Search-based texture synthesis algorithms are sensitive to the order in which texture samples are generated; different synthesis orders yield different textures. Unfortunately, most polygon rasterizers and ray tracers do not guarantee the order with
which surfaces are sampled. To circumvent this problem, textures are synthesized beforehand at some maximum resolution and rendered using texture mapping. We describe a search-based texture synthesis algorithm in which samples can be generated in arbitrary order, yet the resulting texture remains identical. The key to our algorithm is a pyramidal representation in which each texture sample depends only on a fixed number of neighboring samples at each level of the pyramid. The bottom (coarsest) level of the pyramid consists of a noise image, which is small and predetermined. When a sample is requested by the renderer, all samples on which it depends are generated at once. Using this approach, samples can be generated in any order. To make the algorithm efficient, we propose storing texture samples and their dependents in a pyramidal cache. Although the first few samples are expensive to generate, there is substantial reuse, so subsequent samples cost less. Fortunately, most rendering algorithms exhibit good coherence, so cache reuse is high.
Very recent experiments have discovered that localized light in strongly absorbing media displays intriguing diffusive phenomena. Here we develop a first-principles theory of light propagation in open media with arbitrary absorption strength and samp
le length. We show analytically that photons in localized open absorbing media exhibit unusual Brownian motion. Specifically, wave transport follows the diffusion equation with the diffusion coefficient exhibiting spatial resolution. Most strikingly, despite that the system is controlled by two parameters -- the ratio of the localization (absorption) length to the sample length -- the spatially resolved diffusion coefficient displays novel single parameter scaling: it depends on the space via the returning probability. Our analytic predictions for this diffusion coefficient are confirmed by numerical simulations. In the strong absorption limit they agree well with the experimental results.
Remote state preparation (RSP) is a quantum information protocol which allows preparing a quantum state at a distant location with the help of a preshared nonclassical resource state and a classical channel. The efficiency of successfully doing this
task can be represented by the RSP-fidelity of the resource state. In this paper, we study the influence on the RSP-fidelity by applying certain local operations on the resource state. We prove that RSP-fidelity does not increase for any unital local operation. However, for nonunital local operation, such as local amplitude damping channel, we find that some resource states can be enhanced to increase the RSP-fidelity. We give the optimal parameter of symmetric local amplitude damping channel for enhancing Bell-diagonal resource states. In addition, we show RSP-fidelity can suddenly change or even vanish at instant under local decoherence.
Background: Zipfs law and Heaps law are two representatives of the scaling concepts, which play a significant role in the study of complexity science. The coexistence of the Zipfs law and the Heaps law motivates different understandings on the depend
ence between these two scalings, which is still hardly been clarified. Methodology/Principal Findings: In this article, we observe an evolution process of the scalings: the Zipfs law and the Heaps law are naturally shaped to coexist at the initial time, while the crossover comes with the emergence of their inconsistency at the larger time before reaching a stable state, where the Heaps law still exists with the disappearance of strict Zipfs law. Such findings are illustrated with a scenario of large-scale spatial epidemic spreading, and the empirical results of pandemic disease support a universal analysis of the relation between the two laws regardless of the biological details of disease. Employing the United States(U.S.) domestic air transportation and demographic data to construct a metapopulation model for simulating the pandemic spread at the U.S. country level, we uncover that the broad heterogeneity of the infrastructure plays a key role in the evolution of scaling emergence. Conclusions/Significance: The analyses of large-scale spatial epidemic spreading help understand the temporal evolution of scalings, indicating the coexistence of the Zipfs law and the Heaps law depends on the collective dynamics of epidemic processes, and the heterogeneity of epidemic spread indicates the significance of performing targeted containment strategies at the early time of a pandemic disease.
Nonextensive statistics in a Blast-Wave model (TBW) is implemented to describe the identified hadron production in relativistic p+p and nucleus-nucleus collisions. Incorporating the core and corona components within the TBW formalism allows us to des
cribe simultaneously some of the major observations in hadronic observables at the Relativistic Heavy-Ion Collider (RHIC): the Number of Constituent Quark Scaling (NCQ), the large radial and elliptic flow, the effect of gluon saturation and the suppression of hadron production at high transverse momentum (pT) due to jet quenching. In this formalism, the NCQ scaling at RHIC appears as a consequence of non-equilibrium process. Our study also provides concise reference distributions with a least chi2 fit of the available experimental data for future experiments and models.
Tsallis Statistics was used to investigate the non-Boltzmann distribution of particle spectra and their dependence on particle species and beam energy in the relativistic heavy-ion collisions at SPS and RHIC. Produced particles are assumed to acquire
radial flow and be of non-extensive statistics at freeze-out. J/psi and the particles containing strangeness were examined separately to study their radial flow and freeze-out. We found that the strange hadrons approach equilibrium quickly from peripheral to central A+A collisions and they tend to decouple earlier from the system than the light hadrons but with the same final radial flow. These results provide an alternative picture of freeze-outs: a thermalized system is produced at partonic phase; the hadronic scattering at later stage is not enough to maintain the system in equilibrium and does not increase the radial flow of the copiously produced light hadrons. The J/psi in Pb+Pb collisions at SPS is consistent with early decoupling and obtains little radial flow. The J/psi spectra at RHIC are also inconsistent with the bulk flow profile.
In the study of complex networks (systems), the scaling phenomenon of flow fluctuations refers to a certain power-law between the mean flux (activity) $<F_i>$ of the $i$th node and its variance $sigma_i$ as $sigma_i propto < F_{i} > ^{alpha}$. Such s
caling laws are found to be prevalent both in natural and man-made network systems, but our understanding of their origins still remains limited. In this paper, a non-stationary Poisson process model is proposed to give an analytical explanation of the non-universal scaling phenomenon: the exponent $alpha$ varies between 1/2 and 1 depending on the size of sampling time window and the relative strength of the external/internal driven forces of the systems. The crossover behavior and the relation of fluctuation scaling with pseudo long range dependence are also accounted for by the model. Numerical experiments show that the proposed model can recover the multi-scaling phenomenon.
