Ode to being In-Between

A poem about melancholy, loneliness, airports, and travelling

Evaluation of Front Detection Methods for Satellite-Derived SST Data Using In Situ Observations

Sea surface temperature (SST) fronts detected in Advanced Very High Resolution Radiometer (AVHRR) data using automated edge-detection algorithms were compared to fronts found in continuous measurements of SST made aboard a ship of opportunity. Two histograms (a single-image and a multi-image method) and one gradient algorithm were tested for the occurrence of two types of errors: (a) the detection of false fronts and (b) the failure to detect fronts observed in the in situ data. False front error rates were lower for the histogram methods (27%–28%) than for the gradient method (45%). Considering only AVHRR fronts for which the SST gradient along the ship track was greater than 0.1°C km−1, error rates drop to 14% for the histogram methods and 29% for the gradient method. Missed front error rates were lower using the gradient method (16%) than the histogram methods (30%). This error rate drops significantly for the histogram methods (5%–10%) if fronts associated with small-scale SST features (km) are omitted from the comparison. These results suggest that frontal climatologies developed from the application of automated edge-detection methods to long time series of AVHRR images provide acceptably accurate statistics on front occurrence

Private Multiplicative Weights Beyond Linear Queries

A wide variety of fundamental data analyses in machine learning, such as linear and logistic regression, require minimizing a convex function defined by the data. Since the data may contain sensitive information about individuals, and these analyses can leak that sensitive information, it is important to be able to solve convex minimization in a privacy-preserving way. A series of recent results show how to accurately solve a single convex minimization problem in a differentially private manner. However, the same data is often analyzed repeatedly, and little is known about solving multiple convex minimization problems with differential privacy. For simpler data analyses, such as linear queries, there are remarkable differentially private algorithms such as the private multiplicative weights mechanism (Hardt and Rothblum, FOCS 2010) that accurately answer exponentially many distinct queries. In this work, we extend these results to the case of convex minimization and show how to give accurate and differentially private solutions to *exponentially many* convex minimization problems on a sensitive dataset

Characterizing mid-type M dwarfs in the Kepler field with the Discovery Channel Telescope and WIYN

Planet occurrence rates increase with decreasing stellar mass (later spectral types); therefore, M dwarf systems are our most promising targets in the search for exoplanets. The identification and characterization of stars in the original Kepler field was accomplished using photometry alone, resulting in large uncertainties for late-type stars like M dwarfs. In order to more accurately compute the planet occurrence rate around mid- type M dwarfs, we need to better constrain their stellar radii and masses, properties which strongly correlate with other stellar parameters such as temperature and metallicity. These measurements need to be performed on a statistically significant population of stars including systems with and without planets. Therefore, we have begun to spectroscopically characterize the properties of the 559 probable mid-type M dwarfs in the Kepler field using red optical spectra obtained with the DeVeny Spectrograph on the Discovery Channel Telescope (DCT) and Hydra on the WIYN telescope in order to constrain the planet occurrence rate for such stars. We will be presenting initial results from our DCT and WIYN observations, including new temperature, radius, and mass estimates which we can use in occurrence rate calculations.http://adsabs.harvard.edu/abs/2017AAS...22912608HPublished versio

Characterization of mid-type M dwarfs in the Kepler field

The planet occurrence rate has been found to increase with decreasing stellar mass (later spectral types) in the original Kepler field, and one out of four M dwarfs are expected to host Earth-sized planets within their habitable zones. M dwarf systems are, therefore, our most promising targets in the search for exoplanets. Yet the identification and characterization of M dwarfs in the Kepler field was accomplished using photometry alone and unfortunately this method provides large uncertainties for late-type stars. Notably absent from planet occurrence calculations are single planet mid-type M dwarfs (~M2-M6). In order to make an accurate calculation of the planet occurrence rate around mid-type M dwarfs, we need to constrain stellar radii and masses which depend on other stellar parameters (e.g. temperature and metallicity). We have identified 559 probable mid-type M dwarfs using photometric color selection criteria and have started to gather spectra of these objects in order to better constrain stellar properties and refine planet occurrence rates for this population. Here we outline the methods we are using for stellar classification and characterization and present some results from our initial data.http://adsabs.harvard.edu/abs/2016AAS...22743012HPublished versio

