Sensitivity Determination in the CHIPS Neutrino Detector

Through neutrino detection, we strive to provide constraints on various neutrino properties such as $\delta_{CP}$ and mass hierarchy. Neutrinos are difficult to detect and require large neutrino detectors with appropriate conditions to determine $\delta_{CP}$. While several neutrino experiments strive to constrain $\delta_{CP}$, additional detectors are necessary to further constrain these parameters. We present a computational model to determine detector sensitivity towards measuring unknown oscillation properties. This model focused on the CHIPS neutrino detector, a low-cost experiment designed to test detector technologies while providing to the wealth of information on neutrino properties. Sensitivity constraints are presented for $\Delta m^{2}$, $\sin^{2}{(2\theta_{23})}$, and $\delta_{CP}$ at the CHIPS detector

Mitigating the counterpart selection effect for standard sirens

The standard siren method using gravitational-wave observations has great potential to resolve the tension in measurements of the Hubble constant from different experiments. To realize this goal, we must thoroughly understand the sources of potential systematic bias. Among the known sources of systematic uncertainties, selection effects originating from electromagnetic counterpart observations of gravitational-wave sources may dominate the measurements and no method to mitigate this effect is currently established. In this Letter, we develop a new formalism to mitigate the counterpart selection effect. With realistic examples, we show that our formalism can reduce the systematic uncertainty of standard siren Hubble constant measurement to less than 0.6%. We conclude with how to apply our formalism to different electromagnetic emissions and observing scenarios

Surrogate light curve models for kilonovae with comprehensive wind ejecta outflows and parameter estimation for AT2017gfo

The electromagnetic emission resulting from neutron star mergers have been shown to encode properties of the ejected material in their light curves. The ejecta properties inferred from the kilonova emission has been in tension with those calculated based on the gravitational wave signal and numerical relativity models. Motivated by this tension, we construct a broad set of surrogate light curve models derived for kilonova ejecta. The four-parameter family of two-dimensional anisotropic simulations and its associated surrogate explore different assumptions about the wind outflow morphology and outflow composition, keeping the dynamical ejecta component consistent. We present the capabilities of these surrogate models in interpolating kilonova light curves across various ejecta parameters and perform parameter estimation for AT2017gfo both without any assumptions on the outflow and under the assumption that the outflow must be representative of solar r-process abundance patterns. Our parameter estimation for AT2017gfo shows these surrogate models help alleviate the ejecta property discrepancy while also illustrating the impact of systematic modeling uncertainties on these properties, urging further investigation.Comment: 15 pages, 6 figures, data available in Zenodo (https://zenodo.org/record/7335961) and GitHub (https://github.com/markoris/surrogate_kne

Mitigation of the instrumental noise transient in gravitational-wave data surrounding GW170817

In the coming years gravitational-wave detectors will undergo a series of improvements, with an increase in their detection rate by about an order of magnitude. Routine detections of gravitational-wave signals promote novel astrophysical and fundamental theory studies, while simultaneously leading to an increase in the number of detections temporally overlapping with instrumentally- or environmentally-induced transients in the detectors (glitches), often of unknown origin. Indeed, this was the case for the very first detection by the LIGO and Virgo detectors of a gravitational-wave signal consistent with a binary neutron star coalescence, GW170817. A loud glitch in the LIGO-Livingston detector, about one second before the merger, hampered coincident detection (which was initially achieved solely with LIGO-Hanford data). Moreover, accurate source characterization depends on specific assumptions about the behavior of the detector noise that are rendered invalid by the presence of glitches. In this paper, we present the various techniques employed for the initial mitigation of the glitch to perform source characterization of GW170817 and study advantages and disadvantages of each mitigation method. We show that, despite the presence of instrumental noise transients louder than the one affecting GW170817, we are still able to produce unbiased measurements of the intrinsic parameters from simulated injections with properties similar to GW170817.Comment: 11 pages, 3 figures, accepted in PR

Changes in cortical and striatal neurons predict behavioral and electrophysiological abnormalities in a transgenic murine model of Huntington\u27s disease

Neurons in Huntington\u27s disease exhibit selective morphological and subcellular alterations in the striatum and cortex. The link between these neuronal changes and behavioral abnormalities is unclear. We investigated relationships between essential neuronal changes that predict motor impairment and possible involvement of the corticostriatal pathway in developing behavioral phenotypes. We therefore generated heterozygote mice expressing the N-terminal one-third of huntingtin with normal (CT18) or expanded (HD46, HD100) glutamine repeats. The HD mice exhibited motor deficits between 3 and 10 months. The age of onset depended on an expanded polyglutamine length; phenotype severity correlated with increasing age. Neuronal changes in the striatum (nuclear inclusions) preceded the onset of phenotype, whereas cortical changes, especially the accumulation of huntingtin in the nucleus and cytoplasm and the appearance of dysmorphic dendrites, predicted the onset and severity of behavioral deficits. Striatal neurons in the HD mice displayed altered responses to cortical stimulation and to activation by the excitotoxic agent NMDA. Application of NMDA increased intracellular Ca(2+) levels in HD100 neurons compared with wild-type neurons. Results suggest that motor deficits in Huntington\u27s disease arise from cumulative morphological and physiological changes in neurons that impair corticostriatal circuitry