Prefect Transfer of Quantum States on Spin Chain with Dzyaloshinskii- Moriya interaction in inhomogeneous Magnetic field

In this work, we use the Hamiltonian of a modified Dzyaloshinskii-Moriya model and investigate the perfect transfer of the quantum state on the spin networks. In this paper, we calculate fidelity in which fidelity depends on magnetic field and another parameters. Then, by using the numerical analysis we show that the fidelity of the transferred state is determined by magnetic field $B$, exchange coupling $J$ and the Dzyaloshinskii- Moriya interaction $D$. We also found that the perfect transfer of the quantum state is possible with condition $B \gg \Gamma^2\omega^{N/2}$ where $\Gamma =((J+iD)/2)$ and $\omega=\Gamma^*/ \Gamma$.Comment: 8 pages, 2 figure

A Microwave Imaging Procedure for Lung Lesion Detection: Preliminary Results on Multilayer Phantoms

In this work, a feasibility study for lung lesion detection through microwave imaging based on Huygens’ principle (HP) has been performed using multilayer oval shaped phantoms mimicking human torso having a cylindrically shaped inclusion simulating lung lesion. First, validation of the proposed imaging method has been performed through phantom experiments using a dedicated realistic human torso model inside an anechoic chamber, employing a frequency range of 1–5 GHz. Subsequently, the miniaturized torso phantom validation (using both single and double inclusion scenarios) has been accomplished using a microwave imaging (MWI) device, which operates in free space using two antennas in multi-bistatic configuration. The identification of the target’s presence in the lung layer has been achieved on the obtained images after applying both of the following artifact removal procedures: (i) the “rotation subtraction” method using two adjacent transmitting antenna positions, and (ii) the “ideal” artifact removal procedure utilizing the difference between received signals from unhealthy and healthy scenarios. In addition, a quantitative analysis of the obtained images was executed based on the definition of signal to clutter ratio (SCR). The obtained results verify that HP can be utilized successfully to discover the presence and location of the inclusion in the lung-mimicking phantom, achieving an SCR of 9.88 dB

Phase Transition in a Three-States Reaction-Diffusion System

A one-dimensional reaction-diffusion model consisting of two species of particles and vacancies on a ring is introduced. The number of particles in one species is conserved while in the other species it can fluctuate because of creation and annihilation of particles. It has been shown that the model undergoes a continuous phase transition from a phase where the currents of different species of particles are equal to another phase in which they are different. The total density of particles and also their currents in each phase are calculated exactly.Comment: 6 page

Free space operating microwave imaging device for bone lesion detection: a phantom investigation

In this letter, a phantom validation of a low complexity microwave imaging device operating in free space in the 1-6.5 GHz frequency band is presented. The device, initially constructed for breast cancer detection, measures the scattered signals in a multi-bistatic fashion and employs an imaging procedure based on Huygens principle. Detection has been achieved in both bone fracture lesion and bone marrow lesion scenarios using the superimposition of five doublet transmitting positions, after applying the rotation subtraction artefact removal method. A resolution of 5 mm and a signal to clutter ratio (3.35 in linear scale) are achieved confirming the advantage of employing multiple transmitting positions on increased detection capability

Developing Artefact Removal Algorithms to Process Data from a Microwave Imaging Device for Haemorrhagic Stroke Detection

In this paper, we present an investigation of different artefact removal methods for ultra-wideband Microwave Imaging (MWI) to evaluate and quantify current methods in a real environment through measurements using an MWI device. The MWI device measures the scattered signals in a multi-bistatic fashion and employs an imaging procedure based on Huygens principle. A simple two-layered phantom mimicking human head tissue is realised, applying a cylindrically shaped inclusion to emulate brain haemorrhage. Detection has been successfully achieved using the superimposition of five transmitter triplet positions, after applying different artefact removal methods, with the inclusion positioned at 0°, 90°, 180°, and 270°. The different artifact removal methods have been proposed for comparison to improve the stroke detection process. To provide a valid comparison between these methods, image quantification metrics are presented. An “ideal/reference” image is used to compare the artefact removal methods. Moreover, the quantification of artefact removal procedures through measurements using MWI device is performed

3D Huygens Principle based Microwave Imaging through MammoWave Device: Validation through Phantoms.

This work focuses on developing a 3D microwave imaging (MWI) algorithm based on the Huygens principle (HP). Specifically, a novel, fast MWI device (MammoWave) has been presented and exploited for its capabilities of extending image reconstruction from 2D to 3D. For this purpose, dedicated phantoms containing 3D structured inclusion have been prepared with mixtures having different dielectric properties. Phantom measurements have been performed at multiple planes along the z-axis by simultaneously changing the transmitter and receiver antenna height via the graphic user interface (GUI) integrated with MammoWave. We have recorded the complex S21 multi-quote data at multiple planes along the z-axis. The complex multidimensional raw data has been processed via an enhanced HP-based image algorithm for 3D image reconstruction. This paper demonstrates the successful detection and 3D visualization of the inclusion with varying dimensions at multiple planes/cross-sections along the z-axis with a dimensional error lower than 7.5%. Moreover, the paper shows successful detection and 3D visualization of the inclusion in a skull-mimicking phantom having a cylindrically shaped inclusion, with the location of the detected inclusion in agreement with the experimental setup. Additionally, the localization of a 3D structured spherical inclusion has been shown in a more complex scenario using a 3-layer cylindrically shaped phantom, along with the corresponding 3D image reconstruction and visualization

