SETI science working group report

This report covers the initial activities and deliberations of a continuing working group asked to assist the SETI Program Office at NASA. Seven chapters present the group's consensus on objectives, strategies, and plans for instrumental R&D and for a microwave search for extraterrestrial in intelligence (SETI) projected for the end of this decade. Thirteen appendixes reflect the views of their individual authors. Included are discussions of the 8-million-channel spectrum analyzer architecture and the proof-of-concept device under development; signal detection, recognition, and identification on-line in the presence of noise and radio interference; the 1-10 GHz sky survey and the 1-3 GHz targeted search envisaged; and the mutual interests of SETI and radio astronomy. The report ends with a selective, annotated SETI reading list of pro and contra SETI publications

Polaron Transport in the Paramagnetic Phase of Electron-Doped Manganites

The electrical resistivity, Hall coefficient, and thermopower as functions of temperature are reported for lightly electron-doped Ca(1-x)La(x)MnO(3)(0 <= x <= 0.10). Unlike the case of hole-doped ferromagnetic manganites, the magnitude and temperature dependence of the Hall mobility for these compounds is found to be inconsistent with small-polaron theory. The transport data are better described by the Feynman polaron theory and imply intermediate coupling (alpha \~ 5.4) with a band effective mass, m*~4.3 m_0, and a polaron mass, m_p ~ 10 m_0.Comment: 7 pp., 7 Fig.s, to be published, PR

Towards Safe Machine Learning for CPS: Infer Uncertainty from Training Data

Machine learning (ML) techniques are increasingly applied to decision-making and control problems in Cyber-Physical Systems among which many are safety-critical, e.g., chemical plants, robotics, autonomous vehicles. Despite the significant benefits brought by ML techniques, they also raise additional safety issues because 1) most expressive and powerful ML models are not transparent and behave as a black box and 2) the training data which plays a crucial role in ML safety is usually incomplete. An important technique to achieve safety for ML models is "Safe Fail", i.e., a model selects a reject option and applies the backup solution, a traditional controller or a human operator for example, when it has low confidence in a prediction. Data-driven models produced by ML algorithms learn from training data, and hence they are only as good as the examples they have learnt. As pointed in [17], ML models work well in the "training space" (i.e., feature space with sufficient training data), but they could not extrapolate beyond the training space. As observed in many previous studies, a feature space that lacks training data generally has a much higher error rate than the one that contains sufficient training samples [31]. Therefore, it is essential to identify the training space and avoid extrapolating beyond the training space. In this paper, we propose an efficient Feature Space Partitioning Tree (FSPT) to address this problem. Using experiments, we also show that, a strong relationship exists between model performance and FSPT score.Comment: Publication rights licensed to AC

Theory for nucleation at an interface and magnetization reversal of a two-layer nanowire

Nucleation at the interface between two adjoining regions with dissimilar physical properties is investigated using a model for magnetization reversal of a two-layer ferromagnetic nanowire. Each layer of the nanowire is considered to have a different degree of magnetic anisotropy, representing a hard magnetic layer exchange-coupled to a softer layer. A magnetic field applied along the easy axis causes the softer layer to reverse, forming a domain wall close to the interface. For small applied fields this state is metastable and complete reversal of the nanowire takes place via activation over a barrier. A reversal mechanism involving nucleation at an interface is proposed, whereby a domain wall changes in width as it passes from the soft layer to the hard layer during activation. Langer’s statistical theory for the decay of a metastable state is used to derive rates of magnetization reversal, and simple formulas are found in limiting cases for the activation energy, rate of reversal, and critical field at which the metastable state becomes unstable. These formulas depend on the anisotropy difference between each layer, and the behavior of the reversal rate prefactor is interpreted in terms of activation entropy and domain-wall dynamics

Anisotropic weakly localized transport in nitrogen-doped ultrananocrystalline diamond films

We establish the dominant effect of anisotropic weak localization (WL) in three dimensions associated with a propagative Fermi surface, on the conductivity correction in heavily nitrogen doped ultrananocrystalline diamond (UNCD) films based on magneto-resistance studies at low temperatures. Also, low temperature electrical conductivity can show weakly localized transport in 3D combined with the effect of electron-electron interactions in these materials, which is remarkably different from the conductivity in 2DWL or strong localization regime. The corresponding dephasing time of electronic wavefunctions in these systems described as ~ T^-p with p < 1, follows a relatively weak temperature dependence compared to the generally expected nature for bulk dirty metals having $p \geq 1$. The temperature dependence of Hall (electron) mobility together with an enhanced electron density has been used to interpret the unusual magneto-transport features and show delocalized electronic transport in these n-type UNCD films, which can be described as low-dimensional superlattice structures.Comment: 27 pages, 6 figures, To be published in Physical Review

Saturation properties and incompressibility of nuclear matter: A consistent determination from nuclear masses

Starting with a two-body effective nucleon-nucleon interaction, it is shown that the infinite nuclear matter model of atomic nuclei is more appropriate than the conventional Bethe-Weizsacker like mass formulae to extract saturation properties of nuclear matter from nuclear masses. In particular, the saturation density thus obtained agrees with that of electron scattering data and the Hartree-Fock calculations. For the first time using nuclear mass formula, the radius constant $r_0$=1.138 fm and binding energy per nucleon $a_v$ = -16.11 MeV, corresponding to the infinite nuclear matter, are consistently obtained from the same source. An important offshoot of this study is the determination of nuclear matter incompressibility $K_{\infty}$ to be 288$\pm$ 28 MeV using the same source of nuclear masses as input.Comment: 14 latex pages, five figures available on request ( to appear in Phy. Rev. C

Variation bounds for spherical averages

We consider variation operators for the family of spherical means, with special emphasis on $L^p\to L^q$ estimatesMTM2017-82160-C2-1-P RYC2018-025477-I Ikerbasqu