Multivariate time series classification with temporal abstractions

The increase in the number of complex temporal datasets collected today has prompted the development of methods that extend classical machine learning and data mining methods to time-series data. This work focuses on methods for multivariate time-series classification. Time series classification is a challenging problem mostly because the number of temporal features that describe the data and are potentially useful for classification is enormous. We study and develop a temporal abstraction framework for generating multivariate time series features suitable for classification tasks. We propose the STF-Mine algorithm that automatically mines discriminative temporal abstraction patterns from the time series data and uses them to learn a classification model. Our experimental evaluations, carried out on both synthetic and real world medical data, demonstrate the benefit of our approach in learning accurate classifiers for time-series datasets. Copyright © 2009, Assocation for the Advancement of ArtdicaI Intelligence (www.aaai.org). All rights reserved

The Quantum Cocktail Party

We consider the problem of decorrelating states of coupled quantum systems. The decorrelation can be seen as separation of quantum signals, in analogy to the classical problem of signal-separation rising in the so-called cocktail-party context. The separation of signals cannot be achieved perfectly, and we analyse the optimal decorrelation map in terms of added noise in the local separated states. Analytical results can be obtained both in the case of two-level quantum systems and for Gaussian states of harmonic oscillators.Comment: 4 pages, 2figures, revtex

Generating qudits with d=3,4 encoded on two-photon states

We present an experimental method to engineer arbitrary pure states of qudits with d=3,4 using linear optics and a single nonlinear crystal.Comment: 4 pages, 1 eps figure. Minor changes. The title has been changed for publication on Physical Review

X-ray method to study temperature-dependent stripe domains in MnAs/GaAs(001)

MnAs films grown on GaAs (001) exhibit a progressive transition between hexagonal (ferromagnetic) and orthorhombic (paramagnetic) phases at wide temperature range instead of abrupt transition during the first-order phase transition. The coexistence of two phases is favored by the anisotropic strain arising from the constraint on the MnAs films imposed by the substrate. This phase coexistence occurs in ordered arrangement alternating periodic terrace steps. We present here a method to study the surface morphology throughout this transition by means of specular and diffuse scattering of soft x-rays, tuning the photon energy at the Mn 2p resonance. The results show the long-range arrangement of the periodic stripe-like structure during the phase coexistence and its period remains constant, in agreement with previous results using other techniques.Comment: 4 pages, 4 figures, submitted to Applied Physics Letter

A genetic algorithm-assisted semi-adaptive MMSE multi-user detection for MC-CDMA mobile communication systems

In this work, a novel Minimum-Mean Squared-Error (MMSE) multi-user detector is proposed for MC-CDMA transmission systems working over mobile radio channels characterized by time-varying multipath fading. The proposed MUD algorithm is based on a Genetic Algorithm (GA)-assisted per-carrier MMSE criterion. The GA block works in two successive steps: a training-aided step aimed at computing the optimal receiver weights using a very short training sequence, and a decision-directed step aimed at dynamically updating the weights vector during a channel coherence period. Numerical results evidenced BER performances almost coincident with ones yielded by ideal MMSE-MUD based on the perfect knowledge of channel impulse response. The proposed GA-assisted MMSE-MUD clearly outperforms state-of-the-art adaptive MMSE receivers based on deterministic gradient algorithms, especially for high number of transmitting users

Magnetic reconfiguration of MnAs/GaAs(001) observed by Magnetic Force Microscopy and Resonant Soft X-ray Scattering

We investigated the thermal evolution of the magnetic properties of MnAs epitaxial films grown on GaAs(001) during the coexistence of hexagonal/orthorhombic phases using polarized resonant (magnetic) soft X-ray scattering and magnetic force microscopy. The results of the diffuse satellite X-ray peaks were compared to those obtained by magnetic force microscopy and suggest a reorientation of ferromagnetic terraces as temperature rises. By measuring hysteresis loops at these peaks we show that this reorientation is common to all ferromagnetic terraces. The reorientation is explained by a simple model based on the shape anisotropy energy. Demagnetizing factors were calculated for different configurations suggested by the magnetic images. We noted that the magnetic moments flip from an in-plane mono-domain orientation at lower temperatures to a three-domain out-of-plane configuration at higher temperatures. The transition was observed when the ferromagnetic stripe width L is equal to 2.9 times the film thickness d. This is in good agreement with the expected theoretical value of L = 2.6d.Comment: 16 pages in PD

Quantum state decorrelation

We address the general problem of removing correlations from quantum states while preserving local quantum information as much as possible. We provide a complete solution in the case of two qubits, by evaluating the minimum amount of noise that is necessary to decorrelate covariant sets of bipartite states. We show that two harmonic oscillators in arbitrary Gaussian state can be decorrelated by a Gaussian covariant map. Finally, for finite-dimensional Hilbert spaces, we prove that states obtained from most cloning channels (e.g., universal and phase-covariant cloning) can be decorrelated only at the expense of a complete erasure of information about the copied state. More generally, in finite dimension, cloning without correlations is impossible for continuous sets of states. On the contrary, for continuos variables cloning, a slight modification of the customary set-up for cloning coherent states allows one to obtain clones without correlations.Comment: 11 pages, 2 figures, RevTex

Physical realizations of quantum operations

Quantum operations (QO) describe any state change allowed in quantum mechanics, such as the evolution of an open system or the state change due to a measurement. We address the problem of which unitary transformations and which observables can be used to achieve a QO with generally different input and output Hilbert spaces. We classify all unitary extensions of a QO, and give explicit realizations in terms of free-evolution direct-sum dilations and interacting tensor-product dilations. In terms of Hilbert space dimensionality the free-evolution dilations minimize the physical resources needed to realize the QO, and for this case we provide bounds for the dimension of the ancilla space versus the rank of the QO. The interacting dilations, on the other hand, correspond to the customary ancilla-system interaction realization, and for these we derive a majorization relation which selects the allowed unitary interactions between system and ancilla.Comment: 8 pages, no figures. Accepted for publication on Phys. Rev.

Minimum error discrimination of Pauli channels

We solve the problem of discriminating with minimum error probability two given Pauli channels. We show that, differently from the case of discrimination between unitary transformations, the use of entanglement with an ancillary system can strictly improve the discrimination, and any maximally entangled state allows to achieve the optimal discrimination. We also provide a simple necessary and sufficient condition in terms of the structure of the channels for which the ultimate minimum error probability can be achieved without entanglement assistance. When such a condition is satisfied, the optimal input state is simply an eigenstate of one of the Pauli matrices.Comment: 8 pages, no figure

Characterising a universal cloning machine by maximum-likelihood estimation

We apply a general method for the estimation of completely positive maps to the 1-to-2 universal covariant cloning machine. The method is based on the maximum-likelihood principle, and makes use of random input states, along with random projective measurements on the output clones. The downhill simplex algorithm is applied for the maximisation of the likelihood functional.Comment: 5 pages, 2 figure