Quantitative maps of geomagnetic perturbation vectors during substorm onset and recovery

We have produced the first series of spherical harmonic, numerical maps of the time‐dependent surface perturbations in the Earth's magnetic field following the onset of substorms. Data from 124 ground magnetometer stations in the Northern Hemisphere at geomagnetic latitudes above 33° were used. Ground station data averaged over 5 min intervals covering 8 years (1998–2005) were used to construct pseudo auroral upper, auroral lower, and auroral electrojet (AU*, AL*, and AE*) indices. These indices were used to generate a list of substorms that extended from 1998 to 2005, through a combination of automated processing and visual checks. Events were sorted by interplanetary magnetic field (IMF) orientation (at the Advanced Composition Explorer (ACE) satellite), dipole tilt angle, and substorm magnitude. Within each category, the events were aligned on substorm onset. A spherical cap harmonic analysis was used to obtain a least error fit of the substorm disturbance patterns at 5 min intervals up to 90 min after onset. The fits obtained at onset time were subtracted from all subsequent fits, for each group of substorm events. Maps of the three vector components of the averaged magnetic perturbations were constructed to show the effects of substorm currents. These maps are produced for several specific ranges of values for the peak |AL*| index, IMF orientation, and dipole tilt angle. We demonstrate an influence of the dipole tilt angle on the response to substorms. Our results indicate that there are downward currents poleward and upward currents just equatorward of the peak in the substorms' westward electrojet.Key PointsShow quantitative maps of ground geomagnetic perturbations due to substormsThree vector components mapped as function of time during onset and recoveryCompare/contrast results for different tilt angle and sign of IMF Y‐componentPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/110891/1/jgra51610.pd

Neural Attentive Session-based Recommendation

Given e-commerce scenarios that user profiles are invisible, session-based recommendation is proposed to generate recommendation results from short sessions. Previous work only considers the user's sequential behavior in the current session, whereas the user's main purpose in the current session is not emphasized. In this paper, we propose a novel neural networks framework, i.e., Neural Attentive Recommendation Machine (NARM), to tackle this problem. Specifically, we explore a hybrid encoder with an attention mechanism to model the user's sequential behavior and capture the user's main purpose in the current session, which are combined as a unified session representation later. We then compute the recommendation scores for each candidate item with a bi-linear matching scheme based on this unified session representation. We train NARM by jointly learning the item and session representations as well as their matchings. We carried out extensive experiments on two benchmark datasets. Our experimental results show that NARM outperforms state-of-the-art baselines on both datasets. Furthermore, we also find that NARM achieves a significant improvement on long sessions, which demonstrates its advantages in modeling the user's sequential behavior and main purpose simultaneously.Comment: Proceedings of the 2017 ACM on Conference on Information and Knowledge Management. arXiv admin note: text overlap with arXiv:1511.06939, arXiv:1606.08117 by other author

BlinkML: Efficient Maximum Likelihood Estimation with Probabilistic Guarantees

The rising volume of datasets has made training machine learning (ML) models a major computational cost in the enterprise. Given the iterative nature of model and parameter tuning, many analysts use a small sample of their entire data during their initial stage of analysis to make quick decisions (e.g., what features or hyperparameters to use) and use the entire dataset only in later stages (i.e., when they have converged to a specific model). This sampling, however, is performed in an ad-hoc fashion. Most practitioners cannot precisely capture the effect of sampling on the quality of their model, and eventually on their decision-making process during the tuning phase. Moreover, without systematic support for sampling operators, many optimizations and reuse opportunities are lost. In this paper, we introduce BlinkML, a system for fast, quality-guaranteed ML training. BlinkML allows users to make error-computation tradeoffs: instead of training a model on their full data (i.e., full model), BlinkML can quickly train an approximate model with quality guarantees using a sample. The quality guarantees ensure that, with high probability, the approximate model makes the same predictions as the full model. BlinkML currently supports any ML model that relies on maximum likelihood estimation (MLE), which includes Generalized Linear Models (e.g., linear regression, logistic regression, max entropy classifier, Poisson regression) as well as PPCA (Probabilistic Principal Component Analysis). Our experiments show that BlinkML can speed up the training of large-scale ML tasks by 6.26x-629x while guaranteeing the same predictions, with 95% probability, as the full model.Comment: 22 pages, SIGMOD 201

