João C. Costa

SPaCe-GEM: solver of the Einstein equations using GPUs under the gravitoelectromagnetic approximation

Under specific conditions, there is a formal analogy between the fundamental equations of electromagnetism and relativistic gravitation, described by the Einstein field equations of general relativity. In this paper, we report on how we have used this analogy to implement a solver of the Einstein equations adapting algorithms initially developed for electromagnetism, combined with methods of heterogeneous supercomputing, in GPU that can achieve fast computing and exhibit good performance. We also present the results of the simulations used to validate our solver.

Development of a quantum particle in cell algorithm in GPU for solving Maxwell-Bloch equations

In this paper we report on the development of a numerical solver for Vlasov equations based on heterogeneous supercomputing using GPGPUs. The solver adapts techniques from many-body simulation, namely the particlein-cell approach, to describe the interaction between the electromagnetic field and atomic gas whose internal state can be described by the multilevel Bloch equations. We also present the benchmark and performance analysis of the code. We investigate the interaction between two coherent light beams, as a case of study to demonstrate the validation of the code.

Tensor-Based Methods for Blind Spatial Signature Estimation in Multidimensional Sensor Arrays

The estimation of spatial signatures and spatial frequencies is crucial for several practical applications such as radar, sonar, and wireless communications. In this paper, we propose two generalized iterative estimation algorithms to the case in which a multidimensional (-D) sensor array is used at the receiver. The first tensor-based algorithm is an -D blind spatial signature estimator that operates in scenarios where the source’s covariance matrix is nondiagonal and unknown. The second tensor-based algorithm is formulated for the case in which the sources are uncorrelated and exploits the dual-symmetry of the covariance tensor. Additionally, a new tensor-based formulation is proposed for an -shaped array configuration. Simulation results show that our proposed schemes outperform the state-of-the-art matrix-based and tensor-based techniques.

Tensor-based methods for blind spatial signature estimation under arbitrary and unknown source covariance structure ☆

Abstract Spatial signature estimation is a problem encountered in several applications in signal processing such as mobile communications, sonar, radar, astronomy and seismology. In this paper, we propose higher-order tensor methods to solve the blind spatial signature estimation problem using planar arrays. By assuming that sources powers vary between successive time blocks, we recast the spatial and spatiotemporal covariance models for the received data as third-order PARATUCK2 and fourth-order Tucker4 tensor decompositions, respectively. Firstly, by exploiting the multilinear algebraic structure of the proposed tensor models, new iterative algorithms are formulated to blindly estimate the spatial signatures. Secondly, in order to achieve a better spatial resolution, we propose an expanded form of spatial smoothing that returns extra spatial dimensions in comparison with the traditional approaches. Additionally, by exploiting the higher-order structure of the resulting expanded tensor model, a multilinear noise reduction preprocessing step is proposed via higher-order singular value decomposition. We show that the increase on the tensor order provides a more efficient denoising, and consequently a better performance compared to existing spatial smoothing techniques. Finally, a solution based on a multi-stage Khatri–Rao factorization procedure is incorporated as the final stage of our proposed estimators. Our results demonstrate that the proposed tensor methods yield more accurate spatial signature estimates than competing approaches while operating in a challenging scenario where the source covariance structure is unknown and arbitrary (non-diagonal), which is actually the case when sample covariances are computed from a limited number of snapshots.

Influence of Passage Number on the Impact of the Secretome of Adipose Tissue Stem Cells on Neural Survival, Neurodifferentiation and Axonal Growth

