Multigame models of innovation in evolutionary economics

We incorporate information measures representing knowledge into an evolutionary model of coevolving firms and markets whereby the growing orderliness of firms potentiates a predictable progression of market exchange innovations which themselves become beneficial only with the growing orderliness of firms. We do this by generalizing Nelson and Winter style evolutionary models which are well suited to the study of entry, exit, and growth dynamics at the level of individual firms or entire industries. The required innovation is to use information measures to impose an order on the routines constituting a firm, and by correlating order with firm profitability, allow the preferential selection of innovations which increase order. In this viewpoint, the coherent mathematical framework provided by information and probability theory describes firm orderliness and variability, as well as all selection operations. This informational approach allows modelling the synergistic interactions between routines in a single firm and between different firms in a general but comprehensive manner, so that we can successfully model and predict innovations specifically focussed on organizational order. In particular, we can predict the coevolution over time of firm organizational complexity and of increasingly sophisticated market exchange mechanisms for routines permitting that increased organizational order. We demonstrate our approach using numerical simulations and analytic techniques exploiting a multigame player environment.Evolution, Knowledge, Markets, Evolutionary dynamics, Games, Multigame Environments

Inherent size constraints on prokaryote gene networks due to "accelerating" growth

Networks exhibiting "accelerating" growth have total link numbers growing faster than linearly with network size and can exhibit transitions from stationary to nonstationary statistics and from random to scale-free to regular statistics at particular critical network sizes. However, if for any reason the network cannot tolerate such gross structural changes then accelerating networks are constrained to have sizes below some critical value. This is of interest as the regulatory gene networks of single celled prokaryotes are characterized by an accelerating quadratic growth and are size constrained to be less than about 10,000 genes encoded in DNA sequence of less than about 10 megabases. This paper presents a probabilistic accelerating network model for prokaryotic gene regulation which closely matches observed statistics by employing two classes of network nodes (regulatory and non-regulatory) and directed links whose inbound heads are exponentially distributed over all nodes and whose outbound tails are preferentially attached to regulatory nodes and described by a scale free distribution. This model explains the observed quadratic growth in regulator number with gene number and predicts an upper prokaryote size limit closely approximating the observed value.Comment: Corrected error in biological input parameter: 15 pages, 10 figure

Failed "nonaccelerating" models of prokaryote gene regulatory networks

Much current network analysis is predicated on the assumption that important biological networks will either possess scale free or exponential statistics which are independent of network size allowing unconstrained network growth over time. In this paper, we demonstrate that such network growth models are unable to explain recent comparative genomics results on the growth of prokaryote regulatory gene networks as a function of gene number. This failure largely results as prokaryote regulatory gene networks are "accelerating" and have total link numbers growing faster than linearly with network size and so can exhibit transitions from stationary to nonstationary statistics and from random to scale-free to regular statistics at particular critical network sizes. In the limit, these networks can undergo transitions so marked as to constrain network sizes to be below some critical value. This is of interest as the regulatory gene networks of single celled prokaryotes are indeed characterized by an accelerating quadratic growth with gene count and are size constrained to be less than about 10,000 genes encoded in DNA sequence of less than about 10 megabases. We develop two "nonaccelerating" network models of prokaryote regulatory gene networks in an endeavor to match observation and demonstrate that these approaches fail to reproduce observed statistics.Comment: Corrected error in biological input parameter: 13 pages, 9 figure

Novel acoustic sources from squeezed cavities in car tires

This paper demonstrates that the partial squeezing of car tire cavities at ground impact cannot he adequately modeled by the usual acoustic wave equation. A more complete treatment must begin with the Euler equations for fluid flow in a squeezed cavity to derive a wave equation dependent on cavity wall velocities and accelerations. These can be sizable as ground impact causes the walls of a tire cavity to move with velocities of order 1 m/s and with accelerations of 10(3) m/s(2) over time scales of about 1 ms. Further, the geometry of a typical cavity is such that width compression causes significant increases in pressure and density to occur before the arrival of the rarefaction wave propagating from the open end of the cavity begins to exhaust the full length of the cavity. This causes significant departures from equilibrium density and pressure conditions. These influences are demonstrated both analytically and numerically. (C) 1999 Acoustical Society of America. [S0001-4966(99)00708-0]

