Search

Your search keyword '"More P"' showing total 4,902 results
Start Over Author "More P"

Refine your results

more »

more »

more »

more »

more »

more »

more »
4,902 results on '"More P"'

158. Spotlight: the status of radiopharmacy in Africa

Author

Kleynhans, Janke, Summers, Beverly, Sakr, Tamer, Zeevaart, Jan Rijn, Lundie, Maryke, du Plessis, Samantha, Mosima, Lerato, Bentaleb, Naoual, Ekoume, Fany P., Hlongwa, Khanyisile, Shambel, Seble, Mldophane, Amanda, Mangatha, Amreeta, and More, Stuart

Published
2024
Full Text
View/download PDF

167. Leveraging SN Ia spectroscopic similarity to improve the measurement of $H_0$

Author

Murakami, Yukei S., Riess, Adam G., Stahl, Benjamin E., Kenworthy, W. D'Arcy, Pluck, Dahne-More A., Macoretta, Antonella, Brout, Dillon, Jones, David O., Scolnic, Dan M., and Filippenko, Alexei V.

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

Recent studies suggest spectroscopic differences explain a fraction of the variation in Type Ia supernova (SN Ia) luminosities after light-curve/color standardization. In this work, (i) we empirically characterize the variations of standardized SN Ia luminosities, and (ii) we use a spectroscopically inferred parameter, SIP, to improve the precision of SNe Ia along the distance ladder and the determination of the Hubble constant ($H_0$). First, we show that the \texttt{Pantheon+} covariance model modestly overestimates the uncertainty of standardized magnitudes by $\sim 7$%, in the parameter space used by the $\texttt{SH0ES}$ Team to measure $H_0$; accounting for this alone yields $H_0 = 73.01 \pm 0.92$ km s$^{-1}$ Mpc$^{-1}$. Furthermore, accounting for spectroscopic similarity between SNe~Ia on the distance ladder reduces their relative scatter to $\sim0.12$ mag per object (compared to $\sim 0.14$ mag previously). Combining these two findings in the model of SN covariance, we find an overall 14% reduction (to $\pm 0.85$km s$^{-1}$ Mpc$^{-1}$) of the uncertainty in the Hubble constant and a modest increase in its value. Including a budget for systematic uncertainties itemized by Riess et al. (2022a), we report an updated local Hubble constant with $\sim1.2$% uncertainty, $H_0 = 73.29 \pm 0.90$km s$^{-1}$ Mpc$^{-1}$. We conclude that spectroscopic differences among photometrically standardized SNe Ia do not explain the ``Hubble tension." Rather, accounting for such differences increases its significance, as the discrepancy against $\Lambda$CDM calibrated by the ${\it Planck}$ 2018 measurement rises to 5.7$\sigma$., Comment: 28 pages, 15 figures, accepted to JCAP

Published
2023

168. How to out-perform default random forest regression: choosing hyperparameters for applications in large-sample hydrology

Author

Bilolikar, Divya K., More, Aishwarya, Gong, Aella, and Janssen, Joseph

Subjects
Statistics - Applications
Abstract

Predictions are a central part of water resources research. Historically, physically-based models have been preferred; however, they have largely failed at modeling hydrological processes at a catchment scale and there are some important prediction problems that cannot be modeled physically. As such, machine learning (ML) models have been seen as a valid alternative in recent years. In spite of their availability, well-optimized state-of-the-art ML strategies are not being widely used in water resources research. This is because using state-of-the-art ML models and optimizing hyperparameters requires expert mathematical and statistical knowledge. Further, some analyses require many model trainings, so sometimes even expert statisticians cannot properly optimize hyperparameters. To leverage data and use it effectively to drive scientific advances in the field, it is essential to make ML models accessible to subject matter experts by improving automated machine learning resources. ML models such as XGBoost have been recently shown to outperform random forest (RF) models which are traditionally used in water resources research. In this study, based on over 150 water-related datasets, we extensively compare XGBoost and RF. This study provides water scientists with access to quick user-friendly RF and XGBoost model optimization.

Published
2023

169. Baryon masses estimate in heavy flavor QCD

Author

Gómez-Rocha, María, More, Jai, and Serafin, Kamil

Subjects
High Energy Physics - Phenomenology
Abstract

We apply the renormalization group procedure for effective particles (RGPEP) to the QCD eigenvalue problem for only heavy quarks. We derive the effective Hamiltonian that acts on the Fock space by solving the RGPEP equation up to second order in powers of the coupling constant. The eigenstates that contain three quarks and two or more gluons are eliminated by inserting a gluon-mass term in the component with one gluon and formulate the eigenvalue problem for baryons. We estimate masses for $bbb$ and $ccc$ states and find that the results match the estimates obtained in lattice QCD and in quark models., Comment: Presented by Mar{\'i}a G\'omez-Rocha at the International Conference on the Structure of Baryons, November 7-11th, Universidad Pablo de Olavide, Sevilla, Spain. 11 pages, 2 figures, 2 tables

Published
2023
Full Text
View/download PDF

170. Survey of Gravitationally Lensed Objects in HSC Imaging (SuGOHI). IX. Discovery of Strongly Lensed Quasar Candidates

Author

Chan, James H. H., Wong, Kenneth C., Ding, Xuheng, Chao, Dani, Chiu, I-Non, Jaelani, Anton T., Kayo, Issha, More, Anupreeta, Oguri, Masamune, and Suyu, Sherry H.

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

We report the discovery of new lensed quasar candidates in the imaging data of the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP) DR4, covering $1\,310~{\rm deg}^2$ of the sky with seeing of $\approx0.6''$. In addition to two catalogs of MILLIQUAS and AllWISEAGN, which contain confirmed and candidate quasars, we preselect quasar sources using color cuts from the HSC ($grizy$) and unWISE ($W1+W2$) photometric data based on SDSS spectroscopic catalogs. We search for the presence of multiple point sources with similar color through the convolution of the Laplacian of the preselected quasar image cutouts with the Laplacian of the point spread function, resulting in a reduction of lens candidates from $1\,652\,329$ to $121\,511$ ($7.4\%$). After visual binary classification, we grade $6\,199$ ($0.4\%$) potential lenses on a scale of 0 to 3, with 3 indicating a lens and 0 indicating a non-lens. Finally we obtain 162 lens candidates with an average grade of $\geq2$, and among them, we successfully recover 18 known lenses. By fitting the light distribution and removing the known contaminants, we discover that 57 new systems contain at least two point sources and a galaxy in between, including 10 possible quadruply lensed quasars. This new sample of lens candidates exhibits a median separation of $1.26''$ and a magnitude limit of $i\approx22$. Spectroscopic or high-resolution imaging follow up on these newly discovered lensed quasar candidates will further allow their natures to be confirmed., Comment: 25 pages, 14 figures

Published
2023

171. Hyper Suprime-Cam Year 3 Results: Cosmology from Galaxy Clustering and Weak Lensing with HSC and SDSS using the Minimal Bias Model

Author

Sugiyama, Sunao, Miyatake, Hironao, More, Surhud, Li, Xiangchong, Shirasaki, Masato, Takada, Masahiro, Kobayashi, Yosuke, Takahashi, Ryuichi, Nishimichi, Takahiro, Nishizawa, Atsushi J., Rau, Markus M., Zhang, Tianqing, Dalal, Roohi, Mandelbaum, Rachel, Strauss, Michael A., Hamana, Takashi, Oguri, Masamune, Osato, Ken, Kannawadi, Arun, Armstrong, Robert, Komiyama, Yutaka, Lupton, Robert H., Lust, Nate B., Miyazaki, Satoshi, Murayama, Hitoshi, Okura, Yuki, Price, Paul A., Tait, Philip J., Tanaka, Masayuki, and Wang, Shiang-Yu

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

We present cosmological parameter constraints from a blind joint analysis of three two-point correlation functions measured from the Year 3 Hyper Suprime-Cam (HSC-Y3) imaging data, covering 416 deg$^2$, and the SDSS DR11 spectroscopic galaxies spanning the redshift range $[0.15, 0.70]$. We subdivide the SDSS galaxies into three volume-limited samples separated in redshift, each of which acts as a large-scale structure tracer characterized by the measurement of the projected correlation function, $w_{\rm p}(R)$. We also use the measurements of the galaxy-galaxy weak lensing signal $\Delta \Sigma(R)$ for each of these SDSS samples which act as lenses for a secure sample of source galaxies selected from the HSC-Y3 shape catalog based on their photometric redshifts. We combine these measurements with the cosmic shear correlation functions, $\xi_{\pm}(\vartheta)$, measured for our HSC source sample. We model these observables with the minimal bias model of the galaxy clustering observables in the context of a flat $\Lambda$CDM cosmology. We use conservative scale cuts, $R>12$ and $8~h^{-1}$Mpc, for $\Delta\Sigma$ and $w_{\rm p}$, respectively, where the minimal bias model is valid, in addition to conservative prior on the residual bias in the mean redshift of the HSC photometric source galaxies. Our baseline analysis yields $S_8=0.775^{+0.043}_{-0.038}$ (68% C.I.) for the $\Lambda$CDM model, after marginalizing over uncertainties in other parameters. Our value of $S_8$ is consistent with that from the Planck 2018 data, but the credible interval of our result is still relatively large. Our results are statistically consistent with those of a companion paper, which extends this analysis to smaller scales with an emulator-based halo model., Comment: 29 pages, 17 figures, 4 tables, version accepted for publication in PRD together with other HSC Y3 weak lensing cosmology papers - see https://hsc-release.mtk.nao.ac.jp/doc/index.php/wly3/

