3,263 research outputs found
Complete description of polarization effects in emission of a photon by an electron in the field of a strong laser wave
We consider emission of a photon by an electron in the field of a strong
laser wave. Polarization effects in this process are important for a number of
physical problems. A probability of this process for circularly or linearly
polarized laser photons and for arbitrary polarization of all other particles
is calculated. We obtain the complete set of functions which describe such a
probability in a compact invariant form. Besides, we discuss in some detail the
polarization effects in the kinematics relevant to the problem of electron to
photon conversion at photon-photon and photon-electron colliders.Comment: 18 pages, minor changes, published versio
Singular Cross Sections in Muon Colliders
We address the problem that the cross section for the collisions of unstable
particles diverges, if calculated by standard methods. This problem is
considered for beams much smaller than the decay length of the unstable
particle, much larger than the decay length and finally also for pancake-
shaped beams. We find that in all cases this problem can be solved by taking
into account the production/propagation of the unstable particle and/or the
width of the incoming wave packets in momentum space.Comment: 12 pages, 3 figures. References corrected. Removed one sentence about
a fact that was known. Added explaination why one of our graphs is different
as compared to one of the references. Clearified explaination in sec. 3.
The Electroweak Standard Model in the Axial Gauge
We derive the Feynman rules of the standard model in the axial gauge. After
this we prove that the fields and do not correspond to
physical particles. As a consequence, these fields cannot appear as incoming or
outgoing lines in Feynman graphs. We then calculate the contribution of these
fields in the case of a particular decay mode of the top quark.Comment: 16 pages, no figures. Added derivation of polarization su
Jamming-Resistant Learning in Wireless Networks
We consider capacity maximization in wireless networks under adversarial
interference conditions. There are n links, each consisting of a sender and a
receiver, which repeatedly try to perform a successful transmission. In each
time step, the success of attempted transmissions depends on interference
conditions, which are captured by an interference model (e.g. the SINR model).
Additionally, an adversarial jammer can render a (1-delta)-fraction of time
steps unsuccessful. For this scenario, we analyze a framework for distributed
learning algorithms to maximize the number of successful transmissions. Our
main result is an algorithm based on no-regret learning converging to an
O(1/delta)-approximation. It provides even a constant-factor approximation when
the jammer exactly blocks a (1-delta)-fraction of time steps. In addition, we
consider a stochastic jammer, for which we obtain a constant-factor
approximation after a polynomial number of time steps. We also consider more
general settings, in which links arrive and depart dynamically, and where each
sender tries to reach multiple receivers. Our algorithms perform favorably in
simulations.Comment: 22 pages, 2 figures, typos remove
Expressiveness and Completeness in Abstraction
We study two notions of expressiveness, which have appeared in abstraction
theory for model checking, and find them incomparable in general. In
particular, we show that according to the most widely used notion, the class of
Kripke Modal Transition Systems is strictly less expressive than the class of
Generalised Kripke Modal Transition Systems (a generalised variant of Kripke
Modal Transition Systems equipped with hypertransitions). Furthermore, we
investigate the ability of an abstraction framework to prove a formula with a
finite abstract model, a property known as completeness. We address the issue
of completeness from a general perspective: the way it depends on certain
abstraction parameters, as well as its relationship with expressiveness.Comment: In Proceedings EXPRESS/SOS 2012, arXiv:1208.244
Matrix effect in bio-analysis of illicit drugs with LC-MS/MS: Influence of ionization type, sample preparation, and biofluid
AbstractThe purpose of the present work was to evaluate the synergistic effect of ionization type, sample preparation technique, and bio-fluid on the presence of matrix effect in quantitative liquid chromatography (LC)-MS/MS analysis of illicit drugs by post-column infusion experiments with morphine (10-ÎĽg/mL solution). Three bio-fluids (urine, oral fluid, and plasma) were pretreated with four sample preparation procedures [direct injection, dilution, protein precipitation, solid-phase extraction (SPE)] and analyzed by both LC-electrospray ionization (ESI)-MS/MS and LC-atmospheric pressure chemical ionization (APCI)-MS/MS. Our results indicated that both ionization types showed matrix effect, but ESI was more susceptible than APCI. Sample preparation could reduce (clean up) or magnify (pre-concentrate) matrix effect. Residual matrix components were specific to each bio-fluid and interfered at different time points in the chromatogram. We evaluated matrix effect in an early stage of method development and combined optimal ionization type and sample preparation technique for each bio-fluid. Simple dilution of urine was sufficient to allow for the analysis of the analytes of interest by LC-APCI-MS/MS. Acetonitrile protein precipitation provided both sample clean up and concentration for oral fluid analysis, while SPE was necessary for extensive clean up of plasma prior to LC-APCI-MS/MS
An Online Approach to Dynamic Channel Access and Transmission Scheduling
Making judicious channel access and transmission scheduling decisions is
essential for improving performance as well as energy and spectral efficiency
in multichannel wireless systems. This problem has been a subject of extensive
study in the past decade, and the resulting dynamic and opportunistic channel
access schemes can bring potentially significant improvement over traditional
schemes. However, a common and severe limitation of these dynamic schemes is
that they almost always require some form of a priori knowledge of the channel
statistics. A natural remedy is a learning framework, which has also been
extensively studied in the same context, but a typical learning algorithm in
this literature seeks only the best static policy, with performance measured by
weak regret, rather than learning a good dynamic channel access policy. There
is thus a clear disconnect between what an optimal channel access policy can
achieve with known channel statistics that actively exploits temporal, spatial
and spectral diversity, and what a typical existing learning algorithm aims
for, which is the static use of a single channel devoid of diversity gain. In
this paper we bridge this gap by designing learning algorithms that track known
optimal or sub-optimal dynamic channel access and transmission scheduling
policies, thereby yielding performance measured by a form of strong regret, the
accumulated difference between the reward returned by an optimal solution when
a priori information is available and that by our online algorithm. We do so in
the context of two specific algorithms that appeared in [1] and [2],
respectively, the former for a multiuser single-channel setting and the latter
for a single-user multichannel setting. In both cases we show that our
algorithms achieve sub-linear regret uniform in time and outperforms the
standard weak-regret learning algorithms.Comment: 10 pages, to appear in MobiHoc 201
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