Two-dimensional array of microtraps with atomic shift register on a chip

Arrays of trapped atoms are the ideal starting point for developing registers comprising large numbers of physical qubits for storing and processing quantum information. One very promising approach involves neutral atom traps produced on microfabricated devices known as atom chips, as almost arbitrary trap configurations can be realised in a robust and compact package. Until now, however, atom chip experiments have focused on small systems incorporating single or only a few individual traps. Here we report experiments on a two-dimensional array of trapped ultracold atom clouds prepared using a simple magnetic-film atom chip. We are able to load atoms into hundreds of tightly confining and optically resolved array sites. We then cool the individual atom clouds in parallel to the critical temperature required for quantum degeneracy. Atoms are shuttled across the chip surface utilising the atom chip as an atomic shift register and local manipulation of atoms is implemented using a focused laser to rapidly empty individual traps.Comment: 6 pages, 4 figure

Local effective dynamics of quantum systems: A generalized approach to work and heat

By computing the local energy expectation values with respect to some local measurement basis we show that for any quantum system there are two fundamentally different contributions: changes in energy that do not alter the local von Neumann entropy and changes that do. We identify the former as work and the latter as heat. Since our derivation makes no assumptions on the system Hamiltonian or its state, the result is valid even for states arbitrarily far from equilibrium. Examples are discussed ranging from the classical limit to purely quantum mechanical scenarios, i.e. where the Hamiltonian and the density operator do not commute.Comment: 5 pages, 1 figure, published versio

Digital Quantum Simulation with Rydberg Atoms

We discuss in detail the implementation of an open-system quantum simulator with Rydberg states of neutral atoms held in an optical lattice. Our scheme allows one to realize both coherent as well as dissipative dynamics of complex spin models involving many-body interactions and constraints. The central building block of the simulation scheme is constituted by a mesoscopic Rydberg gate that permits the entanglement of several atoms in an efficient, robust and quick protocol. In addition, optical pumping on ancillary atoms provides the dissipative ingredient for engineering the coupling between the system and a tailored environment. As an illustration, we discuss how the simulator enables the simulation of coherent evolution of quantum spin models such as the two-dimensional Heisenberg model and Kitaev's toric code, which involves four-body spin interactions. We moreover show that in principle also the simulation of lattice fermions can be achieved. As an example for controlled dissipative dynamics, we discuss ground state cooling of frustration-free spin Hamiltonians.Comment: submitted to special issue "Quantum Information with Neutral Particles" of "Quantum Information Processing

Teacher and Student-focused Approaches: influence of learning approach and self-efficacy in a psychology postgraduate sample

The current study examined approaches to teaching in a postgraduate psychology sample. This included considering teaching-focused (information transfer) and student-focused (conceptual changes in understanding) approaches to teaching. Postgraduate teachers of psychology ( N = 113) completed a questionnaire measuring their use of a teacher- or student-focused approach, deep and surface approaches to learning and teaching, and research self-efficacy. Standard multiple regressions revealed that the manner in which postgraduate students approached their own studies (i.e., deep or surface learning approach) predicted the use of a teacher- or student-focused approach in their teaching practice. Specifically, postgraduates adopting a deep approach to their own learning were more likely to adopt a teaching-focused approach to their teaching practice. Those adopting a surface approach to their own studies were most likely to adopt a student-focused approach. Furthermore, postgraduates with a high level of teaching self-efficacy were more likely to adopt a student-focused approach to teaching practice. Additionally, postgraduates who had received formal teaching training scored higher on teacher self-efficacy than those who had not received such training. Taken together, the findings suggest the key role of formal training in enhancing self-efficacy in teaching, and demonstrate an association between the learning styles adopted by postgraduate teachers and their approach to teaching. </jats:p

Associating ground magnetometer observations with current or voltage generators

A circuit analogy for magnetosphere‐ionosphere current systems has two extremes for drivers of ionospheric currents: ionospheric electric fields/voltages constant while current/conductivity vary—the “voltage generator”—and current constant while electric field/conductivity vary—the “current generator.” Statistical studies of ground magnetometer observations associated with dayside Transient High Latitude Current Systems (THLCS) driven by similar mechanisms find contradictory results using this paradigm: some studies associate THLCS with voltage generators, others with current generators. We argue that most of this contradiction arises from two assumptions used to interpret ground magnetometer observations: (1) measurements made at fixed position relative to the THLCS field‐aligned current and (2) negligible auroral precipitation contributions to ionospheric conductivity. We use observations and simulations to illustrate how these two assumptions substantially alter expectations for magnetic perturbations associated with either a current or a voltage generator. Our results demonstrate that before interpreting ground magnetometer observations of THLCS in the context of current/voltage generators, the location of a ground magnetometer station relative to the THLCS field‐aligned current and the location of any auroral zone conductivity enhancements need to be taken into account.Key PointsConductivity and location assumptions used to interpret ground magnetic perturbations yield conflicting resultsHigh‐latitude currents associated with voltage generators may instead be associated with current generators, and vice versaWithout better constraints on conductivity/station location relative to currents, conflicts will not be resolvedPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/138366/1/jgra53632.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/138366/2/jgra53632_am.pd