2,849 research outputs found
Conformal Sector in Quantum Gravity
We discuss the conformal factor dynamics in . Accepting the proposal
that higher-derivative dimensionless terms in the anomaly-induced effective
action may be dropped, we obtain a superrenormalizable (like in )
effective theory for the conformal factor. The one-loop analysis of this theory
gives the anomalous scaling dimension for the conformal factor and provides a
natural mechanism to solve the cosmological constant problem.Comment: 9 pages, Oct 27 199
Zeta-Regularization of the O(N) Non-Linear Sigma Model in D dimensions
The O(N) non-linear sigma model in a -dimensional space of the form , , or is studied, where , and
correspond to flat space, a torus and a sphere, respectively. Using zeta
regularization and the expansion, the corresponding partition functions
and the gap equations are obtained. Numerical solutions of the gap equations at
the critical coupling constants are given, for several values of . The
properties of the partition function and its asymptotic behaviour for large
are discussed. In a similar way, a higher-derivative non-linear sigma model is
investigated too. The physical relevance of our results is discussed.Comment: 26 page
First steps towards the certification of an ARM simulator using Compcert
The simulation of Systems-on-Chip (SoC) is nowadays a hot topic because,
beyond providing many debugging facilities, it allows the development of
dedicated software before the hardware is available. Low-consumption CPUs such
as ARM play a central role in SoC. However, the effectiveness of simulation
depends on the faithfulness of the simulator. To this effect, we propose here
to prove significant parts of such a simulator, SimSoC. Basically, on one hand,
we develop a Coq formal model of the ARM architecture while on the other hand,
we consider a version of the simulator including components written in
Compcert-C. Then we prove that the simulation of ARM operations, according to
Compcert-C formal semantics, conforms to the expected formal model of ARM. Size
issues are partly dealt with using automatic generation of significant parts of
the Coq model and of SimSoC from the official textual definition of ARM.
However, this is still a long-term project. We report here the current stage of
our efforts and discuss in particular the use of Compcert-C in this framework.Comment: First International Conference on Certified Programs and Proofs 7086
(2011
Book Review Investor Response to Management Decisions: A Research Based Analysis of Actions and Effects. By Richard M. Altman
Advising Partners and Partnerships Under the New Centralized Partnership Audit Rules: The Need to Amend Partnership and LLC Operating Agreements (PowerPoint)
QUITTING TOGETHER: FORMATIVE RESEARCH TO DEVELOP A SOCIAL MARKETING PLAN FOR SMOKING CESSATION AMONG WOMEN IN A RESIDENTIAL TREATMENT FACILITY FOR SUBSTANCE ABUSE RECOVERY
Both smoking addiction and illicit substance abuse are prevalent issues in the United States today. Furthermore, these are issues that have significant impact on womenâs health and mental state. Despite research that shows that smoking cessation coupled with substance abuse recovery can decrease likelihood of relapse post-recovery, few substance abuse recovery facilities today offer smoking cessation programming options. To address the issue of smoking addiction on top of substance abuse recovery, formative research was conducted through this study to determine the underlying causes of smoking habits coupled with recovery efforts and the attitudes. Through focus group sessions with women in a residential treatment facility in the southeastern US, a determination of the specific audienceâs motivations to smoke and perceived self-efficacy to quit smoking was made. Based on the findings of this formative research, a full social marketing plan was then developed to offer an intervention program option for smoking cessation among a target audience of women undergoing residential treatment for substance abuse. The study conducted and the social marketing developed from it proposes a pilot program that may be implemented in other similar settings with similar populations in the future
Neural-Network Quantum States, String-Bond States, and Chiral Topological States
Neural-Network Quantum States have been recently introduced as an Ansatz for
describing the wave function of quantum many-body systems. We show that there
are strong connections between Neural-Network Quantum States in the form of
Restricted Boltzmann Machines and some classes of Tensor-Network states in
arbitrary dimensions. In particular we demonstrate that short-range Restricted
Boltzmann Machines are Entangled Plaquette States, while fully connected
Restricted Boltzmann Machines are String-Bond States with a nonlocal geometry
and low bond dimension. These results shed light on the underlying architecture
of Restricted Boltzmann Machines and their efficiency at representing many-body
quantum states. String-Bond States also provide a generic way of enhancing the
power of Neural-Network Quantum States and a natural generalization to systems
with larger local Hilbert space. We compare the advantages and drawbacks of
these different classes of states and present a method to combine them
together. This allows us to benefit from both the entanglement structure of
Tensor Networks and the efficiency of Neural-Network Quantum States into a
single Ansatz capable of targeting the wave function of strongly correlated
systems. While it remains a challenge to describe states with chiral
topological order using traditional Tensor Networks, we show that
Neural-Network Quantum States and their String-Bond States extension can
describe a lattice Fractional Quantum Hall state exactly. In addition, we
provide numerical evidence that Neural-Network Quantum States can approximate a
chiral spin liquid with better accuracy than Entangled Plaquette States and
local String-Bond States. Our results demonstrate the efficiency of neural
networks to describe complex quantum wave functions and pave the way towards
the use of String-Bond States as a tool in more traditional machine-learning
applications.Comment: 15 pages, 7 figure
The Infrared Extinction Law at Extreme Depth in a Dark Cloud Core
We combined sensitive near-infrared data obtained with ground-based imagers
on the ESO NTT and VLT telescopes with space mid-infrared data acquired with
the IRAC imager on the Spitzer Space Telescope to calculate the extinction law
A_\lambda/A_K as a function of \lambda between 1.25 and 7.76 micron to an
unprecedented depth in Barnard 59, a star forming, dense core located in the
Pipe Nebula. The ratios A_\lambda/A_K were calculated from the slopes of the
distributions of sources in color-color diagrams \lambda-K vs. H-K. The
distributions in the color-color diagrams are fit well with single slopes to
extinction levels of A_K ~ 7 (A_V ~ 59 mag). Consequently, there appears to be
no significant variation of the extinction law with depth through the B59 line
of sight. However, when slopes are translated into the relative extinction
coefficients A_\lambda/A_K, we find an extinction law which departs from the
simple extrapolation of the near-infrared power law extinction curve, and
agrees more closely with a dust extinction model for a cloud with a total to
selective absorption R_V=5.5 and a grain size distribution favoring larger
grains than those in the diffuse ISM. Thus, the difference we observe could be
possibly due to the effect of grain growth in denser regions. Finally, the
slopes in our diagrams are somewhat less steep than those from the study of
Indebetouw et al. (2005) for clouds with lower column densities, and this
indicates that the extinction law between 3 and 8 micron might vary slightly as
a function of environment.Comment: 22 pages manuscript, 4 figures (2 multipart), 1 tabl
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