ABSTRACT The rate of image acquisition in modern synoptic imaging surveys has already begun to outpace the feasibility of keeping astronomers in the real-time discovery and classification loop. Here ...we present the inner workings of a framework, based on machine-learning algorithms, that captures expert training and ground-truth knowledge about the variable and transient sky to automate (1) the process of discovery on image differences, and (2) the generation of preliminary science-type classifications of discovered sources. Since follow-up resources for extracting novel science from fast-changing transients are precious, self-calibrating classification probabilities must be couched in terms of efficiencies for discovery and purity of the samples generated. We estimate the purity and efficiency in identifying real sources with a two-epoch image-difference discovery algorithm for the Palomar Transient Factory (PTF) survey. Once given a source discovery, using machine-learned classification trained on PTF data, we distinguish between transients and variable stars with a 3.8% overall error rate (with 1.7% errors for imaging within the Sloan Digital Sky Survey footprint). At >96% classification efficiency, the samples achieve 90% purity. Initial classifications are shown to rely primarily on context-based features, determined from the data itself and external archival databases. In the first year of autonomous operations of PTF, this discovery and classification framework led to several significant science results, from outbursting young stars to subluminous Type IIP supernovae to candidate tidal disruption events. We discuss future directions of this approach, including the possible roles of crowdsourcing and the scalability of machine learning to future surveys such as the Large Synoptic Survey Telescope (LSST).
X-ray fluorescence spectra obtained by the MESSENGER spacecraft orbiting Mercury indicate that the planet's surface differs in composition from those of other terrestrial planets. Relatively high ...Mg/Si and low Al/Si and Ca/Si ratios rule out a lunarlike feldspar-rich crust. The sulfur abundance is at least 10 times higher than that of the silicate portion of Earth or the Moon, and this observation, together with a low surface Fe abundance, supports the view that Mercury formed from highly reduced precursor materials, perhaps akin to enstatite chondrite meteorites or anhydrous cometary dust particles. Low Fe and Ti abundances do not support the proposal that opaque oxides of these elements contribute substantially to Mercury's low and variable surface reflectance.
Magnetoelectric multiferroic materials have the potential to transform a range of applications, including tunable microelectronics and multiphase memories. However, the coexistence of ferromagnetism ...and ferroelectricity in single-phase materials is quite rare, driving the development of composite multiferroic materials. In these composites, the coupling arises from strain transfer across a shared interface between the ferroelectric and ferromagnetic phase. This viewpoint article highlights recent work as well as future challenges in the synthesis and characterization of nanostructured multiferroic materials.
We present near- and mid-infrared photometry and spectroscopy from PAIRITEL, IRTF, and Spitzer of a metallicity-unbiased sample of 117 cool, hydrogen-atmosphere white dwarfs (WDs) from the ...Palomar-Green survey and find five with excess radiation in the infrared, translating to a 4.3 super(+2.7) sub(-1.2)% frequency of debris disks. This is slightly higher than, but consistent with the results of previous surveys. Using an initial-final mass relation, we apply this result to the progenitor stars of our sample and conclude that 1-7 M sub(middot in circle) stars have at least a 4.3% chance of hosting planets; an indirect probe of the intermediate-mass regime eluding conventional exoplanetary detection methods. Alternatively, we interpret this result as a limit on accretion timescales as a fraction of WD cooling ages; WDs accrete debris from several generations of disks for ~10 Myr. The average total mass accreted by these stars ranges from that of 200 km asteroids to Ceres-sized objects, indicating that WDs accrete moons and dwarf planets as well as solar system asteroid analogs.
We present the analysis of 205 spatially resolved measurements of the surface composition of Mercury from MESSENGER's X‐Ray Spectrometer. The surface footprints of these measurements are categorized ...according to geological terrain. Northern smooth plains deposits and the plains interior to the Caloris basin differ compositionally from older terrain on Mercury. The older terrain generally has higher Mg/Si, S/Si, and Ca/Si ratios, and a lower Al/Si ratio than the smooth plains. Mercury's surface mineralogy is likely dominated by high‐Mg mafic minerals (e.g., enstatite), plagioclase feldspar, and lesser amounts of Ca, Mg, and/or Fe sulfides (e.g., oldhamite). The compositional difference between the volcanic smooth plains and the older terrain reflects different abundances of these minerals and points to the crystallization of the smooth plains from a more chemically evolved magma source. High‐degree partial melts of enstatite chondrite material provide a generally good compositional and mineralogical match for much of the surface of Mercury. An exception is Fe, for which the low surface abundance on Mercury is still higher than that of melts from enstatite chondrites and may indicate an exogenous contribution from meteoroid impacts.
