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- Zhang, Yichen, et al.
(författare)
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A GPU-based computational framework that bridges neuron simulation and artificial intelligence
- 2023
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Ingår i: Nature Communications. - : Springer Nature. - 2041-1723. ; 14:1
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Tidskriftsartikel (refereegranskat)abstract
- Biophysically detailed multi-compartment models are powerful tools to explore computational principles of the brain and also serve as a theoretical framework to generate algorithms for artificial intelligence (AI) systems. However, the expensive computational cost severely limits the applications in both the neuroscience and AI fields. The major bottleneck during simulating detailed compartment models is the ability of a simulator to solve large systems of linear equations. Here, we present a novel Dendritic Hierarchical Scheduling (DHS) method to markedly accelerate such a process. We theoretically prove that the DHS implementation is computationally optimal and accurate. This GPU-based method performs with 2-3 orders of magnitude higher speed than that of the classic serial Hines method in the conventional CPU platform. We build a DeepDendrite framework, which integrates the DHS method and the GPU computing engine of the NEURON simulator and demonstrate applications of DeepDendrite in neuroscience tasks. We investigate how spatial patterns of spine inputs affect neuronal excitability in a detailed human pyramidal neuron model with 25,000 spines. Furthermore, we provide a brief discussion on the potential of DeepDendrite for AI, specifically highlighting its ability to enable the efficient training of biophysically detailed models in typical image classification tasks.
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2. |
- Bogaerts, Wim, et al.
(författare)
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Scaling programmable silicon photonics circuits
- 2023
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Ingår i: Silicon Photonics XVIII. - : SPIE-Intl Soc Optical Eng.
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Konferensbidrag (refereegranskat)abstract
- We give an overview the progress of our work in silicon photonic programmable circuits, covering the techn stack from the photonic chip over the driver electronics, packaging technologies all the way to the sof layers. On the photonic side, we show our recent results in large-scale silicon photonic circuits with diff tuning technologies, including heaters, MEMS and liquid crystals, and their respective electronic driving sch We look into the scaling potential of these different technologies as the number of tunable elements in a ci increases. Finally, we elaborate on the software routines for routing and filter synthesis to enable the pho programmer.
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3. |
- Fedriani, Rubén, 1991, et al.
(författare)
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The SOFIA Massive (SOMA) Star Formation Survey. IV. Isolated Protostars
- 2023
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Ingår i: Astrophysical Journal. - : American Astronomical Society. - 1538-4357 .- 0004-637X. ; 942:1
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Tidskriftsartikel (refereegranskat)abstract
- We present similar to 10-40 mu m SOFIA-FORCAST images of 11 isolated protostars as part of the SOFIA Massive (SOMA) Star Formation Survey, with this morphological classification based on 37 mu m imaging. We develop an automated method to define source aperture size using the gradient of its background-subtracted enclosed flux and apply this to build spectral energy distributions (SEDs). We fit the SEDs with radiative transfer models, developed within the framework of turbulent core accretion (TCA) theory, to estimate key protostellar properties. Here, we release the sedcreator python package that carries out these methods. The SEDs are generally well fitted by the TCA models, from which we infer initial core masses M ( c ) ranging from 20-430 M (circle dot), clump mass surface densities sigma(cl) similar to 0.3-1.7 g cm(-2), and current protostellar masses m (*) similar to 3-50 M (circle dot). From a uniform analysis of the 40 sources in the full SOMA survey to date, we find that massive protostars form across a wide range of clump mass surface density environments, placing constraints on theories that predict a minimum threshold sigma(cl) for massive star formation. However, the upper end of the m (*)-sigma(cl) distribution follows trends predicted by models of internal protostellar feedback that find greater star formation efficiency in higher sigma(cl) conditions. We also investigate protostellar far-IR variability by comparison with IRAS data, finding no significant variation over an similar to 40 yr baseline.
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4. |
- Staff, Jan, 1977, et al.
(författare)
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Disk Wind Feedback from High-mass Protostars. II. The Evolutionary Sequence
- 2023
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Ingår i: Astrophysical Journal. - 1538-4357 .- 0004-637X. ; 947:1
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Tidskriftsartikel (refereegranskat)abstract
- Star formation is ubiquitously associated with the ejection of accretion-powered outflows that carve bipolar cavities through the infalling envelope. This feedback is expected to be important for regulating the efficiency of star formation from a natal prestellar core. These low-extinction outflow cavities greatly affect the appearance of a protostar by allowing the escape of shorter-wavelength photons. Doppler-shifted CO line emission from outflows is also often the most prominent manifestation of deeply embedded early-stage star formation. Here, we present 3D magnetohydrodynamic simulations of a disk wind outflow from a protostar forming from an initially 60 M ⊙ core embedded in a high-pressure environment typical of massive star-forming regions. We simulate the growth of the protostar from m * = 1 M ⊙ to 26 M ⊙ over a period of ∼100,000 yr. The outflow quickly excavates a cavity with a half opening angle of ∼10° through the core. This angle remains relatively constant until the star reaches 4 M ⊙. It then grows steadily in time, reaching a value of ∼50° by the end of the simulation. We estimate a lower limit to the star formation efficiency (SFE) of 0.43. However, accounting for continued accretion from a massive disk and residual infall envelope, we estimate that the final SFE may be as high as ∼0.7. We examine observable properties of the outflow, especially the evolution of the cavity's opening angle, total mass, and momentum flux, and the velocity distributions of the outflowing gas, and compare with the massive protostars G35.20-0.74N and G339.88-1.26 observed by the Atacama Large Millimeter/submillimeter Array (ALMA), yielding constraints on their intrinsic properties.
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