High energy gamma-rays and hadrons at Mount Fuji

The energy spectra of high energy gamma-rays and hadrons were obtained by the emulsion chamber with 40 c.u. thickness at Mt. Fuji (3750 m). These results are compared with the Monte Carlo calculation based on the same model which is used in a family analysis. Our data are compatible with the model of heavy-enriched primary and scaling in the fragmentation region

Particle interactions at energies over 1000 TeV inferred from gamma-families observed at Mount Fuji

Scaling, mean P sub t, high P sub t jets and others at energies over 1000 TeV are discussed on the basis of gamma-family data with sigma E sub gamma 100 TeV, observed at Mt. Fuji (3750 m). These quantities were examined in connection with the primary composition

Composition of primary cosmic rays at energies 10(15) to approximately 10(16) eV

The sigma epsilon gamma spectrum in 1 approx. 5 x 1000 TV observed at Mt. Fuji suggests that the flux of primary protons 10 to the 15 approx 10th eV is lower by a factor of 2 approx. 3 than a simple extrapolation from lower energies; the integral proton spectrum tends to be steeper than around to the power V and the spectral index tends to be steeper than Epsilon to the -17th power around 10 to the 14th power eV and the spectral index becomes approx. 2.0 around 10 to the 15th power eV. If the total flux of primary particles has no steepening up to approx 10 to the 15th power eV, than the fraction of primary protons to the total flux should be approx 20% in contrast to approx 45% at lower energies

Networks of Recurrent Events, a Theory of Records, and an Application to Finding Causal Signatures in Seismicity

We propose a method to search for signs of causal structure in spatiotemporal data making minimal a priori assumptions about the underlying dynamics. To this end, we generalize the elementary concept of recurrence for a point process in time to recurrent events in space and time. An event is defined to be a recurrence of any previous event if it is closer to it in space than all the intervening events. As such, each sequence of recurrences for a given event is a record breaking process. This definition provides a strictly data driven technique to search for structure. Defining events to be nodes, and linking each event to its recurrences, generates a network of recurrent events. Significant deviations in properties of that network compared to networks arising from random processes allows one to infer attributes of the causal dynamics that generate observable correlations in the patterns. We derive analytically a number of properties for the network of recurrent events composed by a random process. We extend the theory of records to treat not only the variable where records happen, but also time as continuous. In this way, we construct a fully symmetric theory of records leading to a number of new results. Those analytic results are compared to the properties of a network synthesized from earthquakes in Southern California. Significant disparities from the ensemble of acausal networks that can be plausibly attributed to the causal structure of seismicity are: (1) Invariance of network statistics with the time span of the events considered, (2) Appearance of a fundamental length scale for recurrences, independent of the time span of the catalog, which is consistent with observations of the ``rupture length'', (3) Hierarchy in the distances and times of subsequent recurrences.Comment: 19 pages, 13 figure

Testing earthquake links in Mexico from 1978 to the 2017 M = 8.1 Chiapas and M = 7.1 Puebla Shocks

The M = 8.1 Chiapas and the M = 7.1 Puebla earthquakes occurred in the bending part of the subducting Cocos plate 11 days and ~600 km apart, a range that puts them well outside the typical aftershock zone. We find this to be a relatively common occurrence in Mexico, with 14% of M > 7.0 earthquakes since 1900 striking more than 300 km apart and within a 2 week interval, not different from a randomized catalog. We calculate the triggering potential caused by crustal stress redistribution from large subduction earthquakes over the last 40 years. There is no evidence that static stress transfer or dynamic triggering from the 8 September Chiapas earthquake promoted the 19 September earthquake. Both recent earthquakes were promoted by past thrust events instead, including delayed afterslip from the 2012 M = 7.5 Oaxaca earthquake. A repeated pattern of shallow thrust events promoting deep intraslab earthquakes is observed over the past 40 years

Dissipative collisions in 16^{16}O + 27^{27}Al at Elab_{lab}=116 MeV

The inclusive energy distributions of fragments (3$\leq$Z$\leq$7) emitted in the reaction $^{16}$O + $^{27}$Al at $E_{lab} =$116 MeV have been measured in the angular range $\theta_{lab}$= 15$^\circ$ - 115$^\circ$. A non-linear optimisation procedure using multiple Gaussian distribution functions has been proposed to extract the fusion-fission and deep inelastic components of the fragment emission from the experimental data. The angular distributions of the fragments, thus obtained, from the deep inelastic component are found to fall off faster than those from the fusion-fission component, indicating shorter life times of the emitting di-nuclear systems. The life times of the intermediate di-nuclear configurations have been estimated using a diffractive Regge-pole model. The life times thus extracted ($\sim 1 - 5\times 10^{-22}$ Sec.) are found to decrease with the increase in the fragment charge. Optimum Q-values are also found to increase with increasing charge transfer i.e. with the decrease in fragment charge.Comment: 9 pages, 4 figures, 1 tabl

Fractal Dynamics of Earthquakes

Many objects in nature, from mountain landscapes to electrical breakdown and turbulence, have a self-similar fractal spatial structure. It seems obvious that to understand the origin of self-similar structures, one must understand the nature of the dynamical processes that created them: temporal and spatial properties must necessarily be completely interwoven. This is particularly true for earthquakes, which have a variety of fractal aspects. The distribution of energy released during earthquakes is given by the Gutenberg-Richter power law. The distribution of epicenters appears to be fractal with dimension D {approx} 1--1.3. The number of after shocks decay as a function of time according to the Omori power law. There have been several attempts to explain the Gutenberg-Richter law by starting from a fractal distribution of faults or stresses. But this is a hen-and-egg approach: to explain the Gutenberg-Richter law, one assumes the existence of another power-law--the fractal distribution. The authors present results of a simple stick slip model of earthquakes, which evolves to a self-organized critical state. Emphasis is on demonstrating that empirical power laws for earthquakes indicate that the Earth`s crust is at the critical state, with no typical time, space, or energy scale. Of course the model is tremendously oversimplified; however in analogy with equilibrium phenomena they do not expect criticality to depend on details of the model (universality)