Laboratory Determination of the Infrared Band Strengths of Pyrene Frozen in Water Ice: Implications for the Composition of Interstellar Ices

Broad infrared emission features (e.g., at 3.3, 6.2, 7.7, 8.6, and 11.3 microns) from the gas phase interstellar medium have long been attributed to polycyclic aromatic hydrocarbons (PAHs). A significant portion (10%-20%) of the Milky Way's carbon reservoir is locked in PAH molecules, which makes their characterization integral to our understanding of astrochemistry. In molecular clouds and the dense envelopes and disks of young stellar objects (YSOs), PAHs are expected to be frozen in the icy mantles of dust grains where they should reveal themselves through infrared absorption. To facilitate the search for frozen interstellar PAHs, laboratory experiments were conducted to determine the positions and strengths of the bands of pyrene mixed with H2O and D2O ices. The D2O mixtures are used to measure pyrene bands that are masked by the strong bands of H2O, leading to the first laboratory determination of the band strength for the CH stretching mode of pyrene in water ice near 3.25 microns. Our infrared band strengths were normalized to experimentally determined ultraviolet band strengths, and we find that they are generally ~50% larger than those reported by Bouwman et al. based on theoretical strengths. These improved band strengths were used to reexamine YSO spectra published by Boogert et al. to estimate the contribution of frozen PAHs to absorption in the 5-8 micron spectral region, taking into account the strength of the 3.25 micron CH stretching mode. It is found that frozen neutral PAHs contain 5%-9% of the cosmic carbon budget, and account for 2%-9% of the unidentified absorption in the 5-8 micron region.Comment: Accepted for publication in ApJ on 14 Feb 201

Network-wide Configuration Synthesis

Computer networks are hard to manage. Given a set of high-level requirements (e.g., reachability, security), operators have to manually figure out the individual configuration of potentially hundreds of devices running complex distributed protocols so that they, collectively, compute a compatible forwarding state. Not surprisingly, operators often make mistakes which lead to downtimes. To address this problem, we present a novel synthesis approach that automatically computes correct network configurations that comply with the operator's requirements. We capture the behavior of existing routers along with the distributed protocols they run in stratified Datalog. Our key insight is to reduce the problem of finding correct input configurations to the task of synthesizing inputs for a stratified Datalog program. To solve this synthesis task, we introduce a new algorithm that synthesizes inputs for stratified Datalog programs. This algorithm is applicable beyond the domain of networks. We leverage our synthesis algorithm to construct the first network-wide configuration synthesis system, called SyNET, that support multiple interacting routing protocols (OSPF and BGP) and static routes. We show that our system is practical and can infer correct input configurations, in a reasonable amount time, for networks of realistic size (> 50 routers) that forward packets for multiple traffic classes.Comment: 24 Pages, short version published in CAV 201

Organic Agriculture Teaching and Learning in 2025: Transforming the Future Learning Landscape

University instructors are compelled to anticipate future changes in farming and food systems that will impact their students. Sixteen educators met in 2018 to envision the future of organic agriculture courses needed by 2025. Likely future global issues include food access, especially for people of limited economic means; climate change; and fossil fuel costs. Changes that will impact education are increasing demand for quality food, more organic production, and globalization of food systems due to consolidation. Probable course content changes are increasing focus on whole farm systems; designing for resilience in changing physical, economic, environmental, and political climates; and increasing diversity of systems and emergence of the urban and peri-urban food sector. Expected changes in teaching methods include more practical, hands-on learning; face-to-face interactions with farmers; guided practical apprenticeships; and student-driven learning activities. We were surprised by the difficulty that workshop participants confronted in discussing transformational change, often opting for fine-tuning the current system. We identified a need for developing and practicing skills for future visioning, currently a challenge for instructors and for many students