CfAIR2: Near Infrared Light Curves of 94 Type Ia Supernovae

CfAIR2 is a large homogeneously reduced set of near-infrared (NIR) light curves for Type Ia supernovae (SN Ia) obtained with the 1.3m Peters Automated InfraRed Imaging TELescope (PAIRITEL). This data set includes 4607 measurements of 94 SN Ia and 4 additional SN Iax observed from 2005-2011 at the Fred Lawrence Whipple Observatory on Mount Hopkins, Arizona. CfAIR2 includes JHKs photometric measurements for 88 normal and 6 spectroscopically peculiar SN Ia in the nearby universe, with a median redshift of z~0.021 for the normal SN Ia. CfAIR2 data span the range from -13 days to +127 days from B-band maximum. More than half of the light curves begin before the time of maximum and the coverage typically contains ~13-18 epochs of observation, depending on the filter. We present extensive tests that verify the fidelity of the CfAIR2 data pipeline, including comparison to the excellent data of the Carnegie Supernova Project. CfAIR2 contributes to a firm local anchor for supernova cosmology studies in the NIR. Because SN Ia are more nearly standard candles in the NIR and are less vulnerable to the vexing problems of extinction by dust, CfAIR2 will help the supernova cosmology community develop more precise and accurate extragalactic distance probes to improve our knowledge of cosmological parameters, including dark energy and its potential time variation.Comment: 31 pages, 15 figures, 10 tables. Accepted to ApJS. v2 modified to more closely match journal versio

Why is it hard to beat O(n2)O(n^2) for Longest Common Weakly Increasing Subsequence?

The Longest Common Weakly Increasing Subsequence problem (LCWIS) is a variant of the classic Longest Common Subsequence problem (LCS). Both problems can be solved with simple quadratic time algorithms. A recent line of research led to a number of matching conditional lower bounds for LCS and other related problems. However, the status of LCWIS remained open. In this paper we show that LCWIS cannot be solved in strongly subquadratic time unless the Strong Exponential Time Hypothesis (SETH) is false. The ideas which we developed can also be used to obtain a lower bound based on a safer assumption of NC-SETH, i.e. a version of SETH which talks about NC circuits instead of less expressive CNF formulas

Type Ia supernova Hubble diagram with near-infrared and optical observations

We main goal of this paper is to test whether the NIR peak magnitudes of SNe Ia could be accurately estimated with only a single observation obtained close to maximum light, provided the time of B band maximum and the optical stretch parameter are known. We obtained multi-epoch UBVRI and single-epoch J and H photometric observations of 16 SNe Ia in the redshift range z=0.037-0.183, doubling the leverage of the current SN Ia NIR Hubble diagram and the number of SNe beyond redshift 0.04. This sample was analyzed together with 102 NIR and 458 optical light curves (LCs) of normal SNe Ia from the literature. The analysis of 45 well-sampled NIR LCs shows that a single template accurately describes them if its time axis is stretched with the optical stretch parameter. This allows us to estimate the NIR peak magnitudes even with one observation obtained within 10 days from B-band maximum. We find that the NIR Hubble residuals show weak correlation with DM_15 and E(B-V), and for the first time we report a possible dependence on the J_max-H_max color. The intrinsic NIR luminosity scatter of SNe Ia is estimated to be around 0.10 mag, which is smaller than what can be derived for a similarly heterogeneous sample at optical wavelengths. In conclusion, we find that SNe Ia are at least as good standard candles in the NIR as in the optical. We showed that it is feasible to extended the NIR SN Ia Hubble diagram to z=0.2 with very modest sampling of the NIR LCs, if complemented by well-sampled optical LCs. Our results suggest that the most efficient way to extend the NIR Hubble diagram to high redshift would be to obtain a single observation close to the NIR maximum. (abridged)Comment: 39 pages, 15 figures, accepted by A&

Lagrangian Data-Driven Reduced Order Modeling of Finite Time Lyapunov Exponents

There are two main strategies for improving the projection-based reduced order model (ROM) accuracy: (i) improving the ROM, i.e., adding new terms to the standard ROM; and (ii) improving the ROM basis, i.e., constructing ROM bases that yield more accurate ROMs. In this paper, we use the latter. We propose new Lagrangian inner products that we use together with Eulerian and Lagrangian data to construct new Lagrangian ROMs. We show that the new Lagrangian ROMs are orders of magnitude more accurate than the standard Eulerian ROMs, i.e., ROMs that use standard Eulerian inner product and data to construct the ROM basis. Specifically, for the quasi-geostrophic equations, we show that the new Lagrangian ROMs are more accurate than the standard Eulerian ROMs in approximating not only Lagrangian fields (e.g., the finite time Lyapunov exponent (FTLE)), but also Eulerian fields (e.g., the streamfunction). We emphasize that the new Lagrangian ROMs do not employ any closure modeling to model the effect of discarded modes (which is standard procedure for low-dimensional ROMs of complex nonlinear systems). Thus, the dramatic increase in the new Lagrangian ROMs' accuracy is entirely due to the novel Lagrangian inner products used to build the Lagrangian ROM basis

Sketching, Streaming, and Fine-Grained Complexity of (Weighted) LCS

We study sketching and streaming algorithms for the Longest Common Subsequence problem (LCS) on strings of small alphabet size |Sigma|. For the problem of deciding whether the LCS of strings x,y has length at least L, we obtain a sketch size and streaming space usage of O(L^{|Sigma| - 1} log L). We also prove matching unconditional lower bounds. As an application, we study a variant of LCS where each alphabet symbol is equipped with a weight that is given as input, and the task is to compute a common subsequence of maximum total weight. Using our sketching algorithm, we obtain an O(min{nm, n + m^{|Sigma|}})-time algorithm for this problem, on strings x,y of length n,m, with n >= m. We prove optimality of this running time up to lower order factors, assuming the Strong Exponential Time Hypothesis