Self-driven oscillation in Coulomb blockaded suspended carbon nanotubes

Suspended carbon nanotubes are known to support self-driven oscillations due to electromechanical feedback under certain conditions, including low temperatures and high mechanical quality factors. Prior reports identified signatures of such oscillations in Kondo or high-bias transport regimes. Here, we observe self-driven oscillations that give rise to significant conduction in normally Coulomb-blockaded low-bias transport. Using a master equation model, the self-driving is shown to result from strongly energy-dependent electron tunneling, and the dependencies of transport features on bias, gate voltage, and temperature are well reproduced.Comment: Main text + Appendices (8 pages, 10 figures

High Stakes: Oregon Labor Sets Union Agenda for High Skill, High Wage Strategy

[Excerpt] The labor movement of Oregon is responding to the current economic crisis by adopting an agenda to help workers gain control over work and technology. The union agenda emphasizes worker-centered education and urges unions to become advocates for workers to develop their skills

A Lazy Approach for Supporting Nested Transactions

Transactional memory (TM) is a compelling alternative to traditional synchronization, and implementing TM primitives directly in hardware offers a potential performance advantage over software-based methods. In this paper, we demonstrate that many of the actions associated with transaction abort and commit may be performed lazily -- that is, incrementally, and on demand. This technique is ideal for hardware, since it requires little space or work; in addition, it can improve performance by sparing accesses to committing or aborting locations from having to stall until the commit or abort completes. We further show that our lazy abort and commit technique supports open nesting and orElse, two language-level proposals which rely on transactional nesting. We also provide design notes for supporting lazy abort and commit on our own hardware TM system, based on VTM

Inverting the Angular Correlation Function

The two point angular correlation function is an excellent measure of structure in the universe. To extract from it the three dimensional power spectrum, one must invert Limber's Equation. Here we perform this inversion using a Bayesian prior constraining the smoothness of the power spectrum. Among other virtues, this technique allows for the possibility that the estimates of the angular correlation function are correlated from bin to bin. The output of this technique are estimators for the binned power spectrum and a full covariance matrix. Angular correlations mix small and large scales but after the inversion, small scale data can be trivially eliminated, thereby allowing for realistic constraints on theories of large scale structure. We analyze the APM catalogue as an example, comparing our results with previous results. As a byproduct of these tests, we find -- in rough agreement with previous work -- that APM places stringent constraints on Cold Dark Matter inspired models, with the shape parameter constrained to be $0.25\pm 0.04$ (using data with wavenumber $k \le 0.1 h{\rm Mpc}^{-1}$). This range of allowed values use the full power spectrum covariance matrix, but assumes negligible covariance in the off-diagonal angular correlation error matrix, which is estimated with a large angular resolution of 0.5degrees (in the range 0.5 and 20 degrees).Comment: 7 pages, 11 figures, replace to match accepted version, MNRAS in pres