High Resolution Transmission Spectroscopy as a Diagnostic for Jovian Exoplanet Atmospheres: Constraints from Theoretical Models

We present high resolution transmission spectra of giant planet atmospheres from a coupled 3-D atmospheric dynamics and transmission spectrum model that includes Doppler shifts which arise from winds and planetary motion. We model jovian planets covering more than two orders of magnitude in incident flux, corresponding to planets with 0.9 to 55 day orbital periods around solar-type stars. The results of our 3-D dynamical models reveal certain aspects of high resolution transmission spectra that are not present in simple 1-D models. We find that the hottest planets experience strong substellar to anti-stellar (SSAS) winds, resulting in transmission spectra with net blue shifts of up to 3 km s$^{-1}$, whereas less irradiated planets show almost no net Doppler shifts. Compared to 1-D models, peak line strengths are significantly reduced for the hottest atmospheres owing to Doppler broadening from a combination of rotation (which is faster for close-in planets under the assumption of tidal locking) and atmospheric winds. Finally, high resolution transmission spectra may be useful in studying the atmospheres of exoplanets with optically thick clouds since line cores for very strong transitions should remain optically thick to very high altitude. High resolution transmission spectra are an excellent observational test for the validity of 3-D atmospheric dynamics models, because they provide a direct probe of wind structures and heat circulation. Ground-based exoplanet spectroscopy is currently on the verge of being able to verify some of our modeling predictions, most notably the dependence of SSAS winds on insolation. We caution that interpretation of high resolution transmission spectra based on 1-D atmospheric models may be inadequate, as 3-D atmospheric motions can produce a noticeable effect on the absorption signatures.Comment: Accepted to ApJ; 34 pages, 6 figures, 1 tabl

An Observational Diagnostic for Distinguishing Between Clouds and Haze in Hot Exoplanet Atmospheres

The nature of aerosols in hot exoplanet atmospheres is one of the primary vexing questions facing the exoplanet field. The complex chemistry, multiple formation pathways, and lack of easily identifiable spectral features associated with aerosols make it especially challenging to constrain their key properties. We propose a transmission spectroscopy technique to identify the primary aerosol formation mechanism for the most highly irradiated hot Jupiters (HIHJs). The technique is based on the expectation that the two key types of aerosols -- photochemically generated hazes and equilibrium condensate clouds -- are expected to form and persist in different regions of a highly irradiated planet's atmosphere. Haze can only be produced on the permanent daysides of tidally-locked hot Jupiters, and will be carried downwind by atmospheric dynamics to the evening terminator (seen as the trailing limb during transit). Clouds can only form in cooler regions on the night side and morning terminator of HIHJs (seen as the leading limb during transit). Because opposite limbs are expected to be impacted by different types of aerosols, ingress and egress spectra, which primarily probe opposing sides of the planet, will reveal the dominant aerosol formation mechanism. We show that the benchmark HIHJ, WASP-121b, has a transmission spectrum consistent with partial aerosol coverage and that ingress-egress spectroscopy would constrain the location and formation mechanism of those aerosols. In general, using this diagnostic we find that observations with JWST and potentially with HST should be able to distinguish between clouds and haze for currently known HIHJs.Comment: 10 pages, 4 figures, accepted to ApJ Letter

Online open neuroimaging mass meta-analysis

We describe a system for meta-analysis where a wiki stores numerical data in a simple format and a web service performs the numerical computation. We initially apply the system on multiple meta-analyses of structural neuroimaging data results. The described system allows for mass meta-analysis, e.g., meta-analysis across multiple brain regions and multiple mental disorders.Comment: 5 pages, 4 figures SePublica 2012, ESWC 2012 Workshop, 28 May 2012, Heraklion, Greec

"Willingness to Pay for Electric Vehicles and their Attributes"

