Valence Bond Entanglement and Fluctuations in Random Singlet Phases

The ground state of the uniform antiferromagnetic spin-1/2 Heisenberg chain can be viewed as a strongly fluctuating liquid of valence bonds, while in disordered chains these bonds lock into random singlet states on long length scales. We show that this phenomenon can be studied numerically, even in the case of weak disorder, by calculating the mean value of the number of valence bonds leaving a block of $L$ contiguous spins (the valence-bond entanglement entropy) as well as the fluctuations in this number. These fluctuations show a clear crossover from a small $L$ regime, in which they behave similar to those of the uniform model, to a large $L$ regime in which they saturate in a way consistent with the formation of a random singlet state on long length scales. A scaling analysis of these fluctuations is used to study the dependence on disorder strength of the length scale characterizing the crossover between these two regimes. Results are obtained for a class of models which include, in addition to the spin-1/2 Heisenberg chain, the uniform and disordered critical 1D transverse-field Ising model and chains of interacting non-Abelian anyons.Comment: 8 pages, 6 figure

Wearable Sensor Data Based Human Activity Recognition using Machine Learning: A new approach

Recent years have witnessed the rapid development of human activity recognition (HAR) based on wearable sensor data. One can find many practical applications in this area, especially in the field of health care. Many machine learning algorithms such as Decision Trees, Support Vector Machine, Naive Bayes, K-Nearest Neighbor, and Multilayer Perceptron are successfully used in HAR. Although these methods are fast and easy for implementation, they still have some limitations due to poor performance in a number of situations. In this paper, we propose a novel method based on the ensemble learning to boost the performance of these machine learning methods for HAR

Industrial Internet of Things, Big Data, and Artificial Intelligence in the Smart Factory: a survey and perspective

International audienceThanks to the rapid development and applications of advanced technologies, we are experiencing the fourth industrial revolution, or Industry 4.0, which is a revolution towards smart manufacturing. The wide use of cyber physical systems and Internet of Things leads to the era of Big Data in industrial manufacturing. Artificial Intelligence algorithms emerge as powerful analytics tools to process and analyze the Big Data. These advanced technologies result in the introduction of a new concept in the Industry 4.0: the smart Factory. In order to fully understand this new concept in the context of the Industry 4.0, this paper provides a survey on the key components of a smart factory and the link between them, including the Industrial Internet of Things, Big Data and Artificial Intelligence. Several studies and techniques that are used to enable smart manufacturing are reviewed. Finally, we discuss some perspectives for further researches

Number Fluctuation in an interacting trapped gas in one and two dimensions

It is well-known that the number fluctuation in the grand canonical ensemble, which is directly proportional to the compressibility, diverges for an ideal bose gas as T -> 0. We show that this divergence is removed when the atoms interact in one dimension through an inverse square two-body interaction. In two dimensions, similar results are obtained using a self-consistent Thomas-Fermi (TF) model for a repulsive zero-range interaction. Both models may be mapped on to a system of non-interacting particles obeying the Haldane-Wu exclusion statistics. We also calculate the number fluctuation from the ground state of the gas in these interacting models, and compare the grand canonical results with those obtained from the canonical ensemble.Comment: 11 pages, 1 appendix, 3 figures. Submitted to J. Phys. B: Atomic, Molecular & Optica

Polarization of Broad Absorption Line QSOs I. A Spectropolarimetric Atlas

We present a spectropolarimetric survey of 36 broad absorption line quasi-stellar objects (BAL QSOs). The continuum, absorption trough, and emission line polarization of BAL QSOs yield clues about their structure. We confirm that BAL QSOs are in general more highly polarized than non-BAL QSOs, consistent with a more equatorial viewing direction for the former than the latter. We have identified two new highly-polarized QSOs in our sample (1232+1325 and 1333+2840). The polarization rises weakly to the blue in most objects, perhaps due to scattering and absorption by dust particles. We find that a polarization increase in the BAL troughs is a general property of polarized BAL QSOs, indicating an excess of scattered light relative to direct light, and consistent with the unification of BAL QSOs and non-BAL QSOs. We have also discovered evidence of resonantly scattered photons in the red wing of the C IV broad emission lines of a few objects. In most cases, the broad emission lines have lower polarization and a different position angle than the continuum. The polarization characteristics of low-ionization BAL QSOs are similar to those of high-ionization BAL QSOs, suggesting a similar BAL wind geometry.Comment: 39 pages, 6 figures (20 .gif files), accepted for publication in The Astrophysical Journal Supplement

