Blending of Cepheids in M33

A precise and accurate determination of the Hubble constant based on Cepheid variables requires proper characterization of many sources of systematic error. One of these is stellar blending, which biases the measured fluxes of Cepheids and the resulting distance estimates. We study the blending of 149 Cepheid variables in M33 by matching archival Hubble Space Telescope data with images obtained at the WIYN 3.5-m telescope, which differ by a factor of 10 in angular resolution. We find that 55+-4% of the Cepheids have no detectable nearby companions that could bias the WIYN V-band photometry, while the fraction of Cepheids affected below the 10% level is 73+-4%. The corresponding values for the I band are 60+-4% and 72+-4%, respectively. We find no statistically significant difference in blending statistics as a function of period or surface brightness. Additionally, we report all the detected companions within 2 arcseconds of the Cepheids (equivalent to 9 pc at the distance of M33) which may be used to derive empirical blending corrections for Cepheids at larger distances.Comment: v2: Fixed incorrect description of Figure 2 in text. Accepted for publication in AJ. Full data tables can be found in ASCII format as part of the source distribution. A version of the paper with higher-resolution figures can be found at http://faculty.physics.tamu.edu/lmacri/papers/chavez12.pd

Rethinking Measures of Democracy and Welfare State Universalism: Lessons from Subnational Research

Democracy and the welfare state are two of the most extensively studied concepts and themes in the field of comparative politics. Debate about how to best measure the two concepts has failed to contemplate the extent to which political and social rights are uniformly present across distinct regions of the national territory, despite the presence of substantial subnational research that underscores wide variation inside countries. We argue that this omission hampers our understanding of the two phenomena and we propose a new measure of democracy and healthcare unversalism, which we call the Adjusted Measures of Democracy and Welfare Universalism. The new measures integrate territorial inequality into existing national-level indicators, providing a more accurate picture of country performance and opening the door to new, multi-level theory building

Searching for Heavy Dark Matter near the Planck Mass with XENON1T

Multiple viable theoretical models predict heavy dark matter particles with a mass close to the Planck mass, a range relatively unexplored by current experimental measurements. We use 219.4 days of data collected with the XENON1T experiment to conduct a blind search for signals from multiply interacting massive particles (MIMPs). Their unique track signature allows a targeted analysis with only 0.05 expected background events from muons. Following unblinding, we observe no signal candidate events. This Letter places strong constraints on spin-independent interactions of dark matter particles with a mass between 1×10$^{12}$ and 2×10$^{17}$  GeV/c$^2$. In addition, we present the first exclusion limits on spin-dependent MIMP-neutron and MIMP-proton cross sections for dark matter particles with masses close to the Planck scale

Searching for Heavy Dark Matter near the Planck Mass with XENON1T

Multiple viable theoretical models predict heavy dark matter particles with a mass close to the Planck mass, a range relatively unexplored by current experimental measurements. We use 219.4 days of data collected with the XENON1T experiment to conduct a blind search for signals from Multiply-Interacting Massive Particles (MIMPs). Their unique track signature allows a targeted analysis with only 0.05 expected background events from muons. Following unblinding, we observe no signal candidate events. This work places strong constraints on spin-independent interactions of dark matter particles with a mass between 1$\times$10$^{12}\,$GeV/c$^2$ and 2$\times$10$^{17}\,$GeV/c$^2$. In addition, we present the first exclusion limits on spin-dependent MIMP-neutron and MIMP-proton cross-sections for dark matter particles with masses close to the Planck scale.Comment: 7 pages, 6 figure

Detector signal characterization with a Bayesian network in XENONnT

We developed a detector signal characterization model based on a Bayesian network trained on the waveform attributes generated by a dual-phase xenon time projection chamber. By performing inference on the model, we produced a quantitative metric of signal characterization and demonstrate that this metric can be used to determine whether a detector signal is sourced from a scintillation or an ionization process. We describe the method and its performance on electronic-recoil (ER) data taken during the first science run of the XENONnT dark matter experiment. We demonstrate the first use of a Bayesian network in a waveform-based analysis of detector signals. This method resulted in a 3% increase in ER event-selection efficiency with a simultaneously effective rejection of events outside of the region of interest. The findings of this analysis are consistent with the previous analysis from XENONnT, namely a background-only fit of the ER data

