37,116 research outputs found
Matrix factorizations for quantum complete intersections
We introduce twisted matrix factorizations for quantum complete intersections
of codimension two. For such an algebra, we show that in a given dimension,
almost all the indecomposable modules with bounded minimal projective
resolutions correspond to such matrix factorizations.Comment: 13 page
Exchange coupling between two ferromagnetic electrodes separated by a graphene nanoribbon
In this study, based on the self-energy method and the total energy
calculation, the indirect exchange coupling between two semi-infinite
ferromagnetic strips (FM electrodes) separated by metallic graphene nanoribbons
(GNRs) is investigated. In order to form a FM/GNR/FM junction, a graphitic
region of finite length is coupled to the FM electrodes along graphitic zigzag
or armchair interfaces of width . The numerical results show that, the
exchange coupling strength which can be obtained from the difference between
the total energies of electrons in the ferromagnetic and antiferromagnetic
couplings, has an oscillatory behavior, and depends on the Fermi energy and the
length of the central region.Comment: 4 pages, 6 figures, International Conference on Theoretical Physics
'Dubna-Nano2008
Effective restoration of chiral and axial symmetries at finite temperature and density
The effective restoration of chiral and axial symmetries is investigated
within the framework of the SU(3) Nambu-Jona-Lasinio model. The topological
susceptibility, modeled from lattice data at finite temperature, is used to
extract the temperature dependence of the coupling strength of the anomaly. The
study of the scalar and pseudoscalar mixing angles is performed in order to
discuss the evolution of the flavor combinations of pairs and its
consequences for the degeneracy of chiral partners. A similar study at zero
temperature and finite density is also realized.Comment: 5 pages, 1 figure. Talk given at Strange Quark Matter 2004, Cape
Town, South Africa, 15-20 September, 200
Massive stars and globular cluster formation
We first present chemodynamical simulations to investigate how stellar winds
of massive stars influence early dynamical and chemical evolution of forming
globular clusters (GCs). In our numerical models, GCs form in
turbulent,high-density giant molecular clouds (GMCs), which are embedded in a
massive dark matter halo at high redshifts. We show how high-density, compact
stellar systems are formed from GMCs influenced both by physical processes
associated with star formation and by tidal fields of their host halos. We also
show that chemical pollution of GC-forming GMCs by stellar winds from massive
stars can result in star-to-star abundance inhomogeneities among light elements
(e.g., C, N, and O) of stars in GCs. The present model with a canonical initial
mass function (IMF) also shows a C-N anticorrelation that stars with smaller
[C/Fe] have larger [N/Fe] in a GC. Although these results imply that
``self-pollution'' of GC-forming GMCs by stellar winds from massive stars can
cause abundance inhomogeneities of GCs, the present models with different
parameters and canonical IMFs can not show N-rich stars with [N/Fe] ~ 0.8
observed in some GCs (e.g., NGC 6752). We discuss this apparent failure in the
context of massive star formation preceding low-mass one within GC-forming GMCs
(``bimodal star formation scenario''). We also show that although almost all
stars (~97%) show normal He abundances (Y) of ~0.24 some stars later formed in
GMCs can have Y as high as ~0.3 in some models. The number fraction of He-rich
stars with Y >0.26 is however found to be small (~10^-3) for most models.Comment: 10 pages, 8 figures, accepted by Ap
Dataplane Specialization for High-performance OpenFlow Software Switching
OpenFlow is an amazingly expressive dataplane program-
ming language, but this expressiveness comes at a severe
performance price as switches must do excessive packet clas-
sification in the fast path. The prevalent OpenFlow software
switch architecture is therefore built on flow caching, but
this imposes intricate limitations on the workloads that can
be supported efficiently and may even open the door to mali-
cious cache overflow attacks. In this paper we argue that in-
stead of enforcing the same universal flow cache semantics
to all OpenFlow applications and optimize for the common
case, a switch should rather automatically specialize its dat-
aplane piecemeal with respect to the configured workload.
