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Sohail Ahmed

Publications and source records attributed to Sohail Ahmed.

3 recordsLinked to original sources

Phase separation dynamics and active turbulence in a binary fluid mixture

Active matter, encompassing natural systems, converts surrounding energy to sustain autonomous motion, exhibiting unique non-equilibrium behaviors such as active turbulence and phase separation. In this study, we develop a continuum two-fluid model for a binary mixture of an active nematic and a passive Newtonian fluid, coupling Cahn-Hilliard dynamics for phase separation with Beris-Edwards nematohydrodynamics and two distinct momentum equations connected by viscous drag. A phase field-based lattice Boltzmann method is used to investigate the existence of active turbulence and phase separation in the binary mixture. We find that active stress enhances velocity and vorticity differences between phases, and that increased active concentration promotes stronger inter-fluid coupling. Activity not only amplifies turbulent fluctuations but also arrests domain coarsening, leading to a finite characteristic length scale that decreases with increasing activity. Key parameters, like active parameter, tumbling parameter and Frank elastic constant, affect the characteristic scale of flow. These results highlight the role of relative motion and drag-mediated momentum transfer in active binary mixtures, providing a framework for studying systems such as bacterial suspensions in polymeric fluids or active emulsions.

cond-mat.soft

Engineering Optical and Mirror Bi-stability Mechanically

We explain optical and mirrors displacement bistability in a hybrid optomechanical system in the presence of a strong laser driving field and a weak probe field. External modulating fields are applied selectively on movable mirrors. We show that the optomechanical coupling, electromechanical Coulomb coupling and, amplitude & phase of external modulating fields are important parameters to control the optical and mirror displacement bistable behaviour. The parameters values are taken according to presently available experiments. The study may be applied to the realization of a tunable electro opto mechanical switch depending on the optomechanical and Coulomb coupling, frequencies, threshold power, and the amplitude and phase of external mechanical pumps.

quant-ph

A Survey of Conventional and Artificial Intelligence / Learning based Resource Allocation and Interference Mitigation Schemes in D2D Enabled Networks

5th generation networks are envisioned to provide seamless and ubiquitous connection to 1000-fold more devices and is believed to provide ultra-low latency and higher data rates up to tens of Gbps. Different technologies enabling these requirements are being developed including mmWave communications, Massive MIMO and beamforming, Device to Device (D2D) communications and Heterogeneous Networks. D2D communication is a promising technology to enable applications requiring high bandwidth such as online streaming and online gaming etc. It can also provide ultra- low latencies required for applications like vehicle to vehicle communication for autonomous driving. D2D communication can provide higher data rates with high energy efficiency and spectral efficiency compared to conventional communication. The performance benefits of D2D communication can be best achieved when D2D users reuses the spectrum being utilized by the conventional cellular users. This spectrum sharing in a multi-tier heterogeneous network will introduce complex interference among D2D users and cellular users which needs to be resolved. Motivated by limited number of surveys for interference mitigation and resource allocation in D2D enabled heterogeneous networks, we have surveyed different conventional and artificial intelligence based interference mitigation and resource allocation schemes developed in recent years. Our contribution lies in the analysis of conventional interference mitigation techniques and their shortcomings. Finally, the strengths of AI based techniques are determined and open research challenges deduced from the recent research are presented.

cs.AI