KELT-19Ab: A P ∼ 4.6-day Hot Jupiter Transiting a Likely Am Star with a Distant Stellar Companion

We present the discovery of the giant planet KELT-19Ab, which transits the moderately bright (V ∼ 9.9) A8V star TYC 764-1494-1 with an orbital period of 4.61 days. We confirm the planetary nature of the companion via a combination of radial velocities, which limit the mass to ≳4.1 MJ (3s), and a clear Doppler tomography signal, which indicates a retrograde projected spin-orbit misalignment of λ = -179.7-3.8+3.7 degrees. Global modeling indicates that the Teff = 7500 ±110 K host star has M M = 1.62+0.20-0.25 and R = 1.83 0.10 R. The planet has a radius of RP = 1.91 0.11 RJ and receives a stellar insolation flux of ∼ 3.2 10 erg s-1 cm-2, leading to an inferred equilibrium temperature of Teq ∼ 1935 K assuming zero albedo and complete heat redistribution. With a v I sin 84.8 ±2.0 km s = -1, the host is relatively slowly rotating compared to other stars with similar effective temperatures, and it appears to be enhanced in metallic elements but deficient in calcium, suggesting that it is likely an Am star. KELT-19A would be the first detection of an Am host of a transiting planet of which we are aware. Adaptive optics observations of the system reveal the existence of a companion with late-G9V/early-K1V spectral type at a projected separation of »160 au. Radial velocity measurements indicate that this companion is bound. Most Am stars are known to have stellar companions, which are often invoked to explain the relatively slow rotation of the primary. In this case, the stellar companion is unlikely to have caused the tidal braking of the primary. However, it may have emplaced the transiting planetary companion via the Kozai-Lidov mechanism

Artificial Intelligence Approach to the Determination of Physical Properties of Eclipsing Binaries. I. The EBAI Project

Achieving maximum scientific results from the overwhelming volume of astronomical data to be acquired over the next few decades will demand novel, fully automatic methods of data analysis. Artificial intelligence approaches hold great promise in contributing to this goal. Here we apply neural network learning technology to the specific domain of eclipsing binary (EB) stars, of which only some hundreds have been rigorously analyzed, but whose numbers will reach millions in a decade. Well-analyzed EBs are a prime source of astrophysical information whose growth rate is at present limited by the need for human interaction with each EB data-set, principally in determining a starting solution for subsequent rigorous analysis. We describe the artificial neural network (ANN) approach which is able to surmount this human bottleneck and permit EB-based astrophysical information to keep pace with future data rates. The ANN, following training on a sample of 33,235 model light curves, outputs a set of approximate model parameters (T2/T1, (R1+R2)/a, e sin(omega), e cos(omega), and sin i) for each input light curve data-set. The whole sample is processed in just a few seconds on a single 2GHz CPU. The obtained parameters can then be readily passed to sophisticated modeling engines. We also describe a novel method polyfit for pre-processing observational light curves before inputting their data to the ANN and present the results and analysis of testing the approach on synthetic data and on real data including fifty binaries from the Catalog and Atlas of Eclipsing Binaries (CALEB) database and 2580 light curves from OGLE survey data. [abridged]Comment: 52 pages, accepted to Ap

Application Of Digital Signal Analysis, Mass Data Acquisition and Processing Techniques, and Automated Experiment Protocols to the Study of Cardiac Cell Membrane Electrophysiology, with Mathematical Modeling

Traditional methods of collecting, analyzing and storing data from cardiac cell membrane electrophysiology experiments have become increasingly cumbersome and unwieldy as experimental protocols have become more sophisticated and complex. A global approach to collecting, analyzing, refining and storing electrophysiologic data, as well as a new approach to mathematical modeling of cell membrane single ion channel kinetics, was developed. This utilizes a comprehensive microcomputer based system of software with specialized analog and digital electronics for data acquisition, analysis and archiving. Unique discrete signal processing techniques for characterizing the electronic recording system, including specialized hardware and software adapted for minimizing distortions in biosignal recordings, are discussed in detail

