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Showing votes from 2016-06-21 11:30 to 2016-06-24 12:30 | Next meeting is Tuesday Aug 5th, 10:30 am.
The "gamification" of quantum mechanics, or, people are better at quantum mechanics than computers.
http://www.nature.com/nature/journal/v532/n7598/full/nature17620.html
Humans routinely solve problems of immense computational complexity by intuitively forming simple, low-dimensional heuristic strategies1, 2. Citizen science (or crowd sourcing) is a way of exploiting this ability by presenting scientific research problems to non-experts. ‘Gamification’—the application of game elements in a non-game context—isan effective tool with which to enable citizen scientists to provide solutions to research problems. The citizen science games Foldit3, EteRNA4 and EyeWire5 have been used successfully to study protein and RNA folding and neuron mapping, but so far gamification has not been applied to problems in quantum physics. Here we report on Quantum Moves, an online platform gamifying optimization problems in quantum physics. We show that human players are able to find solutions to difficult problems associated with the task of quantum computing6. Players succeed where purely numerical optimization fails, and analyses of their solutions provide insights into the problem of optimization of a more profound and general nature. Using player strategies, we have thus developed a few-parameter heuristic optimization method that efficiently outperforms the most prominent established numerical methods. The numerical complexity associated with time-optimal solutions increases for shorter process durations. To understand this better, we produced a low-dimensional rendering of the optimization landscape. This rendering reveals why traditional optimization methods fail near the quantum speed limit (that is, the shortest process duration with perfect fidelity)7, 8, 9. Combined analyses of optimization landscapes and heuristic solution strategies may benefit wider classes of optimization problems in quantum physics and beyond.
We study the dependence of the number density and properties of quasars on the background galaxy density using the currently largest spectroscopic datasets of quasars and galaxies. We construct a galaxy number density field smoothed over the variable smoothing scale of between approximately 10 and $20\,h^{-1}$Mpc over the redshift range of $0.46<z<0.59$ using the Sloan Digital Sky Survey (SDSS) Data Release 12 (DR12) Constant MASS (CMASS) galaxies. The quasar sample is prepared from the SDSS I/II DR7. We examine the correlation of incidence of quasars with the large-scale background density and dependence of quasar properties such as bolometric luminosity, black hole mass, and Eddington ratio on the large-scale density. We find a monotonic correlation between the quasar number density and large-scale galaxy number density, which is fitted well with a power law relation, $n_Q\propto\rho_G^{0.618}$. We detect weak dependences of quasar properties on the large-scale density such as a positive correlation between black hole mass and density, and a negative correlation between luminosity and density. We discuss the possibility of using quasars as a tracer of large-scale structures at high redshifts, which may be useful for studies of growth of structures in the high redshift universe.
We show that a particle detector can distinguish the interior of a hollow shell from flat space for switching times much shorter than the light-crossing time of the shell, even though the local metrics are indistinguishable. This shows that a particle detector can read out information about the non-local structure of spacetime even when switched on for scales much shorter than the characteristic scale of the non-locality.