Dimensional crossover in a layered ferromagnet detected by spin correlation driven distortions

Magneto-elastic distortions are commonly detected across magnetic long-range ordering (LRO) transitions. In principle, they are also induced by the magnetic short-range ordering (SRO) that precedes a LRO transition, which contains information about short-range correlations and energetics that are essential for understanding how LRO is established. However these distortions are difficult to resolve because the associated atomic displacements are exceedingly small and do not break symmetry. Here we demonstrate high-multipole nonlinear optical polarimetry as a sensitive and mode selective probe of SRO induced distortions using CrSiTe$_3$ as a testbed. This compound is composed of weakly bonded sheets of nearly isotropic ferromagnetically interacting spins that, in the Heisenberg limit, would individually be impeded from LRO by the Mermin-Wagner theorem. Our results show that CrSiTe$_3$ evades this law via a two-step crossover from two- to three-dimensional magnetic SRO, manifested through two successive and previously undetected totally symmetric distortions above its Curie temperature.Comment: 17 pages main text, 4 figures, 12 pages supplementary informatio

New PbSnTe heterojunction laser diode structures with improved performance

Several recent advances in the state-of-the-art of lead tin telluride double heterojunction laser diodes are summarized. Continuous Wave operation to 120 K and pulsed operation to 166 K with single, lowest order transverse mode emission to in excess of four times threshold at 80 K were achieved in buried stripe lasers fabricated by liquid phase epitaxy in the lattice-matched system, lead-tin telluride-lead telluride selenide. At the same time, liquid phase epitaxy was used to produce PbSnTe distributed feedback lasers with much broader continuous single mode tuning ranges than are available from Fabry-Perot lasers. The physics and philosophy behind these advances is as important as the structures and performance of the specific devices embodying the advances, particularly since structures are continually being evolved and the performance continues to be improved

Nonlinear optical probe of tunable surface electrons on a topological insulator

We use ultrafast laser pulses to experimentally demonstrate that the second-order optical response of bulk single crystals of the topological insulator Bi$_2$Se$_3$ is sensitive to its surface electrons. By performing surface doping dependence measurements as a function of photon polarization and sample orientation we show that second harmonic generation can simultaneously probe both the surface crystalline structure and the surface charge of Bi$_2$Se$_3$. Furthermore, we find that second harmonic generation using circularly polarized photons reveals the time-reversal symmetry properties of the system and is surprisingly robust against surface charging, which makes it a promising tool for spectroscopic studies of topological surfaces and buried interfaces

Toeplitz Inverse Covariance-Based Clustering of Multivariate Time Series Data

Subsequence clustering of multivariate time series is a useful tool for discovering repeated patterns in temporal data. Once these patterns have been discovered, seemingly complicated datasets can be interpreted as a temporal sequence of only a small number of states, or clusters. For example, raw sensor data from a fitness-tracking application can be expressed as a timeline of a select few actions (i.e., walking, sitting, running). However, discovering these patterns is challenging because it requires simultaneous segmentation and clustering of the time series. Furthermore, interpreting the resulting clusters is difficult, especially when the data is high-dimensional. Here we propose a new method of model-based clustering, which we call Toeplitz Inverse Covariance-based Clustering (TICC). Each cluster in the TICC method is defined by a correlation network, or Markov random field (MRF), characterizing the interdependencies between different observations in a typical subsequence of that cluster. Based on this graphical representation, TICC simultaneously segments and clusters the time series data. We solve the TICC problem through alternating minimization, using a variation of the expectation maximization (EM) algorithm. We derive closed-form solutions to efficiently solve the two resulting subproblems in a scalable way, through dynamic programming and the alternating direction method of multipliers (ADMM), respectively. We validate our approach by comparing TICC to several state-of-the-art baselines in a series of synthetic experiments, and we then demonstrate on an automobile sensor dataset how TICC can be used to learn interpretable clusters in real-world scenarios.Comment: This revised version fixes two small typos in the published versio

Coexistence of the topological state and a two-dimensional electron gas on the surface of Bi2Se3

