Testing Ho\v{r}ava-Lifshitz gravity using thin accretion disk properties

Recently, a renormalizable gravity theory with higher spatial derivatives in four dimensions was proposed by Horava. The theory reduces to Einstein gravity with a non-vanishing cosmological constant in IR, but it has improved UV behaviors. The spherically symmetric black hole solutions for an arbitrary cosmological constant, which represent the generalization of the standard Schwarzschild-(A)dS solution, has also been obtained for the Horava-Lifshitz theory. The exact asymptotically flat Schwarzschild type solution of the gravitational field equations in Horava gravity contains a quadratic increasing term, as well as the square root of a fourth order polynomial in the radial coordinate, and it depends on one arbitrary integration constant. The IR modified Horava gravity seems to be consistent with the current observational data, but in order to test its viability more observational constraints are necessary. In the present paper we consider the possibility of observationally testing Horava gravity by using the accretion disk properties around black holes. The energy flux, temperature distribution, the emission spectrum as well as the energy conversion efficiency are obtained, and compared to the standard general relativistic case. Particular signatures can appear in the electromagnetic spectrum, thus leading to the possibility of directly testing Horava gravity models by using astrophysical observations of the emission spectra from accretion disks.Comment: 7 pages, 4 figures. V2: minor additions and references added; to appear in Phys. Rev.

Infinite disorder scaling of random quantum magnets in three and higher dimensions

Using a very efficient numerical algorithm of the strong disorder renormalization group method we have extended the investigations about the critical behavior of the random transverse-field Ising model in three and four dimensions, as well as for Erd\H os-R\'enyi random graphs, which represent infinite dimensional lattices. In all studied cases an infinite disorder quantum critical point is identified, which ensures that the applied method is asymptotically correct and the calculated critical exponents tend to the exact values for large scales. We have found that the critical exponents are independent of the form of (ferromagnetic) disorder and they vary smoothly with the dimensionality.Comment: 6 pages, 5 figure

Evaluation of a High-speed Planter in Soybean Production

Timely and quality planting of soybean is important to achievemaximum yield potential. Wet spring soil conditions and rain frequently shorten the time for farmers to plant crops within optimal soil conditions. New planter technology has been introduced that enables farmers to plant their fields faster and more precisely than with traditional planters. Large plot field studies were conducted in Indiana from 2015 to 2017 to evaluate a high-speed planter at various planting speeds with multiple seeding rates on soybean. Seedling emergence, plant distribution, and final yield were evaluated. Three planting speeds [8, 12, and 16 kilometers per hour (kph)] and two seeding rates (222,000 and 321,000 seeds ha−1) were included in all years, and an additional planting speed and seeding rate were included in 2016 (20 kph and 420,000 seeds ha−1, respectively). Overall, planting speed did not impact soybean seedling emergence. Uniformity of plant spacing decreased slightly as the planting speed increased from 8 to 20 kph in 2016. Cool and wet conditions immediately after planting likely led to inconsistent emergence. Final grain yield was not affected by planting speeds or seeding rate except in 2017 when 12 kph planting speed yielded 0.25 Mg ha−1 higher than the other planting speeds. Increasing planting speed can be achieved without detrimentally affecting plant population, plant spacing, and yield in soybean

Renormalization group study of the two-dimensional random transverse-field Ising model

The infinite disorder fixed point of the random transverse-field Ising model is expected to control the critical behavior of a large class of random quantum and stochastic systems having an order parameter with discrete symmetry. Here we study the model on the square lattice with a very efficient numerical implementation of the strong disorder renormalization group method, which makes us possible to treat finite samples of linear size up to $L=2048$. We have calculated sample dependent pseudo-critical points and studied their distribution, which is found to be characterized by the same shift and width exponent: $\nu=1.24(2)$. For different types of disorder the infinite disorder fixed point is shown to be characterized by the same set of critical exponents, for which we have obtained improved estimates: $x=0.982(15)$ and $\psi=0.48(2)$. We have also studied the scaling behavior of the magnetization in the vicinity of the critical point as well as dynamical scaling in the ordered and disordered Griffiths phases

Discovering a junction tree behind a Markov network by a greedy algorithm

In an earlier paper we introduced a special kind of k-width junction tree, called k-th order t-cherry junction tree in order to approximate a joint probability distribution. The approximation is the best if the Kullback-Leibler divergence between the true joint probability distribution and the approximating one is minimal. Finding the best approximating k-width junction tree is NP-complete if k>2. In our earlier paper we also proved that the best approximating k-width junction tree can be embedded into a k-th order t-cherry junction tree. We introduce a greedy algorithm resulting very good approximations in reasonable computing time. In this paper we prove that if the Markov network underlying fullfills some requirements then our greedy algorithm is able to find the true probability distribution or its best approximation in the family of the k-th order t-cherry tree probability distributions. Our algorithm uses just the k-th order marginal probability distributions as input. We compare the results of the greedy algorithm proposed in this paper with the greedy algorithm proposed by Malvestuto in 1991.Comment: The paper was presented at VOCAL 2010 in Veszprem, Hungar