552 research outputs found
Milky Way and Andromeda past-encounters in different gravity models: the impact on the estimated Local Group mass
The Two-body problem of and the Milky Way (MW) galaxies with a
Cosmological Constant background is studied, with emphasis on the possibility
that they experienced Past Encounters. By implementing the Timing Argument
(TA), it is shown that if and the MW have had more than one encounter
then the deduced mass of the Local Group (LG) would be larger. Past encounters
are possible only for non-zero transverse velocity, and their viability is
subject to observations of the imprints of such near collisions. Using a recent
- based measurement of the transverse velocity we show that the presence
of the Cosmological Constant requires the mass for the LG to be higher:
with no Cosmological Constant or
with a Cosmological Constant
background. If the LG has had one past encounter, the LG mass is
with a Cosmological Constant
background. Modified Newtonian Dynamics (MOND) is studied as the accelerations
of the Local Group are fully in the deep-MOND regime. MOND yields the order of
magnitude for the expected baryonic mass only if at least one encounter
occurred. While we only consider the LG as two point masses, our calculations
provide a benchmark for future work with simulations to test Dynamical Friction
and other effects. This model can be also used to test screening mechanisms and
alternative theories of gravity.Comment: 16 pages. A revised versio
Magnetothermal Transport in Spin-Ladder Systems
We study a theoretical model for the magnetothermal conductivity of a
spin-1/2 ladder with low exchange coupling () subject to a strong
magnetic field . Our theory for the thermal transport accounts for the
contribution of spinons coupled to lattice phonon modes in the one-dimensional
lattice. We employ a mapping of the ladder Hamiltonian onto an XXZ spin-chain
in a weaker effective field B_{eff}=B-B_{0}B_{0}=(B_{c1}+B_{c2})/2B{\rm
Br_4(C_5H_{12}N)_2}$ (BPCB).Comment: 14 pages, 4 figure
Evidence for Induced Magnetization in Superconductor-Ferromagnet Hetero-structures: a Scanning Tunnelling Spectroscopy Study
We performed scanning tunneling spectroscopy of c-axis oriented YBCO films on
top of which ferromagnetic SRO islands were grown epitaxially in-situ. When
measured on the ferromagnetic islands, the density of states exhibits small
gap-like features consistent with the expected short range penetration of the
order parameter into the ferromagnet. However, anomalous split-gap structures
are measured on the superconductor in the vicinity of ferromagnetic islands.
This observation may provide evidence for the recently predicted induced
magnetization in the superconductor side of a superconductor/ ferromagnet
junction. The length scale of the effect inside the superconductor was found to
be an order of magnitude larger than the superconducting coherence length. This
is inconsistent with the theoretical prediction of a penetration depth of only
a few superconducting coherence lengths. We discuss a possible origin for this
discrepancy
Finding the Beat: From Socially Coordinated Vocalizations in Songbirds to Rhythmic Entrainment in Humans
Humans and oscine songbirds share the rare capacity for vocal learning. Songbirds have the ability to acquire songs and calls of various rhythms through imitation. In several species, birds can even coordinate the timing of their vocalizations with other individuals in duets that are synchronized with millisecond-accuracy. It is not known, however, if songbirds can perceive rhythms holistically nor if they are capable of spontaneous entrainment to complex rhythms, in a manner similar to humans. Here we review emerging evidence from studies of rhythm generation and vocal coordination across songbirds and humans. In particular, recently developed experimental methods have revealed neural mechanisms underlying the temporal structure of song and have allowed us to test birds\u27 abilities to predict the timing of rhythmic social signals. Surprisingly, zebra finches can readily learn to anticipate the calls of a “vocal robot” partner and alter the timing of their answers to avoid jamming, even in reference to complex rhythmic patterns. This capacity resembles, to some extent, human predictive motor response to an external beat. In songbirds, this is driven, at least in part, by the forebrain song system, which controls song timing and is essential for vocal learning. Building upon previous evidence for spontaneous entrainment in human and non-human vocal learners, we propose a comparative framework for future studies aimed at identifying shared mechanism of rhythm production and perception across songbirds and humans
A kinematic classification of the cosmic web
A new approach for the classification of the cosmic web is presented. In
extension of the previous work of Hahn et al. (2007) and Forero-Romero et al.
