Calibration of the EDGES High-Band Receiver to Observe the Global 21-cm Signature from the Epoch of Reionization

The EDGES High-Band experiment aims to detect the sky-average brightness temperature of the $21$-cm signal from the Epoch of Reionization (EoR) in the redshift range $14.8 \gtrsim z \gtrsim 6.5$. To probe this redshifted signal, EDGES High-Band conducts single-antenna measurements in the frequency range $90-190$ MHz from the Murchison Radio-astronomy Observatory in Western Australia. In this paper, we describe the current strategy for calibration of the EDGES High-Band receiver and report calibration results for the instrument used in the $2015-2016$ observational campaign. We propagate uncertainties in the receiver calibration measurements to the antenna temperature using a Monte Carlo approach. We define a performance objective of $1$~mK residual RMS after modeling foreground subtraction from a fiducial temperature spectrum using a five-term polynomial. Most of the calibration uncertainties yield residuals of $1$~mK or less at $95\%$ confidence. However, current uncertainties in the antenna and receiver reflection coefficients can lead to residuals of up to $20$ mK even in low-foreground sky regions. These dominant residuals could be reduced by 1) improving the accuracy in reflection measurements, especially their phase 2) improving the impedance match at the antenna-receiver interface, and 3) decreasing the changes with frequency of the antenna reflection phase.Comment: Updated to match version accepted by Ap

VHF-band RFI in Geographically Remote Areas

The Experiment to Detect the Global EoR Signature (EDGES) is a radio spectrometer operating between 90 and 205 MHz using a single broadband dipole. The instrument recently completed a deep, three-month continuous measurement campaign in the Murchison Radio-astronomy Observatory (MRO) where it reached sufficient sensitivity to constrain the cosmological epoch of reionization (EoR). EDGES has also been used to conduct short, shallow RFI surveys in remote regions in the United States, including northern Maine and the Catlow Valley in southeast Oregon. Here, we show results on the RFI spectrum seen by EDGES at each of these locations and implications for upcoming low-frequency arrays such as MWA, LWA, LOFAR, and PAPER

Correction-to-scaling exponents for two-dimensional self-avoiding walks

We study the correction-to-scaling exponents for the two-dimensional self-avoiding walk, using a combination of series-extrapolation and Monte Carlo methods. We enumerate all self-avoiding walks up to 59 steps on the square lattice, and up to 40 steps on the triangular lattice, measuring the mean-square end-to-end distance, the mean-square radius of gyration and the mean-square distance of a monomer from the endpoints. The complete endpoint distribution is also calculated for self-avoiding walks up to 32 steps (square) and up to 22 steps (triangular). We also generate self-avoiding walks on the square lattice by Monte Carlo, using the pivot algorithm, obtaining the mean-square radii to ~0.01% accuracy up to N = 4000. We give compelling evidence that the first non-analytic correction term for two-dimensional self-avoiding walks is Delta_1 = 3/2. We compute several moments of the endpoint distribution function, finding good agreement with the field-theoretic predictions. Finally, we study a particular invariant ratio that can be shown, by conformal-field-theory arguments, to vanish asymptotically, and we find the cancellation of the leading analytic correction.Comment: LaTeX 2.09, 56 pages. Version 2 adds a renormalization-group discussion near the end of Section 2.2, and makes many small improvements in the exposition. To be published in the Journal of Statistical Physic

Examining Small Business Adoption of Computerized Accounting Systems Using the Technology Acceptance Model.

Small business owners who fail to adopt modern technology risk placing themselves at a competitive disadvantage. Drawing on Davis\u27s technology acceptance model, the purpose of this study was to examine how small business owners in Central Ohio come to accept and use computerized accounting systems (CAS). The research question addressed the correlation between perceived ease of use, perceived usefulness, and the intent to adopt CAS using multiple linear regression. Data were collected using a survey mailed to 347 small business owners which yielded a sample size of 71 respondents. Results showed a positive correlation between perceived ease of use, perceived usefulness, and the intent to adopt CAS; therefore, the null hypothesis was rejected. The model predicted about 71% of the variations in intent to adopt CAS. Using the portion of the sample where small business owners had not yet adopted CAS (n = 34), the model was able to predict about 63% of the variation, and in the portion where small business owners had already adopted CAS (n = 37), the model was able to predict about 70% of the variation. However, when splitting the sample between small businesses whose owners had already adopted CAS and those who had not yet adopted CAS, importance of ease of use and usefulness changed. Usefulness is more important to nonadopters and ease of use is more important for continued use. The implication for social change is the potential to reduce business failures. The study showed that 83% of small businesses over 5 years old currently use a CAS and only 56% under 5 years old use a CAS. Society could benefit from an increase in the number of successful small businesses, which would then contribute to economic expansion

Detecting positive selection from genome scans of linkage disequilibrium

<p>Abstract</p> <p>Background</p> <p>Though a variety of linkage disequilibrium tests have recently been introduced to measure the signal of recent positive selection, the statistical properties of the various methods have not been directly compared. While most applications of these tests have suggested that positive selection has played an important role in recent human history, the results of these tests have varied dramatically.</p> <p>Results</p> <p>Here, we evaluate the performance of three statistics designed to detect incomplete selective sweeps, LRH and iHS, and ALnLH. To analyze the properties of these tests, we introduce a new computational method that can model complex population histories with migration and changing population sizes to simulate gene trees influenced by recent positive selection. We demonstrate that iHS performs substantially better than the other two statistics, with power of up to 0.74 at the 0.01 level for the variation best suited for full genome scans and a power of over 0.8 at the 0.01 level for the variation best suited for candidate gene tests. The performance of the iHS statistic was robust to complex demographic histories and variable recombination rates. Genome scans involving the other two statistics suffer from low power and high false positive rates, with false discovery rates of up to 0.96 for ALnLH. The difference in performance between iHS and ALnLH, did not result from the properties of the statistics, but instead from the different methods for mitigating the multiple comparison problem inherent in full genome scans.</p> <p>Conclusions</p> <p>We introduce a new method for simulating genealogies influenced by positive selection with complex demographic scenarios. In a power analysis based on this method, iHS outperformed LRH and ALnLH in detecting incomplete selective sweeps. We also show that the single-site iHS statistic is more powerful in a candidate gene test than the multi-site statistic, but that the multi-site statistic maintains a low false discovery rate with only a minor loss of power when applied to a scan of the entire genome. Our results highlight the need for careful consideration of multiple comparison problems when evaluating and interpreting the results of full genome scans for positive selection.</p