In-flight total forces, moments and static aeroelastic characteristics of an oblique-wing research airplane

A low-speed flight investigation has provided total force and moment coefficients and aeroelastic effects for the AD-1 oblique-wing research airplane. The results were interpreted and compared with predictions that were based on wind tunnel data. An assessment has been made of the aeroelastic wing bending design criteria. Lateral-directional trim requirements caused by asymmetry were determined. At angles of attack near stall, flow visualization indicated viscous flow separation and spanwise vortex flow. These effects were also apparent in the force and moment data

Flight characteristics of the AD-1 oblique-wing research aircraft

The AD-1 is a low-speed oblique-wing research airplane. This report reviews the vehicle's basic flight characteristics, including many aerodynamic, stability, and control effects that are unique to an oblique-wing configuration. These effects include the change in sideforce with angle of attack, moment changes with angle of attack and load factor, initial stall on the trailing wing, and inertial coupling caused by a roll-pitch cross product of inertia. An assessment of the handling qualities includes pilot ratings and comments. Ratings were generally satisfactory through 30 deg of wing sweep but degraded with increased sweep. A piloted simulation study indicated that a basic rate feedback control system could be used to improve the handling qualities at higher wing sweeps

Flight-determined aerodynamic derivatives of the AD-1 oblique-wing research airplane

The AD-1 is a variable-sweep oblique-wing research airplane that exhibits unconventional stability and control characteristics. In this report, flight-determined and predicted stability and control derivatives for the AD-1 airplane are compared. The predictions are based on both wind tunnel and computational results. A final best estimate of derivatives is presented

Spectral sequences of Type Ia supernovae. I. Connecting normal and sub-luminous SN Ia and the presence of unburned carbon

Type Ia supernovae are generally agreed to arise from thermonuclear explosions of carbon-oxygen white dwarfs. The actual path to explosion, however, remains elusive, with numerous plausible parent systems and explosion mechanisms suggested. Observationally, type Ia supernovae have multiple subclasses, distinguished by their lightcurves and spectra. This raises the question whether these reflect that multiple mechanisms occur in nature, or instead that explosions have a large but continuous range of physical properties. We revisit the idea that normal and 91bg-like supernovae can be understood as part of a spectral sequence, in which changes in temperature dominate. Specifically, we find that a single ejecta structure is sufficient to provide reasonable fits of both the normal type Ia supernova SN~2011fe and the 91bg-like SN~2005bl, provided that the luminosity and thus temperature of the ejecta are adjusted appropriately. This suggests that the outer layers of the ejecta are similar, thus providing some support of a common explosion mechanism. Our spectral sequence also helps to shed light on the conditions under which carbon can be detected in pre-maximum SN~Ia spectra -- we find that emission from iron can "fill in" the carbon trough in cool SN~Ia. This may indicate that the outer layers of the ejecta of events in which carbon is detected are relatively metal poor compared to events where carbon is not detected

Multiparticle Interference, GHZ Entanglement, and Full Counting Statistics

We investigate the quantum transport in a generalized N-particle Hanbury Brown--Twiss setup enclosing magnetic flux, and demonstrate that the Nth-order cumulant of current cross correlations exhibits Aharonov-Bohm oscillations, while there is no such oscillation in all the lower-order cumulants. The multiparticle interference results from the orbital Greenberger-Horne-Zeilinger entanglement of N indistinguishable particles. For sufficiently strong Aharonov-Bohm oscillations the generalized Bell inequalities may be violated, proving the N-particle quantum nonlocality.Comment: 4 pages, 1 figure, published versio

Spectral modeling of type II supernovae. I. Dilution factors

We present substantial extensions to the Monte Carlo radiative transfer code TARDIS to perform spectral synthesis for type II supernovae. By incorporating a non-LTE ionization and excitation treatment for hydrogen, a full account of free-free and bound-free processes, a self-consistent determination of the thermal state and by improving the handling of relativistic effects, the improved code version includes the necessary physics to perform spectral synthesis for type II supernovae to high precision as required for the reliable inference of supernova properties. We demonstrate the capabilities of the extended version of TARDIS by calculating synthetic spectra for the prototypical type II supernova SN1999em and by deriving a new and independent set of dilution factors for the expanding photosphere method. We have investigated in detail the dependence of the dilution factors on photospheric properties and, for the first time, on changes in metallicity. We also compare our results with two previously published sets of dilution factors by Eastman et al. (1996) and by Dessart & Hillier (2005), and discuss the potential sources of the discrepancies between studies.Comment: 16 pages, 12 figures, 2 tables, accepted for publication in A&

Predicting recessions using trends in the yield spread

The yield spread, measured as the difference between long- and short-term interest rates, is widely regarded as one of the strongest predictors of economic recessions. In this paper, we propose an enhanced recession prediction model that incorporates trends in the value of the yield spread. We expect our model to generate stronger recession signals because a steadily declining value of the yield spread typically indicates growing pessimism associated with the reduced future business activity. We capture trends in the yield spread by considering both the level of the yield spread at a lag of 12 months as well as its value at each of the previous two quarters leading up to the forecast origin, and we evaluate its predictive abilities using both logit and artificial neural network models. Our results indicate that models incorporating information from the time series of the yield spread correctly predict future recession periods much better than models only considering the spread value as of the forecast origin. Furthermore, the results are strongest for our artificial neural network model and logistic regression model that includes interaction terms, which we confirm using both a blocked cross-validation technique as well as an expanding estimation window approach