Exploring the Flame Chemistry of C5Tetrahydrofuranic Biofuels: Tetrahydrofurfuryl Alcohol and 2-Methyltetrahydrofuran

Recently, the combustion chemistry of tetrahydrofurfuryl alcohol (THFA), a potential biofuel, was investigated in a stoichiometric 20 mol % THFA/methane co-fueled premixed flame at 5.3 kPa by our group (Tran, L.-S.; Carstensen, H.-H.; Foo, K. K.; Lamoureux, N.; Gosselin, S.; Gasnot, L.; El-Bakali, A.; Desgroux, P. Experimental and modeling study of the high-temperature combustion chemistry of tetrahydrofurfuryl alcohol. Proc. Combust. Inst. 2021, 38, 631-640, 10.1016/j.proci.2020.07.057). With regard to this, we continue to further explore the combustion chemistry of this biofuel to understand the influence of THFA-doping amounts on the flame chemistry of its mixture with methane and the impact of the alcohol function of THFA on the product spectrum compared to its non-alcoholic fuel counterpart, i.e., 2-methyltetrahydrofuran (MTHF). To accomplish the above said objective, a methane flame, a 10% THFA/methane flame, and a 20% MTHF/methane flame were additionally analyzed at similar conditions using gas chromatography for quantitative species detection and NO laser-induced fluorescence thermometry. More than 40 species (reactants, CO, CO2, H2O, H2, and about 14 hydrocarbons as well as 26 oxygenated intermediates up to 5 carbon atoms) were quantified for each doped biofuel flame. The product distributions and consumption pathways of THFA are similar for the 10 and 20% THFA-doped flames. The maximum yields of most products increase linearly with the amount of doped THFA. However, some species do not follow this trend, indicating interaction chemistry between methane and THFA, which is found to be mainly caused by the reaction of the methyl radical. The difference in the chemical structure in THFA and MTHF has no notable impact on the mole fractions of CO, CO2, H2O, and H2, but significant differences exist for the yields of intermediate species. The doped THFA flame produces more aldehydes, alcohols, and ethers but forms clearly less ketones and hydrocarbons. A slightly upgraded version of our previous kinetic model reproduces most experimental data well and is able to explain the observed differences in intermediate production. © 2021 American Chemical Society

MAXIPOL: Cosmic Microwave Background Polarimetry Using a Rotating Half-Wave Plate

We discuss MAXIPOL, a bolometric balloon-borne experiment designed to measure the E-mode polarization of the cosmic microwave background radiation (CMB). MAXIPOL is the first bolometric CMB experiment to observe the sky using rapid polarization modulation. To build MAXIPOL, the CMB temperature anisotropy experiment MAXIMA was retrofitted with a rotating half-wave plate and a stationary analyzer. We describe the instrument, the observations, the calibration and the reduction of data collected with twelve polarimeters operating at 140 GHz and with a FWHM beam size of 10 arcmin. We present maps of the Q and U Stokes parameters of an 8 deg^2 region of the sky near the star Beta Ursae Minoris. The power spectra computed from these maps give weak evidence for an EE signal. The maximum-likelihood amplitude of l(l+1)C^{EE}_{l}/(2 pi) is 55_{-45}^{+51} uK^2 (68%), and the likelihood function is asymmetric and skewed positive such that with a uniform prior the probability that the amplitude is positive is 96%. This result is consistent with the expected concordance LCDM amplitude of 14 uK^2. The maximum likelihood amplitudes for l(l+1)C^{BB}_{l}/(2 pi) and $\ell(\ell+1)C^{EB}_{\ell}/2\pi$ are -31_{-19}^{+31} and 18_{-34}^{+27} uK^2 (68%), respectively, which are consistent with zero. All of the results are for one bin in the range 151 < l < 693. Tests revealed no residual systematic errors in the time or map domain. A comprehensive discussion of the analysis of the data is presented in a companion paper.Comment: 19 pages, 11 figures, 2 tables, submitted to Ap

Homogenization of weakly coupled systems of Hamilton--Jacobi equations with fast switching rates

We consider homogenization for weakly coupled systems of Hamilton--Jacobi equations with fast switching rates. The fast switching rate terms force the solutions converge to the same limit, which is a solution of the effective equation. We discover the appearance of the initial layers, which appear naturally when we consider the systems with different initial data and analyze them rigorously. In particular, we obtain matched asymptotic solutions of the systems and rate of convergence. We also investigate properties of the effective Hamiltonian of weakly coupled systems and show some examples which do not appear in the context of single equations.Comment: final version, to appear in Arch. Ration. Mech. Ana