Rydberg-atom phase-sensitive detection and the quantum Zeno effect

We present a scheme for experimentally observing the quantum Zeno effect using the quantum-nondemolition measurement recently proposed by Brune et al. [Phys. Rev. Lett. 65, 976 (1990)]. The Zeno effect refers to the freezing of the (unitary) free dynamics of a system by rapid measurements. We generalize the Zeno effect to be any change in the survival probability of an initial state induced by very rapid measurements, when such measurements are the dominant source of fluctuations in the system. We derive a master equation for the evolution of a cavity mode when the photon number is monitored by this method. This equation describes a phase-diffusion process. We propose that this measurement scheme be used to monitor the exchange of a single photon between the cavity and a single Rydberg atom. We show that for very rapid monitoring the free oscillation of the atomic inversion is disrupted and the atom can be trapped close to the initial excited state. This is the quantum Zeno effect

Continuous Position Measurements and the Quantum Zeno Effect

We present a model of continuous (in time) position measurements on a quantum system using a single pseudoclassical meter. The nonselective evolution of the system is described by a master equation which is identical to that obtained from previous models. The selective evolution is described by a stochastic nonlinear Schrödinger equation. The significance of this equation is that the stochastic term has a physical interpretaion. By carefully choosing the parameters which define the meter and the system-meter coupling, we obtain a meter pointer with well-defined position which undergoes fluctuations. This ‘‘jitter’’ in the pointer position gives rise to the stochastic dynamical collapse of the system wave function. By the inclusion of feedback on the meter, the pointer is made to relax towards an appropriate readout. We apply this model to the selective measurement of the position of a particle in a double-well potential. In contrast to a recent claim [H. Fearn and W. E. Lamb, Jr., Phys. Rev. A 46, 1199 (1992)] we show that truly continuous position measurements lead to a quantum Zeno effect in certain parameter regimes. This is manifest by the changing of the particle dynamics from coherent tunneling between the well minima to incoherent flipping, as in a random telegraph. As the measurement strength increases, the average length of time the particle remains stuck in one well increases proportionally

Quantification and Prediction of Stream Dryness in the Interior Highlands

Although ecological studies have noted streams drying in the Interior Highlands, published measurements of streambed dryness are lacking. Clearly, stream drying has the potential to affect benthic macroinvertebrate and fish communities. In 2003, we initiated an assessment of streambed dryness for three streams in the Ouachita Mountains representative of the Central Hills, Ridges, and Valleys. In the following summer, we applied the approach to 15 similar size watersheds in three distinct ecoregions of the Interior Highlands: Ouachita Mountains-Athens Plateau, Ozark Highlands-Springfield Plateau, and Lower Boston Mountains. Repeated dryness measurements were recorded in each stream and correlated to nearby USGS stream gage records. Dryness reached as high as 86% for the Ouachita Mountains in 2003; whereas, flow was continuous in 2004. One stream in the Ozark Highlands dried completely in 2004, and dryness reached 84% in the Boston Mountains. Percent dry streambed was negatively correlated (Spearman rank) to discharge for the Ouachita Mountains in 2003 and the Boston Mountains in2004 (rs =-0.94 and -0.60, respectively; p \u3c 0.05, Ukey-Kramer). Maximum dryness during these months was significantly lower for the Ouachita Mountains than the Boston mountains and Ozark Highlands. Thus, discernable patterns of stream dryness exist among the different ecoregions of the Interior Highlands. Aquatic ecologists and resource managers in these ecoregions could employ such measures to further understand habitat limitations associated with these stream systems

Aurosion: Eroding Sonic Landscapes with the Internet Audio Cyclotron

The authors describe Aurosion, a performance piece utilizing “the largest feedback loop in the world,” the Internet Audio Cyclotron. Using field recordings, they subvert compression algorithms to explore emergent devolution