Yang-Mills condensate dark energy coupled with matter and radiation

The coincidence problem is studied for the dark energy model of effective Yang-Mills condensate in a flat expanding universe during the matter-dominated stage. The YMC energy $\rho_y(t)$ is taken to represent the dark energy, which is coupled either with the matter, or with both the matter and the radiation components. The effective YM Lagrangian is completely determined by quantum field theory up to 1-loop order. It is found that under very generic initial conditions and for a variety of forms of coupling, the existence of the scaling solution during the early stages and the subsequent exit from the scaling regime are inevitable. The transition to the accelerating stage always occurs around a redshift $z\simeq (0.3\sim 0.5)$. Moreover, when the Yang-Mills condensate transfers energy into matter or into both matter and radiation, the equation of state $w_y$ of the Yang-Mills condensate can cross over -1 around $z\sim 2$, and takes on a current value $\simeq -1.1$. This is consistent with the recent preliminary observations on supernovae Ia. Therefore, the coincidence problem can be naturally solved in the effective YMC dark energy models.Comment: 24 pages, 18 figure

Incompleteness of Representation Theory: Hidden symmetries and Quantum Non-Integrability

Representation theory is shown to be incomplete in terms of enumerating all integrable limits of quantum systems. As a consequence, one can find exactly solvable Hamiltonians which have apparently strongly broken symmetry. The number of these hidden symmetries depends upon the realization of the Hamiltonian.Comment: 4 pages, Revtex, Phys. Rev. Lett. , July 27 (1997), in pres

Using LIP to Gloss Over Faces in Single-Stage Face Detection Networks

This work shows that it is possible to fool/attack recent state-of-the-art face detectors which are based on the single-stage networks. Successfully attacking face detectors could be a serious malware vulnerability when deploying a smart surveillance system utilizing face detectors. We show that existing adversarial perturbation methods are not effective to perform such an attack, especially when there are multiple faces in the input image. This is because the adversarial perturbation specifically generated for one face may disrupt the adversarial perturbation for another face. In this paper, we call this problem the Instance Perturbation Interference (IPI) problem. This IPI problem is addressed by studying the relationship between the deep neural network receptive field and the adversarial perturbation. As such, we propose the Localized Instance Perturbation (LIP) that uses adversarial perturbation constrained to the Effective Receptive Field (ERF) of a target to perform the attack. Experiment results show the LIP method massively outperforms existing adversarial perturbation generation methods -- often by a factor of 2 to 10.Comment: to appear ECCV 2018 (accepted version

Irrelevance of memory in the minority game

By means of extensive numerical simulations we show that all the distinctive features of the minority game introduced by Challet and Zhang (1997), are completely independent from the memory of the agents. The only crucial requirement is that all the individuals must posses the same information, irrespective of the fact that this information is true or false.Comment: 4 RevTeX pages, 4 figure