Particle Physics on Ice: Constraints on Neutrino Interactions Far Above the Weak Scale

Ultra-high energy cosmic rays and neutrinos probe energies far above the weak scale. Their usefulness might appear to be limited by astrophysical uncertainties; however, by simultaneously considering up- and down-going events, one may disentangle particle physics from astrophysics. We show that present data from the AMANDA experiment in the South Pole ice already imply an upper bound on neutrino cross sections at energy scales that will likely never be probed at man-made accelerators. The existing data also place an upper limit on the neutrino flux valid for any neutrino cross section. In the future, similar analyses of IceCube data will constrain neutrino properties and fluxes at the O(10%) level.Comment: 4 pages, 1 figure, published versio

Short-Term Memory in Orthogonal Neural Networks

We study the ability of linear recurrent networks obeying discrete time dynamics to store long temporal sequences that are retrievable from the instantaneous state of the network. We calculate this temporal memory capacity for both distributed shift register and random orthogonal connectivity matrices. We show that the memory capacity of these networks scales with system size.Comment: 4 pages, 4 figures, to be published in Phys. Rev. Let

Robustness against Power is PSPACE-complete

Power is a RISC architecture developed by IBM, Freescale, and several other companies and implemented in a series of POWER processors. The architecture features a relaxed memory model providing very weak guarantees with respect to the ordering and atomicity of memory accesses. Due to these weaknesses, some programs that are correct under sequential consistency (SC) show undesirable effects when run under Power. We call these programs not robust against the Power memory model. Formally, a program is robust if every computation under Power has the same data and control dependencies as some SC computation. Our contribution is a decision procedure for robustness of concurrent programs against the Power memory model. It is based on three ideas. First, we reformulate robustness in terms of the acyclicity of a happens-before relation. Second, we prove that among the computations with cyclic happens-before relation there is one in a certain normal form. Finally, we reduce the existence of such a normal-form computation to a language emptiness problem. Altogether, this yields a PSPACE algorithm for checking robustness against Power. We complement it by a matching lower bound to show PSPACE-completeness