This article presents a stated preference study of electric vehicle choice using data from a national survey. We used a choice experiment wherein 3029 respondents were asked to choose between their preferred gasoline vehicle and two electric versions of that preferred vehicle. We estimated a latent class random utility model and used the results to estimate the willingness to pay for five electric vehicle attributes: driving range, charging time, fuel cost saving, pollution reduction, and performance. Driving range, fuel cost savings, and charging time led in importance to respondents. Individuals were willing to pay (wtp) from $35 to$75 for a mile of added driving range, with incremental wtp per mile decreasing at higher distances. They were willing to pay from $425 to$3250 per hour reduction in charging time (for a 50 mile charge). Respondents capitalized about 5 years of fuel saving into the purchase price of an electric vehicle. We simulated our model over a range of electric vehicle configurations and found that people with the highest values for electric vehicles were willing to pay a premium above their wtp for a gasoline vehicle that ranged from $6000 to$16,000 for electric vehicles with the most desirable attributes. At the same time, our results suggest that battery cost must drop significantly before electric vehicles will find a mass market without subsidy.Electric Vehicles, Stated Preference, Discrete Choice

Kepler Transit Depths Contaminated by a Phantom Star

We present ground-based observations from the Discovery Channel Telescope (DCT) of three transits of Kepler-445c---a supposed super-Earth exoplanet with properties resembling GJ 1214b---and demonstrate that the transit depth is approximately 50 percent shallower than the depth previously inferred from Kepler Spacecraft data. The resulting decrease in planetary radius significantly alters the interpretation of the exoplanet's bulk composition. Despite the faintness of the M4 dwarf host star, our ground-based photometry clearly recovers each transit and achieves repeatable 1-sigma precision of approximately 0.2 percent (2 millimags). The transit parameters estimated from the DCT data are discrepant with those inferred from the Kepler data to at least 17-sigma confidence. This inconsistency is due to a subtle miscalculation of the stellar crowding metric during the Kepler pre-search data conditioning (PDC). The crowding metric, or CROWDSAP, is contaminated by a non-existent "phantom star" originating in the USNO-B1 catalog and inherited by the Kepler Input Catalog (KIC). Phantom stars in the KIC are likely rare, but they have the potential to affect statistical studies of Kepler targets that use the PDC transit depths for a large number of exoplanets where individual follow-up observation of each is not possible. The miscalculation of Kepler-445c's transit depth emphasizes the importance of stellar crowding in the Kepler data, and provides a cautionary tale for the analysis of data from the Transiting Exoplanet Survey Satellite (TESS), which will have even larger pixels than Kepler.Comment: 11 pages, 10 figures, 5 tables. Accepted for publication in AJ. Transit light curves will be available from AJ as Db

"Can Vehicle-to-Grid Revenue Help Electric Vehicles on the Market?"

Vehicle-to-grid (V2G) electric vehicles can return power stored in their batteries back to the power grid and be programmed to do so at times when power prices are high. Since providing this service can lead to payments to owners of vehicles, it effectively reduces the cost of electric vehicles. Using data from a national stated preference survey (n = 3029), this paper presents the first study of the potential consumer demand for V2G electric vehicles. In our choice experiment, 3029 respondents compared their preferred gasoline vehicle with two V2G electric vehicles. The V2G vehicles were described by a set of electric vehicle attributes and V2G contract requirements such as “required plug-in time” and “guaranteed minimum driving range”. The contract requirements specify a contract between drivers and a power aggregator for providing reserve power to the grid. Our findings suggest the V2G concept is mostly likely to help EVs on the market if power aggregators operate on pay-as-you-go-basis or provide consumers with advanced cash payment (upfront discounts on the price of EVs) in exchange for V2G restrictions.electric vehicles, vehicle-to-grid, stated preference, latent-class model

Has analytical flexibility increased in imaging studies of bipolar disorder and major depression?

There has been extensive discussion of problems of reproducibility of research. Analytical flexibility may contribute to this, by increasing the likelihood that a reported finding represents a chance result. We explored whether analytical flexibility has increased over time, using human imaging studies of bipolar disorder and major depression. Our results indicate that the number of measures collected per study has increased over time for studies of bipolar disorder, but not for studies of major depression.</jats:p