The ground state of a Gross–Pitaevskii energy with general potential in the Thomas–Fermi limit

We study the ground state which minimizes a Gross–Pitaevskii energy with general non-radial trapping potential, under the unit mass constraint, in the Thomas–Fermi limit where a small parameter tends to 0. This ground state plays an important role in the mathematical treatment of recent experiments on the phenomenon of Bose–Einstein condensation, and in the study of various types of solutions of nonhomogeneous defocusing nonlinear Schrodinger equations. Many of these applications require delicate estimates for the behavior of the ground state near the boundary of the condensate, as the singular parameter tends to zero, in the vicinity of which the ground state has irregular behavior in the form of a steep corner layer. In particular, the role of this layer is important in order to detect the presence of vortices in the small density region of the condensate, understand the superfluid flow around an obstacle, and also has a leading order contribution in the energy. In contrast to previous approaches, we utilize a perturbation argument to go beyond the classical Thomas–Fermi approximation and accurately approximate the layer by the Hastings–McLeod solution of the Painleve–II equation. This settles an open problem, answered very recently only for the special case of the model harmonic potential. In fact, we even improve upon previous results that relied heavily on the radial symmetry of the potential trap. Moreover, we show that the ground state has the maximal regularity available, namely it remains uniformly bounded in the 1/2-Holder norm, which is the exact Holder regularity of the singular limit profile, as the singular parameter tends to zero. Our study is highly motivated by an interesting open problem posed recently by Aftalion, Jerrard, and Royo-Letelier, and an open question of Gallo and Pelinovsky, concerning the removal of the radial symmetry assumption from the potential trap

Enhancement of Secure Hospital Healthcare Monitoring System Based–Software Defined Network (SDN) with Machine Learning

Handling delicate and crucial knowledge by healthcare providers requires security measures to prevent unapproved use. Software-defined networks (SDNs) are extensively used in medical facilities to ensure resource efficiency, security, and superior network management and management. Despite these advantages, SDNs present a significant threat from various assaults due to the sensitivity  of patient information. Our work's primary goal is to propose a global connection between SDN technology and machine learning-based assaults in healthcare. This paper aims to draw attention to a few relevant options. Additionally, we give a framework using software-defined network principles that illustrate linkages between a collection of people, each of whom has a Nano network residing within their bodies, and medical providers via the local network of a medical center. In health care, the initiative is sometimes called an issue of machine learning assault systems and amenities. The current possibilities for machine learning cyberattacks on the medical industry are quite promising. It is also highly well-liked because of its capacity to identify and assess. From a single instrument to the enormous amounts of data gathered, this evolution radically changes how we approach medicine. This work uses a range of ML approaches and attacks to test MLCAH (Machine Learning-based Cyber Attacks Healthcare). For every combination of machine learning methods and assaults, an efficiency assessment highlights the benefits and drawbacks of different algorithms for defending against a specific assault

Numerical Analysis of Horizontal Geothermal Heat Exchanger at Various Burial Depths for Solar PV/T Cooling in South Iraq Weather

Received: 22 May 2024. Revised: 13 September 2024. Accepted: 5 December 2024. Available online: 31 December 2024.It can be described that high solar radiation intensity is the basis for the performance of solar photovoltaic modules. Therefore, it causes a decrease in the efficiency of the panel due to the increase in its surface temperature and thus affects its lifespan due to periodic thermal effects. This paper presents an analysis of the PV panel performance and thermal problems and attempts to solve them by cooling it during the day using water circulation in a heat exchanger embedded in the ground. The present work aims to analyze the thermal exchange process of geothermal heat exchangers by computational simulation approach. The research parameters included changing the depth of the copper pipe loop in the soil at 0.5, 1.0, and 1.5 m, and water flow rate of 0.0278 kg/s, copper pipe length, and thermal conductivity of soil in steady conditions employing the yearly weather data of southern desert in Iraq. The computational simulation results manifested that during the solar day, the fluctuations of outlet water temperature are diminished when the burial depth of the heat exchanger is around 2.0 m due to the soil's elevated thermal inertia. In addition, the temperature of the ground is comparatively stable and these values are higher than the inlet water temperature in winter with low values in summer.The Energy and Renewable Energies Technology Center has helped in the current work and the authors would like to thank the University of Technology-Iraq for that support. Hilla University College is also thanked for the financial support in conducting the research

