Control of Cavity-Induced Drag Using Steady Jets

Separated shear layer oscillations in open cavities can induce drag, noise and vibration. This issue has many aerospace applications such as Landing gears and control surfaces [1]. Recently, phase-cancellation [1] and offinstability frequency excitation [2] & [3] approaches have been incorporated in different open-loop and feedback control systems. Despite the high control performance of these systems, further enhancement is still possible. In this study, steady jets, as shown in fig. 1, are forced through 2mm, two-dimensional slots at the leading and trailing edges of the cavity. In order to study the performance of this novel approach, different cases will be examined, including: jet combination (blowing from cavity leading edge, suction from cavity leading edge and blowing-suction), jet angle (parallel or deflected jet) and jet-to-free stream velocity factor /.

Realizing time crystals in discrete quantum few-body systems

The exotic phenomenon of time translation symmetry breaking under periodic driving - the time crystal - has been shown to occur in many-body systems even in clean setups where disorder is absent. In this work, we propose the realization of time-crystals in few-body systems, both in the context of trapped cold atoms with strong interactions and of a circuit of superconducting qubits. We show how these two models can be treated in a fairly similar way by adopting an effective spin chain description, to which we apply a simple driving protocol. We focus on the response of the magnetization in the presence of imperfect pulses and interactions, and show how the results can be interpreted, in the cold atomic case, in the context of experiments with trapped bosons and fermions. Furthermore, we provide a set of realistic parameters for the implementation of the superconducting circuit.Comment: 6 pages, 4 figure

Multiqubit State Learning with Entangling Quantum Generative Adversarial Networks

The increasing success of classical generative adversarial networks (GANs) has inspired several quantum versions of GANs. Fully quantum mechanical applications of such quantum GANs have been limited to one- and two-qubit systems. In this paper, we investigate the entangling quantum GAN (EQ-GAN) for multiqubit learning. We show that the EQ-GAN can learn a circuit more efficiently compared to a swap test. We also consider the EQ-GAN for learning VQE-approximated eigenstates, and find that it generates excellent overlap matrix elements when learning VQE states of small molecules. However, this does not directly translate to a good estimate of the energy due to a lack of phase estimation. Finally, we consider random state learning with the EQ-GAN for up to six qubits, using different two-qubit gates, and show that it is capable of learning completely random quantum states, something which could be useful in quantum state loading.Comment: 6 pages, 4 figures, 1 table + Supporting materia

Theory of Bubble Nucleation and Cooperativity in DNA Melting

The onset of intermediate states (denaturation bubbles) and their role during the melting transition of DNA are studied using the Peyrard-Bishop-Daxuois model by Monte Carlo simulations with no adjustable parameters. Comparison is made with previously published experimental results finding excellent agreement. Melting curves, critical DNA segment length for stability of bubbles and the possibility of a two states transition are studied.Comment: 4 figures. Accepted for publication in Physical Review Letter

Simulation of transition dynamics to high confinement in fusion plasmas

The transition dynamics from the low (L) to the high (H) confinement mode in magnetically confined plasmas is investigated using a first-principles four-field fluid model. Numerical results are in close agreement with measurements from the Experimental Advanced Superconducting Tokamak - EAST. Particularly, the slow transition with an intermediate dithering phase is well reproduced by the numerical solutions. Additionally, the model reproduces the experimentally determined L-H transition power threshold scaling that the ion power threshold increases with increasing particle density. The results hold promise for developing predictive models of the transition, essential for understanding and optimizing future fusion power reactors

Probing the mechanical unzipping of DNA

A study of the micromechanical unzipping of DNA in the framework of the Peyrard-Bishop-Dauxois model is presented. We introduce a Monte Carlo technique that allows accurate determination of the dependence of the unzipping forces on unzipping speed and temperature. Our findings agree quantitatively with experimental results for homogeneous DNA, and for $\lambda$-phage DNA we reproduce the recently obtained experimental force-temperature phase diagram. Finally, we argue that there may be fundamental differences between {\em in vivo} and {\em in vitro} DNA unzipping

Self-regulation processes and health: The importance of optimism and goal adjustment

ABSTRACT This article discusses how self-regulatory models can be used to understand people’s response to health threats. The article begins with a general discussion of the principles and assumptions of self-regulatory models of behavior. Two distinct lines of research are then presented addressing two important processes of adaptive self-regulation. First, we provide a brief overview of the literature on optimism and adjustment to chronic disease and other health outcomes. Second, we present an overview of the process of disengagement from unattainable goals, focusing on recent research. We close by making recommendations for future research. The purpose of this article is to discuss some of the ways in which self-regulatory models of behavior can help us understand people’s responses to health threats. This article begins with a general discussion of a set of orienting assumptions and principles embedded in models of self-regulation of behavior, placing the heaviest emphasis on our own approach. We then describe two distinct lines of researc