A simple, low-cost, data-logging pendulum built from a computer mouse

Lessons and homework problems involving a pendulum are often a big part of introductory physics classes and laboratory courses from high school to undergraduate levels. Although laboratory equipment for pendulum experiments is commercially available, it is often expensive and may not be affordable for teachers on fixed budgets, particularly in developing countries. We present a low-cost, easy-to-build rotary sensor pendulum using the existing hardware in a ball-type computer mouse. We demonstrate how this apparatus may be used to measure both the frequency and coefficient of damping of a simple physical pendulum. This easily constructed laboratory equipment makes it possible for all students to have hands-on experience with one of the most important simple physical systems.Comment: 3 pages, 3 figure

Resonant forcing of nonlinear systems of differential equations

We study resonances of nonlinear systems of differential equations, including but not limited to the equations of motion of a particle moving in a potential. We use the calculus of variations to determine the minimal additive forcing function that induces a desired terminal response, such as an energy in the case of a physical system. We include the additional constraint that only select degrees of freedom be forced, corresponding to a very general class of problems in which not all of the degrees of freedom in an experimental system are accessible to forcing. We find that certain Lagrange multipliers take on a fundamental physical role as the effective forcing experienced by the degrees of freedom which are not forced directly. Furthermore, we find that the product of the displacement of nearby trajectories and the effective total forcing function is a conserved quantity. We demonstrate the efficacy of this methodology with several examples.Comment: 9 pages, 3 figure

Identification of functional information subgraphs in cultured neural networks

This paper accompanies an oral presentation on the identification of functional information subgraphs in cultured neural networks

Thermal Equilibration of 176-Lu via K-Mixing

In astrophysical environments, the long-lived (\T_1/2 = 37.6 Gy) ground state of 176-Lu can communicate with a short-lived (T_1/2 = 3.664 h) isomeric level through thermal excitations. Thus, the lifetime of 176-Lu in an astrophysical environment can be quite different than in the laboratory. We examine the possibility that the rate of equilibration can be enhanced via K-mixing of two levels near E_x = 725 keV and estimate the relevant gamma-decay rates. We use this result to illustrate the effect of K-mixing on the effective stellar half-life. We also present a network calculation that includes the equilibrating transitions allowed by K-mixing. Even a small amount of K-mixing will ensure that 176-Lu reaches at least a quasi-equilibrium during an s-process triggered by the 22-Ne neutron source.Comment: 9 pages, 6 figure

Identification of functional information subgraphs in complex networks

We present a general information theoretic approach for identifying functional subgraphs in complex networks where the dynamics of each node are observable. We show that the uncertainty in the state of each node can be expressed as a sum of information quantities involving a growing number of correlated variables at other nodes. We demonstrate that each term in this sum is generated by successively conditioning mutual informations on new measured variables, in a way analogous to a discrete differential calculus. The analogy to a Taylor series suggests efficient search algorithms for determining the state of a target variable in terms of functional groups of other degrees of freedom. We apply this methodology to electrophysiological recordings of networks of cortical neurons grown it in vitro. Despite strong stochasticity, we show that each cell's patterns of firing are generally explained by the activity of a small number of other neurons. We identify these neuronal subgraphs in terms of their mutually redundant or synergetic character and reconstruct neuronal circuits that account for the state of each target cell.Comment: 4 pages, 4 figure