Strange matter in the universe

The strange quark matter hypothesis is one of the most exciting speculations of the XX Century Physics. If this hypothesis is correct, the ground state of the matter would be the strange matter, which could form the core of compact objects like neutron stars or even more exotic objects like quarks stars. Due to the high-density and low-temperature regime in these stars, the interaction between quarks through gluon exchange could favor the appearance of a color superconducting state, significantl modifying the equation of state of the system. In this paper we present a general overview of this Subject, taking also into account the effect of strong magnetic field in the quark stars.

Compact Stars and Magnetized CFL Matter

The stability of the color flavor locked phase in the presence of a strong magnetic field is investigated within the phenomenological MIT bag model. It is found that the minimum value of the energy per baryon in a color flavor locked state at vanishing pressure is lower than the corresponding one for unpaired magnetized strange quark matter and, as the magnetic field increases, the energy per baryon decreases. This implies that magnetized color flavor locked matter is more stable and could become the ground state inside neutron stars. The anisotropy of the pressures is discussed. The mass-radius relation for such stars is also studied.

Magnetized color flavor locked state and compact stars

The stability of the color flavor locked phase in the presence of a strong magnetic field is investigated within the phenomenological MIT bag model, taking into account the variation of the strange quark mass, the baryon density, the magnetic field, as well as the bag and gap parameters. It is found that the minimum value of the energy per baryon in a color flavor locked state at vanishing pressure is lower than the corresponding one for unpaired magnetized strange quark matter and, as the magnetic field increases, the energy per baryon decreases. This implies that magnetized colorflavor locked matter is more stable and could become the ground state inside neutron stars. The mass-radius relation for such stars is also studied.

A Compact and Scalable RNS Architecture

Conferência: IEEE 24th International Conference on Application-Specific Systems, Architectures and Processors (ASAP)- Jun 05-07, 2013

Design and optimization of na ultra wideband and compact microwave antenna for radiometric monitoring of brain temperature

We present the modeling efforts on antenna design and frequency selection to monitor brain temperature during prolonged surgery using noninvasive microwave radiometry. A tapered log-spiral antenna design is chosen for its wideband characteristics that allow higher power collection from deep brain. Parametric analysis with the software HFSS is used to optimize antenna performance for deep brain temperature sensing. Radiometric antenna efficiency (eta) is evaluated in terms of the ratio of power collected from brain to total power received by the antenna. Anatomical information extracted from several adult computed tomography scans is used to establish design parameters for constructing an accurate layered 3-D tissue phantom. This head phantom includes separate brain and scalp regions, with tissue equivalent liquids circulating at independent temperatures on either side of an intact skull. The optimized frequency band is 1.1-1.6 GHz producing an average antenna efficiency of 50.3% from a two turn log-spiral antenna. The entire sensor package is contained in a lightweight and low-profile 2.8 cm diameter by 1.5 cm high assembly that can be held in place over the skin with an electromagnetic interference shielding adhesive patch. The calculated radiometric equivalent brain temperature tracks within 0.4 degrees C of the measured brain phantom temperature when the brain phantom is lowered 10. C and then returned to the original temperature (37 degrees C) over a 4.6-h experiment. The numerical and experimental results demonstrate that the optimized 2.5-cm log-spiral antenna is well suited for the noninvasive radiometric sensing of deep brain temperature.

Compact, frequency reconfigurable, printed monopole antenna

This paper proposes a possible implementation of a compact printed monopole antenna, useful to operate in UMTS and WLAN bands. In order to accomplish that, a miniaturization technique based on the application of chip inductors is used in conjunction with frequency reconfiguration capability. The chip inductors change the impedance response of the monopole, allowing to reduce the resonant frequency. In order to be able to operate the antenna in these two different frequencies, an antenna reconfiguration technique based on PIN diodes is applied. This procedure allows the change of the active form of the antenna leading to a shift in the resonant frequency. The prototype measurements show good agreement with the simulation results.

Parallel GPU architecture for hyperspectral unmixing based on augmented Lagrangian method

Hyperspectral imaging has become one of the main topics in remote sensing applications, which comprise hundreds of spectral bands at different (almost contiguous) wavelength channels over the same area generating large data volumes comprising several GBs per flight. This high spectral resolution can be used for object detection and for discriminate between different objects based on their spectral characteristics. One of the main problems involved in hyperspectral analysis is the presence of mixed pixels, which arise when the spacial resolution of the sensor is not able to separate spectrally distinct materials. Spectral unmixing is one of the most important task for hyperspectral data exploitation. However, the unmixing algorithms can be computationally very expensive, and even high power consuming, which compromises the use in applications under on-board constraints. In recent years, graphics processing units (GPUs) have evolved into highly parallel and programmable systems. Specifically, several hyperspectral imaging algorithms have shown to be able to benefit from this hardware taking advantage of the extremely high floating-point processing performance, compact size, huge memory bandwidth, and relatively low cost of these units, which make them appealing for onboard data processing. In this paper, we propose a parallel implementation of an augmented Lagragian based method for unsupervised hyperspectral linear unmixing on GPUs using CUDA. The method called simplex identification via split augmented Lagrangian (SISAL) aims to identify the endmembers of a scene, i.e., is able to unmix hyperspectral data sets in which the pure pixel assumption is violated. The efficient implementation of SISAL method presented in this work exploits the GPU architecture at low level, using shared memory and coalesced accesses to memory.