Searching for Gravitational Waves from Scorpius X-1 with a Cross-correlation Method: from Mock Data to Advanced LIGO

Gravitational waves (GWs) are propagating ripples of space-time predicted by general relativity. 100 years after Albert Einstein published his theory of GR, the Laser Interferometer Gravitational-Wave Observatory (LIGO) found the first direct detection of GW in the first Advanced LIGO observing run. The GW signal known as GW150914 (Abbott et al., 2016), was the first of a series of binary black hole mergers observed by LIGO. These detections marked the beginning of gravitational-wave astronomy. The continuous wave (CW) signal emitted by fast spinning neutron stars (NSs) is an another interesting source for a detector like LIGO. The low-mass X-ray binary (LMXB) Scorpius X-1 (Sco X-1) is considered to be one of the most promising CW sources. With improving sensitivity of advanced detectors and improving methods, we are getting closer to being able to detect an astrophysically feasible GW signal from Sco X-1 in the coming few years. Searching for CWs from NSs of unknown phase evolution is computationally intensive. For a target with large uncertainty in its parameters such as Sco X-1, the fully coherent search is computationally impractical, while faster algorithms have limited sensitivity. The cross-correlation method combines all data-pairs in a maximum time offset from same and different detectors coherently based on the signal model. We can adjust the maximum coherence time to trade off computing cost and sensitivity. The cross-correlation method is flexible and so far the most sensitive. In this dissertation I will present the implementation of Cross-correlation method for Sco X-1, its test on a Sco X-1 mock-data challenge (MDC) data set and the Advanced LIGO O1 observations. This search gave the best results in the Sco X-1 mock data challenge and recent LIGO Sco X-1 search. In the O1 run, the Cross-correlation search managed to improve the upper limit on GW strain strength from Sco X-1 closer than ever before to the level estimated from a torque balance argument

Model-Based Cross-Correlation Search for Gravitational Waves from Scorpius X-1

We consider the cross-correlation search for periodic GWs and its potential application to the LMXB Sco X-1. This method coherently combines data from different detectors at the same time, as well as different times from the same or different detectors. By adjusting the maximum time offset between a pair of data segments to be coherently combined, one can tune the method to trade off sensitivity and computing costs. In particular, the detectable signal amplitude scales as the inverse fourth root of this coherence time. The improvement in amplitude sensitivity for a search with a coherence time of 1hr, compared with a directed stochastic background search with 0.25Hz wide bins is about a factor of 5.4. We show that a search of 1yr of data from Advanced LIGO and Advanced Virgo with a coherence time of 1hr would be able to detect GWs from Sco X-1 at the level predicted by torque balance over a range of signal frequencies from 30-300Hz; if the coherence time could be increased to 10hr, the range would be 20-500Hz. In addition, we consider several technical aspects of the cross-correlation method: We quantify the effects of spectral leakage and show that nearly rectangular windows still lead to the most sensitive search. We produce an explicit parameter-space metric for the cross-correlation search in general and as applied to a neutron star in a circular binary system. We consider the effects of using a signal template averaged over unknown amplitude parameters: the search is sensitive to a combination of the intrinsic signal amplitude and the inclination of the neutron star rotation axis, and the peak of the expected detection statistic is systematically offset from the true signal parameters. Finally, we describe the potential loss of SNR due to unmodelled effects such as signal phase acceleration within the Fourier transform timescale and gradual evolution of the spin frequency.Comment: 27 pages, 12 figures, 4 tables, pdflatex; synchronized to final version published in Phys Rev

Modeling Temporal Pattern and Event Detection using Hidden Markov Model with Application to a Sludge Bulking Data

This paper discusses a method of modeling temporal pattern and event detection based on Hidden Markov Model (HMM) for a continuous time series data. We also provide methods for checking model adequacy and predicting future events. These methods are applied to a real example of sludge bulking data for detecting sludge bulking for a water plant in Chicago

Resampling to accelerate cross-correlation searches for continuous gravitational waves from binary systems

