We present the first experimental study of plasmoid formation in a magnetic reconnection layer undergoing rapid radiative cooling, a regime relevant to extreme astrophysical plasmas. Two exploding aluminum wire arrays, driven by the Z machine, generate a reconnection layer (S_{L}≈120) in which the cooling rate far exceeds the hydrodynamic transit rate (τ_{hydro}/τ_{cool}>100). The reconnection layer generates a transient burst of >1 keV x-ray emission, consistent with the formation and subsequent rapid cooling of the layer. Time-gated x-ray images show fast-moving (up to 50 km s^{-1}) hotspots in the layer, consistent with the presence of plasmoids in 3D resistive magnetohydrodynamic simulations. X-ray spectroscopy shows that these hotspots generate the majority of Al K-shell emission (around 1.6 keV) prior to the onset of cooling, and exhibit temperatures (170 eV) much greater than that of the plasma inflows and the rest of the reconnection layer, thus providing insight into the generation of high-energy radiation in radiatively cooled reconnection events.
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http://dx.doi.org/10.1103/PhysRevLett.132.155102 | DOI Listing |
Sci Adv
January 2025
Université Paris Cité, Institut Pasteur, AP-HP, Inserm, Fondation Pour l'Audition, Institut de l'Audition, IHU reConnect, F-75012 Paris, France.
The temporal structure of sensory inputs contains essential information for their interpretation. Sensory cortex represents these temporal cues through two codes: the temporal sequences of neuronal activity and the spatial patterns of neuronal firing rate. However, it is unknown which of these coexisting codes causally drives sensory decisions.
View Article and Find Full Text PDFObes Surg
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Nanotechnology
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Department of Life Sciences, Università degli Studi di Modena e Reggio Emilia, 41125 Modena, Italy.
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August 2024
Department of Delivery Room, Chengdu Women and Children's Central Hospital, University of Electronic Science and Technology of China, Chengdu, China.
In recent years, semantic segmentation in deep learning has been widely applied in medical image segmentation, leading to the development of numerous models. Convolutional Neural Network (CNNs) have achieved milestone achievements in medical image analysis. Particularly, deep neural networks based on U-shaped architectures and skip connections have been extensively employed in various medical image tasks.
View Article and Find Full Text PDFPhys Rev Lett
April 2024
Plasma Science and Fusion Center, Massachusetts Institute of Technology, Massachusetts 02139, Cambridge, USA.
We present the first experimental study of plasmoid formation in a magnetic reconnection layer undergoing rapid radiative cooling, a regime relevant to extreme astrophysical plasmas. Two exploding aluminum wire arrays, driven by the Z machine, generate a reconnection layer (S_{L}≈120) in which the cooling rate far exceeds the hydrodynamic transit rate (τ_{hydro}/τ_{cool}>100). The reconnection layer generates a transient burst of >1 keV x-ray emission, consistent with the formation and subsequent rapid cooling of the layer.
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