Hidden Cues in Random Line Stereograms

Successful fusion of random-line stereograms with breaks in the vernier acuity range has been interpreted to suggest that the interpolation process underlying hyperacuity is parallel and preliminary to stereomatching. In this paper (a) we demonstrate with computer experiments that vernier cues are not needed to solve the stereomatching problem posed by these stereograms and (b) we provide psychophysical evidence that human stereopsis probably does not use vernier cues alone to achieve fusion of these random-line stereograms.MIT Artificial Intelligence Laborator

Direct calculation of the hard-sphere crystal/melt interfacial free energy

We present a direct calculation by molecular-dynamics computer simulation of the crystal/melt interfacial free energy, $\gamma$, for a system of hard spheres of diameter $\sigma$. The calculation is performed by thermodynamic integration along a reversible path defined by cleaving, using specially constructed movable hard-sphere walls, separate bulk crystal and fluid systems, which are then merged to form an interface. We find the interfacial free energy to be slightly anisotropic with $\gamma$ = 0.62$\pm 0.01$, 0.64$\pm 0.01$ and 0.58$\pm 0.01 k_BT/\sigma^2$ for the (100), (110) and (111) fcc crystal/fluid interfaces, respectively. These values are consistent with earlier density functional calculations and recent experiments measuring the crystal nucleation rates from colloidal fluids of polystyrene spheres that have been interpreted [Marr and Gast, Langmuir {\bf 10}, 1348 (1994)] to give an estimate of $\gamma$ for the hard-sphere system of $0.55 \pm 0.02 k_BT/\sigma^2$, slightly lower than the directly determined value reported here.Comment: 4 pages, 4 figures, submitted to Physical Review Letter

The Regularizing Capacity of Metabolic Networks

Despite their topological complexity almost all functional properties of metabolic networks can be derived from steady-state dynamics. Indeed, many theoretical investigations (like flux-balance analysis) rely on extracting function from steady states. This leads to the interesting question, how metabolic networks avoid complex dynamics and maintain a steady-state behavior. Here, we expose metabolic network topologies to binary dynamics generated by simple local rules. We find that the networks' response is highly specific: Complex dynamics are systematically reduced on metabolic networks compared to randomized networks with identical degree sequences. Already small topological modifications substantially enhance the capacity of a network to host complex dynamic behavior and thus reduce its regularizing potential. This exceptionally pronounced regularization of dynamics encoded in the topology may explain, why steady-state behavior is ubiquitous in metabolism.Comment: 6 pages, 4 figure

Weighted-density approximation for general nonuniform fluid mixtures

In order to construct a general density-functional theory for nonuniform fluid mixtures, we propose an extension to multicomponent systems of the weighted-density approximation (WDA) of Curtin and Ashcroft [Phys. Rev. A 32, 2909 (1985)]. This extension corrects a deficiency in a similar extension proposed earlier by Denton and Ashcroft [Phys. Rev. A 42, 7312 (1990)], in that that functional cannot be applied to the multi-component nonuniform fluid systems with spatially varying composition, such as solid-fluid interfaces. As a test of the accuracy of our new functional, we apply it to the calculation of the freezing phase diagram of a binary hard-sphere fluid, and compare the results to simulation and the Denton-Ashcroft extension.Comment: 4 pages, 4 figures, to appear in Phys. Rev. E as Brief Repor

Learning, Social Intelligence and the Turing Test - why an "out-of-the-box" Turing Machine will not pass the Turing Test

The Turing Test (TT) checks for human intelligence, rather than any putative general intelligence. It involves repeated interaction requiring learning in the form of adaption to the human conversation partner. It is a macro-level post-hoc test in contrast to the definition of a Turing Machine (TM), which is a prior micro-level definition. This raises the question of whether learning is just another computational process, i.e. can be implemented as a TM. Here we argue that learning or adaption is fundamentally different from computation, though it does involve processes that can be seen as computations. To illustrate this difference we compare (a) designing a TM and (b) learning a TM, defining them for the purpose of the argument. We show that there is a well-defined sequence of problems which are not effectively designable but are learnable, in the form of the bounded halting problem. Some characteristics of human intelligence are reviewed including it's: interactive nature, learning abilities, imitative tendencies, linguistic ability and context-dependency. A story that explains some of these is the Social Intelligence Hypothesis. If this is broadly correct, this points to the necessity of a considerable period of acculturation (social learning in context) if an artificial intelligence is to pass the TT. Whilst it is always possible to 'compile' the results of learning into a TM, this would not be a designed TM and would not be able to continually adapt (pass future TTs). We conclude three things, namely that: a purely "designed" TM will never pass the TT; that there is no such thing as a general intelligence since it necessary involves learning; and that learning/adaption and computation should be clearly distinguished.Comment: 10 pages, invited talk at Turing Centenary Conference CiE 2012, special session on "The Turing Test and Thinking Machines

The Interstellar Rubidium Isotope Ratio toward Rho Ophiuchi A

The isotope ratio, 85Rb/87Rb, places constraints on models of the nucleosynthesis of heavy elements, but there is no precise determination of the ratio for material beyond the Solar System. We report the first measurement of the interstellar Rb isotope ratio. Our measurement of the Rb I line at 7800 A for the diffuse gas toward rho Oph A yields a value of 1.21 +/- 0.30 (1-sigma) that differs significantly from the meteoritic value of 2.59. The Rb/K elemental abundance ratio for the cloud also is lower than that seen in meteorites. Comparison of the 85Rb/K and 87Rb/K ratios with meteoritic values indicates that the interstellar 85Rb abundance in this direction is lower than the Solar System abundance. We attribute the lower abundance to a reduced contribution from the r-process. Interstellar abundances for Kr, Cd, and Sn are consistent with much less r-process synthesis for the solar neighborhood compared to the amount inferred for the Solar System.Comment: 12 pages with 2 figures and 1 table; will appear in ApJ Letter