2,806 research outputs found
Spatially extended and high-velocity dispersion molecular component in spiral galaxies: single-dish vs. interferometric observations
Recent studies of the molecular medium in nearby galaxies have provided
mounting evidence that the molecular gas can exist in two phases: one that is
clumpy and organized as molecular clouds and another one that is more diffuse.
This last component has a higher velocity dispersion than the clumpy one. In
order to investigate these two molecular components further, we compare the
fluxes and line widths of CO in NGC 4736 and NGC 5055, two nearby spiral
galaxies for which high-quality interferometric as well as single-dish data
sets are available. Our analysis leads to two main results: 1) Employing three
different methods, we determine the flux recovery of the interferometer as
compared to the single-dish to be within a range of 35-74% for NGC4736 and
81-92% for NGC5055, and 2) when focusing on high (SNR>5) lines of sight, the
single-dish line widths are larger by ~(40+-20)% than the ones derived from
interferometric data; which is in agreement with stacking all lines of sight.
These results point to a molecular gas component that is distributed over
spatial scales larger than 30"(~1kpc), and is therefore filtered out by the
interferometer. The available observations do not allow us to distinguish
between a truly diffuse gas morphology and a uniform distribution of small
clouds that are separated by less than the synthesized beam size (~3" or
~100pc), as they would both be invisible for the interferometer. This high
velocity dispersion component has a dispersion similar to what is found in the
atomic medium, as traced through observations of the HI line.Comment: 12 pages, 5 figures, Accepted to A
Scrutinizing and De-Biasing Intuitive Physics with Neural Stethoscopes
Visually predicting the stability of block towers is a popular task in the
domain of intuitive physics. While previous work focusses on prediction
accuracy, a one-dimensional performance measure, we provide a broader analysis
of the learned physical understanding of the final model and how the learning
process can be guided. To this end, we introduce neural stethoscopes as a
general purpose framework for quantifying the degree of importance of specific
factors of influence in deep neural networks as well as for actively promoting
and suppressing information as appropriate. In doing so, we unify concepts from
multitask learning as well as training with auxiliary and adversarial losses.
We apply neural stethoscopes to analyse the state-of-the-art neural network for
stability prediction. We show that the baseline model is susceptible to being
misled by incorrect visual cues. This leads to a performance breakdown to the
level of random guessing when training on scenarios where visual cues are
inversely correlated with stability. Using stethoscopes to promote meaningful
feature extraction increases performance from 51% to 90% prediction accuracy.
Conversely, training on an easy dataset where visual cues are positively
correlated with stability, the baseline model learns a bias leading to poor
performance on a harder dataset. Using an adversarial stethoscope, the network
is successfully de-biased, leading to a performance increase from 66% to 88%
Spatial mode detection by frequency upconversion
The efficient creation and detection of spatial modes of light has become
topical of late, driven by the need to increase photon-bit-rates in classical
and quantum communications. Such mode creation/detection is traditionally
achieved with tools based on linear optics. Here we put forward a new spatial
mode detection technique based on the nonlinear optical process of
sum-frequency generation. We outline the concept theoretically and demonstrate
it experimentally with intense laser beams carrying orbital angular momentum
and Hermite-Gaussian modes. Finally, we show that the method can be used to
transfer an image from the infrared band to the visible, which implies the
efficient conversion of many spatial modes.Comment: Published version, 4 pages, 5 figure
THE EFFECTS OF FLOW-INHOMOGENEITIES ON MOLECULAR CLOUD FORMATION: LOCAL VERSUS GLOBAL COLLAPSE
Observational evidence from local star-forming regions mandates that star formation occurs shortly after, or even during, molecular cloud formation. Models of molecular cloud formation in large-scale converging flows have identified the physical mechanisms driving the necessary rapid fragmentation. They also point to global gravitational collapse driving supersonic turbulence in molecular clouds. Previous cloud formation models have focused on turbulence generation, gravitational collapse, magnetic fields, and feedback. Here, we explore the effect of structure in the flow on the resulting clouds and the ensuing gravitational collapse. We compare two extreme cases, one with a collision between two smooth streams, and one with streams containing small clumps. We find that structured converging flows lead to a delay of local gravitational collapse ("core formation"). Hence, the cloud has more time to accumulate mass, eventually leading to a strong global collapse, and thus to a high core formation rate. Uniform converging flows fragment hydrodynamically early on, leading to the rapid onset of local gravitational collapse and an overall low core formation rate. This is also mirrored in the core mass distribution: the uniform initial conditions lead to more low-mass cores than the clumpy initial conditions. Kinetic (Ek) and gravitational energy (Eg) budgets suggest that collapse is only prevented for Ek Eg, which occurs for large scales in the smooth flow, and for small scales for the clumpy flow. Whenever Ek ≈ Eg, we observe gravitational collapse on those scales. Signatures of chemical abundance variations evolve differently for the gas phase and for the stellar population. For smooth flows, the forming cloud is well mixed, while its stellar population retains more information about the initial metallicities. For clumpy flows, the gas phase is less well mixed, while the stellar population has lost most of the information about its origin
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