We introduce ES WITCH , a novel switch architecture that
uses on-the-fly template-based code generation to compile
any OpenFlow pipeline into efficient machine code, which
can then be readily used as fast path. We present a proof-
of-concept prototype and we demonstrate on illustrative use
cases that ES WITCH yields a simpler architecture, superior
packet processing speed, improved latency and CPU scala-
bility, and predictable performance. Our prototype can eas-
ily scale beyond 100 Gbps on a single Intel blade even with
complex OpenFlow pipelines
Ação hormonal da leptina em ruminantes.
A leptina, chamada de hormônio da obesidade, é produzida e secretada pelos adipócitos. É um hormônio capaz de alterar o consumo de alimento e o gasto de energia, por parte do animal, pois informa o cérebro sobre a quantidade de energia armazenada em forma de gordura. Propõe-se, nesta Documentos, explicar a ação da leptina em ruminantes. O trabalho apresenta os seguintes tópicos: Polimorfismos no gene da leptina; Expressão gênica da leptina; Os receptores da leptina; Controle do apetite pela leptina; Modulação fisiológica da leptina; Ação da leptina sobre a reprodução.bitstream/CPAF-RO-2010/14318/1/doc107-leptina.pd
Non-collinear coupling between magnetic adatoms in carbon nanotubes
The long range character of the exchange coupling between localized magnetic
moments indirectly mediated by the conduction electrons of metallic hosts often
plays a significant role in determining the magnetic order of low-dimensional
structures. In addition to this indirect coupling, here we show that the direct
exchange interaction that arises when the moments are not too far apart may
induce a non-collinear magnetic order that cannot be characterized by a
Heisenberg-like interaction between the magnetic moments. We argue that this
effect can be manipulated to control the magnetization alignment of magnetic
dimers adsorbed to the walls of carbon nanotubes.Comment: 13 pages, 5 figures, submitted to PR
Suppression of Higgsino mediated proton decay by cancellations in GUTs and strings
A mechanism for the enhancement for proton lifetime in
supersymmetric/supergravity (SUSY/SUGRA) grand unified theories (GUTs) and in
string theory models is discussed where Higgsino mediated proton decay arising
from color triplets (anti-triplets) with charges and
is suppressed by an internal cancellation due to contributions
from different sources. We exhibit the mechanism for an SU(5) model with
Higgs multiplets in addition to the usual Higgs structure of
the minimal model. This model contains both and
Higgs color triplets (anti-triplets) and simple constraints allow for a
complete suppression of Higgsino mediated proton decay. Suppression of proton
decay in an SU(5) model with Planck scale contributions is also considered. The
suppression mechanism is then exhibited for an SO(10) model with a unified
Higgs structure involving representations.The SU(5)
decomposition of contains and
and the cancellation mechanism arises among these
contributions which mirrror the SU(5) case. The cancellation mechanism appears
to be more generally valid for a larger class of unification models.
Specifically the cancellation mechanism may play a role in string model
constructions to suppress proton decay from dimension five operators. The
mechanism allows for the suppression of proton decay consistent with current
data allowing for the possibility that proton decay may be visible in the next
round of nucleon stability experiment.Comment: 26 pages, no figures. Revtex 4. To appear in Physical Review
Neural Dynamics under Active Inference: Plausibility and Efficiency of Information Processing
Active inference is a normative framework for explaining behaviour under the free energy principle—a theory of self-organisation originating in neuroscience. It specifies neuronal dynamics for state-estimation in terms of a descent on (variational) free energy—a measure of the fit between an internal (generative) model and sensory observations. The free energy gradient is a prediction error—plausibly encoded in the average membrane potentials of neuronal populations. Conversely, the expected probability of a state can be expressed in terms of neuronal firing rates. We show that this is consistent with current models of neuronal dynamics and establish face validity by synthesising plausible electrophysiological responses. We then show that these neuronal dynamics approximate natural gradient descent, a well-known optimisation algorithm from information geometry that follows the steepest descent of the objective in information space. We compare the information length of belief updating in both schemes, a measure of the distance travelled in information space that has a direct interpretation in terms of metabolic cost. We show that neural dynamics under active inference are metabolically efficient and suggest that neural representations in biological agents may evolve by approximating steepest descent in information space towards the point of optimal inference
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