We examine the ground state of the random quantum Ising model in a transverse field using a generalization of the Ma-Dasgupta-Hu renormalization group ͑RG͒ scheme. For spatial dimensionality dϭ2, we find that at strong randomness the RG flow for the quantum critical point is towards an infinite-randomness fixed point, as in one dimension. This is consistent with the results of a recent quantum Monte Carlo study by Pich et al. ͓Phys. Rev. Lett. 81, 5916 ͑1998͔͒, including estimates of the critical exponents from our RG that agree well with those from the quantum Monte Carlo. The same qualitative behavior appears to occur for three dimensions; we have not yet been able to determine whether or not it persists to arbitrarily high d. Some consequences of the infinite-randomness fixed point for the quantum critical scaling behavior are discussed. Because frustration is irrelevant in the infinite-randomness limit, the same fixed point should govern both ferromagnetic and spin-glass quantum critical points. This RG maps the random quantum Ising model with strong disorder onto a novel type of percolation/aggregation process.

Classical hard spheres crystallize at equilibrium at high enough density. Crystals made up of stackings of 2-dimensional hexagonal close-packed layers (e.g. f cc , hcp , etc.) differ in entropy by only about 10 −3 k B per sphere (all configurations are degenerate in energy). To readily resolve and study these small entropy differences, we have implemented two different multicanonical Monte Carlo algorithms that allow direct equilibration between crystals with different stacking sequences. Recent work had demonstrated that the fcc stacking has higher entropy than the hcp stacking. We have studied other stackings to demonstrate that the fcc stacking does indeed have the highest entropy of all possible stackings. The entropic interactions we could detect involve three, four and (although with less statistical certainty) five consecutive layers of spheres. These interlayer entropic interactions fall off in strength with increasing distance, as expected; this fall-off appears to be much slower near the melting density than at the maximum (close-packing) density. At maximum density the entropy difference between f cc and hcp stackings is 0.00115± 0.00004 k B per sphere, which is roughly 30% higher than the same quantity measured near the melting transition.

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The assumption that all nodes cooperate to relay packets for each other may not be realistic for commercial wireless ad hoc networks. An autonomous (selfish) node in a wireless network has two disincentives for forwarding for others: energy expenditure (real cost) and possible delays for its own data (opportunity cost). We introduce a mechanism that "fosters cooperation through bribery" in the context of forwarding in ad hoc networks. Using a microeconomic framework based on game theory, we design and analyze a pricing algorithm that encourages forwarding among autonomous nodes by reimbursing forwarding. Taking a joint network-centric and user-centric approach, the revenue maximizing network and utility (measured in bits-per-Joule) maximizing nodes interact through prices for channel use, reimbursements for forwarding, transmitter power control, as well as forwarding and destination preferences. In a three-node (two-sources, one-access-point) network, the network converges to an architecture that induces forwarding only when the network geometries are such that forwarding is likely to increase individual benefits (network revenue and node utilities). For other geometries, the network converges to architectures that do not favor forwarding. We then generalize to a multinode network, where it is seen that the nodes' willingness to forward decrease for large ratios of the average internodal distance to the smallest distance between the access point and any source node. Pricing with reimbursement generally improves the network aggregate utility (or aggregate bits-per-Joule), as well as utilities and revenue compared with the corresponding pricing algorithm without reimbursement.

Hysteresis is commonly seen in the current-voltage characteristics of organic thin-film transistors (OTFTs). In the absence of memory effects associated with the gate dielectric, the hysteresis in p-channel pentacene-based OTFTs, as measured in air and under illumination, was found to be dominated by trapped electrons in the semiconductor. The responsible acceptor-type traps have very long lifetimes. The immobile, previously stored negative charge requires extra holes to balance it, resulting in early establishment of the channel and extra drain current. This model is unique in that it explains the memory effect in terms of the electrostatic effect on the majority carrier population of trapped charge, opposite in sign to the majority carriers. The model is supported by drain current transient decay data. By studying the presence or absence of this effect and repeatedly measuring same devices on one substrate under various ambient and illumination conditions, we found that the responsible acceptor states are introduced by air exposure and illumination and that their formation, as well as the resulting memory effect, is reversible. Efforts were taken in the data analysis to separate the bias stress effect from the memory effect under study. The impact of this memory effect on OTFT measurement and application is discussed.