The Carter Constant for Inclined Orbits About a Massive Kerr Black Hole: I. circular orbits

In an extreme binary black hole system, an orbit will increase its angle of inclination (i) as it evolves in Kerr spacetime. We focus our attention on the behaviour of the Carter constant (Q) for near-polar orbits; and develop an analysis that is independent of and complements radiation reaction models. For a Schwarzschild black hole, the polar orbits represent the abutment between the prograde and retrograde orbits at which Q is at its maximum value for given values of latus rectum (l) and eccentricity (e). The introduction of spin (S = |J|/M2) to the massive black hole causes this boundary, or abutment, to be moved towards greater orbital inclination; thus it no longer cleanly separates prograde and retrograde orbits. To characterise the abutment of a Kerr black hole (KBH), we first investigated the last stable orbit (LSO) of a test-particle about a KBH, and then extended this work to general orbits. To develop a better understanding of the evolution of Q we developed analytical formulae for Q in terms of l, e, and S to describe elliptical orbits at the abutment, polar orbits, and last stable orbits (LSO). By knowing the analytical form of dQ/dl at the abutment, we were able to test a 2PN flux equation for Q. We also used these formulae to numerically calculate the di/dl of hypothetical circular orbits that evolve along the abutment. From these values we have determined that di/dl = -(122.7S - 36S^3)l^-11/2 -(63/2 S + 35/4 S^3) l^-9/2 -15/2 S l^-7/2 -9/2 S l^-5/2. Thus the abutment becomes an important analytical and numerical laboratory for studying the evolution of Q and i in Kerr spacetime and for testing current and future radiation back-reaction models for near-polar retrograde orbits.Comment: 51 pages, 8 figures, accepted by Classical and Quantum Gravity on September 22nd, 201

Learning and adaptation in speech production without a vocal tract

How is the complex audiomotor skill of speaking learned? To what extent does it depend on the specific characteristics of the vocal tract? Here, we developed a touchscreen-based speech synthesizer to examine learning of speech production independent of the vocal tract. Participants were trained to reproduce heard vowel targets by reaching to locations on the screen without visual feedback and receiving endpoint vowel sound auditory feedback that depended continuously on touch location. Participants demonstrated learning as evidenced by rapid increases in accuracy and consistency in the production of trained targets. This learning generalized to productions of novel vowel targets. Subsequent to learning, sensorimotor adaptation was observed in response to changes in the location-sound mapping. These findings suggest that participants learned adaptable sensorimotor maps allowing them to produce desired vowel sounds. These results have broad implications for understanding the acquisition of speech motor control.Published versio

Restoration of Native Biodiversity in Altered Environments: Reintroduction of Atlantic salmon into Lake Ontario

Less than a quarter of reintroduction programs have succeeded in re-establishing a self-sustaining population of an extirpated species. Optimal source population selection, based on an evolutionary perspective, could increase the fitness of translocated individuals, thereby improving the success rate of restoring extirpated populations. Here, using three source populations of Atlantic salmon, Salmo salar (LaHave River, Sebago Lake, and Lac Saint-Jean), that are being used for reintroduction efforts into Lake Ontario, I examined two optimal source population selection approaches: environment matching and adaptive potential. For environment matching, source populations from locations containing similar key environment features as the reintroduction location should contain adaptations to these features. For adaptive potential, source populations with high heritable genetic variation should have the potential to adapt to new selection pressures, such as the key environment features in the reintroduction location. I tested environment matching using experimental settings by exposing the three source populations to two key environment features that are likely impediments to a successful reintroduction of Atlantic salmon into Lake Ontario: the presence of non-native salmonids and a high thiaminase diet that can lead to a thiamine (vitamin B1) deficiency. I also quantified the amount of within-population heritable (additive) genetic variation for early-life history traits to assess the adaptive potential of the source populations. Although the average amount of heritable genetic variation was the highest for early-life history traits of the Sebago population, the amount was low, suggesting that the traits have a limited potential to adapt to any new selection pressures in Lake Ontario. Overall, the Sebago population (a match to both key environment features) had the highest performance, followed by the Saint-Jean population (match to a high thiaminase diet but not non-native salmonids), and finally the LaHave population (not a match to either feature). The pattern of overall performance and the low amount of heritable genetic variation of the three source populations generally supports environment matching over adaptive potential; however, further population comparisons are required over the entire life-cycle and in a fully natural setting to make more robust recommendations for large scale reintroduction efforts of Atlantic salmon into Lake Ontario

Speech Production as State Feedback Control

Spoken language exists because of a remarkable neural process. Inside a speaker's brain, an intended message gives rise to neural signals activating the muscles of the vocal tract. The process is remarkable because these muscles are activated in just the right way that the vocal tract produces sounds a listener understands as the intended message. What is the best approach to understanding the neural substrate of this crucial motor control process? One of the key recent modeling developments in neuroscience has been the use of state feedback control (SFC) theory to explain the role of the CNS in motor control. SFC postulates that the CNS controls motor output by (1) estimating the current dynamic state of the thing (e.g., arm) being controlled, and (2) generating controls based on this estimated state. SFC has successfully predicted a great range of non-speech motor phenomena, but as yet has not received attention in the speech motor control community. Here, we review some of the key characteristics of speech motor control and what they say about the role of the CNS in the process. We then discuss prior efforts to model the role of CNS in speech motor control, and argue that these models have inherent limitations – limitations that are overcome by an SFC model of speech motor control which we describe. We conclude by discussing a plausible neural substrate of our model

