ALIOLI: Adaptive and Lucky Imaging Optics Lightweight Instrument

As a consequence of the evolution in the design and of the modularity of its components, AOLI for the William Herschel Telescope (WHT 4.2m) is much smaller and more efficient than its previous designs. This success has leaded us to plan to condense it even more to get a portable and easy to integrate system, ALIOLI (Adaptive and Lucky Imaging Optics Lightweight Instrument). It consists of a DM+WFS module with a lucky imaging science camera attached. ALIOLI is an AO instrument for the 1-2m class telescopes which will also be used as on-sky testbench for AO developments. Here we describe the setup to be installed at the 1.5m Telescopio Carlos S\'anchez (TCS) at the Spanish Observatorio del Teide (Tenerife, Canary Islands).Comment: 4 pages, 5 figures, conferenc

El Otro Encuentro: Gigi Oltavaro-Hormillosa’s Neo-Queer Precolonial Imagining

This essay examines the performance and video art piece Cosmic Blood, by Gigi Otalvaro-Hormillosa, a queer Colombian and Filipina American artist based in the San Francisco Bay Area. It argues that Cosmic Blood is a performative intervention into dominant modes of reading the racialized and gendered Filipina body, as well as a critique of absolutist notions of national and ethnic belonging. Cosmic Blood challenges the inherent heteronormativity and masculinism of dominant notions of nation and kinship, accomplishing this imaginative intervention by its retroping of the past through a lens of queer desire. Within Otalvaro-Hormillosa’s retelling of the moment of first contact, queer bodily desire is the locus of power relations between colonizer and colonized. In this vision of the past, the figure of the Filipina is presented as a desiring subject, resisting the overdetermined tropes of woman as nation, territory, and land that are both a legacy of colonization, and a persistent narrative within contemporary articulations of national and diasporic belonging. In doing so, Cosmic Blood presents a possibility for forms of belonging that exceed the absolutism of race, ethnicity, and nation, while also imagining a utopian vision of the future that critiques the material conditions of the present

Gaussian semi-parametric estimation of fractional cointegration

We analyse consistent estimation of the memory parameters of a nonstationary fractionally cointegrated vector time series. Assuming that the cointegrating relationship has substantially less memory than the observed series, we show that a multi-variate Gaussian semi-parametric estimate, based on initial consistent estimates and possibly tapered observations, is asymptotically normal. The estimates of the memory parameters can rely either on original (for stationary errors) or on differenced residuals (for nonstationary errors) assuming only a convergence rate for a preliminary slope estimate. If this rate is fast enough, semi-parametric memory estimates are not affected by the use of residuals and retain the same asymptotic distribution as if the true cointegrating relationship were known. Only local conditions on the spectral densities around zero frequency for linear processes are assumed. We concentrate on a bivariate system but discuss multi-variate generalizations and show the performance of the estimates with simulated and real data.Publicad

Nonparametric frequency domain analysis of nonstationary multivariate time series

We analyse the properties of nonparametric spectral estimates when applied to long memory and trending nonstationary multiple time series. We show that they estimate consistently a generalized or pseudo-spectral density matrix at frequencies both close and away from the origin and we obtain the asymptotic distribution of the estimates. Using adequate data tapers this technique is consistent for observations with any degree of nonstationarity, including polynomial trends. We propose an estimate of the degree of fractional cointegration for possibly nonstationary series based on coherence estimates around zero frequency and analyse its finite sample properties in comparison with residual-based inference. We apply this new semiparametric estimate to an example vector time series.Publicad

Non-stationary log-periodogram regression

We study asymptotic properties of the log-periodogram semiparametric estimate of the memory parameter d for non-stationary (d>=1/2) time series with Gaussian increments, extending the results of Robinson (1995) for stationary and invertible Gaussian processes. We generalize the definition of the memory parameter d for non-stationary processes in terms of the (successively) differentiated series. We obtain that the log-periodogram estimate is asymptotically normal for dE[1/2, 3/4) and still consistent for dE[1/2, 1). We show that with adequate data tapers, a modified estimate is consistent and asymptotically normal distributed for any d, including both non-stationary and non-invertible processes. The estimates are invariant to the presence of certain deterministic trends, without any need of estimation.Publicad

Gaussian Semiparametric Estimation of Non-stationary Time Series

Generalizing the definition of the memory parameter d in terms of the differentiated series, we showed in Velasco (Non-stationary log-periodogram regression, Forthcoming J. Economet., 1997) that it is possible to estimate consistently the memory of non-stationary processes using methods designed for stationary long-range-dependent time series. In this paper we consider the Gaussian semiparametric estimate analysed by Robinson (Gaussian semiparametric estimation of long range dependence. Ann. Stat. 23 (1995), 1630–61) for stationary processes. Without a priori knowledge about the possible non-stationarity of the observed process, we obtain that this estimate is consistent for d E (-½, 1) and asymptotically normal for d E (-½,¾) under a similar set of assumptions to those in Robinson's paper. Tapering the observations, we can estimate any degree of non-stationarity, even in the presence of deterministic polynomial trends of time. The semiparametric efficiency of this estimate for stationary sequences also extends to the non-stationary framework.Publicad

Species concepts should not conflict with evolutionary history, but often do

Many phylogenetic systematists have criticized the Biological Species Concept (BSC) because it distorts evolutionary history. While defenses against this particular criticism have been attempted, I argue that these responses are unsuccessful. In addition, I argue that the source of this problem leads to previously unappreciated, and deeper, fatal objections. These objections to the BSC also straightforwardly apply to other species concepts that are not defined by genealogical history. What is missing from many previous discussions is the fact that the Tree of Life, which represents phylogenetic history, is independent of our choice of species concept. Some species concepts are consistent with species having unique positions on the Tree while others, including the BSC, are not. Since representing history is of primary importance in evolutionary biology, these problems lead to the conclusion that the BSC, along with many other species concepts, are unacceptable. If species are to be taxa used in phylogenetic inferences, we need a history-based species concept

Local Cross-validation for Spectrum Bandwidth Choice

We investigate an automatic method of determining a local bandwidth for non-parametric kernel spectral density estimates at a single frequency. This procedure is a modification of a cross-validation technique for global bandwidth choices, avoiding the computation of any pilot estimate based on initial bandwidths or on approximate parametric models. Only local conditions on the spectral density around the frequency of interest are assumed. We illustrate with a Monte Carlo study the performance in finite samples of the bandwidth estimates proposed.Publicad