Footprints on water: The genetic wake of dispersal among reefs

Analysis of genetic data can reveal past and ongoing demographic connections between reef populations. The history, extent, and geography of isolation and exchange help to determine which populations are evolutionarily distinct and how to manage threatened reefs. Here the genetic approaches undertaken to understand connectivity among reefs are reviewed, ranging from early allozyme studies on genetic subdivision, through the use of sequence data to infer population histories, to emerging analyses that pull the influences of the past connections away from the effects of ongoing dispersal. Critically, some of these new approaches can infer migration and isolation over recent generations, thus offering the opportunity to answer many questions about reef connectivity and to better collaborate with ecologists and oceanographers to address problems that remain. © 2007 Springer-Verlag

Large-amplitude electron-acoustic solitons in a dusty plasma with kappa-distributed electrons

The Sagdeev pseudopotential method is used to investigate the occurrence and the dynamics of fully nonlinear electrostatic solitary structures in a plasma containing suprathermal hot electrons, in the presence of massive charged dust particles in the background. The soliton existence domain is delineated, and its parametric dependence on different physical parameters is clarified.Comment: 3 pages, 1 figure, presented as a poster at the 6th International Conference on the Physics of Dusty Plasmas (ICPDP6), Garmisch-Partenkirchen, Germany, 201

Luttinger Liquid Instability in the One Dimensional t-J Model

We study the t-J model in one dimension by numerically projecting the true ground state from a Luttinger liquid trial wave function. We find the model exhibits Luttinger liquid behavior for most of the phase diagram in which interaction strength and density are varied. However at small densities and high interaction strengths a new phase with a gap to spin excitations and enhanced superconducting correlations is found. We show this phase is a Luther-Emery liquid and study its correlation functions.Comment: REVTEX, 11 pages. 4 Figures available on request from [email protected]

Hole-pair hopping in arrangements of hole-rich/hole-poor domains in a quantum antiferromagnet

We study the motion of holes in a doped quantum antiferromagnet in the presence of arrangements of hole-rich and hole-poor domains such as the stripe-phase in high-$T_C$ cuprates. When these structures form, it becomes energetically favorable for single holes, pairs of holes or small bound-hole clusters to hop from one hole-rich domain to another due to quantum fluctuations. However, we find that at temperature of approximately 100 K, the probability for bound hole-pair exchange between neighboring hole-rich regions in the stripe phase, is one or two orders of magnitude larger than single-hole or multi-hole droplet exchange. As a result holes in a given hole-rich domain penetrate further into the antiferromagnetically aligned domains when they do it in pairs. At temperature of about 100 K and below bound pairs of holes hop from one hole-rich domain to another with high probability. Therefore our main finding is that the presence of the antiferromagnetic hole-poor domains act as a filter which selects, from the hole-rich domains (where holes form a self-bound liquid), hole pairs which can be exchanged throughout the system. This fluid of bound hole pairs can undergo a superfluid phase ordering at the above mentioned temperature scale.Comment: Revtex, 6 two-column pages, 4 figure

Entanglement Generation of Nearly-Random Operators

We study the entanglement generation of operators whose statistical properties approach those of random matrices but are restricted in some way. These include interpolating ensemble matrices, where the interval of the independent random parameters are restricted, pseudo-random operators, where there are far fewer random parameters than required for random matrices, and quantum chaotic evolution. Restricting randomness in different ways allows us to probe connections between entanglement and randomness. We comment on which properties affect entanglement generation and discuss ways of efficiently producing random states on a quantum computer.Comment: 5 pages, 3 figures, partially supersedes quant-ph/040505

Green's Function Monte Carlo for Lattice Fermions: Application to the t-J Model

We develop a general numerical method to study the zero temperature properties of strongly correlated electron models on large lattices. The technique, which resembles Green's Function Monte Carlo, projects the ground state component from a trial wave function with no approximations. We use this method to determine the phase diagram of the two-dimensional t-J model, using the Maxwell construction to investigate electronic phase separation. The shell effects of fermions on finite-sized periodic lattices are minimized by keeping the number of electrons fixed at a closed-shell configuration and varying the size of the lattice. Results obtained for various electron numbers corresponding to different closed-shells indicate that the finite-size effects in our calculation are small. For any value of interaction strength, we find that there is always a value of the electron density above which the system can lower its energy by forming a two-component phase separated state. Our results are compared with other calculations on the t-J model. We find that the most accurate results are consistent with phase separation at all interaction strengths.Comment: 22 pages, 22 figure

Commentary: Person-specific, multivariate, and dynamic analytic approaches to actualize ACBS task force recommendations for contextual behavioral science

The ACBS Task Force (Hayes et al., 2021) provided a clear roadmap for researchers to conduct more meaningful and impactful studies. A number of the recommendations encourage researchers to examine psychological processes at the individual level, rather than conduct cross-sectional analysis or analysis on data aggregated across individuals. Similar calls for person-specific analysis have recently echoed across various domains of human inquiry. Scientists seeking to predict specific behaviors have noted that forecasting techniques perform better when applied at the individual level, rather than when using models obtained from aggregated data (e.g., Bonaquist et al., 2021; Cheung et al., 2017). In human brain research, recent years have marked a distinct shift away from analysis on pooled data to the emerging norm requiring person-specific analysis, given differences in brain processes observed across individuals (Gratton et al., 2018; Laumann et al., 2015; Satterthwaite et al., 2018). Additionally, clinicians have long raised concerns about the gap between group-level clinical research and the realities of applied clinical decision-making, assessment, and intervention (Levine et al., 1992). In recent years, clinical science has begun to address these concerns with a shift towards person-specific analysis of behavioral, emotional, and cognitive processes in studies aimed to improve our understanding of the presentation and treatment of psychological distress