Towards Efficient Detection of Small Near-Earth Asteroids Using the Zwicky Transient Facility (ZTF)

We describe ZStreak, a semi-real-time pipeline specialized in detecting small, fast-moving near-Earth asteroids (NEAs) that is currently operating on the data from the newly-commissioned Zwicky Transient Facility (ZTF) survey. Based on a prototype originally developed by Waszczak et al. (2017) for the Palomar Transient Factory (PTF), the predecessor of ZTF, ZStreak features an improved machine-learning model that can cope with the $10\times$ data rate increment between PTF and ZTF. Since its first discovery on 2018 February 5 (2018 CL), ZTF/ZStreak has discovered $45$ confirmed new NEAs over a total of 232 observable nights until 2018 December 31. Most of the discoveries are small NEAs, with diameters less than $\sim100$ m. By analyzing the discovery circumstances, we find that objects having the first to last detection time interval under 2 hr are at risk of being lost. We will further improve real-time follow-up capabilities, and work on suppressing false positives using deep learning.Comment: PASP in pres

A Twilight Search for Atiras, Vatiras, and Co-orbital Asteroids: Preliminary Results

Near-Earth objects (NEOs) that orbit the Sun on or within Earth's orbit are tricky to detect for Earth-based observers due to their proximity to the Sun in the sky. These small bodies hold clues to the dynamical history of the inner solar system as well as the physical evolution of planetesimals in extreme environments. Populations in this region include the Atira and Vatira asteroids, as well as Venus and Earth co-orbital asteroids. Here we present a twilight search for these small bodies, conducted using the 1.2 m Oschin Schmidt and the Zwicky Transient Facility (ZTF) camera at Palomar Observatory. The ZTF twilight survey operates at solar elongations down to 35° with a limiting magnitude of r = 19.5. During a total of 40 evening sessions and 62 morning sessions conducted between 2018 November 15 and 2019 June 23, we detected six Atiras, including two new discoveries, 2019 AQ₃ and 2019 LF₆, but no Vatiras or Earth/Venus co-orbital asteroids. NEO population models show that these new discoveries are likely only the tip of the iceberg, with the bulk of the population yet to be found. The population models also suggest that we have only detected 5%–7% of the H < 20 Atira population over the seven month survey. Co-orbital asteroids are smaller in diameter and require deeper surveys. A systematic and efficient survey of the near-Sun region will require deeper searches and/or facilities that can operate at small solar elongations

MLPerf Inference Benchmark

Machine-learning (ML) hardware and software system demand is burgeoning. Driven by ML applications, the number of different ML inference systems has exploded. Over 100 organizations are building ML inference chips, and the systems that incorporate existing models span at least three orders of magnitude in power consumption and five orders of magnitude in performance; they range from embedded devices to data-center solutions. Fueling the hardware are a dozen or more software frameworks and libraries. The myriad combinations of ML hardware and ML software make assessing ML-system performance in an architecture-neutral, representative, and reproducible manner challenging. There is a clear need for industry-wide standard ML benchmarking and evaluation criteria. MLPerf Inference answers that call. In this paper, we present our benchmarking method for evaluating ML inference systems. Driven by more than 30 organizations as well as more than 200 ML engineers and practitioners, MLPerf prescribes a set of rules and best practices to ensure comparability across systems with wildly differing architectures. The first call for submissions garnered more than 600 reproducible inference-performance measurements from 14 organizations, representing over 30 systems that showcase a wide range of capabilities. The submissions attest to the benchmark's flexibility and adaptability.Comment: ISCA 202

A Systematic Search of Zwicky Transient Facility Data for Ultracompact Binary LISA-detectable Gravitational-wave Sources

Using photometry collected with the Zwicky Transient Facility, we are conducting an ongoing survey for binary systems with short orbital periods (P_b < 1 hr) with the goal of identifying new gravitational-wave sources detectable by the upcoming Laser Interferometer Space Antenna (LISA). We present a sample of 15 binary systems discovered thus far, with orbital periods ranging from 6.91 to 56.35 minutes. Of the 15 systems, seven are eclipsing systems that do not show signs of significant mass transfer. Additionally, we have discovered two AM Canum Venaticorum systems and six systems exhibiting primarily ellipsoidal variations in their lightcurves. We present follow-up spectroscopy and high-speed photometry confirming the nature of these systems, estimates of their LISA signal-to-noise ratios, and a discussion of their physical characteristics

Erratum: Sequence data and association statistics from 12,940 type 2 diabetes cases and controls.

This corrects the article DOI: 10.1038/sdata.2017.179

Large-scale genome-wide association studies and meta-analyses of longitudinal change in adult lung function.

BACKGROUND: Genome-wide association studies (GWAS) have identified numerous loci influencing cross-sectional lung function, but less is known about genes influencing longitudinal change in lung function. METHODS: We performed GWAS of the rate of change in forced expiratory volume in the first second (FEV1) in 14 longitudinal, population-based cohort studies comprising 27,249 adults of European ancestry using linear mixed effects model and combined cohort-specific results using fixed effect meta-analysis to identify novel genetic loci associated with longitudinal change in lung function. Gene expression analyses were subsequently performed for identified genetic loci. As a secondary aim, we estimated the mean rate of decline in FEV1 by smoking pattern, irrespective of genotypes, across these 14 studies using meta-analysis. RESULTS: The overall meta-analysis produced suggestive evidence for association at the novel IL16/STARD5/TMC3 locus on chromosome 15 (P  =  5.71 × 10(-7)). In addition, meta-analysis using the five cohorts with ≥3 FEV1 measurements per participant identified the novel ME3 locus on chromosome 11 (P  =  2.18 × 10(-8)) at genome-wide significance. Neither locus was associated with FEV1 decline in two additional cohort studies. We confirmed gene expression of IL16, STARD5, and ME3 in multiple lung tissues. Publicly available microarray data confirmed differential expression of all three genes in lung samples from COPD patients compared with controls. Irrespective of genotypes, the combined estimate for FEV1 decline was 26.9, 29.2 and 35.7 mL/year in never, former, and persistent smokers, respectively. CONCLUSIONS: In this large-scale GWAS, we identified two novel genetic loci in association with the rate of change in FEV1 that harbor candidate genes with biologically plausible functional links to lung function