A wireless, real-time, social music performance system for mobile phones

The paper reports on the Cellmusic system: a real-time, wireless distributed composition and performance system designed for domestic mobile devices. During a performance, each mobile device communicates with others, and may create sonic events in a passive (non interactive) mode or may influence the output of other devices. Cellmusic distinguishes itself from other mobile phone performance environments in that it is intended for performance in ad hoc locations, with services and performances automatically and dynamically adapting to the number of devices within a given proximity. It is designed to run on a number of mobile phone platforms to allow as wider distribution as possible, again distinguishing itself from other mobile performance systems which primarily run on a single device. Rather than performances being orchestrated or managed, it is intended that users will access it and create a performance in the same manner that they use mobile phones for interacting socially at different times throughout the day. However, this does not preclude the system being used in a more traditional performance environment. This accessibility and portability make it an ideal platform for sonic artists who choose to explore a variety of physical environments (such as parks and other public spaces)

What is Sound?

(Abstract to follow

Laterally Propagating Detonations in Thin Helium Layers on Accreting White Dwarfs

Theoretical work has shown that intermediate mass (0.01Msun<M_He<0.1Msun) Helium shells will unstably ignite on the accreting white dwarf (WD) in an AM CVn binary. For more massive (M>0.8Msun) WDs, these helium shells can be dense enough (5x10^5 g/cc) that the convectively burning region runs away on a timescale comparable to the sound travel time across the shell; raising the possibility for an explosive outcome. The nature of the explosion (i.e. deflagration or detonation) remains ambiguous. In the case of detonation, this causes a laterally propagating front whose properties in these geometrically thin and low density shells we begin to study here. Our calculations show that the radial expansion time of <0.1 s leads to incomplete helium burning, in agreement with recent work by Sim and collaborators, but that the nuclear energy released is still adequate to realize a self-sustaining detonation propagating laterally at slower than the Chapman-Jouguet speed. Our simulations resolve the subsonic region behind the front and are consistent with a direct computation of the reaction structure from the shock strength. The ashes are typically He rich, and consist of predominantly Ti-44, Cr-48, along with a small amount of Fe-52, with very little Ni-56 and with significant Ca-40 in carbon-enriched layers. If this helium detonation results in a Type Ia Supernova, its spectral signatures would appear for the first few days after explosion. (abridged)Comment: 7 pages, 5 figure, accepted to the Astrophysical Journa

Seismic detection of sonic booms

The pressure signals from a sonic boom will produce a small, but detectable, ground motion. The extensive seismic network in southern California, consisting of over 200 sites covering over 50 000 square kilometers, is used to map primary and secondary sonic boom carpets. Data from the network is used to analyze three supersonic overflights in the western United States. The results are compared to ray-tracing computations using a realistic model of the stratified atmospheric at the time of the measurements. The results show sonic boom ground exposure under the real atmosphere is much larger than previously expected or predicted by ray tracing alone. Finally, seismic observations are used to draw some inferences on the origin of a set of "mystery booms" recorded in 1992–1993 in southern California

FPGA-accelerated machine learning inference as a service for particle physics computing

New heterogeneous computing paradigms on dedicated hardware with increased parallelization, such as Field Programmable Gate Arrays (FPGAs), offer exciting solutions with large potential gains. The growing applications of machine learning algorithms in particle physics for simulation, reconstruction, and analysis are naturally deployed on such platforms. We demonstrate that the acceleration of machine learning inference as a web service represents a heterogeneous computing solution for particle physics experiments that potentially requires minimal modification to the current computing model. As examples, we retrain the ResNet-50 convolutional neural network to demonstrate state-of-the-art performance for top quark jet tagging at the LHC and apply a ResNet-50 model with transfer learning for neutrino event classification. Using Project Brainwave by Microsoft to accelerate the ResNet-50 image classification model, we achieve average inference times of 60 (10) milliseconds with our experimental physics software framework using Brainwave as a cloud (edge or on-premises) service, representing an improvement by a factor of approximately 30 (175) in model inference latency over traditional CPU inference in current experimental hardware. A single FPGA service accessed by many CPUs achieves a throughput of 600--700 inferences per second using an image batch of one, comparable to large batch-size GPU throughput and significantly better than small batch-size GPU throughput. Deployed as an edge or cloud service for the particle physics computing model, coprocessor accelerators can have a higher duty cycle and are potentially much more cost-effective.Comment: 16 pages, 14 figures, 2 table