The interacting nature of dwarf galaxies hosting superluminous supernovae

(Abridged) Type I superluminous supernovae (SLSNe I) are rare, powerful explosions whose mechanism and progenitors remain elusive. SLSNe I show a preference for low-metallicity, actively star-forming dwarf galaxies. We investigate whether the hosts of SLSNe I show increased evidence for interaction. We use a sample of 42 SLSN I images obtained with $\textit{HST}$ and measure the number of companion galaxies by counting the objects detected within a given radius from the host. As a comparison, we used two Monte Carlo-based methods to estimate the expected average number of companion objects in the same images, as well as a sample of 32 galaxies that have hosted long gamma-ray bursts (GRBs). About 50% of SLSN I hosts have at least one major companion (within a flux ratio of 1:4) within 5 kpc. The average number of major companions per SLSN I host galaxy is $0.70^{+0.19}_{-0.14}$. Our Monte Carlo comparison methods yield a lower number of companions for random objects of similar brightness in the same image or for the SLSN host after randomly redistributing the sources in the same image. The Anderson-Darling test shows that this difference is statistically significant independent of the redshift range. The same is true for the projected distance distribution of the companions. The SLSN I hosts are, thus, found in areas of their images, where the object number density is greater than average. SLSN I hosts have more companions than GRB hosts ($0.44^{+0.25}_{-0.13}$ companions per host distributed over 25% of the hosts) but the difference is not statistically significant. The difference between their separations is, however, marginally significant. The dwarf galaxies hosting SLSNe I are often part of interacting systems. This suggests that SLSNe I progenitors are formed after a recent burst of star formation. Low metallicity alone cannot explain this tendency.Comment: Accepted for publication in A&A. In v2 replaced graphs with higher quality PDF version

Heat Exchanger Design with Topology Optimization

Topology optimization is proving to be a valuable design tool for physical systems, especially for structural systems. However, its application in the field of heat transfer is less evident but is constantly progressing. In this chapter, we would like to introduce topology optimization in the context of heat exchanger design to the general reader. We also provide a chronological review of available literature to see the current progress of topology optimization in the field of heat transfer and heat exchanger design. We expect that topology optimization will prove to be a valuable tool in heat exchanger design for the coming years

Hydrodynamic nucleation of quantized vortex pairs in a polariton quantum fluid

Quantized vortices appear in quantum gases at the breakdown of superfluidity. In liquid helium and cold atomic gases, they have been indentified as the quantum counterpart of turbulence in classical fluids. In the solid state, composite light-matter bosons known as exciton polaritons have enabled studies of non-equilibrium quantum gases and superfluidity. However, there has been no experimental evidence of hydrodynamic nucleation of polariton vortices so far. Here we report the experimental study of a polariton fluid flowing past an obstacle and the observation of nucleation of quantized vortex pairs in the wake of the obstacle. We image the nucleation mechanism and track the motion of the vortices along the flow. The nucleation conditions are established in terms of local fluid density and velocity measured on the obstacle perimeter. The experimental results are successfully reproduced by numerical simulations based on the resolution of the Gross-Pitaevskii equation

