New computer architectures and their relationship to physics or why computer science is no good

In the past, computation scientists have found it convenient and productive to adopt a model of the computational universe that was very different from our models of the physical universe. This is chaning. As we build bigger computers out of smaller components, our models of computation are forced to change. There is reason to hope that our new models, for specific systems, will be similar to the models of physics. The paper is divided into three sections. The first argues that computer science is missing many of the things that make the laws of physics so powerful—locality, symmetry, invariance of scale. This is why physics is so nice and computer science isn't. The second section gives an example of a new-wave computing machine, and shows some physicslike laws that apply to its computations. The final section gives some reasons for expecting this convergence of physical and computational law.This report describes research done at the Artificial Intelligence Laboratory of the Massachusetts Institute of Technology. Support for the Artificial Intelligence Laboratory's artificial intelligence research is provided in part by the Advanced Research Projects Agency of the Department of Defense under contract with the Office of Naval Research. Contract N000 14-80-c-0505. The author is supported by a fellowship provided by the Fannie and John Hertz Foundation.     

A new experimental method for the study of regions of high spin and excitation energy

The excitation energy in ⁷²Se populated in the reaction ⁵⁸Ni(¹⁶O, 2pγ) for energies between 54.5 and 64.5 MeV has been measured by summing the γ-energy released in each γ-ray cascade. The average γ-multiplicity is simultaneously measured as a function of summed γ-energy. The method is useful for studying the highest regions of angular momentum and excitation energy.     

Adoption as a social marker: Innovation diffusion with outgroup aversion

Social identities are among the key factors driving behavior in complex societies. Signals of social identity are known to influence individual behaviors in the adoption of innovations. Yet the population-level consequences of identity signaling on the diffusion of innovations are largely unknown. Here we use both analytical and agent-based modeling to consider the spread of a beneficial innovation in a structured population in which there exist two groups who are averse to being mistaken for each other. We investigate the dynamics of adoption and consider the role of structural factors such as demographic skew and communication scale on population-level outcomes. We find that outgroup aversion can lead to adoption being delayed or suppressed in one group, and that population-wide underadoption is common. Comparing the two models, we find that differential adoption can arise due to structural constraints on information flow even in the absence of intrinsic between-group differences in adoption rates. Further, we find that patterns of polarization in adoption at both local and global scales depend on the details of demographic organization and the scale of communication. This research has particular relevance to widely beneficial but identity-relevant products and behaviors, such as green technologies, where overall levels of adoption determine the positive benefits that accrue to society at large.     

Gamma-ray multiplicity studies for 40Ar and 86Kr induced reactions leading to Er compound nuclei at limiting angular momenta

The moments of the γ-ray multiplicity distributions as a function of evaporation residue and of E_γ have been determined from γ-multiplicity measurements for the ^{116, 120, 122, 124}Sn(⁴⁰Ar, xn) reactions at 161 ≦ E(Ar) ≦ 236 MeV and for the ⁷⁶Ge(⁸⁶Kr, xn) reaction at 314 ≦ E(Kr) ≦ 376 MeV. Even at the highest incident energies where l_gr ≈ 120 units, it is not possible to populate nuclei with l > 65 units, the limiting l predicted for a rotating liquid drop. For the lowest incident energies these data are in agreement with the decay of a compound system. At the highest incident energy, however, significant deviations are observed from the expected decay of an equilibrated system. Such deviations are indicative of pre-equilibrium particle decay. Statistical calculations utilizing the code GROG12 are used to substantiate these conclusions. No evidence for a lower l-cut in the population of the compound system is observed; however, these data would not be sensitive to an l_cut ? 10 units. The moments of inertia extracted from the edge of the “collective E2 bump” in the 〈M_γ〉 versus E_γ data are in agreement with those predicted for a rotating liquid drop. The average multiplicity of the noncompound processes is estimated to be 8–11 for l_gr ? 100 units and increasing to 21 for l_gr ? 120 units.     

Nuclear reorientation effects for the 26Mg, 28Si(12C, 12C′) reactions at E = 41 MeV

Angular distributions for elastic and inelastic scattering of 41 MeV ¹²C from ²⁶Mg and ²⁸Si have been measured. Corresponding angular distributions from coupled-channels calculations show significant differences depending on whether a prolate or an oblate intrinsic shape is assumed. The ²⁶Mg and ²⁸Si data are best described by calculations with prolate and oblate shapes, respectively, in agreement with previous Coulomb excitation rorientation measurements. The Hendrie scaling procedure fails to accurately predict the measured nuclear β₂ deformation for ²⁶Mg.     

Two-dimensional angular optical scattering for the characterization of airborne microparticles

Two-dimensional angular optical scattering (TAOS) is recorded for several particle shapes and configurations. A lens is used to collect a large solid angle of the light and transform the angular profile into a planar distribution according to the Abbé sine condition. Qualitative agreement is found between experiment and theory for the TAOS from spheroids having the same aspect ratio but different sizes. A distinctive irregular island structure is observed in the TAOS from clusters of Bacillus subtilis spores and polystyrene latex spheres. The density per solid angle of these islands is found to increase with cluster diameter.     

Source apportionment of atmospheric particulate carbon in Las Vegas,Nevada,USA

A study was conducted to quantify wintertime contributions of source types to carbonaceous PM_2.5 at four urban sites in the Las Vegas Valley,one of the most rapidly growing urban areas in the southwestern United States.Twenty-four hour average ambient samples were collected for mass,ions,elements,organic carbon（OC）,elemental carbon（EC）,and trace organic markers analysis.Additional measurements were made to determine diurnal patterns in light-absorbing black carbon（BC） as a marker for combustion sources.Carbonaceous PM sources of on-road gasoline vehicles,on-road diesel vehicles,and off-road diesel engines were characterized with their chemical profiles,as well as fuel-based emission factors, using an In-Plume Sampling System.The Effective Variance Chemical Mass Balance（EV-CMB） source apportionment model was applied to the ambient samples collected,using source profiles developed in this study as well as profiles from other relevant studies.Four main sources contributed to PM_2.5 carbon within the Las Vegas Valley:（1） paved road dust,（2） on-road gasoline vehicles,（3） residential wood combustion,and（4） on-road diesel vehicles.CMB estimated that on-road mixed fleet gasoline vehicles are the largest source for OC and EC at all the sites.The contribution of paved road dust to both OC and EC was 5-10%at the four sites.On-road diesel vehicles contribute 22%of the OC and 34%of the EC at a site near the city center,which is located immediately downwind of a major freeway.Residential wood combustion is a more important source than on-road diesel vehicles for two residential neighborhood sites.These results are consistent with our conceptual model,and the research methodology may be applied to studying other urban areas.     

Structural health monitoring of fixed offshore structures using the bicoherence function of ambient vibration measurements

This paper investigates the use of the bicoherence function of measured structural acceleration to provide automatic early detection of damage in an offshore structure. A detailed simulation model is developed, including realistic wave loading, and is used to assess the performance of the method. The method is shown through analytical and numerical analysis to be insensitive to typical operating parameter variations and to variations in wave excitation force. It is demonstrated that very small changes in stiffness of individual structural members are detectable from measurements of global structural motion.