Electrical manipulation of an electronic two-state system in Ge/Si quantum dots

We calculate that the electron states of strained self-assembled Ge/Si quantum dots provide a convenient two-state system for electrical control. An electronic state localized at the apex of the quantum dot is nearly degenerate with a state localized at the base of the quantum dot. Small electric fields shift the electronic ground state from apex-localized to base-localized, which permits sensitive tuning of the electronic, optical and magnetic properties of the dot. As one example, we describe how spin-spin coupling between two Ge/Si dots can be controlled very sensitively by shifting the individual dot's electronic ground state between apex and base

Ab initio studies of the spin-transfer torque in tunnel junctions

We calculate the spin-transfer torque in Fe/MgO/Fe tunnel junctions and compare the results to those for all-metallic junctions. We show that the spin-transfer torque is interfacial in the ferromagnetic layer to a greater degree than in all-metallic junctions. This result originates in the half metallic behavior of Fe for the $\Delta_1$ states at the Brillouin zone center; in contrast to all-metallic structures, dephasing does not play an important role. We further show that it is possible to get a component of the torque that is out of the plane of the magnetizations and that is linear in the bias. However, observation of such a torque requires highly ideal samples. In samples with typical interfacial roughness, the torque is similar to that in all-metallic multilayers, although for different reasons.Comment: 5 pages, 4 figure

AdS-Carroll Branes

Coset methods are used to determine the action of a co-dimension one brane (domain wall) embedded in (d+1)-dimensional AdS space in the Carroll limit in which the speed of light goes to zero. The action is invariant under the non-linearly realized symmetries of the AdS-Carroll spacetime. The Nambu-Goldstone field exhibits a static spatial distribution for the brane with a time varying momentum density related to the brane's spatial shape as well as the AdS-C geometry. The AdS-C vector field dual theory is obtained.Comment: 47 page

Wind speed statistics for Goldstone, California, anemometer sites

An exploratory wind survey at an antenna complex was summarized statistically for application to future windmill designs. Data were collected at six locations from a total of 10 anemometers. Statistics include means, standard deviations, cubes, pattern factors, correlation coefficients, and exponents for power law profile of wind speed. Curves presented include: mean monthly wind speeds, moving averages, and diurnal variation patterns. It is concluded that three of the locations have sufficiently strong winds to justify consideration for windmill sites

Facilitated sequence counting and assembly by template mutagenesis

Presently, inferring the long-range structure of the DNA templates is limited by short read lengths. Accurate template counts suffer from distortions occurring during PCR amplification. We explore the utility of introducing random mutations in identical or nearly identical templates to create distinguishable patterns that are inherited during subsequent copying. We simulate the applications of this process under assumptions of error-free sequencing and perfect mapping, using cytosine deamination as a model for mutation. The simulations demonstrate that within readily achievable conditions of nucleotide conversion and sequence coverage, we can accurately count the number of otherwise identical molecules as well as connect variants separated by long spans of identical sequence. We discuss many potential applications, such as transcript profiling, isoform assembly, haplotype phasing, and de novo genome assembly

Learning cover context-free grammars from structural data

We consider the problem of learning an unknown context-free grammar when the only knowledge available and of interest to the learner is about its structural descriptions with depth at most $\ell.$ The goal is to learn a cover context-free grammar (CCFG) with respect to $\ell$, that is, a CFG whose structural descriptions with depth at most $\ell$ agree with those of the unknown CFG. We propose an algorithm, called $LA^\ell$, that efficiently learns a CCFG using two types of queries: structural equivalence and structural membership. We show that $LA^\ell$ runs in time polynomial in the number of states of a minimal deterministic finite cover tree automaton (DCTA) with respect to $\ell$. This number is often much smaller than the number of states of a minimum deterministic finite tree automaton for the structural descriptions of the unknown grammar

Aharonov-Bohm oscillations in a mesoscopic ring with a quantum dot

We present an analysis of the Aharonov-Bohm oscillations for a mesoscopic ring with a quantum dot inserted in one of its arms. It is shown that microreversibility demands that the phase of the Aharonov-Bohm oscillations changes {\it abruptly} when a resonant level crosses the Fermi energy. We use the Friedel sum rule to discuss the conservation of the parity of the oscillations at different conductance peaks. Our predictions are illustrated with the help of a simple one channel model that permits the variation of the potential landscape along the ring.Comment: 11 pages, Revtex style, 3 figures under request. Submitted to Phys. Rev. B (rapid communications

Fast Matrix Factorization for Online Recommendation with Implicit Feedback

This paper contributes improvements on both the effectiveness and efficiency of Matrix Factorization (MF) methods for implicit feedback. We highlight two critical issues of existing works. First, due to the large space of unobserved feedback, most existing works resort to assign a uniform weight to the missing data to reduce computational complexity. However, such a uniform assumption is invalid in real-world settings. Second, most methods are also designed in an offline setting and fail to keep up with the dynamic nature of online data. We address the above two issues in learning MF models from implicit feedback. We first propose to weight the missing data based on item popularity, which is more effective and flexible than the uniform-weight assumption. However, such a non-uniform weighting poses efficiency challenge in learning the model. To address this, we specifically design a new learning algorithm based on the element-wise Alternating Least Squares (eALS) technique, for efficiently optimizing a MF model with variably-weighted missing data. We exploit this efficiency to then seamlessly devise an incremental update strategy that instantly refreshes a MF model given new feedback. Through comprehensive experiments on two public datasets in both offline and online protocols, we show that our eALS method consistently outperforms state-of-the-art implicit MF methods. Our implementation is available at https://github.com/hexiangnan/sigir16-eals.Comment: 10 pages, 8 figure

Implications of Electronics Constraints for Solid-State Quantum Error Correction and Quantum Circuit Failure Probability

In this paper we present the impact of classical electronics constraints on a solid-state quantum dot logical qubit architecture. Constraints due to routing density, bandwidth allocation, signal timing, and thermally aware placement of classical supporting electronics significantly affect the quantum error correction circuit's error rate. We analyze one level of a quantum error correction circuit using nine data qubits in a Bacon-Shor code configured as a quantum memory. A hypothetical silicon double quantum dot quantum bit (qubit) is used as the fundamental element. A pessimistic estimate of the error probability of the quantum circuit is calculated using the total number of gates and idle time using a provably optimal schedule for the circuit operations obtained with an integer program methodology. The micro-architecture analysis provides insight about the different ways the electronics impact the circuit performance (e.g., extra idle time in the schedule), which can significantly limit the ultimate performance of any quantum circuit and therefore is a critical foundation for any future larger scale architecture analysis.Comment: 10 pages, 7 figures, 3 table

Magnetoresistance due to Domain Walls in Micron Scale Fe Wires with Stripe Domains

The magnetoresistance (MR) associated with domain boundaries has been investigated in microfabricated bcc Fe (0.65 to 20 $\mu$m linewidth) wires with controlled stripe domains. Domain configurations have been characterized using magnetic force microscopy. MR measurements as a function of field angle, temperature and domain configuration are used to estimate MR contributions due to resistivity anisotropy and domain walls. Evidence is presented that domain boundaries enhance the conductivity in such microstructures over a broad range of temperatures (1.5 K to 80 K).Comment: 8 pages, 3 postscript figures, and 2 jpg images (Fig 1 and 2) to appear in IEEE Transactions on Magnetics (Fall 1998