Block Tridiagonal Reduction of Perturbed Normal and Rank Structured Matrices

It is well known that if a matrix $A\in\mathbb C^{n\times n}$ solves the matrix equation $f(A,A^H)=0$, where $f(x, y)$ is a linear bivariate polynomial, then $A$ is normal; $A$ and $A^H$ can be simultaneously reduced in a finite number of operations to tridiagonal form by a unitary congruence and, moreover, the spectrum of $A$ is located on a straight line in the complex plane. In this paper we present some generalizations of these properties for almost normal matrices which satisfy certain quadratic matrix equations arising in the study of structured eigenvalue problems for perturbed Hermitian and unitary matrices.Comment: 13 pages, 3 figure

Compression of unitary rank--structured matrices to CMV-like shape with an application to polynomial rootfinding

This paper is concerned with the reduction of a unitary matrix U to CMV-like shape. A Lanczos--type algorithm is presented which carries out the reduction by computing the block tridiagonal form of the Hermitian part of U, i.e., of the matrix U+U^H. By elaborating on the Lanczos approach we also propose an alternative algorithm using elementary matrices which is numerically stable. If U is rank--structured then the same property holds for its Hermitian part and, therefore, the block tridiagonalization process can be performed using the rank--structured matrix technology with reduced complexity. Our interest in the CMV-like reduction is motivated by the unitary and almost unitary eigenvalue problem. In this respect, finally, we discuss the application of the CMV-like reduction for the design of fast companion eigensolvers based on the customary QR iteration

A CMV--based eigensolver for companion matrices

In this paper we present a novel matrix method for polynomial rootfinding. By exploiting the properties of the QR eigenvalue algorithm applied to a suitable CMV-like form of a companion matrix we design a fast and computationally simple structured QR iteration.Comment: 14 pages, 4 figure

Breaking Through the 80% Glass Ceiling: Raising the State of the Art in Word Sense Disambiguation by Incorporating Knowledge Graph Information

Neural architectures are the current state of the art in Word Sense Disambiguation (WSD). However, they make limited use of the vast amount of relational information encoded in Lexical Knowledge Bases (LKB). We present Enhanced WSD Integrating Synset Embeddings and Relations (EWISER), a neural supervised architecture that is able to tap into this wealth of knowledge by embedding information from the LKB graph within the neural architecture, and to exploit pretrained synset embeddings, enabling the network to predict synsets that are not in the training set. As a result, we set a new state of the art on almost all the evaluation settings considered, also breaking through, for the first time, the 80% ceiling on the concatenation of all the standard all-words English WSD evaluation benchmarks. On multilingual all-words WSD, we report state-of-the-art results by training on nothing but English

The Sylvester–Kac matrix space

AbstractThe Sylvester–Kac matrix is a tridiagonal matrix with integer entries and integer eigenvalues that appears in a variety of applicative problems. We show that it belongs to a four dimensional linear space of tridiagonal matrices that can be simultaneously reduced to triangular form. We name this space after the matrix

Stray Magnetic Field Compensation with a Scalar Atomic Magnetometer

We describe a system for the compensation of time-dependent stray magnetic fields using a dual channel scalar magnetometer based on non-linear Faraday rotation in synchronously optically pumped Cs vapour. We detail the active control strategy, with an emphasis on the electronic circuitry, based on a simple phase-locked-loop integrated circuit. The performance and limits of the system developed are tested and discussed. The system was applied to significantly improve the detection of free induction decay signals from protons of remotely magnetized water precessing in an ultra-low magnetic field.Comment: 8 pages, 6 figures, 31 refs, v2 (with minor improvements) appearing in Rev.Sc.Instr. June 201

Generationary or “How We Went beyond Word Sense Inventories and Learned to Gloss”

Mainstream computational lexical semantics embraces the assumption that word senses can be represented as discrete items of a predefined inventory. In this paper we show this needs not be the case, and propose a unified model that is able to produce contextually appropriate definitions. In our model, Generationary, we employ a novel span-based encoding scheme which we use to fine-tune an English pre-trained Encoder-Decoder system to generate glosses. We show that, even though we drop the need of choosing from a predefined sense inventory, our model can be employed effectively: not only does Generationary outperform previous approaches in the generative task of Definition Modeling in many settings, but it also matches or surpasses the state of the art in discriminative tasks such as Word Sense Disambiguation and Word-inContext. Finally, we show that Generationary benefits from training on data from multiple inventories, with strong gains on various zeroshot benchmarks, including a novel dataset of definitions for free adjective-noun phrases. The software and reproduction materials are available at http://generationary.org

Energy Recovery from the LNG Regasification Process

The global request of natural gas (NG) is continuously increasing, consequently also the regasification of liquefied natural gas (LNG) is becoming a process largely employed. Liquefied natural gas at a temperature of around 113 K at atmospheric pressure has to be regasified for its transportation by pipeline. The regasification process makes the LNG exergy available for various applications, particularly for the production of electrical energy. Different possibilities to exploit the thermal energy released during regasification are available. New plant configurations whose functioning does not constrain the processes of the regasification terminal are proposed. A possible solution is LNG exploitation as a cold source for ocean thermal energy conversion (OTEC) power plants. Electric energy can be produced also by the exploitation of heat released from hot sources, for instance, the condensation heat of power plants by means of consecutive thermodynamic cycles. The rational use of the cold source (LNG) allows the increment of electrical production and growth of the thermodynamic efficiency, with corresponding environmental benefits

Breve historia de la evolución de HPC en una institución de investigación en la Argentina

La presente ponencia es una breve historia de la evolución de High Performance Computing (HPC) en una Institución de Investigación en la Argentina. Además de la reseña histórica, se pretende mostrar, que en los proyectos importantes son necesarios dos componentes: el conocer y el interés de los gobiernos en que se realicen.Sociedad Argentina de Informática e Investigación Operativ