Affect and Manhattan’s West Side Piers

Derek P. McCormack (2010) argues, Affect, is like an atmosphere: it might not be visible, but at any given point it might be sensed ... Emotion, in turn, can be understood as the sociocultural expression of this felt intensity (643). This paper puts McCormack (2010) and Ben Anderson (2009) into conversation to think through the ways in which atmosphere in relation to affective and emotive life has been conceptualized. I center the affective atmospheres that happen with queer bodies that make New York\u27s west side piers queerly affective. I use queer bodies to signal the dis-identification with heteronormativity or binaristic sexualities. Queer sexualities carry political weight with regard to the comments that the politically loaded term queer brings to public consciousness. So queer sexualities and queer bodies substantively challenge cisgender and heteronormative social institutions that are disgustingly oppressive to the queer bodies that, perhaps, use the piers as a space to mark their affective and emotive capabilities. Ultimately, my aim is to situate atmosphere as an analytic to explore the socio-spatial meanings that are attached to spaces and places. As a result, I wish to further spatial knowledge that considers atmospheres as a legitimate dimension of space and placemaking

Torsos, Selfies, and Blanks: Grindr as a Research Tool and a Field Site

Torsos, Selfies, and Blanks: Grindr as a Research Tool and a Field Sit

Loving Blackness: A Sense Experience

The late bell hooks framed feminist pedagogies as a set of practices and systems that provide a description of feminism, a feminist learning environment, and ways to cultivate a community that is ready for feminist instruction. Using intersectionality, hooks (1992) discussed “loving blackness” as a representational and destabilizing practice to de-center whiteness. hooks (1992, 20) writes, “loving blackness as a political resistance transforms our ways of looking and being, and thus creates conditions necessary for us to move against the forces of domination and death and reclaim black life.” I propose a black feminist praxis teaching tool, “a sense experience,” in support of hooks’ “loving blackness” concept. My teaching tool is a visual and conceptual framing exercise where students locate an image, sound, and feeling that encapsulates Blackness. A sense experience encourages students to analyze the object to discuss black representation in a socio-geo-political context. For example, what themes are highlighted in the text? Why? Ultimately, my teaching tool will 1. succor students’ ability to discuss feminist values including access to discourse, ethics of care, and critical thinking and 2. evaluate how we enact bell hooks’ feminist pedagogy to teach students about social transformation

Enabling high confidence detections of gravitational-wave bursts

With the advanced LIGO and Virgo detectors taking observations the detection of gravitational waves is expected within the next few years. Extracting astrophysical information from gravitational wave detections is a well-posed problem and thoroughly studied when detailed models for the waveforms are available. However, one motivation for the field of gravitational wave astronomy is the potential for new discoveries. Recognizing and characterizing unanticipated signals requires data analysis techniques which do not depend on theoretical predictions for the gravitational waveform. Past searches for short-duration un-modeled gravitational wave signals have been hampered by transient noise artifacts, or "glitches," in the detectors. In some cases, even high signal-to-noise simulated astrophysical signals have proven difficult to distinguish from glitches, so that essentially any plausible signal could be detected with at most 2-3 $\sigma$ level confidence. We have put forth the BayesWave algorithm to differentiate between generic gravitational wave transients and glitches, and to provide robust waveform reconstruction and characterization of the astrophysical signals. Here we study BayesWave's capabilities for rejecting glitches while assigning high confidence to detection candidates through analytic approximations to the Bayesian evidence. Analytic results are tested with numerical experiments by adding simulated gravitational wave transient signals to LIGO data collected between 2009 and 2010 and found to be in good agreement.Comment: 15 pages, 6 figures, submitted to PR

A Dividing City and Limited Education: An Analysis of School Segregation in Chicago, Illinois and Seattle, Washington

Contemporary, residential housing patterns in Chicago, IL and Seattle, WA are becoming re-segregated. I argue the politics of locality tends to catalyze white flight, increase racial and economic isolation, and explicate a skills mismatch phenomenon. By definition, the politics of locality is the way in which individuals choose to separate themselves to protect their property, or the way in which individuals are forcibly situated geographically. This project examines questions of race, class, and citizenship, while analyzing the residential patterns, economic opportunities, and educational policies in Chicago and Seattle, respectivel

The BayesWave analysis pipeline in the era of gravitational wave observations

We describe updates and improvements to the BayesWave gravitational wave transient analysis pipeline, and provide examples of how the algorithm is used to analyze data from ground-based gravitational wave detectors. BayesWave models gravitational wave signals in a morphology-independent manner through a sum of frame functions, such as Morlet-Gabor wavelets or chirplets. BayesWave models the instrument noise using a combination of a parametrized Gaussian noise component and non-stationary and non-Gaussian noise transients. Both the signal model and noise model employ trans-dimensional sampling, with the complexity of the model adapting to the requirements of the data. The flexibility of the algorithm makes it suitable for a variety of analyses, including reconstructing generic unmodeled signals; cross checks against modeled analyses for compact binaries; as well as separating coherent signals from incoherent instrumental noise transients (glitches). The BayesWave model has been extended to account for gravitational wave signals with generic polarization content and the simultaneous presence of signals and glitches in the data. We describe updates in the BayesWave prior distributions, sampling proposals, and burn-in stage that provide significantly improved sampling efficiency. We present standard review checks indicating the robustness and convergence of the BayesWave trans-dimensional sampler

Parameter Estimation for Gravitational-wave Bursts with the BayesWave Pipeline

We provide a comprehensive multi-aspect study of the performance of a pipeline used by the LIGO-Virgo Collaboration for estimating parameters of gravitational-wave bursts. We add simulated signals with four different morphologies (sine-Gaussians (SGs), Gaussians, white-noise bursts, and binary black hole signals) to simulated noise samples representing noise of the two Advanced LIGO detectors during their first observing run. We recover them with the BayesWave (BW) pipeline to study its accuracy in sky localization, waveform reconstruction, and estimation of model-independent waveform parameters. BW localizes sources with a level of accuracy comparable for all four morphologies, with the median separation of actual and estimated sky locations ranging from 25 degrees. 1 to 30 degrees. 3. This is a reasonable accuracy in the two-detector case, and is comparable to accuracies of other localization methods studied previously. As BW reconstructs generic transient signals with SG wavelets, it is unsurprising that BW performs best in reconstructing SG and Gaussian waveforms. The BW accuracy in waveform reconstruction increases steeply with the network signal-to-noise ratio (S/N-net), reaching a 85% and 95% match between the reconstructed and actual waveform below S/N-net approximate to 20 and S/N-net approximate to 50, respectively, for all morphologies. The BW accuracy in estimating central moments of waveforms is only limited by statistical errors in the frequency domain, and is also affected by systematic errors in the time domain as BW cannot reconstruct low-amplitude parts of signals that are overwhelmed by noise. The figures of merit we introduce can be used in future characterizations of parameter estimation pipelines