Indirect Exciton–Phonon Dynamics in MoS2 Revealed by Ultrafast Electron Diffraction

Transition metal dichalcogenides layered nano-crystals are emerging as promising candidates for next-generation optoelectronic and quantum devices. In such systems, the interaction between excitonic states and atomic vibrations is crucial for many fundamental properties, such as carrier mobilities, quantum coherence loss, and heat dissipation. In particular, to fully exploit their valley-selective excitations, one has to understand the many-body exciton physics of zone-edge states. So far, theoretical and experimental studies have mainly focused on the exciton–phonon dynamics in high-energy direct excitons involving zone-center phonons. Here, ultrafast electron diffraction and ab initio calculations are used to investigate the many-body structural dynamics following nearly- resonant excitation of low-energy indirect excitons in MoS₂. By exploiting the large momentum carried by scattered electrons, the excitation of in-plane K- and Q- phonon modes are identified with 𝑬^′ symmetry as key for the stabilization of indirect excitons generated via near-infrared light at 1.55 eV, and light is shed on the role of phonon anharmonicity and the ensuing structural evolution of the MoS₂ crystal lattice. The results highlight the strong selectivity of phononic excitations directly associated with the specific indirect- exciton nature of the wavelength-dependent electronic transitions triggered in the system.     

Excited states of alkali atoms in liquid4He from density functional calculations

Calculations are presented, based on a Density Functional approach, of the first excited states (l=1) of alkali metal atoms (Cs and Na) in liquid ⁴He. We find large departures from the spherical bubble in the liquid⁴He structure when the alkali atom is excited. The shifts from the free atom values of the excitation and emission transition lines are calculated and compared with the experimental results. According to our calculations, the so far unseen radiative deexcitation transition for light alkalis in⁴He may lie in an unexplored infrared region of the spectrum.     

Editorial: Special issue on approximate dynamic programming and reinforcement learning

We are extremely pleased to present this special issue of the Journal of Control Theory and Applications.Approximate dynamic programming (ADP) is a general and effective approach for solving optimal control and estimation problems by adapting to uncertain environments over time.ADP optimizes the sensing objectives accrued over a future time interval with respect to an adaptive control law,conditioned on prior knowledge of the system,its state,and uncertainties.A numerical search over the present value of the control minimizes a Hamilton-Jacobi-Bellman (HJB) equation providing a basis for real-time,approximate optimal control.     

From Images to Shape Models for Object Detection

We present an object class detection approach which fully integrates the complementary strengths offered by shape matchers. Like an object detector, it can learn class models directly from images, and can localize novel instances in the presence of intra-class variations, clutter, and scale changes. Like a shape matcher, it finds the boundaries of objects, rather than just their bounding-boxes. This is achieved by a novel technique for learning a shape model of an object class given images of example instances. Furthermore, we also integrate Hough-style voting with a non-rigid point matching algorithm to localize the model in cluttered images. As demonstrated by an extensive evaluation, our method can localize object boundaries accurately and does not need segmented examples for training (only bounding-boxes).     

Incremental Learning of Skills in a Task-Parameterized Gaussian Mixture Model

Programming by demonstration techniques facilitate the programming of robots. Some of them allow the generalization of tasks through parameters, although they require new training when trajectories different from the ones used to estimate the model need to be added. One of the ways to re-train a robot is by incremental learning, which supplies additional information of the task and does not require teaching the whole task again. The present study proposes three techniques to add trajectories to a previously estimated task-parameterized Gaussian mixture model. The first technique estimates a new model by accumulating the new trajectory and the set of trajectories generated using the previous model. The second technique permits adding to the parameters of the existent model those obtained for the new trajectories. The third one updates the model parameters by running a modified version of the Expectation-Maximization algorithm, with the information of the new trajectories. The techniques were evaluated in a simulated task and a real one, and they showed better performance than that of the existent model.     

Two-space variability compensation technique for speaker verification in short length and reverberant environments

The performance of state-of-the-art speaker verification in uncontrolled environment is affected by different variabilities. Short duration variability is very common in these scenarios and causes the speaker verification performance to decrease quickly while the duration of verification utterances decreases. Linear discriminant analysis (LDA) is the most common session variability compensation algorithm, nevertheless it presents some shortcomings when trained with insufficient data. In this paper we introduce two methods for session variability compensation to deal with short-length utterances on i-vector space. The first method proposes to incorporate the short duration variability information in the within-class variance estimation process. The second proposes to compensate the session and short duration variabilities in two different spaces with LDA algorithms (2S-LDA). First, we analyzed the behavior of the within and between class scatters in the first proposed method. Then, both proposed methods are evaluated on telephone session from NIST SRE-08 for different duration of the evaluation utterances: full (average 2.5 min), 20, 15, 10 and 5 s. The 2S-LDA method obtains good results on different short-length utterances conditions in the evaluations, with a EER relative average improvement of 1.58%, compared to the best baseline (WCCN[LDA]). Finally, we applied the 2S-LDA method in speaker verification under reverberant environment, using different reverberant conditions from Reverb challenge 2013, obtaining an improvement of 8.96 and 23% under matched and mismatched reverberant conditions, respectively.     