Continuous-wave (CW) gravitational waves (GWs) call for computationally-intensive methods. Low signal-to-noise ratio signals need templated searches with long coherent integration times and thus fine parameter-space resolution. Longer integration increases sensitivity. Low-mass x-ray binaries (LMXBs) such as Scorpius X-1 (Sco X-1) may emit accretion-driven CWs at strains reachable by current ground-based observatories. Binary orbital parameters induce phase modulation. This paper describes how resampling corrects binary and detector motion, yielding source-frame time series used for cross-correlation. Compared to the previous, detector-frame, templated cross-correlation method, used for Sco X-1 on data from the first Advanced LIGO observing run (O1), resampling is about 20x faster in the costliest, most-sensitive frequency bands. Speed-up factors depend on integration time and search setup. The speed could be reinvested into longer integration with a forecast sensitivity gain, 20 to 125 Hz median, of approximately 51%, or from 20 to 250 Hz, 11%, given the same per-band cost and setup. This paper's timing model enables future setup optimization. Resampling scales well with longer integration, and at 10x unoptimized cost could reach respectively 2.83x and 2.75x median sensitivities, limited by spin-wandering. Then an O1 search could yield a marginalized-polarization upper limit reaching torque-balance at 100 Hz. Frequencies from 40 to 140 Hz might be probed in equal observing time with 2x improved detectors.Comment: 28 pages, 7 figures, 3 table

The Non-Linear Impact of Digitization on Remittances Inflow: Evidence From the BRICS

Due to the impact of COVID-19, it is important now more than ever to analyze the relationship between the improvement in digitization and the flow of remittances in order to fill the void that has come as a result of stay at home and quarantine orders. Using a comprehensive measure of digitization that encompasses the commonly used proxies of financial technology (Fintech) and employing a System Generalized Method of Moments (GMM) panel estimation methodology on annual data over the period 2004-2018, this paper examines the impact of digitization, as a proxy of Fintech, on the inflow of remittances for a sample of 34 developed and developing countries. Our analysis provides a case study on Brazil, Russia, India, China and South Africa (BRICS), known as five emerging markets with a great number of workers out of abroad and below the average level of digital transfers. Using the Digital Ecosystem Development Index developed by Katz and Calorda (2018), the results of the paper uncover a statistically significant nonlinear relationship between the improvement in digitization measures and the inflow of remittances with an exact threshold level. More specifically, our results for the full sample indicate that improvement in digitization may initially increase the remittances inflow leading to an increase in the stock of remittances received. Nevertheless, once the digitization index reaches its threshold level further improvement in digitization tends decrease as penetration increases, giving rise to a decline in the rate of remittances inflow. This result implies that the marginal effect of the digital penetration is larger when at its lower level, before the threshold level. For countries such as the BRICS, with a level of digitization below the average of our sample, policy makers should apply more aggressive and comprehensive policies to recoup the maximum gains of a digital ecosystem. Hence, our policy implications are directed towards increasing the investments in developing human capacity including carrying different skill development training programs to prepare individuals for the information age, expanding the internet coverage and speed especially in educational establishments, encouraging the use and access of electronic banking by consumers, producers, and governments, and taking cyber security and fraud protection more seriously to encourage the flow of remittances, especially in light of its renewed utility due to the recent pandemic

The Effect of Race/Ethnicity on the Age of Colon Cancer Diagnosis

ABSTRACT BACKGROUND: Colorectal cancer is the third most commonly diagnosed cancer in the United States. Notably, racial/ethnic disparities exist in both incidence and mortality. PURPOSE: The aim of this case study was to investigate the impact of race/ethnicity on age at diagnosis of colorectal cancer in a defined population in Suffolk County, NY. METHODS: Data were retrospectively collected on race/ethnicity, health insurance status, age at diagnosis, stage at diagnosis, gender, smoking status, alcohol intake, tumor location, and body mass index for colorectal cancer patients with medical records in the Stony Brook University Medical Center database (2005-2011). Population-based data on Hispanic and non-Hispanic Whites were obtained from the Surveillance, Epidemiology, and End Results registry of New York State for an overlapping time period. Permutation-based ANCOVA and logistic regression with stepwise variable selection were conducted to identify covariates and first-order interactions associated with younger age at diagnosis and cancer stage as a dependent categorical variable. RESULTS: Of 328 colorectal cancer patients, Hispanics were diagnosed at a median younger age of 57y vs. 67y than non-Hispanic Whites (FDR = 0.001). Twenty-six percent of Hispanics were diagnosed with colorectal cancer prior to the recommended age (50y) for colorectal cancer surveillance compared to 11% of non-Hispanic Whites (FDR =0.007). Analysis of New York State registry data corroborated our findings that Hispanic colorectal cancer patients were diagnosed at a median younger age than non-Hispanic Whites. Permutation-based ANCOVA identified race/ethnicity and health insurance as significantly associated with age of diagnosis (P=0.001). Logistic regression selected (younger) age at diagnosis as being significantly associated with stage IV disease. The limitations of the case study reside in the use of self-reporting of race and ethnicity and in the small sample sizes. CONCLUSIONS: Hispanics may be at higher risk for colorectal cancer (y) and younger age at diagnosis is associated with advanced disease