Published
2023
Full Text
View/download PDF

172. Hyper Suprime-Cam Year 3 Results: Cosmology from Galaxy Clustering and Weak Lensing with HSC and SDSS using the Emulator Based Halo Model

Author

Miyatake, Hironao, Sugiyama, Sunao, Takada, Masahiro, Nishimichi, Takahiro, Li, Xiangchong, Shirasaki, Masato, More, Surhud, Kobayashi, Yosuke, Nishizawa, Atsushi J., Rau, Markus M., Zhang, Tianqing, Takahashi, Ryuichi, Dalal, Roohi, Mandelbaum, Rachel, Strauss, Michael A., Hamana, Takashi, Oguri, Masamune, Osato, Ken, Luo, Wentao, Kannawadi, Arun, Hsieh, Bau-Ching, Armstrong, Robert, Komiyama, Yutaka, Lupton, Robert H., Lust, Nate B., MacArthur, Lauren A., Miyazaki, Satoshi, Murayama, Hitoshi, Okura, Yuki, Price, Paul A., Sunayama, Tomomi, Tait, Philip J., Tanaka, Masayuki, and Wang, Shiang-Yu

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

We present cosmology results from a blinded joint analysis of cosmic shear, $\xi_{\pm}(\vartheta)$, galaxy-galaxy weak lensing, $\Delta\!\Sigma(R)$, and projected galaxy clustering, $w_{\rm p}(R)$, measured from the Hyper Suprime-Cam three-year (HSC-Y3) shape catalog and the Sloan Digital Sky Survey (SDSS) DR11 spectroscopic galaxy catalog - a 3$\times$2pt cosmology analysis. We define luminosity-cut samples of SDSS galaxies to serve as the tracers of $w_{\rm p}$ and as the lens samples for $\Delta\!\Sigma$ in three spectroscopic redshift bins spanning the range $0.15

Published
2023

173. Hyper Suprime-Cam Year 3 Results: Measurements of Clustering of SDSS-BOSS Galaxies, Galaxy-Galaxy Lensing and Cosmic Shear

Author

More, Surhud, Sugiyama, Sunao, Miyatake, Hironao, Rau, Markus Michael, Shirasaki, Masato, Li, Xiangchong, Nishizawa, Atsushi J., Osato, Ken, Zhang, Tianqing, Takada, Masahiro, Hamana, Takashi, Takahashi, Ryuichi, Dalal, Roohi, Mandelbaum, Rachel, Strauss, Michael A., Kobayashi, Yosuke, Nishimichi, Takahiro, Oguri, Masamune, Luo, Wentao, Kannawadi, Arun, Hsieh, Bau-Ching, Armstrong, Robert, Bosch, James, Komiyama, Yutaka, Lupton, Robert H., Lust, Nate B., MacArthur, Lauren A., Miyazaki, Satoshi, Murayama, Hitoshi, Okura, Yuki, Price, Paul A., Tait, Philip J., Tanaka, Masayuki, and Wang, Shiang-Yu

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

We use the Sloan Digital Sky Survey (SDSS) BOSS galaxies and their overlap with approximately 416 sq. degree of deep $grizy$-band imaging from the Subaru Hyper Suprime-Cam Survey (HSC). We measure three two-point correlations that form the basis of the cosmological inference presented in our companion papers, Miyatake et al. and Sugiyama et al. We use three approximately volume limited subsamples of spectroscopic galaxies by their $i$-band magnitude from the SDSS-BOSS: LOWZ (0.1

Published
2023

174. Hyper Suprime-Cam Year 3 Results: Cosmology from Cosmic Shear Power Spectra

Author

Dalal, Roohi, Li, Xiangchong, Nicola, Andrina, Zuntz, Joe, Strauss, Michael A., Sugiyama, Sunao, Zhang, Tianqing, Rau, Markus M., Mandelbaum, Rachel, Takada, Masahiro, More, Surhud, Miyatake, Hironao, Kannawadi, Arun, Shirasaki, Masato, Taniguchi, Takanori, Takahashi, Ryuichi, Osato, Ken, Hamana, Takashi, Oguri, Masamune, Nishizawa, Atsushi J., Malagón, Andrés A. Plazas, Sunayama, Tomomi, Alonso, David, Slosar, Anže, Armstrong, Robert, Bosch, James, Komiyama, Yutaka, Lupton, Robert H., Lust, Nate B., MacArthur, Lauren A., Miyazaki, Satoshi, Murayama, Hitoshi, Nishimichi, Takahiro, Okura, Yuki, Price, Paul A., Tait, Philip J., Tanaka, Masayuki, and Wang, Shiang-Yu

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

We measure weak lensing cosmic shear power spectra from the three-year galaxy shear catalog of the Hyper Suprime-Cam (HSC) Subaru Strategic Program imaging survey. The shear catalog covers $416 \ \mathrm{deg}^2$ of the northern sky, with a mean $i$-band seeing of 0.59 arcsec and an effective galaxy number density of 15 $\mathrm{arcmin}^{-2}$ within our adopted redshift range. With an $i$-band magnitude limit of 24.5 mag, and four tomographic redshift bins spanning $0.3 \leq z_{\mathrm{ph}} \leq 1.5$ based on photometric redshifts, we obtain a high-significance measurement of the cosmic shear power spectra, with a signal-to-noise ratio of approximately 26.4 in the multipole range $300<\ell<1800$. The accuracy of our power spectrum measurement is tested against realistic mock shear catalogs, and we use these catalogs to get a reliable measurement of the covariance of the power spectrum measurements. We use a robust blinding procedure to avoid confirmation bias, and model various uncertainties and sources of bias in our analysis, including point spread function systematics, redshift distribution uncertainties, the intrinsic alignment of galaxies and the modeling of the matter power spectrum. For a flat $\Lambda$CDM model, we find $S_8 \equiv \sigma_8 (\Omega_m/0.3)^{0.5} =0.776^{+0.032}_{-0.033}$, which is in excellent agreement with the constraints from the other HSC Year 3 cosmology analyses, as well as those from a number of other cosmic shear experiments. This result implies a $\sim$$2\sigma$-level tension with the Planck 2018 cosmology. We study the effect that various systematic errors and modeling choices could have on this value, and find that they can shift the best-fit value of $S_8$ by no more than $\sim$$0.5\sigma$, indicating that our result is robust to such systematics., Comment: 35 pages, 18 figures, 6 tables, for coordinated submission to PRD with other HSC Y3 weak lensing cosmology papers - see https://hsc-release.mtk.nao.ac.jp/doc/index.php/wly3/

Published
2023
Full Text
View/download PDF

175. Model-based cross-correlation search for gravitational waves from the low-mass X-ray binary Scorpius X-1 in LIGO O3 data