Search for events in XENON1T associated with Gravitational Waves

We perform a blind search for particle signals in the XENON1T dark matter detector that occur close in time to gravitational wave signals in the LIGO and Virgo observatories. No particle signal is observed in the nuclear recoil, electronic recoil, CE$\nu$NS, and S2-only channels within $\pm$ 500 seconds of observations of the gravitational wave signals GW170104, GW170729, GW170817, GW170818, and GW170823. We use this null result to constrain mono-energetic neutrinos and Beyond Standard Model particles emitted in the closest coalescence GW170817, a binary neutron star merger. We set new upper limits on the fluence (time-integrated flux) of coincident neutrinos down to 17 keV at 90% confidence level. Furthermore, we constrain the product of coincident fluence and cross section of Beyond Standard Model particles to be less than $10^{-29}$ cm$^2$/cm$^2$ in the [5.5-210] keV energy range at 90% confidence level

First Dark Matter Search with Nuclear Recoils from the XENONnT Experiment

We report on the first search for nuclear recoils from dark matter in the form of weakly interacting massive particles (WIMPs) with the XENONnT experiment, which is based on a two-phase time projection chamber with a sensitive liquid xenon mass of 5.9 ton. During the (1.09±0.03)  ton yr exposure used for this search, the intrinsic $^{85}$Kr and $^{222}$Rn concentrations in the liquid target are reduced to unprecedentedly low levels, giving an electronic recoil background rate of (15.8±1.3)  events/ton yr keV in the region of interest. A blind analysis of nuclear recoil events with energies between 3.3 and 60.5 keV finds no significant excess. This leads to a minimum upper limit on the spin-independent WIMP-nucleon cross section of 2.58×10$^{47}$  cm$^2$ for a WIMP mass of 28  GeV/c$^2$ at 90% confidence level. Limits for spin-dependent interactions are also provided. Both the limit and the sensitivity for the full range of WIMP masses analyzed here improve on previous results obtained with the XENON1T experiment for the same exposure

The Triggerless Data Acquisition System of the XENONnT Experiment

The XENONnT detector uses the latest and largest liquid xenon-based timeprojection chamber (TPC) operated by the XENON Collaboration, aimed atdetecting Weakly Interacting Massive Particles and conducting other rare eventsearches. The XENONnT data acquisition (DAQ) system constitutes an upgraded andexpanded version of the XENON1T DAQ system. For its operation, it reliespredominantly on commercially available hardware accompanied by open-source andcustom-developed software. The three constituent subsystems of the XENONnTdetector, the TPC (main detector), muon veto, and the newly introduced neutronveto, are integrated into a single DAQ, and can be operated both independentlyand as a unified system. In total, the DAQ digitizes the signals of 698photomultiplier tubes (PMTs), of which 253 from the top PMT array of the TPCare digitized twice, at $\times10$ and $\times0.5$ gain. The DAQ for the mostpart is a triggerless system, reading out and storing every signal that exceedsthe digitization thresholds. Custom-developed software is used to process theacquired data, making it available within $\mathcal{O}\left(10\text{ s}\right)$for live data quality monitoring and online analyses. The entire system withall the three subsystems was successfully commissioned and has been operatingcontinuously, comfortably withstanding readout rates that exceed $\sim500$ MB/sduring calibration. Livetime during normal operation exceeds $99\%$ and is$\sim90\%$ during most high-rate calibrations. The combined DAQ system hascollected more than 2 PB of both calibration and science data during thecommissioning of XENONnT and the first science run.<br

Using graph theory to analyze biological networks

Understanding complex systems often requires a bottom-up analysis towards a systems biology approach. The need to investigate a system, not only as individual components but as a whole, emerges. This can be done by examining the elementary constituents individually and then how these are connected. The myriad components of a system and their interactions are best characterized as networks and they are mainly represented as graphs where thousands of nodes are connected with thousands of vertices. In this article we demonstrate approaches, models and methods from the graph theory universe and we discuss ways in which they can be used to reveal hidden properties and features of a network. This network profiling combined with knowledge extraction will help us to better understand the biological significance of the system