A microscopic formulation of dynamical spin injection in ferromagnetic-nonmagnetic heterostructures

We develop a microscopic formulation of dynamical spin injection in heterostructure comprising nonmagnetic metals in contact with ferromagnets. The spin pumping current is expressed in terms of Green's function of the nonmagnetic metal attached to the ferromagnet where a precessing magnetization is induced. The formulation allows for the inclusion of spin-orbit coupling and disorder. The Green's functions involved in the expression for the current are expressed in real-space lattice coordinates and can thus be efficiently computed using recursive methods.Comment: 18 pages, 6 figure

Quantum clocks observe classical and quantum time dilation

At the intersection of quantum theory and relativity lies the possibility of a clock experiencing a superposition of proper times. We consider quantum clocks constructed from the internal degrees of relativistic particles that move through curved spacetime. The probability that one clock reads a given proper time conditioned on another clock reading a different proper time is derived. From this conditional probability distribution, it is shown that when the center-of-mass of these clocks move in localized momentum wave packets they observe classical time dilation. We then illustrate a quantum correction to the time dilation observed by a clock moving in a superposition of localized momentum wave packets that has the potential to be observed in experiment. The Helstrom-Holevo lower bound is used to derive a proper time-energy/mass uncertainty relation.Comment: Updated to match published versio

On Power Allocation for Distributed Detection with Correlated Observations and Linear Fusion

We consider a binary hypothesis testing problem in an inhomogeneous wireless sensor network, where a fusion center (FC) makes a global decision on the underlying hypothesis. We assume sensors observations are correlated Gaussian and sensors are unaware of this correlation when making decisions. Sensors send their modulated decisions over fading channels, subject to individual and/or total transmit power constraints. For parallel-access channel (PAC) and multiple-access channel (MAC) models, we derive modified deflection coefficient (MDC) of the test statistic at the FC with coherent reception.We propose a transmit power allocation scheme, which maximizes MDC of the test statistic, under three different sets of transmit power constraints: total power constraint, individual and total power constraints, individual power constraints only. When analytical solutions to our constrained optimization problems are elusive, we discuss how these problems can be converted to convex ones. We study how correlation among sensors observations, reliability of local decisions, communication channel model and channel qualities and transmit power constraints affect the reliability of the global decision and power allocation of inhomogeneous sensors

Joint Spectral Radius and Path-Complete Graph Lyapunov Functions

We introduce the framework of path-complete graph Lyapunov functions for approximation of the joint spectral radius. The approach is based on the analysis of the underlying switched system via inequalities imposed among multiple Lyapunov functions associated to a labeled directed graph. Inspired by concepts in automata theory and symbolic dynamics, we define a class of graphs called path-complete graphs, and show that any such graph gives rise to a method for proving stability of the switched system. This enables us to derive several asymptotically tight hierarchies of semidefinite programming relaxations that unify and generalize many existing techniques such as common quadratic, common sum of squares, and maximum/minimum-of-quadratics Lyapunov functions. We compare the quality of approximation obtained by certain classes of path-complete graphs including a family of dual graphs and all path-complete graphs with two nodes on an alphabet of two matrices. We provide approximation guarantees for several families of path-complete graphs, such as the De Bruijn graphs, establishing as a byproduct a constructive converse Lyapunov theorem for maximum/minimum-of-quadratics Lyapunov functions.Comment: To appear in SIAM Journal on Control and Optimization. Version 2 has gone through two major rounds of revision. In particular, a section on the performance of our algorithm on application-motivated problems has been added and a more comprehensive literature review is presente

Communication between inertial observers with partially correlated reference frames

In quantum communication protocols the existence of a shared reference frame between two spatially separated parties is normally presumed. However, in many practical situations we are faced with the problem of misaligned reference frames. In this paper, we study communication between two inertial observers who have partial knowledge about the Lorentz transformation that relates their frames of reference. Since every Lorentz transformation can be decomposed into a pure boost followed by a rotation, we begin by analysing the effects on communication when the parties have partial knowledge about the transformation relating their frames, when the transformation is either a rotation or pure boost. This then enables us to investigate how the efficiency of communication is affected due to partially correlated inertial reference frames related by an arbitrary Lorentz transformation. Furthermore, we show how the results of previous studies where reference frames are completely uncorrelated are recovered from our results in appropriate limits.Comment: 9 pages, 3 figures, typos corrected, figures update

Future Spot Rate: The Implications in Indonesia

Investors, multinational companies and governments require a rate forecasting to make informed decisions about the hedging of debts and receivables, funding and short-term investments, capital budgeting and long-term financing. The process of making forecasting from market indicators, known as market-based forecasting, is usually developed based on spot rates and forward rates. The current spot rate can be used as forecasting, as the exchange rate reflects the market estimate of the spot rate in a short period of time. The forward rate is used in forecasting, as the exchange rate reflects the market estimate of the spot rate at the end of the forecasting period. Based on the research conducted by Chiang (1986) of the samples used, empirical evidence indicates spot rates and forward rates are significant as predictors of future spots. Empirical evidence suggests that spot rates provide better forecasting results compared to forward rates. The research uses regression models for market-based forecasting methods. The variables used in this study are spot rates, forward rates and future spots. The samples used are from Bank Indonesia for spot rates in January – March 2019 and future spot in April – June 2019, and from Jakarta Futures exchange for forward rates in January – March 2019. The Stochastic and Chow Test models are selected and their use has been evaluated using quality and precise testing measures. Based on the sample period used, empirical evidence suggests that spot rates and forward rates are significant in predicting future spots for EUR, JPY and AUD currencies. Current spot rates provide better forecasting results in predicting Future spot compared to the forward rate. Both the 15Ft">  and 15St">  coefficient are sensitive to new information from the variation of the coefficient and time, it can increase the forecasting of the equation to each currency exchange rate used. The study states that variables from time series should be effectively utilized and utilized in predicting currency exchange rates, as this research demonstrates the absence of dependence on time series Can be concluded that foreign exchange rates in each country follow a pattern that is not stationary. The spot Euro exchange rate turns out to be statistically more accurate with an error rate of 0.004144% forecasting with the value of regression coefficient of Euro exchange rate is a Future Spot = 21.504,88 – 0.341229Spot + 15et+1">