Magnetic Energy Morphing, Capacitive Concept for Ni0.3Zn0.4Ca0.3Fe2O4 Nanoparticles Embedded in Graphene Oxide Matrix, and Studies of Wideband Tunable Microwave Absorption.

Nanoparticles of Ni0.3Zn0.4Ca0.3Fe2O4 (NZCF) were successfully prepared by the facile wet chemical method coupled with the sonochemical method. These nanoparticles were embedded in a graphene oxide (GO) matrix (NZCFG). Rietveld analyses of X-ray diffraction, transmission electron microscope, scanning electron microscope, and X-ray photoelectron spectroscopy were carried out to extract different relevant information regarding the structure, morphology, and ionic state. A major improvement in saturation magnetization is achieved due to substitution of Ca2+ in the ferrite lattice. Interestingly, the observed value of electromagnetic absorption for a sample thickness of 1.5 mm is ∼-67.7 dB at 13.3 GHz, and the corresponding bandwidth is 5.73 GHz. The Cole-Cole plot, the Jonscher power-law fitting, and the Nyquist plot confirm the probability of improved hopping conductance and attractive capacitive behavior in NZCFG. The presence of magnetic energy morphing in combination with a higher attenuation constant, lower skin depth, and various forms of resonance and relaxation makes NZCFG the most suitable for microwave absorption.

Bound on Efficiency of Heat Engine from Uncertainty Relation Viewpoint.

Quantum cycles in established heat engines can be modeled with various quantum systems as working substances. For example, a heat engine can be modeled with an infinite potential well as the working substance to determine the efficiency and work done. However, in this method, the relationship between the quantum observables and the physically measurable parameters-i.e., the efficiency and work done-is not well understood from the quantum mechanics approach. A detailed analysis is needed to link the thermodynamic variables (on which the efficiency and work done depends) with the uncertainty principle for better understanding. Here, we present the connection of the sum uncertainty relation of position and momentum operators with thermodynamic variables in the quantum heat engine model. We are able to determine the upper and lower bounds on the efficiency of the heat engine through the uncertainty relation.

Binary Black Hole Information Loss Paradox and Future Prospects.

Various techniques to tackle the black hole information paradox have been proposed. A new way out to tackle the paradox is via the use of a pseudo-density operator. This approach has successfully dealt with the problem with a two-qubit entangle system for a single black hole. In this paper, we present the interaction with a binary black hole system by using an arrangement of the three-qubit system of Greenberger-Horne-Zeilinger (GHZ) state. We show that our results are in excellent agreement with the theoretical value. We have also studied the interaction between the two black holes by considering the correlation between the qubits in the binary black hole system. The results depict a complete agreement with the proposed model. In addition to the verification, we also propose how modern detection of gravitational waves can be used on our optical setup as an input source, thus bridging the gap with the gravitational wave's observational resources in terms of studying black hole properties with respect to quantum information and entanglement.

Multi-GPU Acceleration of Branchless Distance Driven Projection and Backprojection for Clinical Helical CT.

Model-based image reconstruction (MBIR) techniques have the potential to generate high quality images from noisy measurements and a small number of projections which can reduce the x-ray dose in patients. These MBIR techniques rely on projection and backprojection to refine an image estimate. One of the widely used projectors for these modern MBIR based technique is called branchless distance driven (DD) projection and backprojection. While this method produces superior quality images, the computational cost of iterative updates keeps it from being ubiquitous in clinical applications. In this paper, we provide several new parallelization ideas for concurrent execution of the DD projectors in multi-GPU systems using CUDA programming tools. We have introduced some novel schemes for dividing the projection data and image voxels over multiple GPUs to avoid runtime overhead and inter-device synchronization issues. We have also reduced the complexity of overlap calculation of the algorithm by eliminating the common projection plane and directly projecting the detector boundaries onto image voxel boundaries. To reduce the time required for calculating the overlap between the detector edges and image voxel boundaries, we have proposed a pre-accumulation technique to accumulate image intensities in perpendicular 2D image slabs (from a 3D image) before projection and after backprojection to ensure our DD kernels run faster in parallel GPU threads. For the implementation of our iterative MBIR technique we use a parallel multi-GPU version of the alternating minimization (AM) algorithm with penalized likelihood update. The time performance using our proposed reconstruction method with Siemens Sensation 16 patient scan data shows an average of 24 times speedup using a single TITAN X GPU and 74 times speedup using 3 TITAN X GPUs in parallel for combined projection and backprojection.