A Near-Infrared Spectroscopic Study of Young Field Ultracool Dwarfs

We present a near-infrared (0.9-2.4 microns) spectroscopic study of 73 field ultracool dwarfs having spectroscopic and/or kinematic evidence of youth (~10-300 Myr). Our sample is composed of 48 low-resolution (R~100) spectra and 41 moderate-resolution spectra (R>~750-2000). First, we establish a method for spectral typing M5-L7 dwarfs at near-IR wavelengths that is independent of gravity. We find that both visual and index-based classification in the near-IR provide consistent spectral types with optical spectral types, though with a small systematic offset in the case of visual classification at J and K band. Second, we examine features in the spectra of ~10 Myr ultracool dwarfs to define a set of gravity-sensitive indices based on FeH, VO, K, Na and H-band continuum shape. We then create an index-based method for classifying the gravities of M6-L5 dwarfs that provides consistent results with gravity classifications from optical spectroscopy. Our index-based classification can distinguish between young and dusty objects. Guided by the resulting classifications, we propose a set of low-gravity spectral standards for the near-IR. Finally, we estimate the ages corresponding to our gravity classifications.Comment: Published in ApJ. IDL program for calculating indices (allers13_index.pro) included in the source gzipped ta

Class-based Rough Approximation with Dominance Principle

Dominance-based Rough Set Approach (DRSA), as the extension of Pawlak's Rough Set theory, is effective and fundamentally important in Multiple Criteria Decision Analysis (MCDA). In previous DRSA models, the definitions of the upper and lower approximations are preserving the class unions rather than the singleton class. In this paper, we propose a new Class-based Rough Approximation with respect to a series of previous DRSA models, including Classical DRSA model, VC-DRSA model and VP-DRSA model. In addition, the new class-based reducts are investigated.Comment: Submitted to IEEE-GrC201

Pulsar-black hole binaries: prospects for new gravity tests with future radio telescopes

The anticipated discovery of a pulsar in orbit with a black hole is expected to provide a unique laboratory for black hole physics and gravity. In this context, the next generation of radio telescopes, like the Five-hundred-metre Aperture Spherical radio Telescope (FAST) and the Square Kilometre Array (SKA), with their unprecedented sensitivity, will play a key role. In this paper, we investigate the capability of future radio telescopes to probe the spacetime of a black hole and test gravity theories, by timing a pulsar orbiting a stellar-mass-black-hole (SBH). Based on mock data simulations, we show that a few years of timing observations of a sufficiently compact pulsar-SBH (PSR-SBH) system with future radio telescopes would allow precise measurements of the black hole mass and spin. A measurement precision of one per cent can be expected for the spin. Measuring the quadrupole moment of the black hole, needed to test GR's no-hair theorem, requires extreme system configurations with compact orbits and a large SBH mass. Additionally, we show that a PSR-SBH system can lead to greatly improved constraints on alternative gravity theories even if they predict black holes (practically) identical to GR's. This is demonstrated for a specific class of scalar-tensor theories. Finally, we investigate the requirements for searching for PSR-SBH systems. It is shown that the high sensitivity of the next generation of radio telescopes is key for discovering compact PSR-SBH systems, as it will allow for sufficiently short survey integration times.Comment: 20 pages, 11 figures, 1 table, accepted for publication in MNRA

Robust Lattice Alignment for K-user MIMO Interference Channels with Imperfect Channel Knowledge

In this paper, we consider a robust lattice alignment design for K-user quasi-static MIMO interference channels with imperfect channel knowledge. With random Gaussian inputs, the conventional interference alignment (IA) method has the feasibility problem when the channel is quasi-static. On the other hand, structured lattices can create structured interference as opposed to the random interference caused by random Gaussian symbols. The structured interference space can be exploited to transmit the desired signals over the gaps. However, the existing alignment methods on the lattice codes for quasi-static channels either require infinite SNR or symmetric interference channel coefficients. Furthermore, perfect channel state information (CSI) is required for these alignment methods, which is difficult to achieve in practice. In this paper, we propose a robust lattice alignment method for quasi-static MIMO interference channels with imperfect CSI at all SNR regimes, and a two-stage decoding algorithm to decode the desired signal from the structured interference space. We derive the achievable data rate based on the proposed robust lattice alignment method, where the design of the precoders, decorrelators, scaling coefficients and interference quantization coefficients is jointly formulated as a mixed integer and continuous optimization problem. The effect of imperfect CSI is also accommodated in the optimization formulation, and hence the derived solution is robust to imperfect CSI. We also design a low complex iterative optimization algorithm for our robust lattice alignment method by using the existing iterative IA algorithm that was designed for the conventional IA method. Numerical results verify the advantages of the proposed robust lattice alignment method