Scale Invariance of the Homentropic Inviscid Euler Equations with Application to the Noh Problem. (arXiv:1911.08069v1 [math.AP])

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We investigate the inviscid compressible flow (Euler) equations constrained by an equation of state (EOS) whose functional form is an arbitrary function of density. Under the aforementioned condition, we interrogate the scale-invariance of the inviscid Euler equations using symmetry methods. We find that under general conditions, we can reduce the inviscid Euler equations into a…

SHRY:a $\underline{\rm S}$uite for $\underline{\rm H}$igh-th$\underline{\rm r}$oughput generation of models with atomic substitutions implemented by p$\underline{\rm y}$thon. (arXiv:1911.08071v1 [physics.comp-ph])

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We considered the problem how to handle the exploding number of possibilities to choose atomic sites to be replaced by substituents in the supercell modeling of alloys, solid solutions, intermetallic compounds and doped materials. The number sometimes amounts to $\sim$ trillion, as we show in some selected examples, and hence straightforward manner to write out…

Strain Engineering of Quantum emitters in Hexagonal Boron Nitride. (arXiv:1911.08072v1 [cond-mat.mtrl-sci])

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Quantum emitters in hexagonal boron nitride (hBN) are promising building blocks for the realization of integrated quantum photonic systems. However, spectral inhomogeneity of the sources limits their potential applications. Here, we apply tensile strain to quantum emitters embedded in few-layer hBN films and realize both red and blue spectral shifts with tuning magnitudes up to…

Comparison Against Task Driven Artificial Neural Networks Reveals Functional Organization of Mouse Visual Cortex. (arXiv:1911.07986v1 [q-bio.NC])

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Partially inspired by features of computation in visual cortex, deep neural networks compute hierarchical representations of their inputs. While these networks have been highly successful in machine learning, it remains unclear to what extent they can aid our understanding of cortical function. Several groups have developed metrics that provide a quantitative comparison between representations computed…

Monte Carlo Simulations of DNA Damage and Cellular Response to Hadron Irradiation. (arXiv:1911.08000v1 [q-bio.QM])

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Numerical simulations are performed on a stochastic model based on Monte Carlo damage simulation process and Markov Chain Monte Carlo techniques to investigate the formation and evaluation of isolated and multiple DNA damage and cellular survival by light ionizing radiation in a colony of tumour cells. The contribution of the local clustering of the strand…

The Complexity-Stability Debate, Chemical Organization Theory, and the Identi cation of Non-Classical Structures in Ecology. (arXiv:1911.08006v1 [q-bio.PE])

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We present a novel approach to represent ecological systems using reaction networks, and show how a particular framework called Chemical Organization Theory (COT) sheds new light on the longstanding complexity-stability debate. Namely, COT provides a novel conceptual landscape plenty of analytic tools to explore the interplay between structure and stability of ecological systems. Given a…

Emergence of life in an inflationary universe. (arXiv:1911.08092v1 [q-bio.PE])

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Abiotic emergence of ordered information stored in the form of RNA is an important unresolved problem concerning the origin of life. A polymer longer than 40–100 nucleotides is necessary to expect a self-replicating activity, but the formation of such a long polymer having a correct nucleotide sequence by random reactions seems statistically unlikely. However, our…

Learning-Assisted Competitive Algorithms for Peak-Aware Energy Scheduling. (arXiv:1911.07972v1 [cs.DS])

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In this paper, we study the peak-aware energy scheduling problem using the competitive framework with machine learning prediction. With the uncertainty of energy demand as the fundamental challenge, the goal is to schedule the energy output of local generation units such that the electricity bill is minimized. While this problem has been tackled using classic…

Physical Layer Security in Vehicular Communication Networks in the Presence of Interference. (arXiv:1911.07977v1 [eess.SP])

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This paper studies the physical layer security of a vehicular communication network in the presence of interference constraints by analysing its secrecy capacity. The system considers a legitimate receiver node and an eavesdropper node, within a shared network, both under the effect of interference from other users. The double-Rayleigh fading channel is used to capture…

WITCHcraft: Efficient PGD attacks with random step size. (arXiv:1911.07989v1 [cs.LG])

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State-of-the-art adversarial attacks on neural networks use expensive iterative methods and numerous random restarts from different initial points. Iterative FGSM-based methods without restarts trade off performance for computational efficiency because they do not adequately explore the image space and are highly sensitive to the choice of step size. We propose a variant of Projected Gradient…