Generalized Semimagic Squares for Digital Halftoning

Completing Aronov et al.'s study on zero-discrepancy matrices for digital halftoning, we determine all (m, n, k, l) for which it is possible to put mn consecutive integers on an m-by-n board (with wrap-around) so that each k-by-l region holds the same sum. For one of the cases where this is impossible, we give a heuristic method to find a matrix with small discrepancy.Comment: 6 pages, 6 figure

On a Possibility to Measure Thermoelectric Power in SNS Structures

Two dissimilar Josephson junctions, which are connected to a heater can act as precise batteries. Because of the difference in thermoelectric power of these batteries, circuit with two dissimilar batteries, under heat flow $\Delta T\sim 10^{-5}K$ would have a net EMF $10^{-11} V$ around the zero-resistance loop leading to a loop's magnetic flux oscillating in time. It is shown its theoretical value is proportional to both the temperature difference as well as the disparity in the thermoelectric powers of the two junctions.Comment: 5 page

High-frequency spin valve effect in ferromagnet-semiconductor-ferromagnet structure based on precession of injected spins

New mechanism of magnetoresistance, based on tunneling-emission of spin polarized electrons from ferromagnets (FM) into semiconductors (S) and precession of electron spin in the semiconductor layer under external magnetic field, is described. The FM-S-FM structure is considered, which includes very thin heavily doped (delta-doped) layers at FM-S interfaces. At certain parameters the structure is highly sensitive at room-temperature to variations of the field with frequencies up to 100 GHz. The current oscillates with the field, and its relative amplitude is determined only by the spin polarizations of FM-S junctions at relatively large bias voltage.Comment: 5 pages, 2 figures, (v2) new plot with a dependence of current J on magnetic field H added in Fig.2 (top panel), minor amendments in the text; (v3) minor typos corrected. To appear in Phys. Rev. Letter

Spin injection dependent metamagnetic transition

We define the metamagnetic phase transition of itinerant electrons controlled by the spin injection mechanism. The current flow between a ferromagnetic metal and a metamagnetic metal produces the non-equilibrium shift of chemical potential for spin up and spin down electrons that acts as an effective magnetic field driving the metamagnetic transition.Comment: 6 pages, 3 figure

Theory of thermal spin-charge coupling in electronic systems

The interplay between spin transport and thermoelectricity offers several novel ways of generating, manipulating, and detecting nonequilibrium spin in a wide range of materials. Here we formulate a phenomenological model in the spirit of the standard model of electrical spin injection to describe the electronic mechanism coupling charge, spin, and heat transport and employ the model to analyze several different geometries containing ferromagnetic (F) and nonmagnetic (N) regions: F, F/N, and F/N/F junctions which are subject to thermal gradients. We present analytical formulas for the spin accumulation and spin current profiles in those junctions that are valid for both tunnel and transparent (as well as intermediate) contacts. For F/N junctions we calculate the thermal spin injection efficiency and the spin accumulation induced nonequilibrium thermopower. We find conditions for countering thermal spin effects in the N region with electrical spin injection. This compensating effect should be particularly useful for distinguishing electronic from other mechanisms of spin injection by thermal gradients. For F/N/F junctions we analyze the differences in the nonequilibrium thermopower (and chemical potentials) for parallel and antiparallel orientations of the F magnetizations, as evidence and a quantitative measure of the spin accumulation in N. Furthermore, we study the Peltier and spin Peltier effects in F/N and F/N/F junctions and present analytical formulas for the heat evolution at the interfaces of isothermal junctions.Comment: to be published in PRB (in press), 19 pages, 19 figure

Subsampling in Smoothed Range Spaces

We consider smoothed versions of geometric range spaces, so an element of the ground set (e.g. a point) can be contained in a range with a non-binary value in $[0,1]$. Similar notions have been considered for kernels; we extend them to more general types of ranges. We then consider approximations of these range spaces through $\varepsilon$-nets and $\varepsilon$-samples (aka $\varepsilon$-approximations). We characterize when size bounds for $\varepsilon$-samples on kernels can be extended to these more general smoothed range spaces. We also describe new generalizations for $\varepsilon$-nets to these range spaces and show when results from binary range spaces can carry over to these smoothed ones.Comment: This is the full version of the paper which appeared in ALT 2015. 16 pages, 3 figures. In Algorithmic Learning Theory, pp. 224-238. Springer International Publishing, 201

Finding Pairwise Intersections Inside a Query Range

We study the following problem: preprocess a set O of objects into a data structure that allows us to efficiently report all pairs of objects from O that intersect inside an axis-aligned query range Q. We present data structures of size $O(n({\rm polylog} n))$ and with query time $O((k+1)({\rm polylog} n))$ time, where k is the number of reported pairs, for two classes of objects in the plane: axis-aligned rectangles and objects with small union complexity. For the 3-dimensional case where the objects and the query range are axis-aligned boxes in R^3, we present a data structures of size $O(n\sqrt{n}({\rm polylog} n))$ and query time $O((\sqrt{n}+k)({\rm polylog} n))$. When the objects and query are fat, we obtain $O((k+1)({\rm polylog} n))$ query time using $O(n({\rm polylog} n))$ storage

Restrictions on modeling spin injection by resistor networks

Because of the technical difficulties of solving spin transport equations in inhomogeneous systems, different resistor networks are widely applied for modeling spin transport. By comparing an analytical solution for spin injection across a ferromagnet - paramagnet junction with a resistor model approach, its essential limitations stemming from inhomogeneous spin populations are clarified.Comment: To be published in a special issue of Semicond. Sci. Technol., Guest editor Prof. G. Landweh

Spin and orbital effects in a 2D electron gas in a random magnetic field

Using the method of superbosonization we consider a model of a random magnetic field (RMF) acting on both orbital motion and spin of electrons in two dimensions. The method is based on exact integration over one particle degrees of freedom and reduction of the problem to a functional integral over supermatrices $Q({\bf r},{\bf r^{\prime}})$. We consider a general case when both the direction of the RMF and the g-factor of the Zeeman splitting are arbitrary. Integrating out fast variations of $Q$ we come to a standard collisional unitary non-linear $\sigma$-model. The collision term consists of orbital, spin and effective spin-orbital parts. For a particular problem of a fixed direction of RMF, we show that additional soft excitations identified with spin modes should appear. Considering $\delta$% -correlated weak RMF and putting g=2 we find the transport time $\tau_{tr}$. This time is 2 times smaller than that for spinless particles.Comment: 9 pages, no figure

Orthogonal Range Reporting and Rectangle Stabbing for Fat Rectangles

In this paper we study two geometric data structure problems in the special case when input objects or queries are fat rectangles. We show that in this case a significant improvement compared to the general case can be achieved. We describe data structures that answer two- and three-dimensional orthogonal range reporting queries in the case when the query range is a \emph{fat} rectangle. Our two-dimensional data structure uses $O(n)$ words and supports queries in $O(\log\log U +k)$ time, where $n$ is the number of points in the data structure, $U$ is the size of the universe and $k$ is the number of points in the query range. Our three-dimensional data structure needs $O(n\log^{\varepsilon}U)$ words of space and answers queries in $O(\log \log U + k)$ time. We also consider the rectangle stabbing problem on a set of three-dimensional fat rectangles. Our data structure uses $O(n)$ space and answers stabbing queries in $O(\log U\log\log U +k)$ time.Comment: extended version of a WADS'19 pape