Magnificent Desolation

The traditional method for intensity-based sound power estimates often used in engineering applications is limited in bandwidth by microphone phase mismatch at low frequencies and by microphone spacing at high frequencies. To overcome these limitations, the Phase and Amplitude Gradient Estimator (PAGE) method [Gee, Neilsen, Sommerfeldt, Akamine, and Okamoto, J. Acoust. Soc. Am. 141(4), EL357–EL362 (2017)] is applied to sound power for a reference sound source, a blender, and a vacuum cleaner. Sound power measurements taken according to ISO 3741:2010 (2010) are compared against traditional- and PAGE-processed intensity-based sound power estimates measured according to ANSI S12.12-1992 (R2017). While the traditional method underestimates the sound power at the spatial Nyquist frequency by 7–10 dB, the PAGE-based sound power is accurate up to the spatial Nyquist frequency, and above when phase unwrapping is successful.

In ocean acoustics, many types of optimizations have been employed to locate acoustic sources and estimate the properties of the seabed. How these tasks can take advantage of recent advances in deep learning remains as open questions, especially due to the lack of labeled field data. In this work, a Convolutional Neural Network (CNN) is used to find seabed type and source range simultaneously from 1 s pressure time series from impulsive sounds. Simulated data are used to train the CNN before application to signals from a single hydrophone signal during the 2017 Seabed Characterization Experiment. The training data includes four seabeds representing deep mud, mud over sand, sandy silt, and sand, and a wide range of source parameters. When applied to measured data, the trained CNN predicts expected seabed types and obtains ranges within 0.5 km when the source-receiver range is greater than 5 km, showing the potential for such algorithms to address these problems.

Context. Dust in late-type galaxies in the local Universe is responsible for absorbing approximately one third of the energy emitted by stars. It is often assumed that dust heating is mainly attributable to the absorption of ultraviolet and optical photons emitted by the youngest (≤100 Myr) stars. Consequently, thermal re-emission by dust at far-infrared wavelengths is often linked to the star-formation activity of a galaxy. However, several studies argue that the contribution to dust heating by much older stellar populations might be more significant than previously thought. Advances in radiation transfer simulations finally allow us to actually quantify the heating mechanisms of diffuse dust by the stellar radiation field.

Aims. As one of the main goals in the DustPedia project, we have developed a framework to construct detailed 3D stellar and dust radiative transfer models for nearby galaxies. In this study, we analyse the contribution of the different stellar populations to the dust heating in four nearby face-on barred galaxies: NGC 1365, M 83, M 95, and M 100. We aim to quantify the fraction directly related to young stellar populations, both globally and on local scales, and to assess the influence of the bar on the heating fraction.

Methods. From 2D images we derive the 3D distributions of stars and dust. To model the complex geometries, we used SKIRT, a state-of-the-art 3D Monte Carlo radiative transfer code designed to self-consistently simulate the absorption, scattering, and thermal re-emission by the dust for arbitrary 3D distributions.

Results. We derive global attenuation laws for each galaxy and confirm that galaxies of high specific star-formation rate have shallower attenuation curves and weaker UV bumps. On average, 36.5% of the bolometric luminosity is absorbed by dust in our galaxy sample. We report a clear effect of the bar structure on the radial profiles of the dust-heating fraction by the young stellar populations, and the dust temperature. We find that the young stellar populations are the main contributors to the dust heating, donating, on average ∼59% of their luminosity to this purpose throughout the galaxy. This dust-heating fraction drops to ∼53% in the bar region and ∼38% in the bulge region where the old stars are the dominant contributors to the dust heating. We also find a strong link between the heating fraction by the young stellar populations and the specific star-formation rate.