Correlation of gravimetric and satellite geodetic data Interim progress report, 11 Sep. 1967 - 29 Feb. 1968

Gravimetric and geodetic data correlation for satellite position prediction accuracy with error analysi

Time-Frequency Analysis Reveals Pairwise Interactions in Insect Swarms

The macroscopic emergent behavior of social animal groups is a classic example of dynamical self-organization, and is thought to arise from the local interactions between individuals. Determining these interactions from empirical data sets of real animal groups, however, is challenging. Using multicamera imaging and tracking, we studied the motion of individual flying midges in laboratory mating swarms. By performing a time-frequency analysis of the midge trajectories, we show that the midge behavior can be segmented into two distinct modes: one that is independent and composed of low-frequency maneuvers, and one that consists of higher-frequency nearly harmonic oscillations conducted in synchrony with another midge. We characterize these pairwise interactions, and make a hypothesis as to their biological function

Searching for Effective Forces in Laboratory Insect Swarms

Collective animal behaviour is often modeled by systems of agents that interact via effective social forces, including short-range repulsion and long-range attraction. We search for evidence of such effective forces by studying laboratory swarms of the flying midge Chironomus riparius. Using multi-camera stereoimaging and particle-tracking techniques, we record three-dimensional trajectories for all the individuals in the swarm. Acceleration measurements show a clear short-range repulsion, which we confirm by considering the spatial statistics of the midges, but no conclusive long-range interactions. Measurements of the mean free path of the insects also suggest that individuals are on average very weakly coupled, but that they are also tightly bound to the swarm itself. Our results therefore suggest that some attractive interaction maintains cohesion of the swarms, but that this interaction is not as simple as an attraction to nearest neighbours

Alien Registration- Ouellette, Marie G. (Lewiston, Androscoggin County)

https://digitalmaine.com/alien_docs/27946/thumbnail.jp

Why do financial markets asymmetrically smile? A simple formula in the multi-factor Heston model

A simple approach to determining the Gaussian kernel that constitutes the backbone of the multi-factor Heston model is proposed based on a suitable expansion in powers of volatilities of volatilities. This analysis provides Black-Scholes-like formulas for pricing European vanilla options, allowing for accurate approximations of the option prices under the multi-factor Heston model up to volatilities of volatilities on the order of 50%. The analysis also leads to a simple formula for the implied volatility showing that changes in the convexity of the volatility smile are due only to price skewness, and an easy formula to reproduce volatility indices via the realized volatility. Interestingly, the variance of the Gaussian kernel is equal to the variance of the continuously compounded return in the case of the Heston model. The empirical analyses presented assess the potential of our approach to capture market distortions while adequately forecasting the dynamics of the VIX index

Intrinsic Fluctuations and Driven Response of Insect Swarms

Animals of all sizes form groups, as acting together can convey advantages over acting alone; thus, collective animal behavior has been identified as a promising template for designing engineered systems. However, models and observations have focused predominantly on characterizing the overall group morphology, and often focus on highly ordered groups such as bird flocks. We instead study a disorganized aggregation (an insect mating swarm), and compare its natural fluctuations with the group-level response to an external stimulus. We quantify the swarm’s frequency-dependent linear response and its spectrum of intrinsic fluctuations, and show that the ratio of these two quantities has a simple scaling with frequency. Our results provide a new way of comparing models of collective behavior with experimental data

Long-Range Acoustic Interactions in Insect Swarms: An Adaptive Gravity Model

The collective motion of groups of animals emerges from the net effect of the interactions between individual members of the group. In many cases, such as birds, fish, or ungulates, these interactions are mediated by sensory stimuli that predominantly arise from nearby neighbors. But not all stimuli in animal groups are short range. Here, we consider mating swarms of midges, which are thought to interact primarily via long-range acoustic stimuli. We exploit the similarity in form between the decay of acoustic and gravitational sources to build a model for swarm behavior. By accounting for the adaptive nature of the midges\u27 acoustic sensing, we show that our \u27adaptive gravity\u27 model makes mean-field predictions that agree well with experimental observations of laboratory swarms. Our results highlight the role of sensory mechanisms and interaction range in collective animal behavior. Additionally, the adaptive interactions that we present here open a new class of equations of motion, which may appear in other biological contexts

Long-range Acoustic Interactions in Insect Swarms: An Adaptive Gravity Model

The collective motion of groups of animals emerges from the net effect of the interactions between individual members of the group. In many cases, such as birds, fish, or ungulates, these interactions are mediated by sensory stimuli that predominantly arise from nearby neighbors. But not all stimuli in animal groups are short range. Here, we consider mating swarms of midges, which interact primarily via long-range acoustic stimuli. We exploit the similarity in form between the decay of acoustic and gravitational sources to build a model for swarm behavior. By accounting for the adaptive nature of the midges' acoustic sensing, we show that our "adaptive gravity" model makes mean-field predictions that agree well with experimental observations of laboratory swarms. Our results highlight the role of sensory mechanisms and interaction range in collective animal behavior. The adaptive interactions that we present here open a new class of equations of motion, which may appear in other biological contexts.Comment: 25 pages, 15 figure

Correlation of gravimetric and satellite geodetic data, part 2 Interim scientific report, 11 Sep. 1967 - 29 Feb. 1968

Graphical output from computer correlated gravimetric and satellite geodetic dat