Author

The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration, Abbott, R., Abe, H., Acernese, F., Ackley, K., Adhicary, S., Adhikari, N., Adhikari, R. X., Adkins, V. K., Adya, V. B., Affeldt, C., Agarwal, D., Agathos, M., Aguiar, O. D., Aiello, L., Ain, A., Ajith, P., Akutsu, T., Albanesi, S., Alfaidi, R. A., Alléné, C., Allocca, A., Altin, P. A., Amato, A., Anand, S., Ananyeva, A., Anderson, S. B., Anderson, W. G., Ando, M., Andrade, T., Andres, N., Andrés-Carcasona, M., Andrić, T., Ansoldi, S., Antelis, J. M., Antier, S., Apostolatos, T., Appavuravther, E. Z., Appert, S., Apple, S. K., Arai, K., Araya, A., Araya, M. C., Areeda, J. S., Arène, M., Aritomi, N., Arnaud, N., Arogeti, M., Aronson, S. M., Asada, H., Ashton, G., Aso, Y., Assiduo, M., Melo, S. Assis de Souza, Aston, S. M., Astone, P., Aubin, F., AultONeal, K., Babak, S., Badaracco, F., Badger, C., Bae, S., Bae, Y., Bagnasco, S., Bai, Y., Baier, J. G., Baird, J., Bajpai, R., Baka, T., Ball, M., Ballardin, G., Ballmer, S. W., Baltus, G., Banagiri, S., Banerjee, B., Bankar, D., Barayoga, J. C., Barish, B. C., Barker, D., Barneo, P., Barone, F., Barr, B., Barsotti, L., Barsuglia, M., Barta, D., Bartlett, J., Barton, M. A., Bartos, I., Basak, S., Bassiri, R., Basti, A., Bawaj, M., Bayley, J. C., Bazzan, M., Bécsy, B., Bedakihale, V. M., Beirnaert, F., Bejger, M., Belahcene, I., Bell, A. S., Benedetto, V., Beniwal, D., Benoit, W., Bentley, J. D., BenYaala, M., Bera, S., Berbel, M., Bergamin, F., Berger, B. K., Bernuzzi, S., Beroiz, M., Bersanetti, D., Bertolini, A., Betzwieser, J., Beveridge, D., Bhandare, R., Bhandari, A. V., Bhardwaj, U., Bhatt, R., Bhattacharjee, D., Bhaumik, S., Bianchi, A., Bilenko, I. A., Bilicki, M., Billingsley, G., Bini, S., Birnholtz, O., Biscans, S., Bischi, M., Biscoveanu, S., Bisht, A., Biswas, B., Bitossi, M., Bizouard, M. -A., Blackburn, J. K., Blair, C. D., Blair, D. G., Blair, R. M., Bobba, F., Bode, N., Boër, M., Bogaert, G., Boldrini, M., Bolingbroke, G. N., Bonavena, L. D., Bondarescu, R., Bondu, F., Bonilla, E., Bonnand, R., Booker, P., Bork, R., Boschi, V., Bose, N., Bose, S., Bossilkov, V., Boudart, V., Bouffanais, Y., Bozzi, A., Bradaschia, C., Brady, P. R., Bramley, A., Branch, A., Branchesi, M., Brau, J. E., Breschi, M., Briant, T., Briggs, J. H., Brillet, A., Brinkmann, M., Brockill, P., Brooks, A. F., Brooks, J., Brown, D. D., Brunett, S., Bruno, G., Bruntz, R., Bryant, J., Bucci, F., Buchanan, J., Bulik, T., Bulten, H. J., Buonanno, A., Burtnyk, K., Buscicchio, R., Buskulic, D., Buy, C., Byer, R. L., Davies, G. S. Cabourn, Cabras, G., Cabrita, R., Cadonati, L., Cagnoli, G., Cahillane, C., Bustillo, J. Calderón, Callaghan, J. D., Callister, T. A., Calloni, E., Camp, J. B., Canepa, M., Caneva, G., Cannavacciuolo, M., Cannon, K. C., Cao, H., Cao, Z., Capistran, L. A., Capocasa, E., Capote, E., Carapella, G., Carbognani, F., Carlassara, M., Carlin, J. B., Carpinelli, M., Carrillo, G., Carter, J. J., Carullo, G., Diaz, J. Casanueva, Casentini, C., Castaldi, G., Caudill, S., Cavaglià, M., Cavalier, F., Cavalieri, R., Cella, G., Cerdá-Durán, P., Cesarini, E., Chaibi, W., Chakalis, W., Subrahmanya, S. Chalathadka, Champion, E., Chan, C. -H., Chan, C., Chan, C. L., Chan, K., Chan, M., Chandra, K., Chang, I. P., Chang, W., Chanial, P., Chao, S., Chapman-Bird, C., Charlton, P., Chassande-Mottin, E., Chatterjee, C., Chatterjee, Debarati, Chatterjee, Deep, Chaturvedi, M., Chaty, S., Chen, C., Chen, D., Chen, H. Y., Chen, J., Chen, K., Chen, X., Chen, Y. -B., Chen, Y. -R., Chen, Y., Cheng, H., Chessa, P., Cheung, H. Y., Chia, H. Y., Chiadini, F., Chiang, C-Y., Chiarini, G., Chierici, R., Chincarini, A., Chiofalo, M. L., Chiummo, A., Choudhary, R. K., Choudhary, S., Christensen, N., Chu, Q., Chu, Y-K., Chua, S. S. Y., Chung, K. W., Ciani, G., Ciecielag, P., Cieślar, M., Cifaldi, M., Ciobanu, A. A., Ciolfi, R., Clara, F., Clark, J. A., Clarke, T. A., Clearwater, P., Clesse, S., Cleva, F., Coccia, E., Codazzo, E., Cohadon, P. -F., Cohen, D. E., Colleoni, M., Collette, C. G., Colombo, A., Colpi, M., Compton, C. M., Conti, L., Cooper, S. J., Corban, P., Corbitt, T. R., Cordero-Carrión, I., Corezzi, S., Cornish, N. J., Corsi, A., Cortese, S., Coschizza, A. C., Cotesta, R., Cottingham, R., Coughlin, M. W., Coulon, J. -P., Countryman, S. T., Cousins, B., Couvares, P., Coward, D. M., Cowart, M. J., Coyne, D. C., Coyne, R., Craig, K., Creighton, J. D. E., Creighton, T. D., Criswell, A. W., Croquette, M., Crowder, S. G., Cudell, J. R., Cullen, T. J., Cumming, A., Cummings, R., Cuoco, E., Curyło, M., Dabadie, P., Canton, T. Dal, Dall'Osso, S., Dálya, G., Dana, A., D'Angelo, B., Danilishin, S., D'Antonio, S., Danzmann, K., Darsow-Fromm, C., Dasgupta, A., Datrier, L. E. H., Datta, Sayantani, Dattilo, V., Dave, I., Davier, M., Davis, D., Davis, M. C., Daw, E. J., Dax, M., DeBra, D., Deenadayalan, M., Degallaix, J., De Laurentis, M., Deléglise, S., Del Favero, V., De Lillo, F., De Lillo, N., Dell'Aquila, D., Del Pozzo, W., De Matteis, F., D'Emilio, V., Demos, N., Dent, T., Depasse, A., De Pietri, R., De Rosa, R., De Rossi, C., DeSalvo, R., De Simone, R., Dhurandhar, S., Diab, R., Díaz, M. C., Didio, N. A., Dietrich, T., Di Fiore, L., Di Fronzo, C., Di Giorgio, C., Di Giovanni, F., Di Giovanni, M., Di Girolamo, T., Diksha, D., Di Lieto, A., Di Michele, A., Di Pace, S., Di Palma, I., Di Renzo, F., Divakarla, A. K., Dmitriev, A., Doctor, Z., Doleva, P. P., Donahue, L., D'Onofrio, L., Donovan, F., Dooley, K. L., Dooney, T., Doravari, S., Dorosh, O., Drago, M., Driggers, J. C., Drori, Y., Ducoin, J. -G., Dunn, L., Dupletsa, U., Durante, O., D'Urso, D., Duverne, P. -A., Dwyer, S. E., Eassa, C., Easter, P. J., Ebersold, M., Eckhardt, T., Eddolls, G., Edelman, B., Edo, T. B., Edy, O., Effler, A., Eguchi, S., Eichholz, J., Eikenberry, S. S., Eisenmann, M., Eisenstein, R. A., Ejlli, A., Engelby, E., Enomoto, Y., Errico, L., Essick, R. C., Estellés, H., Estevez, D., Etzel, T., Evans, M., Evans, T. M., Evstafyeva, T., Ewing, B. E., Fabrizi, F., Faedi, F., Fafone, V., Fair, H., Fairhurst, S., Fan, P. C., Farah, A. M., Farr, B., Farr, W. M., Favaro, G., Favata, M., Fays, M., Fazio, M., Feicht, J., Fejer, M. M., Fenyvesi, E., Ferguson, D. L., Fernandez-Galiana, A., Ferrante, I., Ferreira, T. A., Fidecaro, F., Figura, P., Fiori, A., Fiori, I., Fishbach, M., Fisher, R. P., Fittipaldi, R., Fiumara, V., Flaminio, R., Floden, E., Fong, H. K., Font, J. A., Fornal, B., Forsyth, P. W. F., Franke, A., Frasca, S., Frasconi, F., Freed, J. P., Frei, Z., Freise, A., Freitas, O., Frey, R., Fritschel, P., Frolov, V. V., Fronzé, G. G., Fujii, Y., Fujikawa, Y., Fujimoto, Y., Fulda, P., Fyffe, M., Gabbard, H. A., Gabella, W. E., Gadre, B. U., Gair, J. R., Gais, J., Galaudage, S., Gamba, R., Ganapathy, D., Ganguly, A., Gao, D. -F., Gao, D., Gaonkar, S. G., Garaventa, B., García-Núñez, C., García-Quirós, C., Gardner, K. A., Gargiulo, J., Garufi, F., Gasbarra, C., Gateley, B., Gayathri, V., Ge, G. -G., Gemme, G., Gennai, A., George, J., Gerberding, O., Gergely, L., Ghonge, S., Ghosh, Abhirup, Ghosh, Archisman, Ghosh, Shaon, Ghosh, Shrobana, Ghosh, Tathagata, Giacoppo, L., Giaime, J. A., Giardina, K. D., Gibson, D. R., Gier, C., Giri, P., Gissi, F., Gkaitatzis, S., Glanzer, J., Gleckl, A. E., Godoy, F. G., Godwin, P., Goetz, E., Goetz, R., Golomb, J., Goncharov, B., González, G., Gosselin, M., Gouaty, R., Gould, D. W., Goyal, S., Grace, B., Grado, A., Graham, V., Granata, M., Granata, V., Gras, S., Grassia, P., Gray, C., Gray, R., Greco, G., Green, A. C., Green, R., Gretarsson, A. M., Gretarsson, E. M., Griffith, D., Griffiths, W. L., Griggs, H. L., Grignani, G., Grimaldi, A., Grimm, S. J., Grote, H., Grunewald, S., Gruson, A. S., Guerra, D., Guidi, G. M., Guimaraes, A. R., Gulati, H. K., Gulminelli, F., Gunny, A. M., Guo, H. -K., Guo, Y., Gupta, Anchal, Gupta, Anuradha, Gupta, P., Gupta, S. K., Gurs, J., Gustafson, R., Gutierrez, N., Guzman, F., Ha, S., Hadiputrawan, I. P. W., Haegel, L., Haino, S., Halim, O., Hall, E. D., Hamilton, E. Z., Hammond, G., Han, W. -B., Haney, M., Hanks, J., Hanna, C., Hannam, M. D., Hannuksela, O., Hansen, H., Hanson, J., Harada, R., Harder, T., Haris, K., Harms, J., Harry, G. M., Harry, I. W., Hartwig, D., Hasegawa, K., Haskell, B., Haster, C. -J., Hathaway, J. S., Hattori, K., Haughian, K., Hayakawa, H., Hayama, K., Hayes, F. J., Healy, J., Heidmann, A., Heidt, A., Heintze, M. C., Heinze, J., Heinzel, J., Heitmann, H., Hellman, F., Hello, P., Helmling-Cornell, A. F., Hemming, G., Hendry, M., Heng, I. S., Hennes, E., Hennig, J. -S., Hennig, M., Henshaw, C., Hernandez, A. G., Vivanco, F. Hernandez, Heurs, M., Hewitt, A. L., Higginbotham, S., Hild, S., Hill, P., Himemoto, Y., Hines, A. S., Hirata, N., Hirose, C., Ho, T-C., Hochheim, S., Hofman, D., Hohmann, J. N., Holcomb, D. G., Holland, N. A., Hollows, I. J., Holmes, Z. J., Holt, K., Holz, D. E., Hong, Q., Hough, J., Hourihane, S., Howell, D., Howell, E. J., Hoy, C. G., Hoyland, D., Hreibi, A., Hsieh, B-H., Hsieh, H-F., Hsiung, C., Huang, H-Y., Huang, P., Huang, Y-C., Huang, Y. -J., Huang, Y., Hübner, M. T., Huddart, A. D., Hughey, B., Hui, D. C. Y., Hui, V., Husa, S., Huttner, S. H., Huxford, R., Huynh-Dinh, T., Hyland, J., Iandolo, G. A., Ide, S., Idzkowski, B., Iess, A., Inayoshi, K., Inoue, Y., Iosif, P., Irwin, J., Gupta, Ish, Isi, M., Ito, K., Itoh, Y., Iyer, B. R., JaberianHamedan, V., Jacqmin, T., Jacquet, P. -E., Jadhav, S. J., Jadhav, S. P., Jain, T., James, A. L., Jan, A. Z., Jani, K., Janquart, J., Janssens, K., Janthalur, N. N., Jaranowski, P., Jariwala, D., Jarov, S., Jaume, R., Jenkins, A. C., Jenner, K., Jeon, C., Jia, W., Jiang, J., Jin, H. -B., Johns, G. R., Johnston, R., Johny, N., Jones, A. W., Jones, D. I., Jones, P., Jones, R., Joshi, P., Ju, L., Jung, K., Jung, P., Junker, J., Juste, V., Kaihotsu, K., Kajita, T., Kakizaki, M., Kalaghatgi, C., Kalogera, V., Kamai, B., Kamiizumi, M., Kanda, N., Kandhasamy, S., Kang, G., Kanner, J. B., Kao, Y., Kapadia, S. J., Kapasi, D. P., Karat, S., Karathanasis, C., Karki, S., Kashyap, R., Kasprzack, M., Kastaun, W., Kato, T., Katsanevas, S., Katsavounidis, E., Katzman, W., Kaur, T., Kawabe, K., Kawaguchi, K., Kéfélian, F., Keitel, D., Key, J. S., Khadka, S., Khalili, F. Y., Khan, S., Khanam, T., Khazanov, E. A., Khetan, N., Khursheed, M., Kijbunchoo, N., Kim, C., Kim, J. C., Kim, J., Kim, K., Kim, P., Kim, W. S., Kim, Y. -M., Kimball, C., Kimura, N., King, B., Kinley-Hanlon, M., Kirchhoff, R., Kissel, J. S., Klimenko, S., Klinger, T., Knee, A. M., Knust, N., Kobayashi, Y., Koch, P., Koehlenbeck, S. M., Koekoek, G., Kohri, K., Kokeyama, K., Koley, S., Kolitsidou, P., Kolstein, M., Kondrashov, V., Kong, A. K. H., Kontos, A., Korobko, M., Kossak, R. V., Kovalam, M., Koyama, N., Kozak, D. B., Kozakai, C., Kranzhoff, L., Kringel, V., Krishnendu, N. V., Królak, A., Kuehn, G., Kuijer, P., Kulkarni, S., Kumar, A., Kumar, Praveen, Kumar, Prayush, Kumar, Rahul, Kumar, Rakesh, Kume, J., Kuns, K., Kuromiya, Y., Kuroyanagi, S., Kuwahara, S., Kwak, K., Lacaille, G., Lagabbe, P., Laghi, D., Lalande, E., Lalleman, M., Lamberts, A., Landry, M., Lane, B. B., Lang, R. N., Lange, J., Lantz, B., La Rosa, I., Lartaux-Vollard, A., Lasky, P. D., Lawrence, J., Laxen, M., Lazzarini, A., Lazzaro, C., Leaci, P., Leavey, S., LeBohec, S., Lecoeuche, Y. K., Lee, E., Lee, H. M., Lee, H. W., Lee, K., Lee, R., Legred, I. N., Lehmann, J., Lemaître, A., Lenti, M., Leonardi, M., Leonova, E., Leroy, N., Letendre, N., Levesque, C., Levin, Y., Leviton, J. N., Leyde, K., Li, A. K. Y., Li, B., Li, K. L., Li, P., Li, T. G. F., Li, X., Lin, C-Y., Lin, E. T., Lin, F-K., Lin, F-L., Lin, H. L., Lin, L. C. -C., Linde, F., Linker, S. D., Littenberg, T. B., Liu, G. C., Liu, J., Liu, X., Llamas, F., Lo, R. K. L., Lo, T., London, L. T., Longo, A., Lopez, D., Portilla, M. Lopez, Lorenzini, M., Loriette, V., Lormand, M., Losurdo, G., Lott, T. P., Lough, J. D., Lousto, C. O., Lovelace, G., Lowry, M. J., Lucaccioni, J. F., Lück, H., Lumaca, D., Lundgren, A. P., Lung, Y., Luo, L. -W., Lussier, A. W., Lynam, J. E., Ma'arif, M., Macas, R., MacInnis, M., Macleod, D. M., MacMillan, I. A. O., Macquet, A., Hernandez, I. Magaña, Magazzù, C., Magee, R. M., Maggiore, R., Magnozzi, M., Mahesh, S., Majorana, E., Makarem, C. N., Maksimovic, I., Maliakal, S., Malik, A., Man, N., Mandic, V., Mangano, V., Mannix, B. R., Mansell, G. L., Mansingh, G., Manske, M., Mantovani, M., Mapelli, M., Marchesoni, F., Pina, D. Marín, Marion, F., Mark, Z., Márka, S., Márka, Z., Markakis, C., Markosyan, A. S., Markowitz, A., Maros, E., Marquina, A., Marsat, S., Martelli, F., Martin, I. W., Martin, R. M., Martinez, M., Martinez, V. A., Martinez, V., Martinovic, K., Martynov, D. V., Marx, E. J., Masalehdan, H., Mason, K., Masserot, A., Masso-Reid, M., Mastrogiovanni, S., Matas, A., Mateu-Lucena, M., Matiushechkina, M., Mavalvala, N., McCann, J. J., McCarthy, R., McClelland, D. E., McClincy, P. K., McCormick, S., McCuller, L., McGhee, G. I., McGinn, J., McGuire, S. C., McIsaac, C., McIver, J., McLeod, A., McRae, T., McWilliams, S. T., Meacher, D., Mehmet, M., Mehta, A. K., Meijer, Q., Melatos, A., Mendell, G., Menendez-Vazquez, A., Menoni, C. S., Mercer, R. A., Mereni, L., Merfeld, K., Merilh, E. L., Merritt, J. D., Merzougui, M., Messenger, C., Messick, C., Meyers, P. M., Meylahn, F., Mhaske, A., Miani, A., Miao, H., Michaloliakos, I., Michel, C., Michimura, Y., Middleton, H., Mihaylov, D. P., Miller, A., Miller, A. L., Miller, B., Millhouse, M., Mills, J. C., Milotti, E., Minenkov, Y., Mio, N., Mir, Ll. M., Miravet-Tenés, M., Mishkin, A., Mishra, C., Mishra, T., Mistry, T., Mitchell, A. L., Mitra, S., Mitrofanov, V. P., Mitselmakher, G., Mittleman, R., Miyakawa, O., Miyo, K., Miyoki, S., Mo, Geoffrey, Modafferi, L. M., Moguel, E., Mogushi, K., Mohapatra, S. R. P., Mohite, S. R., Molina-Ruiz, M., Mondal, C., Mondin, M., Montani, M., Moore, C. J., Moragues, J., Moraru, D., Morawski, F., More, A., More, S., Moreno, C., Moreno, G., Mori, Y., Morisaki, S., Morisue, N., Moriwaki, Y., Mours, B., Mow-Lowry, C. M., Mozzon, S., Muciaccia, F., Mukherjee, D., Mukherjee, Soma, Mukherjee, Subroto, Mukherjee, Suvodip, Mukund, N., Mullavey, A., Munch, J., Muñiz, E. A., Murray, P. G., Muusse, S., Nadji, S. L., Nagano, K., Nagar, A., Nagar, T., Nakamura, K., Nakano, H., Nakano, M., Nakayama, Y., Napolano, V., Nardecchia, I., Narikawa, T., Narola, H., Naticchioni, L., Nayak, R. K., Neil, B. F., Neilson, J., Nelson, A., Nelson, T. J. N., Nery, M., Neubauer, P., Neunzert, A., Ng, K. Y., Ng, S. W. S., Nguyen, C., Nguyen, P., Nguyen, T., Quynh, L. Nguyen, Ni, J., Ni, W. -T., Nichols, S. A., Nieradka, G., Nishimoto, T., Nishizawa, A., Nissanke, S., Nitoglia, E., Niu, W., Nocera, F., Norman, M., North, C., Notte, J., Novak, J., Nozaki, S., Nurbek, G., Nuttall, L. K., Obayashi, Y., Oberling, J., O'Brien, B. D., O'Dell, J., Oelker, E., Oertel, M., Ogaki, W., Oganesyan, G., Oh, J. J., Oh, K., Oh, S. H., O'Hanlon, T., Ohashi, M., Ohashi, T., Ohkawa, M., Ohme, F., Ohta, H., Okutani, Y., Oliveri, R., Olivetto, C., Oohara, K., Oram, R., O'Reilly, B., Ormiston, R. G., Ormsby, N. D., Orselli, M., O'Shaughnessy, R., O'Shea, E., Oshino, S., Ossokine, S., Osthelder, C., Otabe, S., Ottaway, D. J., Overmier, H., Pace, A. E., Pagano, G., Pagano, R., Pagliaroli, G., Pai, A., Pai, S. A., Pal, S., Palamos, J. R., Palashov, O., Palomba, C., Pan, K. -C., Panda, P. K., Pang, P. T. H., Pannarale, F., Pant, B. C., Panther, F. H., Paoletti, F., Paoli, A., Paolone, A., Pappas, G., Parisi, A., Park, J., Parker, W., Pascucci, D., Pasqualetti, A., Passaquieti, R., Passuello, D., Patel, M., Patel, N. R., Pathak, M., Patricelli, B., Patron, A. S., Paul, S., Payne, E., Pedraza, M., Pedurand, R., Pegna, R., Pegoraro, M., Pele, A., Arellano, F. E. Peña, Penano, S., Penn, S., Perego, A., Pereira, A., Pereira, T., Perez, C. J., Périgois, C., Perkins, C. C., Perreca, A., Perriès, S., Perry, J. W., Pesios, D., Petermann, J., Pfeiffer, H. P., Pham, H., Pham, K. A., Phukon, K. S., Phurailatpam, H., Piccinni, O. J., Pichot, M., Piendibene, M., Piergiovanni, F., Pierini, L., Pierra, G., Pierro, V., Pillant, G., Pillas, M., Pilo, F., Pinard, L., Pineda-Bosque, C., Pinto, I. M., Pinto, M., Piotrzkowski, B. J., Piotrzkowski, K., Pirello, M., Pitkin, M. D., Placidi, A., Placidi, E., Planas, M. L., Plastino, W., Poggiani, R., Polini, E., Pong, D. Y. T., Ponrathnam, S., Porter, E. K., Posnansky, C., Poulton, R., Powell, J., Pracchia, M., Pradier, T., Prajapati, A. K., Prasai, K., Prasanna, R., Pratten, G., Principe, M., Prodi, G. A., Prokhorov, L., Prosposito, P., Prudenzi, L., Puecher, A., Punturo, M., Puosi, F., Puppo, P., Pürrer, M., Qi, H., Quartey, N., Quetschke, V., Quinonez, P. J., Quitzow-James, R., Raab, F. J., Raaijmakers, G., Radkins, H., Radulesco, N., Raffai, P., Rail, S. X., Raja, S., Rajan, C., Ramirez, K. E., Ramirez, T. D., Ramos-Buades, A., Rana, D., Rana, J., Rangnekar, P. R., Rapagnani, P., Ray, A., Raymond, V., Raza, N., Razzano, M., Read, J., Regimbau, T., Rei, L., Reid, S., Reid, S. W., Reinhard, M., Reitze, D. H., Relton, P., Renzini, A., Rettegno, P., Revenu, B., Reyes, J., Reza, A., Rezac, M., Rezaei, A. S., Ricci, F., Richards, D., Richardson, J. W., Richardson, L., Riles, K., Rinaldi, S., Robertson, C., Robertson, N. A., Robie, R., Robinet, F., Rocchi, A., Rodriguez, S., Rolland, L., Rollins, J. G., Romanelli, M., Romano, R., Romel, C. L., Romero, A., Romero-Shaw, I. M., Romie, J. H., Ronchini, S., Roocke, T. J., Rosa, L., Rose, C. A., Rosińska, D., Ross, M. P., Rossello, M., Rowan, S., Rowlinson, S. J., Roy, Santosh, Roy, Soumen, Royzman, A., Rozza, D., Ruggi, P., Ruiz-Rocha, K., Ryan, K., Sachdev, S., Sadecki, T., Sadiq, J., Saffarieh, P., Saha, S., Saito, Y., Sakai, K., Sakellariadou, M., Sakon, S., Salafia, O. S., Salces-Carcoba, F., Salconi, L., Saleem, M., Salemi, F., Sallé, M., Samajdar, A., Sanchez, E. J., Sanchez, J. H., Sanchez, L. E., Sanchis-Gual, N., Sanders, J. R., Sanuy, A., Saravanan, T. R., Sarin, N., Sasli, A., Sassolas, B., Satari, H., Sathyaprakash, B. S., Sauter, O., Savage, R. L., Savant, V., Sawada, T., Sawant, H. L., Sayah, S., Schaetzl, D., Scheel, M., Scheuer, J., Schiworski, M. G., Schmidt, P., Schmidt, S., Schnabel, R., Schneewind, M., Schofield, R. M. S., Schönbeck, A., Schulte, B. W., Schutz, B. F., Schwartz, E., Scott, J., Scott, S. M., Seglar-Arroyo, M., Sekiguchi, Y., Sellers, D., Sengupta, A. S., Sentenac, D., Seo, E. G., Sequino, V., Sergeev, A., Servignat, G., Setyawati, Y., Shaffer, T., Shahriar, M. S., Shaikh, M. A., Shams, B., Shao, L., Sharma, A., Sharma, P., Shawhan, P., Shcheblanov, N. S., Sheela, A., Sheridan, E., Shikano, Y., Shikauchi, M., Shimizu, H., Shimode, K., Shinkai, H., Shishido, T., Shoda, A., Shoemaker, D. H., Shoemaker, D. M., ShyamSundar, S., Sieniawska, M., Sigg, D., Silenzi, L., Singer, L. P., Singh, D., Singh, M. K., Singh, N., Singha, A., Sintes, A. M., Sipala, V., Skliris, V., Slagmolen, B. J. J., Slaven-Blair, T. J., Smetana, J., Smith, J. R., Smith, L., Smith, R. J. E., Soldateschi, J., Somala, S. N., Somiya, K., Song, I., Soni, K., Soni, S., Sordini, V., Sorrentino, F., Sorrentino, N., Soulard, R., Souradeep, T., Spagnuolo, V., Spencer, A. P., Spera, M., Spinicelli, P., Srivastava, A. K., Srivastava, V., Stachie, C., Stachurski, F., Steer, D. A., Steinlechner, J., Steinlechner, S., Stergioulas, N., Stops, D. J., Strain, K. A., Strang, L. C., Stratta, G., Strong, M. D., Strunk, A., Sturani, R., Stuver, A. L., Suchenek, M., Sudhagar, S., Sugimoto, R., Suh, H. G., Sullivan, A. G., Summerscales, T. Z., Sun, L., Sunil, S., Sur, A., Suresh, J., Sutton, P. J., Suzuki, Takamasa, Suzuki, Takanori, Suzuki, Toshikazu, Swinkels, B. L., Syx, A., Szczepańczyk, M. J., Szewczyk, P., Tacca, M., Tagoshi, H., Tait, S. C., Takahashi, H., Takahashi, R., Takano, S., Takeda, H., Takeda, M., Talbot, C. J., Talbot, C., Tamanini, N., Tanaka, K., Tanaka, Taiki, Tanaka, Takahiro, Tanasijczuk, A. J., Tanioka, S., Tanner, D. B., Tao, D., Tao, L., Tapia, R. D., Martín, E. N. Tapia San, Taranto, C., Taruya, A., Tasson, J. D., Tenorio, R., Terhune, J. E. S., Terkowski, L., Themann, H., Thirugnanasambandam, M. P., Thomas, M., Thomas, P., Thomas, S., Thompson, D., Thompson, E. E., Thompson, J. E., Thondapu, S. R., Thorne, K. A., Thrane, E., Tiwari, Shubhanshu, Tiwari, Srishti, Tiwari, V., Toivonen, A. M., Tolley, A. E., Tomaru, T., Tomura, T., Tonelli, M., Torres-Forné, A., Torrie, C. I., Melo, I. Tosta e, Tournefier, E., Töyrä, D., Trapananti, A., Travasso, F., Traylor, G., Trenado, J., Trevor, M., Tringali, M. C., Tripathee, A., Troiano, L., Trovato, A., Trozzo, L., Trudeau, R. J., Tsai, D., Tsang, K. W., Tsang, T., Tsao, J-S., Tse, M., Tso, R., Tsuchida, S., Tsukada, L., Tsuna, D., Tsutsui, T., Turbang, K., Turconi, M., Turski, C., Tuyenbayev, D., Ubach, H., Ubhi, A. S., Uchikata, N., Uchiyama, T., Udall, R. P., Ueda, A., Uehara, T., Ueno, K., Ueshima, G., Unnikrishnan, C. S., Urban, A. L., Ushiba, T., Utina, A., Vahlbruch, H., Vaidya, N., Vajente, G., Vajpeyi, A., Valdes, G., Valentini, M., Vallero, S., Valsan, V., van Bakel, N., van Beuzekom, M., van Dael, M., Brand, J. F. J. van den, Broeck, C. Van Den, Vander-Hyde, D. C., Van de Walle, A., van Dongen, J., van Haevermaet, H., van Heijningen, J. V., Vanosky, J., van Putten, M. H. P. M., van Ranst, Z., van Remortel, N., Vardaro, M., Vargas, A. F., Varma, V., Vasúth, M., Vecchio, A., Vedovato, G., Veitch, J., Veitch, P. J., Venneberg, J., Venugopalan, G., Verdier, P., Verkindt, D., Verma, P., Verma, Y., Vermeulen, S. M., Veske, D., Vetrano, F., Viceré, A., Vidyant, S., Viets, A. D., Vijaykumar, A., Villa-Ortega, V., Vinet, J. -Y., Virtuoso, A., Vitale, S., Vocca, H., von Reis, E. R. G., von Wrangel, J. S. A., Vorvick, C., Vyatchanin, S. P., Wade, L. E., Wade, M., Wagner, K. J., Walet, R. C., Walker, M., Wallace, G. S., Wallace, L., Wang, J., Wang, J. Z., Wang, W. H., Ward, R. L., Warner, J., Was, M., Washimi, T., Washington, N. Y., Watada, K., Watarai, D., Watchi, J., Wayt, K. E., Weaver, B., Weaving, C. R., Webster, S. A., Weinert, M., Weinstein, A. J., Weiss, R., Weller, C. M., Weller, R. A., Wellmann, F., Wen, L., Weßels, P., Wette, K., Whelan, J. T., White, D. D., Whiting, B. F., Whittle, C., Wilk, O. S., Wilken, D., Williams, C. E., Williams, D., Williams, M. J., Williamson, A. R., Willis, J. L., Willke, B., Wipf, C. C., Woan, G., Woehler, J., Wofford, J. K., Wojtowicz, I. A., Wong, D., Wong, I. C. F., Wright, M., Wu, C., Wu, D. S., Wu, H., Wysocki, D. M., Xiao, L., Yadav, N., Yamada, T., Yamamoto, H., Yamamoto, K., Yamamoto, T., Yamashita, K., Yamazaki, R., Yang, F. W., Yang, K. Z., Yang, L., Yang, Y. -C., Yang, Y., Yang, Yang, Yap, M. J., Yeeles, D. W., Yeh, S. -W., Yelikar, A. B., Yokoyama, J., Yokozawa, T., Yoo, J., Yoshioka, T., Yu, Hang, Yu, Haocun, Yuzurihara, H., Zadrożny, A., Zanolin, M., Zeidler, S., Zelenova, T., Zendri, J. -P., Zevin, M., Zhan, M., Zhang, H., Zhang, J., Zhang, L., Zhang, R., Zhang, T., Zhang, Y., Zhao, C., Zhao, G., Zhao, Y., Zhao, Yue, Zheng, Y., Zhou, R., Zhu, X. J., Zhu, Z. -H., Zimmerman, A. B., Zucker, M. E., and Zweizig, J.

