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The critical issue in cosmology today lies in determining if the cosmological constant is the underlying ingredient of dark energy. Our profound lack of understanding of the physics of dark energy places severe constrains on our ability to say anything about its possible dynamical nature. Quoted errors on the equation of state, w(z), are so heavily dependent on necessarily over-simplified parameterisations they are at risk of being rendered meaningless. Moreover, the existence of degeneracies between the reconstructed w(z) and the matter and curvature densities weakens any conclusions still further. We propose consistency tests for the cosmological constant which provide a direct observational signal if Lambda is wrong, regardless of the densities of matter and curvature. As an example of its utility, our flat case test can warn of a small transition from w(z)=-1 of 20% from SNAP quality data at 4-sigma, even when direct reconstruction techniques see virtually no evidence for deviation from Lambda. It is shown to successfully rule out a wide range of non-Lambda dark energy models with no reliance on knowledge of Omega_m using SNAP-quality data and a large range for using 10^5 supernovae as forecasted for LSST.
Under the aegis of isospin conservation, the amplitudes in Born approximation, i.e., considering the only one-photon-exchange mechanism, of the decay $psito Lambda overline Sigma{}^0+{rm c.c.}$, where $psi$ is a vector charmonium, and of the reaction
Lambda Virginis (LamVir) is a well-known double-lined spectroscopic Am binary with the interesting property that both stars are very similar in abundance but one is sharp-lined and the other is broad-lined. We present combined interferometric and spe
The unprecedented success of deep neural networks in many applications has made these networks a prime target for adversarial exploitation. In this paper, we introduce a benchmark technique for detecting backdoor attacks (aka Trojan attacks) on deep
We analyze Dark Energy Survey (DES) data to constrain a cosmological model where a subset of parameters -- focusing on $Omega_m$ -- are split int
We present an algorithm to decide whether a given ideal in the polynomial ring contains a monomial without using Grobner bases, factorization or sub-resultant computations.