Performance assessment of real-time data management on wireless sensor networks

Technological advances in recent years have allowed the maturity of Wireless Sensor Networks (WSNs), which aim at performing environmental monitoring and data collection. This sort of network is composed of hundreds, thousands or probably even millions of tiny smart computers known as wireless sensor nodes, which may be battery powered, equipped with sensors, a radio transceiver, a Central Processing Unit (CPU) and some memory. However due to the small size and the requirements of low-cost nodes, these sensor node resources such as processing power, storage and especially energy are very limited. Once the sensors perform their measurements from the environment, the problem of data storing and querying arises. In fact, the sensors have restricted storage capacity and the on-going interaction between sensors and environment results huge amounts of data. Techniques for data storage and query in WSN can be based on either external storage or local storage. The external storage, called warehousing approach, is a centralized system on which the data gathered by the sensors are periodically sent to a central database server where user queries are processed. The local storage, in the other hand called distributed approach, exploits the capabilities of sensors calculation and the sensors act as local databases. The data is stored in a central database server and in the devices themselves, enabling one to query both. The WSNs are used in a wide variety of applications, which may perform certain operations on collected sensor data. However, for certain applications, such as real-time applications, the sensor data must closely reflect the current state of the targeted environment. However, the environment changes constantly and the data is collected in discreet moments of time. As such, the collected data has a temporal validity, and as time advances, it becomes less accurate, until it does not reflect the state of the environment any longer. Thus, these applications must query and analyze the data in a bounded time in order to make decisions and to react efficiently, such as industrial automation, aviation, sensors network, and so on. In this context, the design of efficient real-time data management solutions is necessary to deal with both time constraints and energy consumption. This thesis studies the real-time data management techniques for WSNs. It particularly it focuses on the study of the challenges in handling real-time data storage and query for WSNs and on the efficient real-time data management solutions for WSNs. First, the main specifications of real-time data management are identified and the available real-time data management solutions for WSNs in the literature are presented. Secondly, in order to provide an energy-efficient real-time data management solution, the techniques used to manage data and queries in WSNs based on the distributed paradigm are deeply studied. In fact, many research works argue that the distributed approach is the most energy-efficient way of managing data and queries in WSNs, instead of performing the warehousing. In addition, this approach can provide quasi real-time query processing because the most current data will be retrieved from the network. Thirdly, based on these two studies and considering the complexity of developing, testing, and debugging this kind of complex system, a model for a simulation framework of the real-time databases management on WSN that uses a distributed approach and its implementation are proposed. This will help to explore various solutions of real-time database techniques on WSNs before deployment for economizing money and time. Moreover, one may improve the proposed model by adding the simulation of protocols or place part of this simulator on another available simulator. For validating the model, a case study considering real-time constraints as well as energy constraints is discussed. Fourth, a new architecture that combines statistical modeling techniques with the distributed approach and a query processing algorithm to optimize the real-time user query processing are proposed. This combination allows performing a query processing algorithm based on admission control that uses the error tolerance and the probabilistic confidence interval as admission parameters. The experiments based on real world data sets as well as synthetic data sets demonstrate that the proposed solution optimizes the real-time query processing to save more energy while meeting low latency.Fundação para a Ciência e Tecnologi

An adaptive scheme for quantum state tomography

The process of inferring and reconstructing the state of a quantum system from the results of measurements, better known as quantum state tomography, constitutes a crucial task in the emerging field of quantum technologies. Today it is possible to experimentally control quantum systems containing tens of entangled qubits and perform measurements of arbitrary observables with great accuracy. However, in order to complete characterize an unknown $n$-qubit state, quantum state tomography requires a number of measurements which grows exponentially with $n$. A possible way to avoid this problem consists in performing an incomplete tomographic procedure able to provide a good estimate of the true state with few measurements. This thesis proposes a scheme for $n$-qubit state tomography which aims to improve the fidelity between the reconstructed state and the target state. In particular, the scheme identifies the next measurement to perform based on the knowledge already acquired from the previous measurements on the experimental prepared state. The performance of this scheme was finally analyzed by means of simulations of quantum state tomography with product measurements as well as with entangled measurements. In both cases one observes that the here proposed adaptive scheme significantly outperforms a standard scheme in terms of the fidelity of the reconstructed state

Solitons, vortices and shell structure in ultracold atomic quantum systems

This dissertation deals with finite-size effects in a few different quantum many-body phenomena in ultracold atomic systems. The finite-sized systems were simulated numerically using both mean-field methods and methods beyond mean-field, e.g. quadratic configuration interaction and exact diagonalization. The thesis is based on five scientific papers:Paper I is about the finite-size effects in the dynamics of a few-body soliton-like state. The collapses and revivals of the solitary wavefront in the particle density is characterized both analytically and numerically in the limit of weak interactions.Paper II analyzes a scheme to renormalize the contact interaction when used for exact diagonalization in a two-dimensional space. By relating the coupling strength in the diagonalization using the two-particle system, for which regularized solutions exists, converged results are obtained.Paper III deals with the formation of quantized vortices when stirring a harmonically trapped finite-sized system with a quadrupole deformation. I the energy spectrum the avoided crossing is found to be described by either of two types of correlated states. The type of avoided crossing can be controlled by the inclusion of an extra quartic deformation. Hysteresis in the mean-field description is found to be related to the types of avoided crossings exhibited and the full many-body time-evolution is compared to mean-field results. Paper IV investigates vortices in rotating fermionic droplets with dipole-dipole interactions. The vortex structure is found to still be present after the interaction is made anisotropic by having the dipoles tilt. Paper V contains an investigation of the effects on shell structure in fermionic droplets with dipole-dipole interactions. For a anisotropic harmonic oscillator, by tilting the dipoles, the shell structure of an isotropic oscillator can be restored