Heisenberg frustrated magnets: a nonperturbative approach

Frustrated magnets are a notorious example where the usual perturbative methods are in conflict. Using a nonperturbative Wilson-like approach, we get a coherent picture of the physics of Heisenberg frustrated magnets everywhere between $d=2$ and $d=4$. We recover all known perturbative results in a single framework and find the transition to be weakly first order in $d=3$. We compute effective exponents in good agreement with numerical and experimental data.Comment: 5 pages, Revtex, technical details available at http://www.lpthe.jussieu.fr/~tissie

Why do Hurst exponents of traded value increase as the logarithm of company size?

The common assumption of universal behavior in stock market data can sometimes lead to false conclusions. In statistical physics, the Hurst exponents characterizing long-range correlations are often closely related to universal exponents. We show, that in the case of time series of the traded value, these Hurst exponents increase logarithmically with company size, and thus are non-universal. Moreover, the average transaction size shows scaling with the mean transaction frequency for large enough companies. We present a phenomenological scaling framework that properly accounts for such dependencies.Comment: 10 pages, 4 figures, to appear in the Proceedings of the International Workshop on Econophysics of Stock Markets and Minority Games, Calcutta, 200

Accounting for nuclear and mito genome in dairy cattle breeding - a simulation study

Mitochondria play a significant role in numerous cellular processes through proteins encoded by both the nuclear genome (nDNA) and mito genome (mDNA), and increasing evidence shows that traits of interest might be affected by mito-nuclear interactions. While the variation in nDNA is influenced by mutations and recombination of parental genomes, the variation in mDNA is solely driven by mutations. In addition, mDNA is inherited in a haploid form, from the dam. Cattle populations show significant variation in mDNA between and within breeds. Past research suggests that variation in mDNA accounts for 1–5% of the phenotypic variation in dairy traits. Here we simulated a dairy cattle breeding program to assess the impact of accounting for mDNA variation in pedigree-based and genome-based genetic evaluations on the accuracy of estimated breeding values for mDNA and nDNA components. We also examined the impact of alternative definitions of breeding values on genetic gain, including nDNA and mDNA components that both impact phenotype expression, but mDNA is inherited only maternally. We found that accounting for mDNA variation increased accuracy between +0.01 and +0.03 for different categories of animals, especially for young bulls (+0.03) and females without genotype data (between +0.01 and +0.03). Different scenarios of modeling and breeding value definition impacted genetic gain. The standard approach of ignoring mDNA variation achieved competitive genetic gain. Modeling, but not selecting on mDNA expectedly reduced genetic gain, while optimal use of mDNA variation recovered the genetic gain

Tricritical behavior of the frustrated XY antiferromagnet

Extensive histogram Monte-Carlo simulations of the XY antiferromagnet on a stacked triangular lattice reveal exponent estimates which strongly favor a scenario of mean-field tricritical behavior for the spin-order transition. The corresponding chiral-order transition occurs at the same temperature but appears to be decoupled from the spin-order. These results are relevant to a wide class of frustrated systems with planar-type order and serve to resolve a long-standing controversy regarding their criticality.Comment: J1K 2R1 4 pages (RevTex 3.0), 4 figures available upon request, Report# CRPS-94-0

Fractional derivatives of random walks: Time series with long-time memory

We review statistical properties of models generated by the application of a (positive and negative order) fractional derivative operator to a standard random walk and show that the resulting stochastic walks display slowly-decaying autocorrelation functions. The relation between these correlated walks and the well-known fractionally integrated autoregressive (FIGARCH) models, commonly used in econometric studies, is discussed. The application of correlated random walks to simulate empirical financial times series is considered and compared with the predictions from FIGARCH and the simpler FIARCH processes. A comparison with empirical data is performed.Comment: 10 pages, 14 figure

Why have asset price properties changed so little in 200 years

We first review empirical evidence that asset prices have had episodes of large fluctuations and been inefficient for at least 200 years. We briefly review recent theoretical results as well as the neurological basis of trend following and finally argue that these asset price properties can be attributed to two fundamental mechanisms that have not changed for many centuries: an innate preference for trend following and the collective tendency to exploit as much as possible detectable price arbitrage, which leads to destabilizing feedback loops.Comment: 16 pages, 4 figure

Liquidity and the multiscaling properties of the volume traded on the stock market

We investigate the correlation properties of transaction data from the New York Stock Exchange. The trading activity f(t) of each stock displays a crossover from weaker to stronger correlations at time scales 60-390 minutes. In both regimes, the Hurst exponent H depends logarithmically on the liquidity of the stock, measured by the mean traded value per minute. All multiscaling exponents tau(q) display a similar liquidity dependence, which clearly indicates the lack of a universal form assumed by other studies. The origin of this behavior is both the long memory in the frequency and the size of consecutive transactions.Comment: 7 pages, 3 figures, submitted to Europhysics Letter

Model for fitting longitudinal traits subject to threshold response applied to genetic evaluation for heat tolerance

A semi-parametric non-linear longitudinal hierarchical model is presented. The model assumes that individual variation exists both in the degree of the linear change of performance (slope) beyond a particular threshold of the independent variable scale and in the magnitude of the threshold itself; these individual variations are attributed to genetic and environmental components. During implementation via a Bayesian MCMC approach, threshold levels were sampled using a Metropolis step because their fully conditional posterior distributions do not have a closed form. The model was tested by simulation following designs similar to previous studies on genetics of heat stress. Posterior means of parameters of interest, under all simulation scenarios, were close to their true values with the latter always being included in the uncertain regions, indicating an absence of bias. The proposed models provide flexible tools for studying genotype by environmental interaction as well as for fitting other longitudinal traits subject to abrupt changes in the performance at particular points on the independent variable scale

Monte Carlo renormalization group study of the Heisenberg and XY antiferromagnet on the stacked triangular lattice and the chiral ϕ4\phi^4 model

With the help of the improved Monte Carlo renormalization-group scheme, we numerically investigate the renormalization group flow of the antiferromagnetic Heisenberg and XY spin model on the stacked triangular lattice (STA-model) and its effective Hamiltonian, 2N-component chiral $\phi^4$ model which is used in the field-theoretical studies. We find that the XY-STA model with the lattice size $126\times 144 \times 126$ exhibits clear first-order behavior. We also find that the renormalization-group flow of STA model is well reproduced by the chiral $\phi^4$ model, and that there are no chiral fixed point of renormalization-group flow for N=2 and 3 cases. This result indicates that the Heisenberg-STA model also undergoes first-order transition.Comment: v1:15 pages, 15 figures v2:updated references v3:added comments on the higher order irrelevant scaling variables v4:added results of larger sizes v5:final version to appear in J.Phys.Soc.Jpn Vol.72, No.

Critical behavior of frustrated systems: Monte Carlo simulations versus Renormalization Group

We study the critical behavior of frustrated systems by means of Pade-Borel resummed three-loop renormalization-group expansions and numerical Monte Carlo simulations. Amazingly, for six-component spins where the transition is second order, both approaches disagree. This unusual situation is analyzed both from the point of view of the convergence of the resummed series and from the possible relevance of non perturbative effects.Comment: RevTex, 10 pages, 3 Postscript figure