Key Points
Analysis of spatially resolved X‐ray spectrometry data from MESSENGER
Volcanic smooth plains units differ compositionally from older terrains
Mercury's surface consists of high‐Mg mafic minerals, plagioclase, and sulfides
Long-duration gamma-ray bursts (GRBs) are widely believed to be highly collimated explosions (bipolar conical outflows with half-opening angle theta{approx} 1{sup 0}-10{sup 0}). As a result of this ...beaming factor, the true energy release from a GRB is usually several orders of magnitude smaller than the observed isotropic value. Measuring this opening angle, typically inferred from an achromatic steepening in the afterglow light curve (a 'jet' break), has proven exceedingly difficult in the Swift era. Here, we undertake a study of five of the brightest (in terms of the isotropic prompt gamma-ray energy release, E{sub g}amma{sub ,iso}) GRBs in the Swift era to search for jet breaks and hence constrain the collimation-corrected energy release. We present multi-wavelength (radio through X-ray) observations of GRBs 050820A, 060418, and 080319B, and construct afterglow models to extract the opening angle and beaming-corrected energy release for all three events. Together with results from previous analyses of GRBs 050904 and 070125, we find evidence for an achromatic jet break in all five events, strongly supporting the canonical picture of GRBs as collimated explosions. The most natural explanation for the lack of observed jet breaks from most Swift GRBs is therefore selection effects. However, the opening angles for the events in our sample are larger than would be expected if all GRBs had a canonical energy release of {approx}10{sup 51} erg. The total energy release we measure for the 'hyper-energetic' (E{sub tot} {approx}> 10{sup 52} erg) events in our sample is large enough to start challenging models with a magnetar as the compact central remnant.
The MESSENGER Gamma-Ray Spectrometer measured the average surface abundances of the radioactive elements potassium (K, 1150 ± 220 parts per million), thorium (Th, 220 ± 60 parts per billion), and ...uranium (U, 90 ± 20 parts per billion) in Mercury's northern hemisphere. The abundance of the moderately volatile element K, relative to Th and U, is inconsistent with physical models for the formation of Mercury requiring extreme heating of the planet or its precursor materials, and supports formation from volatile-containing material comparable to chondritic meteorites. Abundances of K, Th, and U indicate that internal heat production has declined substantially since Mercury's formation, consistent with widespread volcanism shortly after the end of late heavy bombardment 3.8 billion years ago and limited, isolated volcanic activity since.
Although hematopoietic stem cell transplantation (HCT) is the only curative treatment for acute myeloid leukemia (AML), it is associated with significant treatment related morbidity and mortality. ...There is great need for predictive biomarkers associated with overall survival (OS) and clinical outcomes. We hypothesized that circulating metabolic, inflammatory, and immune molecules have potential as predictive biomarkers for AML patients who receive HCT treatment. This retrospective study was designed with an exploratory approach to comprehensively characterize immune, inflammatory, and metabolomic biomarkers. We identified patients with AML who underwent HCT and had existing baseline plasma samples. Using those samples (n = 34), we studied 65 blood based metabolomic and 61 immune/inflammatory related biomarkers, comparing patients with either long-term OS (≥ 3 years) or short-term OS (OS ≤ 1 years). We also compared the immune/inflammatory response and metabolomic biomarkers in younger vs. older AML patients (≤30 years vs. ≥ 55 years old). In addition, the biomarker profiles were analyzed for their association with clinical outcomes, namely OS, chronic graft versus host disease (cGVHD), acute graft versus host disease (aGVHD), infection and relapse. Several baseline biomarkers were elevated in older versus younger patients, and baseline levels were lower for three markers (IL13, SAA, CRP) in patients with OS ≥ 3 years. We also identified immune/inflammatory response markers associated with aGVHD (IL-9, Eotaxin-3), cGVHD (Flt-1), infection (D-dimer), or relapse (IL-17D, bFGF, Eotaxin-3). Evaluation of metabolic markers demonstrated higher baseline levels of medium- and long-chain acylcarnitines (AC) in older patients, association with aGVHD (lactate, long-chain AC), and cGVHD (medium-chain AC). These differentially expressed profiles merit further evaluation as predictive biomarkers.
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