releases; the first one, Data Release 13, was made available in 2016 July

    Sloan Digital Sky Survey IV: mapping the Milky Way, nearby galaxies, and the distant universe

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    We describe the Sloan Digital Sky Survey IV (SDSS-IV), a project encompassing three major spectroscopic programs. The Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2) is observing hundreds of thousands of Milky Way stars at high resolution and high signal-to-noise ratios in the near-infrared. The Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey is obtaining spatially resolved spectroscopy for thousands of nearby galaxies (median ). The extended Baryon Oscillation Spectroscopic Survey (eBOSS) is mapping the galaxy, quasar, and neutral gas distributions between and 3.5 to constrain cosmology using baryon acoustic oscillations, redshift space distortions, and the shape of the power spectrum. Within eBOSS, we are conducting two major subprograms: the SPectroscopic IDentification of eROSITA Sources (SPIDERS), investigating X-ray AGNs and galaxies in X-ray clusters, and the Time Domain Spectroscopic Survey (TDSS), obtaining spectra of variable sources. All programs use the 2.5 m Sloan Foundation Telescope at the Apache Point Observatory; observations there began in Summer 2014. APOGEE-2 also operates a second near-infrared spectrograph at the 2.5 m du Pont Telescope at Las Campanas Observatory, with observations beginning in early 2017. Observations at both facilities are scheduled to continue through 2020. In keeping with previous SDSS policy, SDSS-IV provides regularly scheduled public data releases; the first one, Data Release 13, was made available in 2016 July

    Reconstruction of primary vertices at the ATLAS experiment in Run 1 proton–proton collisions at the LHC

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    This paper presents the method and performance of primary vertex reconstruction in proton–proton collision data recorded by the ATLAS experiment during Run 1 of the LHC. The studies presented focus on data taken during 2012 at a centre-of-mass energy of √s=8 TeV. The performance has been measured as a function of the number of interactions per bunch crossing over a wide range, from one to seventy. The measurement of the position and size of the luminous region and its use as a constraint to improve the primary vertex resolution are discussed. A longitudinal vertex position resolution of about 30μm is achieved for events with high multiplicity of reconstructed tracks. The transverse position resolution is better than 20μm and is dominated by the precision on the size of the luminous region. An analytical model is proposed to describe the primary vertex reconstruction efficiency as a function of the number of interactions per bunch crossing and of the longitudinal size of the luminous region. Agreement between the data and the predictions of this model is better than 3% up to seventy interactions per bunch crossing
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