Neutron Electric Dipole Moment at Fixed Topology

We describe the finite volume effects of CP-odd quantities, such as the neutron electric dipole moment and the anapole moment in the $\theta$-vacuum, under different topological sectors. We evaluate the three-point Green's functions for the electromagnetic current in a fixed non-trivial topological sector in order to extract these CP-odd observables. We discuss the role of zero modes in the CP-odd Green's function and show that, in the quenched approximation, there is a power divergence in the quark mass for CP-odd quantities at finite volume.Comment: 12 pages, revised manuscript to be publishe

Examining the crossover from hadronic to partonic phase in QCD

It is argued that, due to the existence of two vacua -- perturbative and physical -- in QCD, the mechanism for the crossover from hadronic to partonic phase is hard to construct. The challenge is: how to realize the transition between the two vacua during the gradual crossover of the two phases. A possible solution of this problem is proposed and a mechanism for crossover, consistent with the principle of QCD, is constructed. The essence of this mechanism is the appearance and growing up of a kind of grape-shape perturbative vacuum inside the physical one. A dynamical percolation model based on a simple dynamics for the delocalization of partons is constructed to exhibit this mechanism. The crossover from hadronic matter to sQGP as well as the transition from sQGP to wQGP in the increasing of temperature is successfully described by using this model with a temperature dependent parameter.Comment: 4 pages, 4 figure

Polaronic effect in the x-ray absorption spectra of La1-x Ca x MnO3 manganites.

X-ray absorption spectroscopy (XAS) is performed to study changes in the electronic structures of colossal magnetoresistance (CMR) and charged ordered (CO) La1-x Ca x MnO3 manganites with respect to temperature. The pre-edge features in O and Mn K-edge XAS spectra, which are highly sensitive to the local distortion of MnO6 octahedral, exhibit contrasting temperature dependence between CMR and CO samples. The seemingly counter-intuitive XAS temperature dependence can be reconciled in the context of polarons. These results help identify the most relevant orbital states associated with polarons and highlight the crucial role played by polarons in understanding the electronic structures of manganites

Consistent Anisotropic Repulsions for Simple Molecules

We extract atom-atom potentials from the effective spherical potentials that suc cessfully model Hugoniot experiments on molecular fluids, e.g., $O_2$ and $N_2$. In the case of $O_2$ the resulting potentials compare very well with the atom-atom potentials used in studies of solid-state propertie s, while for $N_2$ they are considerably softer at short distances. Ground state (T=0K) and room temperatu re calculations performed with the new $N-N$ potential resolve the previous discrepancy between experimental and theoretical results.Comment: RevTeX, 5 figure

Analyzing Robustness of the Deep Reinforcement Learning Algorithm in Ramp Metering Applications Considering False Data Injection Attack and Defense

Ramp metering is the act of controlling on-going vehicles to the highway mainlines. Decades of practices of ramp metering have proved that ramp metering can decrease total travel time, mitigate shockwaves, decrease rear-end collisions by smoothing the traffic interweaving process, etc. Besides traditional control algorithm like ALINEA, Deep Reinforcement Learning (DRL) algorithms have been introduced to build a finer control. However, two remaining challenges still hinder DRL from being implemented in the real world: (1) some assumptions of algorithms are hard to be matched in the real world; (2) the rich input states may make the model vulnerable to attacks and data noises. To investigate these issues, we propose a Deep Q-Learning algorithm using only loop detectors information as inputs in this study. Then, a set of False Data Injection attacks and random noise attack are designed to investigate the robustness of the model. The major benefit of the model is that it can be applied to almost any ramp metering sites regardless of the road geometries and layouts. Besides outcompeting the ALINEA method, the Deep Q-Learning method also shows a good robustness through training among very different demands and geometries. For example, during the testing case in I-24 near Murfreesboro, TN, the model shows its robustness as it still outperforms ALINEA algorithm under Fast Gradient Sign Method attacks. Unlike many previous studies, the model is trained and tested in completely different environments to show the capabilities of the model.Comment: 11 pages, 5 figure

Character expansion of Kac–Moody correction factors

A correction factor naturally arises in the theory of p-adic Kac–Moody groups. We expand the correction factor into a sum of irreducible characters of the underlying Kac–Moody algebra. We derive a formula for the coefficients which lie in the ring of power series with integral coefficients. In the case that the Weyl group is a universal Coxeter group, we show that the coefficients are actually polynomials