6,619 research outputs found
A Factor Graph Approach to Automated Design of Bayesian Signal Processing Algorithms
The benefits of automating design cycles for Bayesian inference-based
algorithms are becoming increasingly recognized by the machine learning
community. As a result, interest in probabilistic programming frameworks has
much increased over the past few years. This paper explores a specific
probabilistic programming paradigm, namely message passing in Forney-style
factor graphs (FFGs), in the context of automated design of efficient Bayesian
signal processing algorithms. To this end, we developed "ForneyLab"
(https://github.com/biaslab/ForneyLab.jl) as a Julia toolbox for message
passing-based inference in FFGs. We show by example how ForneyLab enables
automatic derivation of Bayesian signal processing algorithms, including
algorithms for parameter estimation and model comparison. Crucially, due to the
modular makeup of the FFG framework, both the model specification and inference
methods are readily extensible in ForneyLab. In order to test this framework,
we compared variational message passing as implemented by ForneyLab with
automatic differentiation variational inference (ADVI) and Monte Carlo methods
as implemented by state-of-the-art tools "Edward" and "Stan". In terms of
performance, extensibility and stability issues, ForneyLab appears to enjoy an
edge relative to its competitors for automated inference in state-space models.Comment: Accepted for publication in the International Journal of Approximate
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Entropy and entanglement in a bipartite quasi-Hermitian system and its Hermitian counterparts
We consider a quantum oscillator coupled to a bath of other oscillators.
The total system evolves with a quasi-Hermitian Hamiltonian. Associated to it
is a family of Hermitian systems, parameterized by a unitary map . Our main
goal is to find the influence of on the entropy and the entanglement in the
Hermitian systems. We calculate explicitly the reduced density matrix of the
single oscillator for all Hermitian systems and show that, regardless of ,
their von Neumann entropy oscillates with a common period which is twice that
of the non-Hermitian system. We show that generically, the oscillator and the
bath are entangled for almost all times. While the amount of entanglement
depends on the choice of , it is independent of when averaged over a
period. These results describe some universality in the physical properties of
all Hermitian systems associated to a given non-Hermitian one
DASCH Discovery of Large Amplitude ~10-100 Year Variability in K Giants
Here we present the discovery of three unusual long-term variables found in
the Digital Access to a Sky Century at Harvard (DASCH) project, with ~1
magnitude variations in their lightcurves on ~10-100 yr timescales. They are
all spectroscopically identified as K2III giant stars, probably in the thick
disk. Their lightcurves do not match any previously measured for known types of
variable stars, or any theoretical model reported for red giants, and instead
suggest a new dust formation mechanism or the first direct observation of
"short" timescale evolution-driven variability. More theoretical work on the
lithium flash near the Red Giant Branch (RGB) bump and the helium shell
ignition in the lower Asymptotic Giant Branch (AGB), as well as long term
monitoring of K2III thick disk stars is needed.Comment: 6 pages, 3 figures. Accepted for publication in ApJ Letters. Typo
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Numerical simulation of spreading drops
We consider a liquid drop that spreads on a wettable surface. Different time evolutions have been observed for the base radius r depending of the relative role played by inertia, viscosity, surface tension and the wetting condition. Numerical simulations were performed to discuss the relative effect of these parameters on the spreading described by the evolution of the base radius r(t) and the spreading time tS. Different power law evolutions r(t) ∝ tⁿ have been observed when varying the parameters. At the early stage of the spreading, the power law t½ (n = 1/2) is observed as long as capillarity is balanced by inertia at the contact line. When increasing the viscosity contribution, the exponent n is found to increase despite the increase of the spreading time. The effect of the surface wettability is observed for liquids more viscous than water. For a small contact angle, the power law t½ is then followed by the famous Tanner law t1/10 once the drop shape has reached a spherical cap
Refining Obstacle Perception Safety Zones via Maneuver-Based Decomposition
A critical task for developing safe autonomous driving stacks is to determine
whether an obstacle is safety-critical, i.e., poses an imminent threat to the
autonomous vehicle. Our previous work showed that Hamilton Jacobi reachability
theory can be applied to compute interaction-dynamics-aware perception safety
zones that better inform an ego vehicle's perception module which obstacles are
considered safety-critical. For completeness, these zones are typically larger
than absolutely necessary, forcing the perception module to pay attention to a
larger collection of objects for the sake of conservatism. As an improvement,
we propose a maneuver-based decomposition of our safety zones that leverages
information about the ego maneuver to reduce the zone volume. In particular, we
propose a "temporal convolution" operation that produces safety zones for
specific ego maneuvers, thus limiting the ego's behavior to reduce the size of
the safety zones. We show with numerical experiments that maneuver-based zones
are significantly smaller (up to 76% size reduction) than the baseline while
maintaining completeness.Comment: * indicates equal contribution. Accepted into the IEEE Intelligent
Vehicles Symposium 202
A New Mid-Infrared and X-ray Machine Learning Algorithm to Discover Compton-thick AGN
We present a new method to predict the line-of-sight column density (NH)
values of active galactic nuclei (AGN) based on mid-infrared (MIR), soft, and
hard X-ray data. We developed a multiple linear regression machine learning
algorithm trained with WISE colors, Swift-BAT count rates, soft X-ray hardness
ratios, and an MIR-soft X-ray flux ratio. Our algorithm was trained off 451 AGN
from the Swift-BAT sample with known NH and has the ability to accurately
predict NH values for AGN of all levels of obscuration, as evidenced by its
Spearman correlation coefficient value of 0.86 and its 75% classification
accuracy. This is significant as few other methods can be reliably applied to
AGN with Log(NH <) 22.5. It was determined that the two soft X-ray hardness
ratios and the MIR-soft X-ray flux ratio were the largest contributors towards
accurate NH determination. This algorithm will contribute significantly to
finding Compton-thick (CT-) AGN (NH >= 10^24 cm^-2), thus enabling us to
determine the true intrinsic fraction of CT-AGN in the local universe and their
contribution to the Cosmic X-ray Background
The born again (VLTP) scenario revisited: The mass of the remnants and implications for V4334 Sgr
We present 1-D numerical simulations of the very late thermal pulse
(VLTP) scenario for a wide range of remnant masses. We show that by taking
into account the different possible remnant masses, the observed evolution of
V4334 Sgr (a.k.a. Sakurai's Object) can be reproduced within the standard
1D-MLT stellar evolutionary models without the inclusion of any
reduced mixing efficiency. Our simulations hint at a consistent picture with
present observations of V4334 Sgr. From energetics, and within the standard MLT
approach, we show that low mass remnants \hbox{(\msun)} are
expected to behave markedly different than higher mass remnants
\hbox{(\msun)} in the sense that the latter are not expected to
expand significantly as a result of the violent H-burning that takes place
during the VLTP. We also assess the discrepancy in the born again times
obtained by different authors by comparing the energy that can be liberated by
H-burning during the VLTP event.Comment: Submitted to MNRAS. In includes an appendix regarding the treatment
of reduced convective motions within the Mixing Length Theor
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