7,743 research outputs found
Composite quantum systems and environment-induced heating
In recent years, much attention has been paid to the development of
techniques which transfer trapped particles to very low temperatures. Here we
focus our attention on a heating mechanism which contributes to the finite
temperature limit in laser sideband cooling experiments with trapped ions. It
is emphasized that similar heating processes might be present in a variety of
composite quantum systems whose components couple individually to different
environments. For example, quantum optical heating effects might contribute
significantly to the very high temperatures which occur during the collapse
phase in sonoluminescence experiments. It might even be possible to design
composite quantum systems, like atom-cavity systems, such that they
continuously emit photons even in the absence of external driving.Comment: 4 pages, 1 figur
A finite element method for a fourth order surface equation with application to the onset of cell blebbing
A variational problem for a fourth order parabolic surface partial differential equation is discussed. It contains nonlinear lower order terms, on which we only make abstract assumptions, and which need to be defined for specified problems.We derive a semi-discrete scheme based on the surface finite element method, show a-priori error estimates, and use the analytical results to prove well-posedness. Furthermore, we present a computational framework where specific problems can be conveniently implemented and, later on, altered with relative ease. It uses a domain specific language implemented in Python. The high level program control can also be done within the Python scripting environment. The computationally expensive step of evolving the solution over time is carried out by binding to an efficient C++ software back-end. The study is motivated by cell blebbing, which can be instrumental for cell migration. Starting with a force balance for the cell membrane, we derive a continuum model for some mechanical and geometrical aspects of the onset of blebbing in a form that fits into the abstract framework.
It is flexible in that it allows for amending force contributions related to membrane tension or the presence of linker molecules between membrane and cell cortex. Cell membrane geometries given in terms of a parametrisation or obtained from image data can be accounted for by the software. The use of a domain specific language to describe the model makes is straightforward to add additional effects such as reaction-diffusion equations modelling some biochemistry on the cell membrane.Some numerical simulations illustrate the approach
Amplify-and-Forward Relaying in Two-Hop Diffusion-Based Molecular Communication Networks
This paper studies a three-node network in which an intermediate
nano-transceiver, acting as a relay, is placed between a nano-transmitter and a
nano-receiver to improve the range of diffusion-based molecular communication.
Motivated by the relaying protocols used in traditional wireless communication
systems, we study amplify-and-forward (AF) relaying with fixed and variable
amplification factor for use in molecular communication systems. To this end,
we derive a closed-form expression for the expected end-to-end error
probability. Furthermore, we derive a closed-form expression for the optimal
amplification factor at the relay node for minimization of an approximation of
the expected error probability of the network. Our analytical and simulation
results show the potential of AF relaying to improve the overall performance of
nano-networks.Comment: 7 pages, 6 figures, 1 table. Submitted to the 2015 IEEE Global
Communications Conference (GLOBECOM) on April 15, 201
Empirically Analyzing the Effect of Dataset Biases on Deep Face Recognition Systems
It is unknown what kind of biases modern in the wild face datasets have
because of their lack of annotation. A direct consequence of this is that total
recognition rates alone only provide limited insight about the generalization
ability of a Deep Convolutional Neural Networks (DCNNs). We propose to
empirically study the effect of different types of dataset biases on the
generalization ability of DCNNs. Using synthetically generated face images, we
study the face recognition rate as a function of interpretable parameters such
as face pose and light. The proposed method allows valuable details about the
generalization performance of different DCNN architectures to be observed and
compared. In our experiments, we find that: 1) Indeed, dataset bias has a
significant influence on the generalization performance of DCNNs. 2) DCNNs can
generalize surprisingly well to unseen illumination conditions and large
sampling gaps in the pose variation. 3) Using the presented methodology we
reveal that the VGG-16 architecture outperforms the AlexNet architecture at
face recognition tasks because it can much better generalize to unseen face
poses, although it has significantly more parameters. 4) We uncover a main
limitation of current DCNN architectures, which is the difficulty to generalize
when different identities to not share the same pose variation. 5) We
demonstrate that our findings on synthetic data also apply when learning from
real-world data. Our face image generator is publicly available to enable the
community to benchmark other DCNN architectures.Comment: Accepted to CVPR 2018 Workshop on Analysis and Modeling of Faces and
Gestures (AMFG
Pragmatic Low-Power Interoperability: ContikiMAC vs TinyOS LPL
Standardization has driven interoperability at multiple layers of the stack, such as the routing and application layers, standardization of radio duty cycling mechanisms have not yet reached the same maturity. In this work, we pitch the two de facto standard flavors of sender-initiated radio duty cycling mechanisms against each other: ContikiMAC and TinyOS LPL. Our aim is to explore pragmatic interoperability mechanisms at the radio duty cycling layer. This will lead to better understanding of interoperability problems moving forward, as radio duty cycling mechanisms get standardized. Our results show that the two flavors can be configured to operate together but that parameter configuration may severely hurt performance
Charming Higgs
We present a simple supersymmetric model where the dominant decay mode of the
lightest Higgs boson is h->2eta->4c where eta is a light pseudoscalar and c is
the charm quark. For such decays the Higgs mass can be smaller than 100 GeV
without conflict with experiment. Together with the fact that both the Higgs
and the pseudoscalar eta are pseudo-Goldstone bosons, this resolves the little
hierarchy problem.Comment: 6 pages, 2 figure
Fast all-optical nuclear spin echo technique based on EIT
We demonstrate an all-optical Raman spin echo technique, using
Electromagnetically Induced Transparency (EIT) to create the different pulses
of the spin echo sequence: initialization, pi-rotation, and readout. The first
pulse of the sequence induces coherence directly from a mixed state, and the
technique is used to measure the nuclear spin coherence of an inhomogeneously
broadened ensemble of rare-earth ions (Pr). In contrast to previous
experiments it does not require any preparatory hole burning pulse sequences,
which greatly shortens the total duration of the sequence. The effect of the
different pulses is characterized by quantum state tomography and is compared
with simulations. We demonstrate two applications of the technique by using the
spin echo sequence to accurately compensate a magnetic field across our sample,
and to measure the coherence time at high temperatures up to 11 K, where
standard preparation techniques are difficult to implement. We explore the
potential of the technique and possible applications.Comment: 8 pages, 6 figure
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