First 100 ms of a long-lived magnetized neutron star formed in a binary neutron star merger

The recent multimessenger observation of the short gamma-ray burst (SGRB) GRB 170817A together with the gravitational wave (GW) event GW170817 provides evidence for the long-standing hypothesis associating SGRBs with binary neutron star (BNS) mergers. The nature of the remnant object powering the SGRB, which could have been either an accreting black hole (BH) or a long-lived magnetized neutron star (NS), is, however, still uncertain. General relativistic magnetohydrodynamic (GRMHD) simulations of the merger process represent a powerful tool to unravel the jet launching mechanism, but so far most simulations focused the attention on a BH as the central engine, while the long-lived NS scenario remains poorly investigated. Here, we explore the latter by performing a GRMHD BNS merger simulation extending up to ~100 ms after merger, much longer than any previous simulation of this kind. This allows us to (i) study the emerging structure and amplification of the magnetic field and observe a clear saturation at magnetic energy $E_\mathrm{mag} \sim 10^{51}$ erg, (ii) follow the magnetically supported expansion of the outer layers of the remnant NS and its evolution into an ellipsoidal shape without any surrounding torus, and (iii) monitor density, magnetization, and velocity along the axis, observing no signs of jet formation. We also argue that the conditions at the end of the simulation disfavor later jet formation on subsecond timescales if no BH is formed. Furthermore, we examine the rotation profile of the remnant, the conversion of rotational energy associated with differential rotation, the overall energy budget of the system, and the evolution of the GW frequency spectrum. Finally, we perform an additional simulation where we induce the collapse to a BH ~70 ms after merger, in order to gain insights on the prospects for massive accretion tori in case of a late collapse. We find that...Comment: 14 pages, 16 figures, matches published version in PR

Lost in Translation

A poster describing a linguistic service

Tying in Two-Sided Markets with Multi-Homing

We identify two issues in Choi's (2010) paper on tying in two-sided markets published in this Journal, and provide solutions to both of them. First, we point out that the equilibrium in the absence of tying requires more restrictive conditions and does not satisfy a natural equilibrium refinement criterion. We offer an alternative timing structure that validates the equilibrium derived in Choi (2010) under the conditions provided there. Second, we show that his equilibrium analysis with tying ignores a profitable deviation. We rectify this analysis under our alternative timing structure and derive the (mixed-strategy) equilibrium with tying. We also show by means of simulations that tying is welfare-enhancing whenever it is profitable, which is consistent with the main finding in Choi (2010)

Hippocampus and basal forebrain volumes modulate effects of anticholinergic treatment on delayed recall in healthy older adults.

"Introduction Volumes of hippocampus and cholinergic basal forebrain are associated with delayed recall performance and may modulate the effect of a muscarinic receptor antagonist on delayed recall in healthy volunteers Methods We studied 15 older adults before and after the oral administration of a single dose of 1 or 2 mg of the preferential M1 muscarinic receptor antagonist trihexyphenidyl (Artane™) or placebo in a double-blind randomized cross-over design. Hippocampus and basal forebrain volumes were measured using magnetic resonance imaging. Results We found a significant interaction between treatment and hippocampus volume and a trend level effect between treatment and anterior basal forebrain volume on task performance, with an attenuation of the association between volume size and performance with trihexyphenidyl. Discussion These findings suggest a reduction of delayed recall performance with increasing doses of the muscarinic antagonist that is related to an uncoupling of the association of task performance with cholinergic basal forebrain and hippocampus volumes.

