Cumulants of the three state Potts model and of nonequilibrium models with C3v symmetry

The critical behavior of two-dimensional stochastic lattice gas models with C3v symmetry is analyzed. We study the cumulants of the order parameter for the three state (equilibrium) Potts model and for two irreversible models whose dynamic rules are invariant under the symmetry operations of the point group C3v. By means of extensive numerical analysis of the phase transition we show that irreversibility does not affect the critical behavior of the systems. In particular we find that the Binder reduced fourth order cumulant takes a universal value U* which is the same for the three state Potts model and for the irreversible models. The same universal behavior is observed for the reduced third-order cumulant.Comment: gzipped tar file containing: 1 latex file + 6 eps figure

The role of the coherence in the cross-correlation analysis of diffraction patterns from two-dimensional dense mono-disperse systems

The investigation of the static and dynamic structural properties of colloidal systems relies on techniques capable of atomic resolution in real space and femtosecond resolution in time. Recently, the cross-correlation function (CCF) analysis of both X-rays and electron diffraction patterns from dilute and dense aggregates has demonstrated the ability to retrieve information on the sample's local order and symmetry. Open questions remain regarding the role of the beam coherence in the formation of the diffraction pattern and the properties of the CCF, especially in dense systems. Here, we simulate the diffraction patterns of dense two-dimensional monodisperse systems of different symmetries, varying the transverse coherence of the probing wave, and analyze their CCF. We study samples with different symmetries at different size scale, as for example, pentamers arranged into a four-fold lattice where each pentamer is surrounded by triangular lattices, both ordered and disordered. In such systems, different symmetry modulations are arising in the CCF at specific scattering vectors. We demonstrate that the amplitude of the CCF is a fingerprint of the degree of the ordering in the sample and that at partial transverse coherence, the CCF of a dense sample corresponds to that of an individual scattering object.Comment: 22 pages, 7 figure

The role of controllability in optimizing quantum dynamics

This paper discusses the important role of controllability played on the complexity of optimizing quantum mechanical control systems. The study is based on a topology analysis of the corresponding quantum control landscape, which is referred to as the optimization objective as a functional of control fields. We find that the degree of controllability is closely relevant with the ruggedness of the landscape, which determines the search efficiency for global optima. This effect is demonstrated via the gate fidelity control landscape of a system whose controllability is restricted on a SU(2) dynamic symmetry group. We show that multiple local false traps (i.e., non-global suboptima) exist even if the target gate is realizable and that the number of these traps is increased by the loss of controllability, while the controllable systems are always devoid of false traps.Comment: 13 pages, 3 figure

Thomas-Ehrman effect in a three-body model: 16^{16}Ne case

The dynamic mechanism of the Thomas-Ehrman shift is studied in three-cluster systems by example of $^{16}$Ne and $^{16}$C isobaric mirror partners. We predict configuration mixings for $0^+$ and $2^+$ states in $^{16}$Ne and $^{16}$C. Large isospin symmetry breaking on the level of wave function component weights is demonstrated for these states and discussed as three-body mechanism of Thomas-Ehrman shift. It is shown that the description of the Coulomb displacement energies requires a consistency among three parameters: the $^{16}$Ne decay energy $E_T$, the $^{15}$F ground state energy $E_r$, and the configuration mixing parameters for the $^{16}$Ne/$^{16}$C $0^+$ and $2^+$ states. Basing on this analysis we infer the $^{15}$F $1/2^+$ ground state energy to be $E_r=1.39-1.42$ MeV.Comment: 10 pages 8 figure

Symmetry-Adapted Machine Learning for Information Security

Symmetry-adapted machine learning has shown encouraging ability to mitigate the security risks in information and communication technology (ICT) systems. It is a subset of artificial intelligence (AI) that relies on the principles of processing future events by learning past events or historical data. The autonomous nature of symmetry-adapted machine learning supports effective data processing and analysis for security detection in ICT systems without the interference of human authorities. Many industries are developing machine-learning-adapted solutions to support security for smart hardware, distributed computing, and the cloud. In our Special Issue book, we focus on the deployment of symmetry-adapted machine learning for information security in various application areas. This security approach can support effective methods to handle the dynamic nature of security attacks by extraction and analysis of data to identify hidden patterns of data. The main topics of this Issue include malware classification, an intrusion detection system, image watermarking, color image watermarking, battlefield target aggregation behavior recognition model, IP camera, Internet of Things (IoT) security, service function chain, indoor positioning system, and crypto-analysis