Subjects
Astrophysics - High Energy Astrophysical Phenomena, General Relativity and Quantum Cosmology
Abstract

We present the results of a model-based search for continuous gravitational waves from the low-mass X-ray binary Scorpius X-1 using LIGO detector data from the third observing run of Advanced LIGO, Advanced Virgo and KAGRA. This is a semicoherent search which uses details of the signal model to coherently combine data separated by less than a specified coherence time, which can be adjusted to balance sensitivity with computing cost. The search covered a range of gravitational-wave frequencies from 25Hz to 1600Hz, as well as ranges in orbital speed, frequency and phase determined from observational constraints. No significant detection candidates were found, and upper limits were set as a function of frequency. The most stringent limits, between 100Hz and 200Hz, correspond to an amplitude h0 of about 1e-25 when marginalized isotropically over the unknown inclination angle of the neutron star's rotation axis, or less than 4e-26 assuming the optimal orientation. The sensitivity of this search is now probing amplitudes predicted by models of torque balance equilibrium. For the usual conservative model assuming accretion at the surface of the neutron star, our isotropically-marginalized upper limits are close to the predicted amplitude from about 70Hz to 100Hz; the limits assuming the neutron star spin is aligned with the most likely orbital angular momentum are below the conservative torque balance predictions from 40Hz to 200Hz. Assuming a broader range of accretion models, our direct limits on gravitational-wave amplitude delve into the relevant parameter space over a wide range of frequencies, to 500Hz or more., Comment: 19 pages, Open Access Journal PDF

Published
2022
Full Text
View/download PDF

176. Educational Equity: Study Abroad for Underrepresented Minority and First-Gen Public Health Students

Author

Archana More Sharma

Abstract

For public health students, global education supports development of core skills towards becoming effective leaders and advocates for health equity. Despite the growing number of undergraduate students participating in experiential study abroad opportunities, there remains a stark educational disparity: racial and ethnic minority students continue to be underrepresented. Less than 20% of Hispanic/Latinx and African American students participate in study abroad (NAFSA, 2022). This situation is especially urgent given the shortage of diverse public health professionals. It is imperative for the educational pipeline to address the structural limitations that hinder access to academic opportunities for diverse and disadvantaged students. To meet the challenge, our institution created a course expressly for underrepresented minorities and first-generation public health students. This article describes the course's intentional design, implementation, and assessment of long-term outcomes. Findings highlight the impact of this experience for minority and first-gen students as they entered graduate education and the public health workforce. All participants voiced benefits in developing relevant career skills, global citizenship, and personal growth. As public health educators, our focus on health equity must include equitable access to innovative experiences for underserved public health students as fundamental to public health pedagogy.

Published
2023
Full Text
View/download PDF

185. Science with the Daksha high energy transients mission

Author

Bhalerao, Varun, Sawant, Disha, Pai, Archana, Tendulkar, Shriharsh, Vadawale, Santosh, Bhattacharya, Dipankar, Rana, Vikram, Adalja, Hitesh Kumar L., Anupama, G C, Bala, Suman, Banerjee, Smaranika, Basu, Judhajeet, Belatikar, Hrishikesh, Beniamini, Paz, Bhaganagare, Mahesh, Bhaskar, Ankush, Bhattacharjee, Soumyadeep, Bose, Sukanta, Cenko, Brad, Vijay Chanda, Mehul, Dewangan, Gulab, Dixit, Vishal, Dutta, Anirban, Gawade, Priyanka, Ghodgaonkar, Abhijeet, Kumar Goyal, Shiv, Gunasekaran, Suresh, Hemanth, Manikantan, Hotokezaka, Kenta, Iyyani, Shabnam, Guruprasad, P. J., Kasliwal, Mansi, G. Koyande, Jayprakash, Kulkarni, Salil, Kutty, APK, Ladiya, Tinkal, Mahapatra, Suddhasatta, Marla, Deepak, Mate, Sujay, Mehla, Advait, Mithun, N. P. S., More, Surhud, Mote, Rakesh, Mukherjee, Dipanjan, Narang, Sanjoli, Narendranath, Shyama, Nema, Ayush, Nimbalkar, Sudhanshu, Nissanke, Samaya, Palit, Sourav, Patel, Jinaykumar, Patel, Arpit, Paul, Biswajit, Pradeep, Priya, Ramachandran, Prabhu, Roy, Kinjal, Saiguhan, B.S. Bharath, Saji, Joseph, Saleem, M., Saraogi, Divita, Sastry, Parth, Shanmugam, M., Sharma, Piyush, Shetye, Amit, Singh, Nishant, Singh, Shreeya, Singhal, Akshat, Sreekumar, S., Sridhar, Srividhya, Srinivasan, Rahul, Tallur, Siddharth, K. Tiwari, Neeraj, Lakshmi Vadladi, Amrutha, Vaishnava, C.S., Vishwakarma, Sandeep, and Waratkar, Gaurav