KELT-19Ab: A P ~ 4.6-day Hot Jupiter Transiting a Likely Am Star with a Distant Stellar Companion

We present the discovery of the giant planet KELT-19Ab, which transits the moderately bright (V ~ 9.9) A8V star TYC 764-1494-1 with an orbital period of 4.61 days. We confirm the planetary nature of the companion via a combination of radial velocities, which limit the mass to ≾ 4.1 M_J (3σ), and a clear Doppler tomography signal, which indicates a retrograde projected spin–orbit misalignment of λ = -179.7^(+3.7)_(-3.8) degrees. Global modeling indicates that the T_(eff) = 7500 ± 110 K host star has M⋆ = 1.62^(+0.25)_(-0.20) M⊙ and R⋆ = 1.83 ± 0.10 R⊙. The planet has a radius of R_p = 1.91 ± 0.11 R_J and receives a stellar insolation flux of ~3.2 x 10^9 erg s^(-1) cm^(-2), leading to an inferred equilibrium temperature of T_(eq) ~ 1935 K assuming zero albedo and complete heat redistribution. With a ν sin I* = 84.8 ± 2.0 km s^(-1), the host is relatively slowly rotating compared to other stars with similar effective temperatures, and it appears to be enhanced in metallic elements but deficient in calcium, suggesting that it is likely an Am star. KELT-19A would be the first detection of an Am host of a transiting planet of which we are aware. Adaptive optics observations of the system reveal the existence of a companion with late-G9V/early-K1V spectral type at a projected separation of ≈160 au. Radial velocity measurements indicate that this companion is bound. Most Am stars are known to have stellar companions, which are often invoked to explain the relatively slow rotation of the primary. In this case, the stellar companion is unlikely to have caused the tidal braking of the primary. However, it may have emplaced the transiting planetary companion via the Kozai–Lidov mechanism

Sparse Nonlinear MIMO Filtering and Identification

In this chapter system identification algorithms for sparse nonlinear multi input multi output (MIMO) systems are developed. These algorithms are potentially useful in a variety of application areas including digital transmission systems incorporating power amplifier(s) along with multiple antennas, cognitive processing, adaptive control of nonlinear multivariable systems, and multivariable biological systems. Sparsity is a key constraint imposed on the model. The presence of sparsity is often dictated by physical considerations as in wireless fading channel-estimation. In other cases it appears as a pragmatic modelling approach that seeks to cope with the curse of dimensionality, particularly acute in nonlinear systems like Volterra type series. Three dentification approaches are discussed: conventional identification based on both input and output samples, semi–blind identification placing emphasis on minimal input resources and blind identification whereby only output samples are available plus a–priori information on input characteristics. Based on this taxonomy a variety of algorithms, existing and new, are studied and evaluated by simulation

Pan-STARRS Pixel Analysis: Source Detection and Characterization

Over 3 billion astronomical sources have been detected in the more than 22 million orthogonal transfer CCD images obtained as part of the Pan-STARRS1 3π survey. Over 85 billion instances of those sources have been automatically detected and characterized by the Pan-STARRS Image Processing Pipeline photometry software, psphot. This fast, automatic, and reliable software was developed for the Pan-STARRS project but is easily adaptable to images from other telescopes. We describe the analysis of the astronomical sources by psphot in general as well as for the specific case of the third processing version used for the first two public releases of the Pan-STARRS 3π Survey data

