Regression with strongly correlated data

This paper discusses linear regression of strongly correlated data that arises, for example, in magnetohydrodynamic equilibrium reconstructions. We have proved that, generically, the covariance matrix of the estimated regression parameters for fixed sample size goes to zero as the correlations become unity. That is, in this limit the estimated parameters are known with perfect accuracy. Simple examples are shown to illustrate this effect and the nature of the exceptional cases in which the estimate covariance does not go to zero

Randomness in Competitions

We study the effects of randomness on competitions based on an elementary random process in which there is a finite probability that a weaker team upsets a stronger team. We apply this model to sports leagues and sports tournaments, and compare the theoretical results with empirical data. Our model shows that single-elimination tournaments are efficient but unfair: the number of games is proportional to the number of teams N, but the probability that the weakest team wins decays only algebraically with N. In contrast, leagues, where every team plays every other team, are fair but inefficient: the top $\sqrt{N}$ of teams remain in contention for the championship, while the probability that the weakest team becomes champion is exponentially small. We also propose a gradual elimination schedule that consists of a preliminary round and a championship round. Initially, teams play a small number of preliminary games, and subsequently, a few teams qualify for the championship round. This algorithm is fair and efficient: the best team wins with a high probability and the number of games scales as $N^{9/5}$, whereas traditional leagues require N^3 games to fairly determine a champion.Comment: 10 pages, 8 figures, reviews arXiv:physics/0512144, arXiv:physics/0608007, arXiv:cond-mat/0607694, arXiv:physics/061221

Calcium dynamics during fertilization in C. elegans

BACKGROUND: Of the animals typically used to study fertilization-induced calcium dynamics, none is as accessible to genetics and molecular biology as the model organism Caenorhabditis elegans. Motivated by the experimental possibilities inherent in using such a well-established model organism, we have characterized fertilization-induced calcium dynamics in C. elegans. RESULTS: Owing to the transparency of the nematode, we have been able to study the calcium signal in C. elegans fertilization in vivo by monitoring the fluorescence of calcium indicator dyes that we introduce into the cytosol of oocytes. In C. elegans, fertilization induces a single calcium transient that is initiated soon after oocyte entry into the spermatheca, the compartment that contains sperm. Therefore, it is likely that the calcium transient is initiated by contact with sperm. This calcium elevation spreads throughout the oocyte, and decays monotonically after which the cytosolic calcium concentration returns to that preceding fertilization. Only this single calcium transient is observed. CONCLUSION: Development of a technique to study fertilization induced calcium transients opens several experimental possibilities, e.g., identification of the signaling events intervening sperm binding and calcium elevation, identifying the possible roles of the calcium elevation such as the completion of meiosis, the formation of the eggshell, and the establishing of the embryo's axis of symmetry

Transient Pattern Formation in an Active Matter Contact Poisoning Model

One of the most notable features in repulsive particle based active matter systems is motility-induced-phase separation (MIPS) where a dense, often crystalline phase coexists with a low density fluid. In most active matter studies, the activity is kept constant as a function of time; however, there are many examples of active systems in which individual particles transition from living or moving to dead or nonmotile due to lack of fuel, infection, or poisoning. Here we consider an active matter particle system at densities where MIPS does not occur. When we add a small number of infected particles that can effectively poison other particles, rendering them nonmotile, we find a rich variety of time dependent pattern formation, including MIPS, a wetting phase, and a fragmented state formed when mobile particles plow through an nonmotile packing. We map out the patterns as a function of time scaled by the duration of the epidemic, and show that the pattern formation is robust for a wide range of poisoning rates and activity levels. We also show that pattern formation does not occur in a random death model, but requires the promotion of nucleation by contact poisoning. Our results should be relevant to biological and active matter systems where there is some form of poisoning, death, or transition to nonmotility.Comment: 7 pages, 6 figure

How to Choose a Champion

League competition is investigated using random processes and scaling techniques. In our model, a weak team can upset a strong team with a fixed probability. Teams play an equal number of head-to-head matches and the team with the largest number of wins is declared to be the champion. The total number of games needed for the best team to win the championship with high certainty, T, grows as the cube of the number of teams, N, i.e., T ~ N^3. This number can be substantially reduced using preliminary rounds where teams play a small number of games and subsequently, only the top teams advance to the next round. When there are k rounds, the total number of games needed for the best team to emerge as champion, T_k, scales as follows, T_k ~N^(\gamma_k) with gamma_k=1/[1-(2/3)^(k+1)]. For example, gamma_k=9/5,27/19,81/65 for k=1,2,3. These results suggest an algorithm for how to infer the best team using a schedule that is linear in N. We conclude that league format is an ineffective method of determining the best team, and that sequential elimination from the bottom up is fair and efficient.Comment: 6 pages, 3 figure