A new generation of interferometric instruments is emerging, which aims to use intensity mapping of redshifted 21 cm radiation to measure the large-scale structure of the Universe at z ≃ 1-2 over ...wide areas of the sky. While these instruments typically have limited angular resolution, they cover huge volumes and thus can be used to provide large samples of rare objects. In this paper we study how well such instruments could find spatially extended large-scale structures, such as cosmic voids, using a matched filter formalism. Such a formalism allows us to work in Fourier space, the natural space for interferometers, and to study the impact of finite u - v coverage, noise and foregrounds on our ability to recover voids. We find that in the absence of foregrounds, such instruments would provide enormous catalogs of voids, with high completeness, but that control of foregrounds is key to realizing this goal.
We sought to determine if higher plasma levels of brain injury biomarkers neurofilament light (NfL), phosphorylated tau 181 (pT181), tau, and ubiquitin C-terminal hydrolase L1 (UCHL1) were associated ...with unfavorable outcomes in children supported on extracorporeal membrane oxygenation (ECMO) with and without preceding cardiac arrest.
We conducted a secondary analysis of a two-center prospective observational study of ECMO patients 0-<18 years. Plasma concentrations of NfL, pT181, tau, and UCHL1 were measured on ECMO days 1, 2 and 3. Unfavorable outcome was defined as in-hospital mortality or discharge Pediatric Cerebral Performance Category (PCPC) >2 with decline from baseline PCPC among survivors.
Among 88 children on ECMO, mean tau levels were significantly higher on each of the first three ECMO days in children who underwent extracorporeal cardiopulmonary resuscitation (ECPR) compared to those with non-ECPR cardiac arrest or with no cardiac arrest preceding ECMO. Higher ECMO day 1 tau levels were significantly associated with increased hazard of unfavorable outcome in unadjusted (HR, 1.35, 95% CI 1.09–1.66) and adjusted (HR, 1.42; 95% CI 1.13–1.79) models. Higher levels of NfL or pT181 were not associated with increased hazard for unfavorable outcome in multivariable models.UCHL1 values were outside of detectable limits and thus deferred from analysis.
Levels of tau were significantly associated with increased hazard of death or unfavorable neurologic outcome in unadjusted and adjusted models. Biomarkers of brain injury, particularly tau, may aid in detection of neurologic injury and neuroprognostication in patients on ECMO with and without preceding cardiac arrest.
Anatomy of cosmic tidal reconstruction Karaçaylı, Naim Göksel; Padmanabhan, Nikhil
Monthly notices of the Royal Astronomical Society,
04/2019, Letnik:
486, Številka:
3
Journal Article
Recenzirano
21-cm intensity surveys aim to map neutral hydrogen atoms in the universe through hyper-fine emission. Unfortunately, long-wavelength (low-wavenumber) radial modes are highly contaminated by smooth ...astrophysical foregrounds that are six orders of magnitude brighter than the cosmological signal. This contamination also leaks into higher radial and angular wavenumber modes and forms a foreground wedge. Cosmic tidal reconstruction aims to extract the large-scale signal from anisotropic features in the local small-scale power spectrum through non-linear tidal interactions; losing small-scale modes to foreground wedge will impair its performance. In this paper, we review tidal interaction theory and estimator construction, and derive the theoretical expressions for the reconstructed spectra. We show the reconstruction is robust against peculiar velocities. Removing low line-of-sight k modes, we demonstrate cross-correlation coefficient r is greater than 0.7 on large scales (k ≲ 0.1 h Mpc-1) even with a cut-off value |$k^c_{\Vert }=0.1$| h Mpc-1. Discarding wedge modes yields 0.3 ≲ r ≲ 0.5 and completely removes the dependency on |$k^c_{\Vert}$| . Our theoretical predictions agree with these numerical simulations.
Abstract We present the first study on the gravitational impact of supernova feedback in an isolated soliton and a spherically symmetric dwarf SFDM halo of virial mass 1 × 1010M⊙. We use a boson mass ...m = 10−22eV/c2 and a soliton core rc ≈ 0.7kpc, comparable to typical half-light radii of Local Group dwarf galaxies. We simulate the rapid gas removal from the center of the soliton by a concentric external time-dependent Hernquist potential. We explore two scenarios of feedback blowouts: i) a massive single burst, and ii) multiple consecutive blowouts injecting the same total energy to the system, including various magnitudes for the blowouts in both scenarios. In all cases, we find one single blowout has a stronger effect on reducing the soliton central density. Feedback leads to central soliton densities that oscillate quasi-periodically for an isolated soliton and stochastically for a SFDM halo. The range in the density amplitude depends on the strength of the blowout, however we observe typical variations of a factor of ≥2. One important consequence of the stochastic fluctuating densities is that, if we had no prior knowledge of the system evolution, we can only know the configuration profile at a specific time within some accuracy. By fitting soliton profiles at different times to our simulated structures, we found the (1-σ) scatter of their time-dependent density profiles. For configurations within the 1σ range, we find the inferred boson mass is typically less than 20% different from the real value used in our simulations. Finally, we compare the observed dynamical masses of field dwarf galaxies in our Local Group with the implied range of viable solitons from our simulations and find good agreement.
ABSTRACT
We present a cosmic density field reconstruction method that augments the traditional reconstruction algorithms with a convolutional neural network (CNN). Following previous work, the key ...component of our method is to use the reconstructed density field as the input to the neural network. We extend this previous work by exploring how the performance of these reconstruction ideas depends on the input reconstruction algorithm, the reconstruction parameters, and the shot noise of the density field, as well as the robustness of the method. We build an eight-layer CNN and train the network with reconstructed density fields computed from the Quijote suite of simulations. The reconstructed density fields are generated by both the standard algorithm and a new iterative algorithm. In real space at z = 0, we find that the reconstructed field is 90 per cent correlated with the true initial density out to $k\sim 0.5 \, \mathrm{ h}\, \rm {Mpc}^{-1}$, a significant improvement over $k\sim 0.2 \, \mathrm{ h}\, \rm {Mpc}^{-1}$ achieved by the input reconstruction algorithms. We find similar improvements in redshift space, including an improved removal of redshift space distortions at small scales. We also find that the method is robust across changes in cosmology. Additionally, the CNN removes much of the variance from the choice of different reconstruction algorithms and reconstruction parameters. However, the effectiveness decreases with increasing shot noise, suggesting that such an approach is best suited to high density samples. This work highlights the additional information in the density field beyond linear scales as well as the power of complementing traditional analysis approaches with machine learning techniques.
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