UWB Microwave Imaging for Inclusions Detection: Methodology for Comparing Artefact Removal Algorithms

An investigation is presented on Artefact Removal Methods for Ultra-Wideband (UWB) Microwave Imaging. Simulations have been done representing UWB signals transmitted onto a cylindrical head-mimicking phantom containing an inclusion having dielectric properties imitating an haemorrhagic stroke. The ideal image is constructed by applying a Huygens’ Principle based imaging algorithm to the difference between the electric field outside the cylinder with an inclusion and the electric field outside the same cylinder with no inclusion. Eight different artefact removal methods are then applied, with the inclusion positioned at \u1d70b and −\u1d70b/4 radians, respectively. The ideal image is then used as a reference image to compare the artefact removal methods employing a novel Image Quality Index, calculated using a weighted combination of image quality metrics. The Summed Symmetric Differential method performed very well in our simulations

Frequency Selection to Improve the Performance of Microwave Breast Cancer Detecting Support Vector Model by Using Genetic Algorithm

This paper presents an innovative paradigm for breast cancer detection by leveraging a Support Vector Machine (SVM) based model fueled with numerical data obtained from the cutting-edge MammoWave device. Operating in the microwave spectrum between 1 to 9 GHz and boasting a 5 MHz sampling rate, MammoWave emerges as a groundbreaking solution, specifically addressing the limitations posed by conventional methods, particularly for women under 50. This technological advancement opens a promising avenue for more frequent and precise breast health monitoring. To enhance the efficacy of the SVM model, our research introduces a metaheuristic-based methodology, strategically navigating the selection of frequencies crucial for breast cancer detection within the MammoWave dataset. Overcoming the challenge of judicious frequency selection, our approach employs wrapper methods in metaheuristic algorithms. These algorithms iterate through subsets of frequencies, guided by the SVM model's performance, culminating in the identification of the optimal frequency subset that significantly refines precision in breast cancer detection. Moreover, a novel cost function is proposed to strike a balanced trade-off between sensitivity and specificity, ensuring an acceptable accuracy rate. The results exhibit a noteworthy 10% increase in specificity, a milestone achievement for the MammoWave device, yielding an overall detection rate of approximately 62%. This research underscores the potential of seamlessly integrating metaheuristic algorithms into frequency selection, thereby contributing significantly to the ongoing refinement of MammoWave's capabilities in breast cancer detection

Microwave imaging for stroke detection: validation on head-mimicking phantom

This paper provides initial results on the efficacy of Huygens Principle (HP) microwave imaging for haemorrhagic stroke detection. This is done using both simulations and measurements in an anechoic chamber. Microstrip antennas operating between 1 and 2 GHz have been designed, constructed and used for imaging a human head model in Computer Simulation Technology (CST) software. A 3D model consisting of human head tissues of Ella is employed in the simulation. An emulated haemorrhagic stroke with the dielectric properties equivalent to the blood has been inserted in Ella. Moreover, a 3-layered head-mimicking phantom containing an inclusion has been constructed. Frequency-domain measurements have been performed in an anechoic chamber using a Vector Network Analyser arrangement to obtain the transfer function (S21) between two antennas. Both simulations and measurements show that the HP based technique may be used for haemorrhagic stroke detection. Among linear scattering techniques, the HP based technique allows to detect dielectric inhomogeneities in the frequency domain. HP can also be used if the antennas and phantom are in free space, i.e. no coupling liquid is required. Detection of the haemorrhagic stroke has been achieved after removing the artefacts. Artefact removal is an essential step of any microwave imaging system and current artefact removal approaches have been shown to be ineffective in the specific scenario of brain imaging. However, one of this paper’s novel contributions is the proposal of an artefact removal algorithm based on a subtraction between S21 obtained using measurements, which achieves improved performance while having a much lower computational complexity

A Phantom Investigation to Quantify Huygens Principle Based Microwave Imaging for Bone Lesion Detection

This paper demonstrates the outcomes of a feasibility study of a microwave imaging procedure based on the Huygens principle for bone lesion detection. This study has been performed using a dedicated phantom and validated through measurements in the frequency range of 1–3 GHz using one receiving and one transmitting antenna in free space. Specifically, a multilayered bone phantom, which is comprised of cortical bone and bone marrow layers, was fabricated. The identification of the lesion’s presence in different bone layers was performed on images that were derived after processing through Huygens’ principle, the S21 signals measured inside an anechoic chamber in multi-bistatic fashion. The quantification of the obtained images was carried out by introducing parameters such as the resolution and signal-to-clutter ratio (SCR). The impact of different frequencies and bandwidths (in the 1–3 GHz range) in lesion detection was investigated. The findings showed that the frequency range of 1.5–2.5 GHz offered the best resolution (1.1 cm) and SCR (2.22 on a linear scale). Subtraction between S21 obtained using two slightly displaced transmitting positions was employed to remove the artefacts; the best artefact removal was obtained when the spatial displacement was approximately of the same magnitude as the dimension of the lesio