Published
2024
Full Text
View/download PDF

188. Dose-Response Relationship between Obstructive Sleep Apnea Therapy Adherence and Healthcare Utilization

Author

Malhotra, Atul, Sterling, Kimberly L, Cistulli, Peter A, Pépin, Jean-Louis, Chen, Jiaming, Woodford, Caleb, Alpert, Naomi, More, Suyog, Nunez, Carlos M, and Benjafield, Adam V

Subjects
Biomedical and Clinical Sciences, Cardiovascular Medicine and Haematology, Clinical Sciences, Clinical Research, Lung, Health Services, Sleep Research, Respiratory, Good Health and Well Being, Adult, Humans, Continuous Positive Airway Pressure, Patient Acceptance of Health Care, Patient Compliance, Sleep Apnea, Obstructive, Emergency Service, Hospital, positive airway pressure, dose-response, OSA, healthcare resource utilization, hospitalization, emergency room visits, dose–response, Cardiovascular medicine and haematology, Clinical sciences
Abstract

Rationale: Clear definition of optimal positive airway pressure therapy usage in patients with obstructive sleep apnea is not possible because of scarce data on the relationship between usage hours and major clinical outcomes. Objective: To investigate the dose-response relationship between positive airway pressure usage and healthcare resource utilization and determine the minimum device usage required for benefit. Methods: A linked data set combined deidentified payer-sourced administrative medical/pharmacy claims data from more than 100 U.S. health plans and individual patient positive airway pressure usage data. Eligible adults (age ⩾18 yr) had a new obstructive sleep apnea diagnosis between June 2014 and April 2018. All received positive airway pressure therapy (AirSense 10; ResMed) with claims data for ⩾1 year before, and 2 years after, device setup. Healthcare resource utilization was determined on the basis of the number of all-cause hospitalizations and emergency room visits over 3, 12, and 24 months after positive airway pressure initiation. Results: Data from 179,188 patients showed a clear dose-response relationship between daily positive airway pressure usage and healthcare utilization. Minimum device usage required for benefit was 1-3 hours per night. There was a statistically significant decrease in hospitalizations and emergency room visits at all time points (all Ps

Published
2023

189. Gluon contribution to the mechanical properties of a dressed quark in light-front Hamiltonian QCD

Author

More, Jai, Mukherjee, Asmita, Nair, Sreeraj, and Saha, Sudeep

Subjects
High Energy Physics - Phenomenology
Abstract

We calculate the contribution to the gravitational form factors (GFFs) from the gluon part of the energy-momentum tensor in QCD. We take a simple spin $1/2$ composite state, namely a quark dressed with a gluon. We use the light-front Hamiltonian QCD approach in the light-front gauge. We also present the effect of the gluon on the mechanical properties like the pressure, shear and energy distributions of the dressed quark state., Comment: 17 pages, 8 figures

Published
2023
Full Text
View/download PDF

190. Exploring the hidden Universe: A novel phenomenological approach for recovering arbitrary gravitational-wave millilensing configurations

Author

Liu, Anna, Wong, Isaac C. F., Leong, Samson H. W., More, Anupreeta, Hannuksela, Otto A., and Li, Tjonnie G. F.

Subjects
General Relativity and Quantum Cosmology, Astrophysics - High Energy Astrophysical Phenomena, High Energy Physics - Phenomenology
Abstract

Since the first detection of gravitational waves in 2015, gravitational-wave astronomy has emerged as a rapidly advancing field that holds great potential for studying the cosmos, from probing the properties of black holes to testing the limits of our current understanding of gravity. One important aspect of gravitational-wave astronomy is the phenomenon of gravitational lensing, where massive intervening objects can bend and magnify gravitational waves, providing a unique way to probe the distribution of matter in the universe, as well as finding applications to fundamental physics, astrophysics, and cosmology. However, current models for gravitational-wave millilensing - a specific form of lensing where small-scale astrophysical objects can split a gravitational wave signal into multiple copies - are often limited to simple isolated lenses, which is not realistic for complex lensing scenarios. In this paper, we present a novel phenomenological approach to incorporate millilensing in data analysis in a model-independent fashion. Our approach enables the recovery of arbitrary lens configurations without the need for extensive computational lens modeling, making it a more accurate and computationally efficient tool for studying the distribution of matter in the universe using gravitational-wave signals. When gravitational-wave lensing observations become possible, our method can provide a powerful tool for studying complex lens configurations, including dark matter subhalos and MACHOs., Comment: 12 pages, 8 figures

Published
2023
Full Text
View/download PDF

191. With Shared Microexponents, A Little Shifting Goes a Long Way

Author

Rouhani, Bita, Zhao, Ritchie, Elango, Venmugil, Shafipour, Rasoul, Hall, Mathew, Mesmakhosroshahi, Maral, More, Ankit, Melnick, Levi, Golub, Maximilian, Varatkar, Girish, Shao, Lei, Kolhe, Gaurav, Melts, Dimitry, Klar, Jasmine, L'Heureux, Renee, Perry, Matt, Burger, Doug, Chung, Eric, Deng, Zhaoxia, Naghshineh, Sam, Park, Jongsoo, and Naumov, Maxim

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Computer Science - Hardware Architecture
Abstract

This paper introduces Block Data Representations (BDR), a framework for exploring and evaluating a wide spectrum of narrow-precision formats for deep learning. It enables comparison of popular quantization standards, and through BDR, new formats based on shared microexponents (MX) are identified, which outperform other state-of-the-art quantization approaches, including narrow-precision floating-point and block floating-point. MX utilizes multiple levels of quantization scaling with ultra-fine scaling factors based on shared microexponents in the hardware. The effectiveness of MX is demonstrated on real-world models including large-scale generative pretraining and inferencing, and production-scale recommendation systems.

Published
2023

192. Rod-climbing rheometry revisited

Author

More, Rishabh V., Patterson, Reid, Pashkovski, Eugene, and McKinley, Gareth H.

Subjects
Physics - Fluid Dynamics
Abstract

The rod-climbing or Weissenberg effect in which the free surface of a complex fluid climbs a thin rotating rod is a popular and convincing experiment demonstrating the existence of elasticity in polymeric fluids. The interface shape depends on the rotation rate, fluid elasticity, surface tension, and inertia. By solving the equations of motion in the low rotation rate limit for a second-order fluid, a mathematical relationship between the interface deflection and the fluid material functions, specifically the first and second normal stress differences, emerges. This relationship has been used in the past to measure the climbing constant, a combination of the first ($\Psi_{1,0}$) and second ($\Psi_{2,0}$) normal stress difference coefficients from experimental observations of rod-climbing in the low inertia limit. However, a quantitative reconciliation of such observations with the capabilities of modern-day torsional rheometers is lacking. To this end, we combine rod-climbing experiments with both small amplitude oscillatory shear flow measurements and steady shear measurements of the first normal stress difference from commercial rheometers to quantify the values of both normal stress differences for a series of polymer solutions. Furthermore, by retaining the oft-neglected inertial terms, we show that the climbing constant $\hat{\beta}=0.5\Psi_{1,0}+2\Psi_{2,0}$ can be measured even when the fluids, in fact, experience rod descending. A climbing condition derived by considering the competition between elasticity and inertial effects accurately predicts whether a fluid will undergo rod-climbing or rod-descending. The analysis and observations presented in this study establish rotating rod rheometry as a prime candidate for measuring normal stress differences in polymeric fluids at low shear rates that are often below commercial rheometers' sensitivity limits.

Published
2023

193. Gear-up for the Action Replay: Leveraging Lensing for Enhanced Gravitational-Wave Early-Warning

Author

Magare, Sourabh, Kapadia, Shasvath J., More, Anupreeta, Singh, Mukesh Kumar, Ajith, Parameswaran, and Ramprakash, A. N.

