Signatures of criticality arise in simple neural population models with correlations

Large-scale recordings of neuronal activity make it possible to gain insights into the collective activity of neural ensembles. It has been hypothesized that neural populations might be optimized to operate at a 'thermodynamic critical point', and that this property has implications for information processing. Support for this notion has come from a series of studies which identified statistical signatures of criticality in the ensemble activity of retinal ganglion cells. What are the underlying mechanisms that give rise to these observations? Here we show that signatures of criticality arise even in simple feed-forward models of retinal population activity. In particular, they occur whenever neural population data exhibits correlations, and is randomly sub-sampled during data analysis. These results show that signatures of criticality are not necessarily indicative of an optimized coding strategy, and challenge the utility of analysis approaches based on equilibrium thermodynamics for understanding partially observed biological systems.Comment: 36 pages, LaTeX; added journal reference on page 1, added link to code repositor

Quiet Sun Center to Limb Variation of the Linear Polarization Observed by CLASP2 Across the Mg ii h and k Lines

The CLASP2 (Chromospheric LAyer Spectro-Polarimeter 2) sounding rocket mission was launched on 2019 April 11. CLASP2 measured the four Stokes parameters of the Mg ii h and k spectral region around 2800 &Aring; along a 200'' slit at three locations on the solar disk, achieving the first spatially and spectrally resolved observations of the solar polarization in this near-ultraviolet region. The focus of the work presented here is the center-to-limb variation of the linear polarization across these resonance lines, which is produced by the scattering of anisotropic radiation in the solar atmosphere. The linear polarization signals of the Mg ii h and k lines are sensitive to the magnetic field from the low to the upper chromosphere through the Hanle and magneto-optical effects. We compare the observations to theoretical predictions from radiative transfer calculations in unmagnetized semiempirical models, arguing that magnetic fields and horizontal inhomogeneities are needed to explain the observed polarization signals and spatial variations. This comparison is an important step in both validating and refining our understanding of the physical origin of these polarization signatures, and also in paving the way toward future space telescopes for probing the magnetic fields of the solar upper atmosphere via ultraviolet spectropolarimetry. &nbsp;</p

Combining Sparsity DEM Inversions with Event Tracking for AIA Data

We introduce a modified version of the ASGARD code (Automated Selection and Grouping of events in A/A Regional Data). Originally written to detect and group brightenings ("events") in the AIA EUV channels, it now includes the sparsity DEM inversion method and instead detects emission measure enhancements in different temperature bins. Ultimately, the goal is to automatically determine heating and cooling rates in different coronal structures

Introduction of the ASGARD Code

ASGARD stands for 'Automated Selection and Grouping of events in AIA Regional Data'. The code is a refinement of the event detection method in Ugarte-Urra & Warren (2014). It is intended to automatically detect and group brightenings ('events') in the AIA EUV channels, to record event parameters, and to find related events over multiple channels. Ultimately, the goal is to automatically determine heating and cooling timescales in the corona and to significantly increase statistics in this respect. The code is written in IDL and requires the SolarSoft library. It is parallelized and can run with multiple CPUs. Input files are regions of interest (ROIs) in time series of AIA images from the JSOC cutout service (http://jsoc.stanford.edu/ajax/exportdata.html). The ROIs need to be tracked, co-registered, and limited in time (typically 12 hours)

The Force Cone Method Applied to Explain Hidden Whirls in Tribology

In tribologically loaded materials, folding instabilities and vortices lead to the formation of complex internal structures. This is true for geological as well as nanoscopic contacts. Classically, these structures have been described by Kelvin–Helmholtz instabilities or shear localization. We here introduce an alternative explanation based on an intuitive approach referred to as the force cone method. It is considered how whirls are situated near forces acting on a free surface of an elastic or elastoplastic solid. The force cone results are supplemented by finite element simulations. Depending on the direction of the acting force, one or two whirls are predicted by the simplified force cone method. In 3D, there is always a ring shaped whirl present. These modelling findings were tested in simple model experiments. The results qualitatively match the predictions and whirl formation was found. The force cone method and the experiments may seem trivial, but they are an ideal tool to intuitively understand the presence of whirls within a solid under a tribological load. The position of these whirls was found at the predicted places and the force cone method allows a direct approach to understand the complex processes in the otherwise buried interfaces of tribologically loaded materials