3,847 research outputs found
Nos\'e-Hoover Dynamics in Quantum Phase Space
Thermal fluctuations in time-dependent quantum processes are treated by a
constant-temperature generalization of Wigner's formulation of quantum
mechanics in phase space. To this end, quantum Nos\`e-Hoover dynamics is
defined by generalizing the Moyal bracket. Computational applications of the
formalism, together with further theoretical developments, are discussed.Comment: 4 pages, no figure
Test results of a prototype designed to detect horizontal cosmic ray flux
In this paper we report test results from a prototype designed to detect
muons from horizontal air shower at large zenith angle,
. To detect horizontal tracks and their directions we
select them according the muon vertical equivalent charge and we measure the
time of flight with a time resolution of 800 ps. Several measurements are
collected at different zenith angles. The background studies performed with two
modules show that the main source is due to tracks crossing the module at the
same time. The upper limit of background flux for a single twin module is
estimated to be . We estimated the
size of the surface array necessary to detect the shower flux of the order of
if originated by Tau Air-Showers
secondaries of GZK neutrino Tau below the horizons.Comment: 12 pages, 13 figure
Coarse-graining MARTINI model for molecular-dynamics simulations of the wetting properties of graphitic surfaces with non-ionic, long-chain and T-shaped surfactants
We report on a molecular dynamics investigation of the wetting properties of
graphitic surfaces by various solutions at concentrations 1-8 wt% of
commercially available non-ionic surfactants with long hydrophilic chains,
linear or T-shaped. These are surfactants of length up to 160 [\AA]. It turns
out that molecular dynamics simulations of such systems ask for a number of
solvent particles that can be reached without seriously compromising
computational efficiency only by employing a coarse-grained model. The MARTINI
force field with polarizable water offers a framework particularly suited for
the parameterization of our systems. In general, its advantages over other
coarse-grained models are the possibility to explore faster long time scales
and the wider range of applicability. Although the accuracy is sometimes put
under question, the results for the wetting properties by pure water are in
good agreement with those for the corresponding atomistic systems and
theoretical predictions. On the other hand, the bulk properties of various
aqueous surfactant solutions indicate that the micellar formation process is
too strong. For this reason, a typical experimental configuration is better
approached by preparing the droplets with the surfactants arranged in the
initial state in the vicinity of contact line. Cross-comparisons are possible
and illuminating, but equilibrium contanct angles as obtained from simulations
overestimate the experimental results. Nevertheless, our findings can provide
guidelines for the preliminary assessment and screening of surfactants. [See
pdf file for full abstract]Comment: Revised version. Publication: http://dx.doi.org/10.1063/1.4747827.
Material: https://sites.google.com/site/material4sim
Deterministic constant-temperature dynamics for dissipative quantum systems
A novel method is introduced in order to treat the dissipative dynamics of
quantum systems interacting with a bath of classical degrees of freedom. The
method is based upon an extension of the Nos\`e-Hoover chain (constant
temperature) dynamics to quantum-classical systems. Both adiabatic and
nonadiabatic numerical calculations on the relaxation dynamics of the
spin-boson model show that the quantum-classical Nos\`e-Hoover chain dynamics
represents the thermal noise of the bath in an accurate and simple way.
Numerical comparisons, both with the constant energy calculation and with the
quantum-classical Brownian motion treatment of the bath, show that the
quantum-classical Nos\`e-Hoover Chain dynamics can be used to introduce
dissipation in the evolution of a quantum subsystem even with just one degree
of freedom for the bath. The algorithm can be computationally advantageous in
modeling, within computer simulation, the dynamics of a quantum subsystem
interacting with complex molecular environments.Comment: Revised versio
Testing Human Ability To Detect Deepfake Images of Human Faces
Deepfakes are computationally-created entities that falsely represent
reality. They can take image, video, and audio modalities, and pose a threat to
many areas of systems and societies, comprising a topic of interest to various
aspects of cybersecurity and cybersafety. In 2020 a workshop consulting AI
experts from academia, policing, government, the private sector, and state
security agencies ranked deepfakes as the most serious AI threat. These experts
noted that since fake material can propagate through many uncontrolled routes,
changes in citizen behaviour may be the only effective defence. This study aims
to assess human ability to identify image deepfakes of human faces
(StyleGAN2:FFHQ) from nondeepfake images (FFHQ), and to assess the
effectiveness of simple interventions intended to improve detection accuracy.
