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Unexpectedly strong X-ray emission from extragalactic radio jets on kiloparsec scales has been one of the major discoveries of Chandra, the only X-ray observatory capable of sub-arcsecond-scale imaging. The origin of this X-ray emission, which appears as a second spectral component from that of the radio emission, has been debated for over two decades. The most commonly assumed mechanism is inverse-Compton upscattering of the cosmic microwave background by very low-energy electrons in a still highly relativistic jet. Under this mechanism, no variability in the X-ray emission is expected. Here we report the detection of X-ray variability in the large-scale jet population, using a novel statistical analysis of 53 jets with multiple Chandra observations. Taken as a population, we find that the distribution of P values from a Poisson model is strongly inconsistent with steady emission, with a global P value of 1.96 × 10−4 under a Kolmogorov–Smirnov test against the expected uniform (0, 1) distribution. These results strongly imply that the dominant mechanism of X-ray production in kiloparsec-scale jets is synchrotron emission by a second population of electrons reaching multi-teraelectronvolt energies. X-ray variability on the timescale of months to a few years implies extremely small emitting volumes much smaller than the cross-section of the jet. 

Abstract The fruit flyDrosophila melanogastercombines surprisingly sophisticated behaviour with a highly tractable nervous system. A large part of the fly’s success as a model organism in modern neuroscience stems from the concentration of collaboratively generated molecular genetic and digital resources. As presented in our FlyWire companion paper¹, this now includes the first full brain connectome of an adult animal. Here we report the systematic and hierarchical annotation of this ∼130,000-neuron connectome including neuronal classes, cell types and developmental units (hemilineages). This enables any researcher to navigate this huge dataset and find systems and neurons of interest, linked to the literature through the Virtual Fly Brain database². Crucially, this resource includes 4,552 cell types. 3,094 are rigorous consensus validations of cell types previously proposed in the “hemibrain” connectome³. In addition, we propose 1,458 new cell types, arising mostly from the fact that the FlyWire connectome spans the whole brain, whereas the hemibrain derives from a subvolume. Comparison of FlyWire and the hemibrain showed that cell type counts and strong connections were largely stable, but connection weights were surprisingly variable within and across animals. Further analysis defined simple heuristics for connectome interpretation: connections stronger than 10 unitary synapses or providing >1% of the input to a target cell are highly conserved. Some cell types showed increased variability across connectomes: the most common cell type in the mushroom body, required for learning and memory, is almost twice as numerous in FlyWire as the hemibrain. We find evidence for functional homeostasis through adjustments of the absolute amount of excitatory input while maintaining the excitation-inhibition ratio. Finally, and surprisingly, about one third of the cell types proposed in the hemibrain connectome could not yet be reliably identified in the FlyWire connectome. We therefore suggest that cell types should be defined to be robust to inter-individual variation, namely as groups of cells that are quantitatively more similar to cells in a different brain than to any other cell in the same brain. Joint analysis of the FlyWire and hemibrain connectomes demonstrates the viability and utility of this new definition. Our work defines a consensus cell type atlas for the fly brain and provides both an intellectual framework and open source toolchain for brain-scale comparative connectomics. 

Since the launch of Chandra twenty years ago, one of the greatest mysteries surrounding Quasar Jets is the production mechanism for their extremely high X-ray luminosity. Two mechanisms have been proposed. In the first view, the X-ray emission is inverse-Comptonized CMB photons. This view requires a jet that is highly relativistic (bulk Lorentz factor >20–40) on scales of hundreds of kiloparsecs, and a jet that is comparably or more powerful than the black hole’s Eddington luminosity. The second possibility is synchrotron emission from a high-energy population of electrons. This requires a much less powerful jet that does not need to be relativistically beamed, but it imposes other extreme requirements, namely the need to accelerate particles to >100 TeV energies at distances of hundreds of kiloparsecs from the active nucleus. We are exploring these questions using a suite of observations from a diverse group of telescopes, including the Hubble Space Telescope (HST), Chandra X-ray Observatory (CXO), Fermi Gamma-ray Space Telescope and various radio telescope arrays. Our results strongly favor the hypothesis that the X-ray emission is synchrotron radiation from a separate, high-energy electron population. We discuss the observations, results and new questions brought up by these surprising results. We investigate the physical processes and magnetic field structure that may help to accelerate particles to such extreme energies. 

Abstract Connections between neurons can be mapped by acquiring and analyzing electron microscopic (EM) brain images. In recent years, this approach has been applied to chunks of brains to reconstruct local connectivity maps that are highly informative, yet inadequate for understanding brain function more globally. Here, we present the first neuronal wiring diagram of a whole adult brain, containing 5×10⁷chemical synapses between ∼130,000 neurons reconstructed from a femaleDrosophila melanogaster. The resource also incorporates annotations of cell classes and types, nerves, hemilineages, and predictions of neurotransmitter identities. Data products are available by download, programmatic access, and interactive browsing and made interoperable with other fly data resources. We show how to derive a projectome, a map of projections between regions, from the connectome. We demonstrate the tracing of synaptic pathways and the analysis of information flow from inputs (sensory and ascending neurons) to outputs (motor, endocrine, and descending neurons), across both hemispheres, and between the central brain and the optic lobes. Tracing from a subset of photoreceptors all the way to descending motor pathways illustrates how structure can uncover putative circuit mechanisms underlying sensorimotor behaviors. The technologies and open ecosystem of the FlyWire Consortium set the stage for future large-scale connectome projects in other species. 

The data is from a direct numerical simulation of forced isotropic turbulence on a 10243 periodic grid, using a pseudo-spectral parallel code. Time integration of the viscous term is done analytically using integrating factor. The other terms are integrated using a second-order Adams-Bashforth scheme and the nonlinear term is written in vorticity form1. The simulation is de-aliased using phase-shift and a 2√2 /3 truncation2,3. Energy is injected by keeping constant the total energy in modes such that their wave-number magnitude is less or equal to 2. After the simulation has reached a statistical stationary state, 5028 frames of data, which includes the 3 components of the velocity vector and the pressure, are generated and ingested into the database. The duration of the stored data is about five large-eddy turnover times.