Recoil velocities from equal-mass binary black-hole mergers: a systematic investigation of spin-orbit aligned configurations

Binary black-hole systems with spins aligned with the orbital angular momentum are of special interest, as studies indicate that this configuration is preferred in nature. If the spins of the two bodies differ, there can be a prominent beaming of the gravitational radiation during the late plunge, causing a recoil of the final merged black hole. We perform an accurate and systematic study of recoil velocities from a sequence of equal-mass black holes whose spins are aligned with the orbital angular momentum, and whose individual spins range from a = +0.584 to -0.584. In this way we extend and refine the results of a previous study and arrive at a consistent maximum recoil of 448 +- 5 km/s for anti-aligned models as well as to a phenomenological expression for the recoil velocity as a function of spin ratio. This relation highlights a nonlinear behavior, not predicted by the PN estimates, and can be readily employed in astrophysical studies on the evolution of binary black holes in massive galaxies. An essential result of our analysis is the identification of different stages in the waveform, including a transient due to lack of an initial linear momentum in the initial data. Furthermore we are able to identify a pair of terms which are largely responsible for the kick, indicating that an accurate computation can be obtained from modes up to l=3. Finally, we provide accurate measures of the radiated energy and angular momentum, finding these to increase linearly with the spin ratio, and derive simple expressions for the final spin and the radiated angular momentum which can be easily implemented in N-body simulations of compact stellar systems. Our code is calibrated with strict convergence tests and we verify the correctness of our measurements by using multiple independent methods whenever possible.Comment: 24 pages, 15 figures, 5 table

The Structure of Fitness Landscapes in Antibiotic Resistant Bacteria : : Molecular Origins and Evolutionary Consequences

Antibiotic use is so ingrained in modern healthcare and agriculture that it can be difficult to imagine life in the pre-antibiotic era of the twentieth century. Many privileges we currently take for granted as rights, e.g., modern surgery, would not be possible without these drugs. But the rapid rise of antibiotic resistance may soon thrust the world back into this era. In order to predict (and ultimately prevent) the emergence of antibiotic resistance, it is crucial to establish quantitative, predictive links between the fitness of drug resistant organisms and the molecular mechanisms conferring resistance. Although the resistance mechanisms are often well characterized in vitro, their contributions to microbial fitness may depend critically on the environment and on the internal state of bacteria, which are often unknown in quantitative terms. To bridge this gap I investigate E. coli strains constitutively expressing resistance to translation-inhibiting antibiotics. The results show that in the presence of drugs, genes providing drug resistance are subject to an innate, positive feedback due to the global effect of drug- inhibited growth on gene expression. This feedback results in complex behaviors for isogenic populations of cells, including an abrupt drop in the growth rate of cultures at a threshold drug concentration. At drug concentrations below this threshold, cells exhibit growth bistability-- the coexistence of large populations of non-growing cells among otherwise identical, but growing, cells. This work demonstrates for the first time that many bacteria remain susceptible to an antibiotic even as they carry resistance to it. These behaviors do not appear in strains that lack drug resistance, and a quantitative characterization of drug-drug resistance interactions reveals a whole that is surprisingly richer than its parts. A mathematical model of bacterial growth based on the innate feedback predicts the onset of bistability and the growth rates of growing sub-populations, without invoking any ad hoc fitting parameters. Furthermore, the model describes a fitness landscape for bacterial drug resistance in different environments, allowing me to characterize the factors that determine the evolvability of resistance. The approach I use can be generalized to study resistance against other classes of antibiotics, besides the translation inhibitors studied her

Identifying affective personality profiles: A latent profile analysis of the Affective Neuroscience Personality Scales

Based on evolutionary theory, a recent model in affective neuroscience delineated six emotional brain systems at the core of human personality: SEEKING, CARING, PLAYFULNESS, FEAR, ANGER, SADNESS. The Affective Neuroscience Personality Scales (ANPS) assess their functioning. Using a person-centred approach of the ANPS, this study: (i) examined the existence of latent personality profiles, (ii) studied their gender invariance, (iii) assessed their longitudinal (4 years) stability, and (iv) explored how they relate to several intrapersonal, interpersonal, and emotion regulation skills. Latent Profile Analysis in 2 samples (Canadian, longitudinal, N = 520; French, cross-sectional, N = 830) found that, qualitatively, 3 profiles characterized both populations and genders, with one distinction for the second profile where the French women endorsed slightly higher and lower scores for, respectively, the negative and positive emotions. Whilst not being quantitatively similar across genders, the personality profiles remained consistent across time in the longitudinal sample. Associations between profiles and intrapersonal (e.g. depression), interpersonal (e.g. empathy), and emotion regulation skills measures (e.g. emotional intelligence) offered concurrent validity evidence. This person centred approach to ANPS offers a holistic and parsimonious way to study affective personality dimensions. It opens promising avenues for future studies on the predictive value of ANPS profiles, and for personality-targeted interventions