Using an online survey, 280 participants were randomly allocated to one of four
groups: a control group, and 3 assistance interventions. Each participant was
shown a sequence of 20 images randomly selected from a pool of 50 deepfake and
50 real images of human faces. Participants were asked if each image was
AI-generated or not, to report their confidence, and to describe the reasoning
behind each response. Overall detection accuracy was only just above chance and
none of the interventions significantly improved this. Participants' confidence
in their answers was high and unrelated to accuracy. Assessing the results on a
per-image basis reveals participants consistently found certain images harder
to label correctly, but reported similarly high confidence regardless of the
image. Thus, although participant accuracy was 62% overall, this accuracy
across images ranged quite evenly between 85% and 30%, with an accuracy of
below 50% for one in every five images. We interpret the findings as suggesting
that there is a need for an urgent call to action to address this threat
On the Geometry and Entropy of Non-Hamiltonian Phase Space
We analyze the equilibrium statistical mechanics of canonical, non-canonical
and non-Hamiltonian equations of motion by throwing light into the peculiar
geometric structure of phase space. Some fundamental issues regarding time
translation and phase space measure are clarified. In particular, we emphasize
that a phase space measure should be defined by means of the Jacobian of the
transformation between different types of coordinates since such a determinant
is different from zero in the non-canonical case even if the phase space
compressibility is null. Instead, the Jacobian determinant associated with
phase space flows is unity whenever non-canonical coordinates lead to a
vanishing compressibility, so that its use in order to define a measure may not
be always correct. To better illustrate this point, we derive a mathematical
condition for defining non-Hamiltonian phase space flows with zero
compressibility. The Jacobian determinant associated with time evolution in
phase space is altogether useful for analyzing time translation invariance. The
proper definition of a phase space measure is particularly important when
defining the entropy functional in the canonical, non-canonical, and
non-Hamiltonian cases. We show how the use of relative entropies can circumvent
some subtle problems that are encountered when dealing with continuous
probability distributions and phase space measures. Finally, a maximum
(relative) entropy principle is formulated for non-canonical and
non-Hamiltonian phase space flows.Comment: revised introductio
Wetting and contact-line effects for spherical and cylindrical droplets on graphene layers: A comparative molecular-dynamics investigation
In Molecular Dynamics (MD) simulations, interactions between water molecules
and graphitic surfaces are often modeled as a simple Lennard-Jones potential
between oxygen and carbon atoms. A possible method for tuning this parameter
consists of simulating a water nanodroplet on a flat graphitic surface,
measuring the equilibrium contact angle, extrapolating it to the limit of a
macroscopic droplet and finally matching this quantity to experimental results.
Considering recent evidence demonstrating that the contact angle of water on a
graphitic plane is much higher than what was previously reported, we estimate
the oxygen-carbon interaction for the recent SPC/Fwwater model. Results
indicate a value of about 0.2 kJ/mol, much lower than previous estimations. We
then perform simulations of cylindrical water filaments on graphitic surfaces,
in order to compare and correlate contact angles resulting from these two
different systems. Results suggest that modified Young's equation does not
describe the relation between contact angle and drop size in the case of
extremely small systems and that contributions different from the one deriving
from contact line tension should be taken into account.Comment: To be published on Physical Review E (http://pre.aps.org/
Rotating "Black Holes" with Holes in the Horizon
Kerr-Schild solutions of the Einstein-Maxwell field equations, containing
semi-infinite axial singular lines, are investigated.
It is shown that axial singularities break up the black hole, forming holes
in the horizon. As a result, a tube-like region appears which allows matter to
escape from the interior without crossing the horizon. It is argued that axial
singularities of this kind, leading to very narrow beams, can be created in
black holes by external electromagnetic or gravitational excitations and may be
at the origin of astrophysically observable effects such as jet formation.Comment: Revtex, 6 pages, 3 figures. Corrected version. To appear in Phys Rev
D, Rapid Communication
Warning: Humans Cannot Reliably Detect Speech Deepfakes
Speech deepfakes are artificial voices generated by machine learning models.
Previous literature has highlighted deepfakes as one of the biggest security
threats arising from progress in artificial intelligence due to their potential
for misuse. However, studies investigating human detection capabilities are
limited. We presented genuine and deepfake audio to n = 529 individuals and
asked them to identify the deepfakes. We ran our experiments in English and
Mandarin to understand if language affects detection performance and
decision-making rationale. We found that detection capability is unreliable.
Listeners only correctly spotted the deepfakes 73% of the time, and there was
no difference in detectability between the two languages. Increasing listener
awareness by providing examples of speech deepfakes only improves results
slightly. As speech synthesis algorithms improve and become more realistic, we
can expect the detection task to become harder. The difficulty of detecting
speech deepfakes confirms their potential for misuse and signals that defenses
against this threat are needed
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