11,435 research outputs found
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
Simple implementation of high fidelity controlled-SWAP gates and quantum circuit exponentiation of non-Hermitian gates
The swap gate is an entangling swapping gate where the qubits obtain a
phase of if the state of the qubits is swapped. Here we present a simple
implementation of the controlled-swap gate. The gate can be implemented with
several controls and works by applying a single flux pulse. The gate time is
independent of the number of controls, and we find high fidelities for any
number of controls. We discuss an implementation of the gates using
superconducting circuits and present a realistic implementation proposal, where
we have taken decoherence noise and fabrication errors on the superconducting
chip in to account, by Monte Carlo simulating possible errors. The general idea
presented in this paper is, however, not limited to such implementations. An
exponentiation of quantum gates is desired in some quantum information schemes
and we therefore also present a quantum circuit for probabilistic
exponentiating the swap gate and other non-Hermitian gates.Comment: 16 Pages, 10 figures, 4 tables. Version accepted for publication in
PR
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 -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
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