The Removal of Artificially Generated Polarization in SHARP Maps

We characterize the problem of artificial polarization for the Submillimeter High Angular Resolution Polarimeter (SHARP) through the use of simulated data and observations made at the Caltech Submillimeter Observatory (CSO). These erroneous, artificial polarization signals are introduced into the data through misalignments in the bolometer sub-arrays plus pointing drifts present during the data-taking procedure. An algorithm is outlined here to address this problem and correct for it, provided that one can measure the degree of the sub-array misalignments and telescope pointing drifts. Tests involving simulated sources of Gaussian intensity profile indicate that the level of introduced artificial polarization is highly dependent upon the angular size of the source. Despite this, the correction algorithm is effective at removing up to 60% of the artificial polarization during these tests. The analysis of Jupiter data taken in January 2006 and February 2007 indicates a mean polarization of 1.44%+/-0.04% and 0.95%+/-0.09%, respectively. The application of the correction algorithm yields mean reductions in the polarization of approximately 0.15% and 0.03% for the 2006 and 2007 data sets, respectively.Comment: 19 pages, 7 figure

A Complex Window-Based Joint-Chirp-Rate-Time-Frequency Transform for BBH Merger Gravitational Wave Signal Detection

With the development of machine-learning algorithms, many attempts have been made to use Artificial Neural Networks (ANN) for complicated tasks related to data classification, pattern recognition, and predictive modeling. Among such applications include Binary Black Hole (BBH) and Binary Neutron Star (BNS) merger Gravitational Wave (GW) signal detection and forecasting. Image neural networks that use time-frequency spectrograms as inputs remain one of the most prominent methods due to their relevance to highly efficient and robust ANN architectures. Earlier studies used traditional Fourier transform-based time-frequency decomposition methods for spectrogram generation, which have had difficulties identifying rapid frequency changes in merger signals with heavy background noise. The primary objective of this study is to develop a signal decomposition technique for improved GW signal classification and detection performance using ANN. We introduce the Joint-Chirp-rate-Time-Frequency transform (JCTFT), in which complex-valued window functions are used to modulate the amplitude, frequency, and phase of the input signal. In addition, we outline general techniques for generating chirp rate enhanced time-frequency spectrograms from the results of a JCTFT. We found improved signal localization performance of the JCTFT in comparison to the short-time-Fourier-transform method with a moderate-to-high amount of background noise. The JCTFT can be applied to existing and next-generation GW detector signals. The inclusion of the chirp rate makes the JCTFT computation more time-consuming. Further studies will aim to improve the efficiency and performance of JCTFT numerical computations.Comment: 14 pages, 6 figure

A Study of Elliptical Last Stable Orbits About a Massive Kerr Black Hole

The last stable orbit (LSO) of a compact object (CO) is an important boundary condition when performing numerical analysis of orbit evolution. Although the LSO is already well understood for the case where a test-particle is in an elliptical orbit around a Schwarzschild black hole (SBH) and for the case of a circular orbit about a Kerr black hole (KBH) of normalised spin, S (|J|/M^2, where J is the spin angular momentum of the KBH); it is worthwhile to extend our knowledge to include elliptical orbits about a KBH. This extension helps to lay the foundation for a better understanding of gravitational wave (GW) emission. The mathematical developments described in this work sprang from the use of an effective potential (V) derived from the Kerr metric, which encapsulates the Lense-Thirring precession. That allowed us to develop a new form of analytical expression to calculate the LSO Radius for circular orbits (R_LSO) of arbitrary KBH spin. We were then able to construct a numerical method to calculate the latus rectum (l_LSO) for an elliptical LSO. Abstract Formulae for E^2 (square of normalised orbital energy) and L^2 (square of normalised orbital angular momentum) in terms of eccentricity, e, and latus rectum, l, were previously developed by others for elliptical orbits around an SBH and then extended to the KBH case; we used these results to generalise our analytical l_LSO equations to elliptical orbits. LSO data calculated from our analytical equations and numerical procedures, and those previously published, are then compared and found to be in excellent agreement.Comment: 42 pages, 9 figures, accepted for publication in Classical and Quantum Gravit

Sensorimotor adaptation affects perceptual compensation for coarticulation

A given speech sound will be realized differently depending on the context in which it is produced. Listeners have been found to compensate perceptually for these coarticulatory effects, yet it is unclear to what extent this effect depends on actual production experience. In this study, whether changes in motor-to-sound mappings induced by adaptation to altered auditory feedback can affect perceptual compensation for coarticulation is investigated. Specifically, whether altering how the vowel [i] is produced can affect the categorization of a stimulus continuum between an alveolar and a palatal fricative whose interpretation is dependent on vocalic context is tested. It was found that participants could be sorted into three groups based on whether they tended to oppose the direction of the shifted auditory feedback, to follow it, or a mixture of the two, and that these articulatory responses, not the shifted feedback the participants heard, correlated with changes in perception. These results indicate that sensorimotor adaptation to altered feedback can affect the perception of unaltered yet coarticulatorily-dependent speech sounds, suggesting a modulatory role of sensorimotor experience on speech perceptio