Rumor spreading in social networks

Social networks are an interesting class of graphs likely to become of increasing importance in the future, not only theoretically, but also for its probable applications to ad hoc and mobile networking. Rumor spreading is one of the basic mechanisms for information dissemination in networks; its relevance stemming from its simplicity of implementation and effectiveness. In this paper, we study the performance of rumor spreading in the classic preferential attachment model of Bollobás et al. which is considered to be a valuable model for social networks. We prove that, in these networks: (a) The standard PUSH-PULL strategy delivers the message to all nodes within O(log²n) rounds with high probability; (b) by themselves, PUSH and PULL require polynomially many rounds. (These results are under the assumption that m, the number of new links added with each new node is at least 2. If m=1 the graph is disconnected with high probability, so no rumor spreading strategy can work.) Our analysis is based on a careful study of some new properties of preferential attachment graphs which could be of independent interest.     

SusyMath: A Mathematica package for quantum superfield calculations

SusyMath is a Mathematica package for quantum superfield calculations. It defines a standard form to translate the correction to the effective action corresponding to a given supergraph into a Mathematica expression, which is then evaluated and simplified. Several functions for manipulations of these expressions are provided, and the package also has the ability to save the outcomes of its calculations in form.

Program summary

Title of program: SusyMathCatalogue identifier:ADYQ_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADYQ_v1_0Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland, also at http://fma.if.usp.br/~alysson/SusyMathLicensing provisions: LGPL, CPC non-profit use licenseProgramming language: MathematicaPlatform: Any platform supporting Mathematica 4.0 or higherComputer tested on: PC (Athlon64 X2 +3800); 1 GB RAMOperating system under which the program has been tested: Linux (Debian 4.0); XOrg 7.0.22; Mathematica 5.2No. of lines in distributed program, including test data, etc.:42 472No. of bytes in distributed program, including test data, etc.:471 596Distribution format:tar.gzNature of the problem: Evaluate quantum corrections to the effective action of supersymmetric field theories, formulated in the superfield formalism, both in three- and four-spacetime dimensions.Solution method: A set of procedures for integration by parts, application of the algebra of covariant derivatives and Grassman integration, along with several auxiliary functions, is introduced.Restrictions: At the moment, the background field method is not implemented, but the system is designed to be further generalized.Running time: Depends on the complexity of the problem. From seconds for simpler one-loop diagrams to several hours for simple two-loop graphs.     

Arity and alternation: a proper hierarchy in higher order logics

We study the effect of simultaneously bounding the maximal-arity of the higher-order variables and the alternation of quantifiers in higher-order logics, as to their expressive power on finite structures (or relational databases). Let $\mathit{AA}^i(r,m)$ be the class of (i?+?1)-th order logic formulae where all quantifiers are grouped together at the beginning of the formulae, forming m alternating blocks of consecutive existential and universal quantifiers, and such that the maximal-arity (a generalization of the concept of arity, not just the maximal of the arities of the quantified variables) of the higher-order variables is bounded by r. Note that, the order of the quantifiers in the prefix may be mixed. We show that, for every i?≥?1, the resulting $\mathit{AA}^i(r,m)$ hierarchy of formulae of (i?+?1)-th order logic is proper. This extends a result by Makowsky and Pnueli who proved that the same hierarchy in second-order logic is proper. In both cases the strategy used to prove the results consists in considering formulae which, represented as finite structures, satisfy themselves. As the well known diagonalization argument applies here, this gives rise, for each order i and each level of the $\mathit{AA}^i(r,m)$ hierarchy of arity and alternation, to a class of formulae which is not definable in that level, but which is definable in a higher level of the same hierarchy. We then use a similar argument to prove that the classes of $\Sigma^i_m \cup \Pi^i_m$ formulae in which the higher-order variables of all orders up to i?+?1 have maximal-arity at most r, also induce a proper hierarchy in each higher-order logic of order i?≥?3. It is not known whether the correspondent hierarchy in second-order logic is proper. Using the concept of finite model truth definitions introduced by M. Mostowski, we give a sufficient condition for that to be the case.