No Arabic abstract
Whether it be physical, biological or social processes, complex systems exhibit dynamics that are exceedingly difficult to understand or predict from underlying principles. Here we report a striking correspondence between the collective excitation dynamics of a laser driven ultracold gas of Rydberg atoms and the spreading of diseases, which in turn opens up a highly controllable experimental platform for studying non-equilibrium dynamics on complex networks. We find that the competition between facilitated excitation and spontaneous decay results in a fast growth of the number of excitations that follows a characteristic sub-exponential time dependence which is empirically observed as a key feature of real epidemics. Based on this we develop a quantitative microscopic susceptible-infected-susceptible (SIS) model which links the growth and final excitation density to the dynamics of an emergent heterogeneous network and rare active region effects associated to an extended Griffiths phase. This provides physical insights into the nature of non-equilibrium criticality in driven many-body systems and the mechanisms leading to non-universal power-laws in the dynamics of complex systems.
Atomic nuclei can be spontaneously deformed into non-spherical shapes as many-nucleon systems. We discuss to what extent a similar deformation takes place in many-electron systems. To this end, we employ several many-body methods, such as the unrestricted Hartree-Fock method, post-Hartree-Fock methods, and the density functional theory, to compute the electron distribution in atoms. We show that the electron distribution of open-shell atoms is deformed due solely to the single-particle valence orbitals, while the core part remains spherical. This is in contrast to atomic nuclei, which can be deformed collectively. We qualitatively discuss the origin for this apparent difference between atoms and nuclei by estimating the energy change due to deformation. We find that nature of the interaction plays an essential role for the collective deformation.
Genetic regulation is a key component in development, but a clear understanding of the structure and dynamics of genetic networks is not yet at hand. In this paper we investigate these properties within an artificial genome model originally introduced by Reil (1999). We analyze statistical properties of randomly generated genomes both on the sequence- and network level, and show that this model correctly predicts the frequency of genes in genomes as found in experimental data. Using an evolutionary algorithm based on stabilizing selection for a phenotype, we show that dynamical robustness against single base mutations, as well as against random changes in initial states of regulatory dynamics that mimic stochastic fluctuations in environmental conditions, can emerge in parallel. Point mutations at the sequence level have strongly non-linear effects on network wiring, including as well structurally neutral mutations and simultaneous rewiring of multiple connections, which occasionally lead to strong reorganization of the attractor landscape and metastability of evolutionary dynamics. Evolved genomes exhibit characteristic patterns on both sequence and network level.
We establish a localization phase diagram for light in a random three-dimensional (3D) ensemble of motionless two-level atoms with a three-fold degenerate upper level, in a strong static magnetic field. Localized modes appear in a narrow spectral band when the number density of atoms $rho$ exceeds a critical value $rho_c simeq 0.1 k_0^3$, where $k_0$ is the wave number of light in the free space. A critical exponent of the localization transition taking place upon varying the frequency of light at a constant $rho > rho_c$ is estimated to be $ u = 1.57 pm 0.07$. This classifies the transition as an Anderson localization transition of 3D orthogonal universality class.
We study the single-particle properties of a system formed by ultracold atoms loaded into the manifold of $l=1$ Orbital Angular Momentum (OAM) states of an optical lattice with a diamond chain geometry. Through a series of successive basis rotations, we show that the OAM degree of freedom induces phases in some tunneling amplitudes of the tight-binding model that are equivalent to a net $pi$ flux through the plaquettes and give rise to a topologically non-trivial band structure and protected edge states. In addition, we demonstrate that quantum interferences between the different tunneling processes involved in the dynamics may lead to Aharanov-Bohm caging in the system. All these analytical results are confirmed by exact diagonalization numerical calculations.
In contrast to software simulations of neural networks, hardware or neuromorphic implementations have often limited or no tunability. While such networks promise great improvements in terms of speed and energy efficiency, their performance is limited by the difficulty to apply efficient teaching. We propose a system of non-tunable exciton-polariton nodes and an efficient teaching method that relies on the precise measurement of the nonlinear node response and the subsequent use of the backpropagation algorithm. We demonstrate experimentally that the classification accuracy in the MNIST handwritten digit benchmark is greatly improved compared to the case where backpropagation is not used.