Spritz: General Relativistic Magnetohydrodynamics with Neutrinos

We here present a new version of the publicly available general relativistic magnetohydrodynamic (GRMHD) code $\texttt{Spritz}$, which now includes an approximate neutrino leakage scheme able to handle neutrino cooling and heating. The leakage scheme is based on the publicly available $\texttt{ZelmaniLeak}$ code, with a few modifications in order to properly work with $\texttt{Spritz}$. We discuss the involved equations, physical assumptions, and implemented numerical methods, along with a large battery of general relativistic tests performed with and without magnetic fields. Our tests demonstrate the correct implementation of the neutrino leakage scheme, paving the way for further improvements of our neutrino treatment and the first application to magnetized binary neutron star mergers. We also discuss the implementation in the $\texttt{Spritz}$ code of high-order methods for a more accurate evolution of hydrodynamical quantities.Comment: 34 pages, 16 figures. The code is available on Zenodo as version 1.1.0 at https://doi.org/10.5281/zenodo.3689751. Initial data and equation of state used in this paper can be downloaded from https://drive.google.com/drive/folders/1kGBRW_AhKjHrOi76uXXPRyaCc1BfgqQN?usp=sharin

Experimental and Analytical Research on Fracture Processes in Rock

Experimental studies on fracture propagation and coalescence were conducted which together with previous tests by this group on gypsum and marble, provide information on fracturing. Specifically, different fracture geometries wsere tested, which together with the different material properties will provide the basis for analytical/numerical modeling. INitial steps on the models were made as were initial investigations on the effect of pressurized water on fracture coalescence

Neural operator learning of heterogeneous mechanobiological insults contributing to aortic aneurysms

[EN] Thoracic aortic aneurysm (TAA) is a localized dilatation of the aorta that can lead to life-threatening dissection or rupture. In vivo assessments of TAA progression are largely limited to measurements of aneurysm size and growth rate. There is promise, however, that computational modelling of the evolving biomechanics of the aorta could predict future geometry and properties from initiating mechanobiological insults. We present an integrated framework to train a deep operator network (DeepONet)-based surrogate model to identify TAA contributing factors using synthetic finite-element-based datasets. For training, we employ a constrained mixture model of aortic growth and remodelling to generate maps of local aortic dilatation and distensibility for multiple TAA risk factors. We evaluate the performance of the surrogate model for insult distributions varying from fusiform (analytically defined) to complex (randomly generated). We propose two frameworks, one trained on sparse information and one on full-field greyscale images, to gain insight into a preferred neural operator-based approach. We show that this continuous learning approach can predict the patient-specific insult profile associated with any given dilatation and distensibility map with high accuracy, particularly when based on full-field images. Our findings demonstrate the feasibility of applying DeepONet to support transfer learning of patient-specific inputs to predict TAA progression.This work was supported by the National Institutes of Health (grant nos. P01 HL134605 and U01 HL142518)Goswami, S.; Li, DS.; Rego, BV.; Latorre, M.; Humphrey, JD.; Karniadakis, GE. (2022). Neural operator learning of heterogeneous mechanobiological insults contributing to aortic aneurysms. Journal of The Royal Society Interface. 19(193):1-16. https://doi.org/10.1098/rsif.2022.04101161919

The Case for Climate Conscious, Low Carbon Federal Procurement

Purchasing practices are one of many contributors to the climate crisis. As the world’s largest purchaser of goods and services, the U.S. Federal Government is in a unique position to cut a significant portion of national emissions through the development of more responsible, sustainable, and—most importantly—climate-conscious supply chains. According to the Office of the Federal Chief Sustainability Officer, federal supply chain emissions associated with federal contracts are twice as high as Federal Scope 1 and Scope 2 emissions, combined. As such, reforming Federal procurement practices to limit direct emissions as well as emissions in supply chains can play a crucial role in reaching the goal of net-zero emissions by 2050. The Biden Administration has taken a strong stance on climate change, initiating, reinstating, and further developing necessary policy adjustments such as transitioning the government fleet to electric vehicles, supporting energy efficiency in buildings, and the uptake in renewable energy generation, and drafting a new Federal Sustainability Plan. The RCRC Committee has prepared recommendations relevant to Federal procurement practices to help achieve maximum emissions reductions at both the government and national levels