(2009) the new algorithm is based on the analysis of the velocity shear tensor
rather than the gravitational tidal tensor. The procedure consists of the
construction of the the shear tensor at each (grid) point in space and the
evaluation of its three eigenvectors. A given point is classified to be either
a void, sheet, filament or a knot according to the number of eigenvalues above
a certain threshold, 0, 1, 2, or 3 respectively. The threshold is treated as a
free parameter that defines the web. The algorithm has been applied to a dark
matter only, high resolution simulation of a box of side-length 64Mpc
and N = particles with the framework of the WMAP5/LCDM model. The
resulting velocity based cosmic web resolves structures down to <0.1Mpc
scales, as opposed to the ~1Mpc scale of the tidal based web. The
under-dense regions are made of extended voids bisected by planar sheets, whose
density is also below the mean. The over-dense regions are vastly dominated by
the linear filaments and knots. The resolution achieved by the velocity based
cosmic web provides a platform for studying the formation of halos and galaxies
within the framework of the cosmic web.Comment: 8 pages, 4 Figures, MNRAS Accepted 2012 June 19. Received 2012 May
10; in original form 2011 August 2
Halo detection via large-scale Bayesian inference
We present a proof-of-concept of a novel and fully Bayesian methodology
designed to detect halos of different masses in cosmological observations
subject to noise and systematic uncertainties. Our methodology combines the
previously published Bayesian large-scale structure inference algorithm, HADES,
and a Bayesian chain rule (the Blackwell-Rao Estimator), which we use to
connect the inferred density field to the properties of dark matter halos. To
demonstrate the capability of our approach we construct a realistic galaxy mock
catalogue emulating the wide-area 6-degree Field Galaxy Survey, which has a
median redshift of approximately 0.05. Application of HADES to the catalogue
provides us with accurately inferred three-dimensional density fields and
corresponding quantification of uncertainties inherent to any cosmological
observation. We then use a cosmological simulation to relate the amplitude of
the density field to the probability of detecting a halo with mass above a
specified threshold. With this information we can sum over the HADES density
field realisations to construct maps of detection probabilities and demonstrate
the validity of this approach within our mock scenario. We find that the
probability of successful of detection of halos in the mock catalogue increases
as a function of the signal-to-noise of the local galaxy observations. Our
proposed methodology can easily be extended to account for more complex
scientific questions and is a promising novel tool to analyse the cosmic
large-scale structure in observations.Comment: 17 pages, 13 figures. Accepted for publication in MNRAS following
moderate correction
Diffusion-limited reactions on a two-dimensional lattice with binary disorder
Reaction-diffusion systems where transition rates exhibit quenched disorder
are common in physical and chemical systems. We study pair reactions on a
periodic two-dimensional lattice, including continuous deposition and
spontaneous desorption of particles. Hopping and desorption are taken to be
thermally activated processes. The activation energies are drawn from a binary
distribution of well depths, corresponding to `shallow' and `deep' sites. This
is the simplest non-trivial distribution, which we use to examine and explain
fundamental features of the system. We simulate the system using kinetic Monte
Carlo methods and provide a thorough understanding of our findings. We show
that the combination of shallow and deep sites broadens the temperature window
in which the reaction is efficient, compared to either homogeneous system. We
also examine the role of spatial correlations, including systems where one type
of site is arranged in a cluster or a sublattice. Finally, we show that a
simple rate equation model reproduces simulation results with very good
accuracy.Comment: 9 pages, 5 figure
Harnessing Soluble NK Cell Killer Receptors for the Generation of Novel Cancer Immune Therapy
The natural cytotoxic receptors (NCRs) are a unique set of activating proteins expressed mainly on the surface of natural killer (NK) cells. The NCRs, which include three members; NKp46, NKp44 and NKp30, are critically involved in NK cytotoxicity against different targets, including a wide range of tumor cells derived from various origins. Even though the tumor ligands of the NCRs have not been identified yet, the selective manner by which these receptors target tumor cells may provide an excellent basis for the development of novel anti-tumor therapies. To test the potential use of the NCRs as anti-tumor agents, we generated soluble NCR-Ig fusion proteins in which the constant region of human IgG1 was fused to the extracellular portion of the receptor. We demonstrate, using two different human prostate cancer cell lines, that treatment with NKp30-Ig, dramatically inhibits tumor growth in vivo. Activated macrophages were shown to mediate an ADCC response against the NKp30-Ig coated prostate cell lines. Finally, the Ig fusion proteins were also demonstrated to discriminate between benign prostate hyperplasia and prostate cancer. This may provide a novel diagnostic modality in the difficult task of differentiating between these highly common pathological conditions
Evaluation of the Multiplane Method for Efficient Simulations of Reaction Networks
Reaction networks in the bulk and on surfaces are widespread in physical,
chemical and biological systems. In macroscopic systems, which include large
populations of reactive species, stochastic fluctuations are negligible and the
reaction rates can be evaluated using rate equations. However, many physical
systems are partitioned into microscopic domains, where the number of molecules
in each domain is small and fluctuations are strong. Under these conditions,
the simulation of reaction networks requires stochastic methods such as direct
integration of the master equation. However, direct integration of the master
equation is infeasible for complex networks, because the number of equations
proliferates as the number of reactive species increases. Recently, the
multiplane method, which provides a dramatic reduction in the number of
equations, was introduced [A. Lipshtat and O. Biham, Phys. Rev. Lett. 93,
170601 (2004)]. The reduction is achieved by breaking the network into a set of
maximal fully connected sub-networks (maximal cliques). Lower-dimensional
master equations are constructed for the marginal probability distributions
associated with the cliques, with suitable couplings between them. In this
paper we test the multiplane method and examine its applicability. We show that
the method is accurate in the limit of small domains, where fluctuations are
strong. It thus provides an efficient framework for the stochastic simulation
of complex reaction networks with strong fluctuations, for which rate equations
fail and direct integration of the master equation is infeasible. The method
also applies in the case of large domains, where it converges to the rate
equation results
Diffusion-limited reactions on disordered surfaces with continuous distributions of binding energies
We study the steady state of a stochastic particle system on a
two-dimensional lattice, with particle influx, diffusion and desorption, and
the formation of a dimer when particles meet. Surface processes are thermally
activated, with (quenched) binding energies drawn from a \emph{continuous}
distribution. We show that sites in this model provide either coverage or
mobility, depending on their energy. We use this to analytically map the system
to an effective \emph{binary} model in a temperature-dependent way. The
behavior of the effective model is well-understood and accurately describes key
quantities of the system: Compared with discrete distributions, the temperature
window of efficient reaction is broadened, and the efficiency decays more
slowly at its ends. The mapping also explains in what parameter regimes the
system exhibits realization dependence.Comment: 23 pages, 8 figures. Submitted to: Journal of Statistical Mechanics:
Theory and Experimen
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