Computing by nowhere increasing complexity

A cellular automaton is presented whose governing rule is that the Kolmogorov complexity of a cell's neighborhood may not increase when the cell's present value is substituted for its future value. Using an approximation of this two-dimensional Kolmogorov complexity the underlying automaton is shown to be capable of simulating logic circuits. It is also shown to capture trianry logic described by a quandle, a non-associative algebraic structure. A similar automaton whose rule permits at times the increase of a cell's neighborhood complexity is shown to produce animated entities which can be used as information carriers akin to gliders in Conway's game of life

Force-induced desorption of a linear polymer chain adsorbed on an attractive surface

We consider a model of self-avoiding walk on a lattice with on-site repulsion and an attraction for every vertex of the walk visited on the surface to study force-induced desorption of a linear polymer chain adsorbed on an attractive surface and use the exact enumeration technique for analyzing how the critical force for desorption $f_c(T)$ depends on the temperature. The curve $f_c(T)$ gives the boundary separating the adsorbed phase from the desorbed phase. Our results show that in two dimensions where surface is a line the force $f_c(T)$ increases monotonically as temperature is lowered and becomes almost constant at very low temperatures. In case of three-dimensions we, however, find re-entrance, i. e. $f_c(T)$ goes through a maximum as temperature is lowered. The behaviour of the polymer chain at different values of temperature and force is examined by calculating the probability distribution of the height from the surface of the vertex at which external force is applied.Comment: Preprint 15 pages with 8figures and two tables. The file table-2d.ps and table-3d.ps lists C_N(Ns,h) for given N with all possible Ns and h in two and three dimension

Mesoscopic theory for fluctuating active nematics

Peer reviewedPublisher PD

Chiral Symmetry Breaking and Pion Wave Function

We consider here chiral symmetry breaking through nontrivial vacuum structure with quark antiquark condensates. We then relate the condensate function to the wave function of pion as a Goldstone mode. This simultaneously yields the pion also as a quark antiquark bound state as a localised zero mode in vacuum. We illustrate the above with Nambu Jona-Lasinio model to calculate different pionic properties in terms of the vacuum structure for breaking of exact or approximate chiral symmetry, as well as the condensate fluctuations giving rise to $\sigma$ mesons.Comment: latex, revtex, 16 page

Disorder-induced topological change of the superconducting gap structure in iron pnictides

In superconductors with unconventional pairing mechanisms, the energy gap in the excitation spectrum often has nodes, which allow quasiparticle excitations at low energies. In many cases, e.g. $d$-wave cuprate superconductors, the position and topology of nodes are imposed by the symmetry, and thus the presence of gapless excitations is protected against disorder. Here we report on the observation of distinct changes in the gap structure of iron-pnictide superconductors with increasing impurity scattering. By the successive introduction of nonmagnetic point defects into BaFe$_2$(As$_{1-x}$P$_x$)$_2$ crystals via electron irradiation, we find from the low-temperature penetration depth measurements that the nodal state changes to a nodeless state with fully gapped excitations. Moreover, under further irradiation the gapped state evolves into another gapless state, providing bulk evidence of unconventional sign-changing $s$-wave superconductivity. This demonstrates that the topology of the superconducting gap can be controlled by disorder, which is a strikingly unique feature of iron pnictides.Comment: 5 pages, 4 figure

Aperiodic tumbling of microrods advected in a microchannel flow

We report on an experimental investigation of the tumbling of microrods in the shear flow of a microchannel (40 x 2.5 x 0.4 mm). The rods are 20 to 30 microns long and their diameters are of the order of 1 micron. Images of the centre-of-mass motion and the orientational dynamics of the rods are recorded using a microscope equipped with a CCD camera. A motorised microscope stage is used to track individual rods as they move along the channel. Automated image analysis determines the position and orientation of a tracked rods in each video frame. We find different behaviours, depending on the particle shape, its initial position, and orientation. First, we observe periodic as well as aperiodic tumbling. Second, the data show that different tumbling trajectories exhibit different sensitivities to external perturbations. These observations can be explained by slight asymmetries of the rods. Third we observe that after some time, initially periodic trajectories lose their phase. We attribute this to drift of the centre of mass of the rod from one to another stream line of the channel flow.Comment: 14 pages, 8 figures, as accepted for publicatio

Getting CICY high

Supervised machine learning can be used to predict properties of string geometries with previously unknown features. Using the complete intersection Calabi–Yau (CICY) threefold dataset as a theoretical laboratory for this investigation, we use low h1,1 geometries for training and validate on geometries with large h1,1. Neural networks and Support Vector Machines successfully predict trends in the number of Kähler parameters of CICY threefolds. The numerical accuracy of machine learning improves upon seeding the training set with a small number of samples at higher h1,1

Machine learning CICY threefolds

The latest techniques from Neural Networks and Support Vector Machines (SVM) are used to investigate geometric properties of Complete Intersection Calabi–Yau (CICY) threefolds, a class of manifolds that facilitate string model building. An advanced neural network classifier and SVM are employed to (1) learn Hodge numbers and report a remarkable improvement over previous efforts, (2) query for favourability, and (3) predict discrete symmetries, a highly imbalanced problem to which both Synthetic Minority Oversampling Technique (SMOTE) and permutations of the CICY matrix are used to decrease the class imbalance and improve performance. In each case study, we employ a genetic algorithm to optimise the hyperparameters of the neural network. We demonstrate that our approach provides quick diagnostic tools capable of shortlisting quasi-realistic string models based on compactification over smooth CICYs and further supports the paradigm that classes of problems in algebraic geometry can be machine learned

Structure of the Vacuum in Nuclear Matter - A Nonperturbative Approach

We compute the vacuum polarisation correction to the binding energy of nuclear matter in the Walecka model using a nonperturbative approach. We first study such a contribution as arising from a ground state structure with baryon-antibaryon condensates. This yields the same results as obtained through the relativistic Hartree approximation of summing tadpole diagrams for the baryon propagator. Such a vacuum is then generalized to include quantum effects from meson fields through scalar-meson condensates. The method is applied to study properties of nuclear matter and leads to a softer equation of state giving a lower value of the incompressibility than would be reached without quantum effects. The density dependent effective sigma mass is also calculated including such vacuum polarisation effects.Comment: 26 pages including 5 eps files, uses revtex style; PACS number: 21.65.+f,21.30.+