Mesenchymal stem cells (MSCs), and within them adipose tissue derived stem cells (ASCs), have been shown to have therapeutic effects on central nervous system (CNS) cell populations. Such effects have been mostly attributed to soluble factors, as well as vesicles, present in their secretome. Yet, little is known about the impact that MSC passaging might have in the secretion therapeutic profile. Our aim was to show how human ASCs (hASCs) passage number influences the effect of their secretome in neuronal survival, differentiation and axonal growth. For this purpose, post-natal rat hippocampal primary cultures, human neural progenitor cell (hNPCs) cultures and dorsal root ganglia (DRGs) explants were incubated with secretome, collected as conditioned media (CM), obtained from hASCs in P3, P6, P9 and P12. Results showed no differences when comparing percentages of MAP-2 positive cells (a mature neuronal marker) in neuronal cultures or hNPCs, after incubation with hASCs secretome from different passages. The same was observed regarding DRG neurite outgrowth. In order to characterize the secretomes obtained from different passages, a proteomic analysis was performed, revealing that its composition did not vary significantly with passage number P3 to P12. Results allowed us to identify several key proteins, such as pigment epithelium derived factor (PEDF), DJ-1, interleucin-6 (IL-6) and galectin, all of which have already proven to play neuroprotective and neurodifferentiating roles. Proteins that promote neurite outgrowth were also found present, such as semaphorin 7A and glypican-1. We conclude that cellular passaging does not influence significantly hASCss secretome properties especially their ability to support post-natal neuronal survival, induce neurodifferentiation and promote axonal growth.

Solving the multi-level Maxwell-Bloch equations using GPGPU computing for the simulation of nonlinear optics in atomic gases

We present a numerical implementation of a solver for the Maxwell-Bloch equations to calculate the propagation of a light pulse in a nonlinear medium composed of an atomic gas in one, two and three dimensional systems. This implementation solves the wave equation of light using a finite difference method in the time domain scheme, while the Bloch equations for the atomic population in each point of the simulation domain are integrated using splitting methods. We present numerical simulations of atomic-gas systems and performance benchmarks.

Indoors positioning through VLC technology using an a-SiC:H photodetector

The work presented in this paper supports the viability of a navigation system based on Visible Light Communication (VLC) for indoors applications. The system design uses RGB LEDs and an a:SiC:H photodetector. An optoelectronic characterization of the devices used in the integrated system is presented to support the main results, namely the decoding strategy. The photodetector is a pin-pin heterostructure that works as an optical filter, presenting a selective spectral sensitivity dependent on the external optical bias. The red and blue light emitted from the white RGB LEDs were modulated at different frequencies. With this configuration each cardinal direction becomes assigned to a specific set of optical excitation (wavelength and frequency). The decoding of the output photocurrent allows the identification of the input optical signals and the determination of the correspondent spatial direction. The localization algorithm makes use of the Fourier transform to identify the frequencies present in the photocurrent signal and the wavelength filtering properties of the sensor under front and back optical bias to detect the existing red and blue signals. The viability of the system is demonstrated through the implementation of an automatic algorithm to infer the photodetector cardinal direction. Additional research on the light intensity is presented to investigate the accuracy of the spatial position along a cardinal direction.

Tunable light fluids using quantum atomic optical systems

The realization of tabletop optical analogue experiments of superfluidity relies on the engineering of suitable optical media, with tailored optical properties. This work shows how quantum atomic optical systems can be used to develop highly tunable optical media, with localized control of both linear and nonlinear susceptibility. Introducing the hydrodynamic description of light, the superfluidity of light in these atomic media is investigated through GPU-enhanced numerical simulations, with the numeric observation of the superfluidic signature of suppressed scattering through a defect.

Space-time refraction of light in time dependent media: the analogue within the analogue

The problem of electromagnetic wave propagation in time varying media is very old, but in recent years it has been revisited at a more fundamental level leading to the introduction of several new concepts, such as Time Refraction. These concepts explore the symmetries between space and time and can be transposed to different fields by establishing powerful analogies between effects in Electrodynamics, Optics and problems in Quantum Cosmology and in what is sometimes called Analogue Gravity. We examine the alteration of the ordinary (spatial) Fresnel laws of refraction at the interface between two media when the optical properties of one of the media varies in time.

The analogue quantum mechanical of plasmonic atoms

Localized plasmons in metallic nanostructures present strong analogies with Quantum Mechanical problems of particles trapped in potential wells. In this paper we take this analogy further using the Madelung Formalism of Quantum Mechanics to express the fluid equations describing the charge density of the conduction electrons and corresponding interaction with light in terms of an effective generalized Non-linear Schr¨odinger equations. Within this context, it is possible to develop the analogy of a plasmonic atom and molecule that exhibits Rabi oscillations, Stark effect, among other Quantum Mechanical effects.