Topological insulators are a recently discovered class of materials with fascinating properties: While the inside of the solid is insulating, fundamental symmetry considerations require the surfaces to be metallic. The metallic surface states show an unconventional spin texture, electron dynamics and stability. Recently, surfaces with only a single Dirac cone dispersion have received particular attention. These are predicted to play host to a number of novel physical phenomena such as Majorana fermions, magnetic monopoles and unconventional superconductivity. Such effects will mostly occur when the topological surface state lies in close proximity to a magnetic or electric field, a (superconducting) metal, or if the material is in a confined geometry. Here we show that a band bending near to the surface of the topological insulator Bi$_2$Se$_3$ gives rise to the formation of a two-dimensional electron gas (2DEG). The 2DEG, renowned from semiconductor surfaces and interfaces where it forms the basis of the integer and fractional quantum Hall effects, two-dimensional superconductivity, and a plethora of practical applications, coexists with the topological surface state in Bi$_2$Se$_3$. This leads to the unique situation where a topological and a non-topological, easily tunable and potentially superconducting, metallic state are confined to the same region of space.Comment: 12 pages, 3 figure

Don't bleach chaotic data

A common first step in time series signal analysis involves digitally filtering the data to remove linear correlations. The residual data is spectrally white (it is ``bleached''), but in principle retains the nonlinear structure of the original time series. It is well known that simple linear autocorrelation can give rise to spurious results in algorithms for estimating nonlinear invariants, such as fractal dimension and Lyapunov exponents. In theory, bleached data avoids these pitfalls. But in practice, bleaching obscures the underlying deterministic structure of a low-dimensional chaotic process. This appears to be a property of the chaos itself, since nonchaotic data are not similarly affected. The adverse effects of bleaching are demonstrated in a series of numerical experiments on known chaotic data. Some theoretical aspects are also discussed.Comment: 12 dense pages (82K) of ordinary LaTeX; uses macro psfig.tex for inclusion of figures in text; figures are uufile'd into a single file of size 306K; the final dvips'd postscript file is about 1.3mb Replaced 9/30/93 to incorporate final changes in the proofs and to make the LaTeX more portable; the paper will appear in CHAOS 4 (Dec, 1993

A Nonlinear Super-Exponential Rational Model of Speculative Financial Bubbles

Keeping a basic tenet of economic theory, rational expectations, we model the nonlinear positive feedback between agents in the stock market as an interplay between nonlinearity and multiplicative noise. The derived hyperbolic stochastic finite-time singularity formula transforms a Gaussian white noise into a rich time series possessing all the stylized facts of empirical prices, as well as accelerated speculative bubbles preceding crashes. We use the formula to invert the two years of price history prior to the recent crash on the Nasdaq (april 2000) and prior to the crash in the Hong Kong market associated with the Asian crisis in early 1994. These complex price dynamics are captured using only one exponent controlling the explosion, the variance and mean of the underlying random walk. This offers a new and powerful detection tool of speculative bubbles and herding behavior.Comment: Latex document of 24 pages including 5 eps figure

An upper limit for the water outgassing rate of the main-belt comet 176P/LINEAR observed with Herschel/HIFI

176P/LINEAR is a member of the new cometary class known as main-belt comets (MBCs). It displayed cometary activity shortly during its 2005 perihelion passage that may be driven by the sublimation of sub-surface ices. We have therefore searched for emission of the H2O 110-101 ground state rotational line at 557 GHz toward 176P/LINEAR with the Heterodyne Instrument for the Far Infrared (HIFI) on board the Herschel Space Observatory on UT 8.78 August 2011, about 40 days after its most recent perihelion passage, when the object was at a heliocentric distance of 2.58 AU. No H2O line emission was detected in our observations, from which we derive sensitive 3-sigma upper limits for the water production rate and column density of < 4e25 molec/s and of < 3e10 cm^{-2}, respectively. From the peak brightness measured during the object's active period in 2005, this upper limit is lower than predicted by the relation between production rates and visual magnitudes observed for a sample of comets by Jorda et al. (2008) at this heliocentric distance. Thus, 176P/LINEAR was likely less active at the time of our observation than during its previous perihelion passage. The retrieved upper limit is lower than most values derived for the H2O production rate from the spectroscopic search for CN emission in MBCs.Comment: 5 pages, 2 figures. Minor changes to match published versio