FPGA-based DOCSIS upstream demodulation

In recent years, the state-of-the-art in field programmable gate array (FPGA) technology has been advancing rapidly. Consequently, the use of FPGAs is being considered in many applications which have traditionally relied upon application-specific integrated circuits (ASICs). FPGA-based designs have a number of advantages over ASIC-based designs, including lower up-front engineering design costs, shorter time-to-market, and the ability to reconfigure devices in the field. However, ASICs have a major advantage in terms of computational resources. As a result, expensive high performance ASIC algorithms must be redesigned to fit the limited resources available in an FPGA. Concurrently, coaxial cable television and internet networks have been undergoing significant upgrades that have largely been driven by a sharp increase in the use of interactive applications. This has intensified demand for the so-called upstream channels, which allow customers to transmit data into the network. The format and protocol of the upstream channels are defined by a set of standards, known as DOCSIS 3.0, which govern the flow of data through the network. Critical to DOCSIS 3.0 compliance is the upstream demodulator, which is responsible for the physical layer reception from all customers. Although upstream demodulators have typically been implemented as ASICs, the design of an FPGA-based upstream demodulator is an intriguing possibility, as FPGA-based demodulators could potentially be upgraded in the field to support future DOCSIS standards. Furthermore, the lower non-recurring engineering costs associated with FPGA-based designs could provide an opportunity for smaller companies to compete in this market. The upstream demodulator must contain complicated synchronization circuitry to detect, measure, and correct for channel distortions. Unfortunately, many of the synchronization algorithms described in the open literature are not suitable for either upstream cable channels or FPGA implementation. In this thesis, computationally inexpensive and robust synchronization algorithms are explored. In particular, algorithms for frequency recovery and equalization are developed. The many data-aided feedforward frequency offset estimators analyzed in the literature have not considered intersymbol interference (ISI) caused by micro-reflections in the channel. It is shown in this thesis that many prominent frequency offset estimation algorithms become biased in the presence of ISI. A novel high-performance frequency offset estimator which is suitable for implementation in an FPGA is derived from first principles. Additionally, a rule is developed for predicting whether a frequency offset estimator will become biased in the presence of ISI. This rule is used to establish a channel excitation sequence which ensures the proposed frequency offset estimator is unbiased. Adaptive equalizers that compensate for the ISI take a relatively long time to converge, necessitating a lengthy training sequence. The convergence time is reduced using a two step technique to seed the equalizer. First, the ISI equivalent model of the channel is estimated in response to a specific short excitation sequence. Then, the estimated channel response is inverted with a novel algorithm to initialize the equalizer. It is shown that the proposed technique, while inexpensive to implement in an FPGA, can decrease the length of the required equalizer training sequence by up to 70 symbols. It is shown that a preamble segment consisting of repeated 11-symbol Barker sequences which is well-suited to timing recovery can also be used effectively for frequency recovery and channel estimation. By performing these three functions sequentially using a single set of preamble symbols, the overall length of the preamble may be further reduced

The SPIRITS Sample of Luminous Infrared Transients: Uncovering Hidden Supernovae and Dusty Stellar Outbursts in Nearby Galaxies

We present a systematic study of the most luminous (M IR [Vega magnitudes] brighter than −14) infrared (IR) transients discovered by the SPitzer InfraRed Intensive Transients Survey (SPIRITS) between 2014 and 2018 in nearby galaxies (D 12) show multiple, luminous IR outbursts over several years and have directly detected, massive progenitors in archival imaging. With analyses of extensive, multiwavelength follow-up, we suggest the following possible classifications: five obscured core-collapse supernovae (CCSNe), two erupting massive stars, one luminous red nova, and one intermediate-luminosity red transient. We define a control sample of all optically discovered transients recovered in SPIRITS galaxies and satisfying the same selection criteria. The control sample consists of eight CCSNe and one Type Iax SN. We find that 7 of the 13 CCSNe in the SPIRITS sample have lower bounds on their extinction of 2 < A V < 8. We estimate a nominal fraction of CCSNe in nearby galaxies that are missed by optical surveys as high as ${38.5}_{-21.9}^{+26.0} \%$ (90% confidence). This study suggests that a significant fraction of CCSNe may be heavily obscured by dust and therefore undercounted in the census of nearby CCSNe from optical searches