High-Temperature Alkali Vapor Cells with Anti-Relaxation Surface Coatings

Antirelaxation surface coatings allow long spin relaxation times in alkali-metal cells without buffer gas, enabling faster diffusion of the alkali atoms throughout the cell and giving larger signals due to narrower optical linewidths. Effective coatings were previously unavailable for operation at temperatures above 80 C. We demonstrate that octadecyltrichlorosilane (OTS) can allow potassium or rubidium atoms to experience hundreds of collisions with the cell surface before depolarizing, and that an OTS coating remains effective up to about 170 C for both potassium and rubidium. We consider the experimental concerns of operating without buffer gas and with minimal quenching gas at high vapor density, studying the stricter need for effective quenching of excited atoms and deriving the optical rotation signal shape for atoms with resolved hyperfine structure in the spin-temperature regime. As an example of a high-temperature application of antirelaxation coated alkali vapor cells, we operate a spin-exchange relaxation-free atomic magnetometer with sensitivity of 6 fT/sqrt(Hz) and magnetic linewidth as narrow as 2 Hz.Comment: 8 pages, 5 figures. The following article appeared in Journal of Applied Physics and may be found at http://link.aip.org/link/?jap/106/11490

Quantum optical waveform conversion

Currently proposed architectures for long-distance quantum communication rely on networks of quantum processors connected by optical communications channels [1,2]. The key resource for such networks is the entanglement of matter-based quantum systems with quantum optical fields for information transmission. The optical interaction bandwidth of these material systems is a tiny fraction of that available for optical communication, and the temporal shape of the quantum optical output pulse is often poorly suited for long-distance transmission. Here we demonstrate that nonlinear mixing of a quantum light pulse with a spectrally tailored classical field can compress the quantum pulse by more than a factor of 100 and flexibly reshape its temporal waveform, while preserving all quantum properties, including entanglement. Waveform conversion can be used with heralded arrays of quantum light emitters to enable quantum communication at the full data rate of optical telecommunications.Comment: submitte

Outsourcing labour to the cloud

Various forms of open sourcing to the online population are establishing themselves as cheap, effective methods of getting work done. These have revolutionised the traditional methods for innovation and have contributed to the enrichment of the concept of 'open innovation'. To date, the literature concerning this emerging topic has been spread across a diverse number of media, disciplines and academic journals. This paper attempts for the first time to survey the emerging phenomenon of open outsourcing of work to the internet using 'cloud computing'. The paper describes the volunteer origins and recent commercialisation of this business service. It then surveys the current platforms, applications and academic literature. Based on this, a generic classification for crowdsourcing tasks and a number of performance metrics are proposed. After discussing strengths and limitations, the paper concludes with an agenda for academic research in this new area

Geometric reasoning via internet crowdsourcing

The ability to interpret and reason about shapes is a peculiarly human capability that has proven difficult to reproduce algorithmically. So despite the fact that geometric modeling technology has made significant advances in the representation, display and modification of shapes, there have only been incremental advances in geometric reasoning. For example, although today's CAD systems can confidently identify isolated cylindrical holes, they struggle with more ambiguous tasks such as the identification of partial symmetries or similarities in arbitrary geometries. Even well defined problems such as 2D shape nesting or 3D packing generally resist elegant solution and rely instead on brute force explorations of a subset of the many possible solutions. Identifying economic ways to solving such problems would result in significant productivity gains across a wide range of industrial applications. The authors hypothesize that Internet Crowdsourcing might provide a pragmatic way of removing many geometric reasoning bottlenecks.This paper reports the results of experiments conducted with Amazon's mTurk site and designed to determine the feasibility of using Internet Crowdsourcing to carry out geometric reasoning tasks as well as establish some benchmark data for the quality, speed and costs of using this approach.After describing the general architecture and terminology of the mTurk Crowdsourcing system, the paper details the implementation and results of the following three investigations; 1) the identification of "Canonical" viewpoints for individual shapes, 2) the quantification of "similarity" relationships with-in collections of 3D models and 3) the efficient packing of 2D Strips into rectangular areas. The paper concludes with a discussion of the possibilities and limitations of the approach

First-principles quantum dynamics for fermions: Application to molecular dissociation

We demonstrate that the quantum dynamics of a many-body Fermi-Bose system can be simulated using a Gaussian phase-space representation method. In particular, we consider the application of the mixed fermion-boson model to ultracold quantum gases and simulate the dynamics of dissociation of a Bose-Einstein condensate of bosonic dimers into pairs of fermionic atoms. We quantify deviations of atom-atom pair correlations from Wick's factorization scheme, and show that atom-molecule and molecule-molecule correlations grow with time, in clear departures from pairing mean-field theories. As a first-principles approach, the method provides benchmarking of approximate approaches and can be used to validate dynamical probes for characterizing strongly correlated phases of fermionic systems.Comment: Final published versio

Two-dimensional Nanolithography Using Atom Interferometry

We propose a novel scheme for the lithography of arbitrary, two-dimensional nanostructures via matter-wave interference. The required quantum control is provided by a pi/2-pi-pi/2 atom interferometer with an integrated atom lens system. The lens system is developed such that it allows simultaneous control over atomic wave-packet spatial extent, trajectory, and phase signature. We demonstrate arbitrary pattern formations with two-dimensional 87Rb wavepackets through numerical simulations of the scheme in a practical parameter space. Prospects for experimental realizations of the lithography scheme are also discussed.Comment: 36 pages, 4 figure

Measurement of the hyperfine splitting of the 6S1/2_{1/2} level in rubidium

We present a measurement of the hyperfine splitting of the 6S$_{1/2}$ excited level of rubidium using two photon absorption spectroscopy in a glass cell. The values we obtain for the magnetic dipole constant A are 239.18(03) MHz and 807.66(08) MHz for $^{85}$Rb and $^{87}$Rb, respectively. The combination of the magnetic moments of the two isotopes and our measurements show a hyperfine anomaly in this atomic excited state. The observed hyperfine anomaly difference has a value of $_{87}\delta_{85}=-0.0036(2)$ due to the finite distribution of nuclear magnetization, the Bohr-Weisskopf effect.Comment: 12 pages, 14 figure

Validation of purdue engineering shape benchmark clusters by crowdsourcing

The effective organization of CAD data archives is central to PLM and consequently content based retrieval of 2D drawings and 3D models is often seen as a "holy grail" for the industry. Given this context, it is not surprising that the vision of a "Google for shape", which enables engineers to search databases of 3D models for components similar in shape to a query part, has motivated numerous researchers to investigate algorithms for computing geometric similarity. Measuring the effectiveness of the many approaches proposed has in turn lead to the creation of benchmark datasets against which researchers can compare the performance of their search engines. However to be useful the datasets used to measure the effectiveness of 3D retrieval algorithms must not only define a collection of models, but also provide a canonical specification of their relative similarity. Because the objective of shape retrieval algorithms is (typically) to retrieve groups of objects that humans perceive as "similar" these benchmark similarity relationships have (by definition) to be manually determined through inspection