Subjects
Astrophysics - High Energy Astrophysical Phenomena, General Relativity and Quantum Cosmology
Abstract

Pre-merger gravitational-wave (GW) sky-localisation of binary neutron star (BNS) and neutron star black hole (NSBH) coalescence events, would enable telescopes to capture precursors and electromagnetic (EM) emissions around the time of the merger. We propose a novel astrophysical scenario that could provide early-warning times of hours to days before coalescence with sub-arcsecond localisation, provided that these events are gravitationally lensed. The key idea is that if the BNS/NSBH is lensed, then so must the host galaxy identified via the EM counterpart. From the angular separation of the lensed host galaxy images, as well as its redshift and the (foreground) lens redshift, we demonstrate that we can predict the time delays assuming a standard lens model. Encouraged by the non-trivial upper limits on the detection rates of lensed BNS/NSBH mergers that we estimate for upcoming observing runs of the LIGO-Virgo-Kagra and third generation networks, we assess the feasibility and benefits of our method. To that end, we study the effect of limited angular resolution of the telescopes on our ability to predict the time delays. We find that with an angular resolution of $0.05''$, we can predict time delays of $> 1$ day with $1\sigma$ error-bar of $\mathcal{O}$(hours) at best. We also construct realistic time delay distributions of detectable lensed BNSs/NSBHs to forecast the early-warning times we might expect in the observing scenarios we consider., Comment: 10 pages, 5 figures

Published
2023

194. The GRAVITY+ Project: Towards All-sky, Faint-Science, High-Contrast Near-Infrared Interferometry at the VLTI

Author

Collaboration, GRAVITY, Abuter, Roberto, Alarcon, Patricio, Allouche, Fatme, Amorim, Antonio, Bailet, Christophe, Bedigan, Helen, Berdeu, Anthony, Berger, Jean-Philippe, Berio, Philippe, Bigioli, Azzurra, Blaho, Richard, Boebion, Olivier, Bolzer, Marie-Lena, Bonnet, Henri, Bourdarot, Guillaume, Bourget, Pierre, Brandner, Wolfgang, Cardenas, Cesar, Conzelmann, Ralf, Comin, Mauro, Clénet, Yann, Courtney-Barrer, Benjamin, Dallilar, Yigit, Davies, Ric, Defrère, Denis, Delboulbé, Alain, Delplancke-Ströbele, Françoise, Dembet, Roderick, de Zeeuw, Tim, Drescher, Antonia, Eckart, Andreas, Édouard, Clemence, Eisenhauer, Frank, Fabricius, Maximilian, Feuchtgruber, Helmut, Finger, Gert, Schreiber, Natascha M. Förster, Fuenteseca, Eloy, Garcia, Enrique, Garcia, Paulo, Gao, Feng, Gendron, Eric, Genzel, Reinhard, Gil, Juan Pablo, Gillessen, Stefan, Gomes, Tiago, Gonté, Frédéric, Gouvret, Carole, Guajardo, Patricia, Guidolin, Ivan, Guieu, Sylvain, Guzmann, Ronald, Hackenberg, Wolfgang, Haddad, Nicolas, Hartl, Michael, Haubois, Xavier, Haußmann, Frank, Heißel, Gernot, Henning, Thomas, Hippler, Stefan, Hönig, Sebastian, Horrobin, Matthew, Hubin, Norbert, Jacqmart, Estelle, Jocou, Laurent, Kaufer, Andreas, Kervella, Pierre, Kirchbauer, Jean-Paul, Kolb, Johan, Korhonen, Heidi, Kreidberg, Laura, Krempl, Peter, Lacour, Sylvestre, Lagarde, Stephane, Lai, Olivier, Lapeyrère, Vincent, Laugier, Romain, Bouquin, Jean-Baptiste Le, Leftley, James, Léna, Pierre, Lewis, Steffan, Lutz, Dieter, Magnard, Yves, Mang, Felix, Marcotto, Aurelie, Maurel, Didier, Mérand, Antoine, Millour, Florentin, More, Nikhil, Nowack, Hugo, Nowak, Matthias, Oberti, Sylvain, Olivares, Francisco, Ott, Thomas, Pallanca, Laurent, Paumard, Thibaut, Perraut, Karine, Perrin, Guy, Petrov, Romain, Pfuhl, Oliver, Pourré, Nicolas, Rabien, Sebastian, Rau, Christian, Riquelme, Miguel, Robbe-Dubois, Sylvie, Rochat, Sylvain, Salman, Muhammad, Scherbarth, Malte, Schöller, Markus, Schubert, Joseph, Schuhler, Nicolas, Shangguan, Jinyi, Shchekaturov, Pavel, Shimizu, Taro, Scheithauer, Silvia, Sevin, Arnaud, Soenke, Christian, Soulez, Ferreol, Spang, Alain, Stadler, Eric, Straubmeier, Christian, Sturm, Eckhard, Sykes, Calvin, Tacconi, Linda, Tischer, Helmut, Tristram, Konrad, Vincent, Frédéric, von Fellenberg, Sebastiano, Uysal, Sinem, Widmann, Felix, Wieprecht, Ekkehard, Wiezorrek, Erich, Woillez, Julien, Yazıcı, Şenol, and Zins, Gérard

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics
Abstract

The GRAVITY instrument has been revolutionary for near-infrared interferometry by pushing sensitivity and precision to previously unknown limits. With the upgrade of GRAVITY and the Very Large Telescope Interferometer (VLTI) in GRAVITY+, these limits will be pushed even further, with vastly improved sky coverage, as well as faint-science and high-contrast capabilities. This upgrade includes the implementation of wide-field off-axis fringe-tracking, new adaptive optics systems on all Unit Telescopes, and laser guide stars in an upgraded facility. GRAVITY+ will open up the sky to the measurement of black hole masses across cosmic time in hundreds of active galactic nuclei, use the faint stars in the Galactic centre to probe General Relativity, and enable the characterisation of dozens of young exoplanets to study their formation, bearing the promise of another scientific revolution to come at the VLTI., Comment: Published in the ESO Messenger

Published
2023
Full Text
View/download PDF

195. Strong gravitational lensing and microlensing of supernovae

Author

Suyu, Sherry H., Goobar, Ariel, Collett, Thomas, More, Anupreeta, and Vernardos, Giorgos

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - High Energy Astrophysical Phenomena
Abstract

Strong gravitational lensing and microlensing of supernovae (SNe) are emerging as a new probe of cosmology and astrophysics in recent years. We provide an overview of this nascent research field, starting with a summary of the first discoveries of strongly lensed SNe. We describe the use of the time delays between multiple SN images as a way to measure cosmological distances and thus constrain cosmological parameters, particularly the Hubble constant, whose value is currently under heated debates. New methods for measuring the time delays in lensed SNe have been developed, and the sample of lensed SNe from the upcoming Rubin Observatory Legacy Survey of Space and Time (LSST) is expected to provide competitive cosmological constraints. Lensed SNe are also powerful astrophysical probes. We review the usage of lensed SNe to constrain SN progenitors, acquire high-z SN spectra through lensing magnifications, infer SN sizes via microlensing, and measure properties of dust in galaxies. The current challenge in the field is the rarity and difficulty in finding lensed SNe. We describe various methods and ongoing efforts to find these spectacular explosions, forecast the properties of the expected sample of lensed SNe from upcoming surveys particularly the LSST, and summarize the observational follow-up requirements to enable the various scientific studies. We anticipate the upcoming years to be exciting with a boom in lensed SN discoveries., Comment: 48 pages, 18 figures; to be submitted to Space Science Reviews, Topical Collection "Strong Gravitational Lensing", eds. J. Wambsganss et al

Published
2023
Full Text
View/download PDF

196. Stellar mass dependence of galaxy size-dark matter halo radius relation probed by Subaru-HSC survey weak lensing measurements

Author

Mishra, Preetish K., Rana, Divya, and More, Surhud

Subjects
Astrophysics - Astrophysics of Galaxies, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

We investigate the stellar mass-dependence of the galaxy size-dark matter halo radius relation for low redshift galaxies using weak gravitational lensing measurements. Our sample consists of $\sim$38,000 galaxies more massive than $10^{8}{\rm M}_{\odot}h^{-2}$ and within $z<0.3$ drawn from the overlap of GAMA survey DR4 and HSC-SSP PDR2. We divide our sample into a number of stellar mass bins and measure stacked weak lensing signals. We model the signals using a conditional stellar mass function to infer the stellar mass-halo mass relation. We fit a single S\'ersic model to HSC $i$-band images of our galaxies and obtain their three-dimensional half-light radii. We use these measurements to construct a median galaxy size-mass relation. We then combine these relations to infer the galaxy size-halo radius relation. We confirm that this relation appears linear given the statistical errors, i.e. the ratio of galaxy size to halo radius remains constant over two orders of magnitudes in stellar mass above $\sim 10^{9} {\rm M}_{\odot}h^{-2}$. Extrapolating the stellar mass-halo mass relation below this limit, we see an indication of a decreasing galaxy size-halo radius ratio with the decline in stellar mass. At stellar mass $\sim 10^{8} {\rm M}_{\odot}h^{-2}$ the ratio becomes 30% smaller than its value in linear regime. The possible existence of a such trend in dwarf galaxy sectors calls for either modification in models employing a constant fraction of halo angular momentum transferred to explain sizes of dwarfs or else points towards our lack of knowledge about dark matter haloes of low-mass galaxies., Comment: 20 pages, 12 figures, accepted in MNRAS

Published
2023

197. The impact of human expert visual inspection on the discovery of strong gravitational lenses

Author

Rojas, Karina, Collett, Thomas E., Ballard, Daniel, Magee, Mark R., Birrer, Simon, Buckley-Geer., Elizabeth, Chan, James H. H., Clément, Benjamin, Diego, José M., Gentile, Fabrizio, González, Jimena, Joseph, Rémy, Mastache, Jorge, Schuldt, Stefan, Tortora, Crescenzo, Verdugo, Tomás, Verma, Aprajita, Daylan, Tansu, Millon, Martin, Jackson, Neal, Dye, Simon, Melo, Alejandra, Mahler, Guillaume, Ogando, Ricardo L. C., Courbin, Frédéric, Fritz, Alexander, Herle, Aniruddh, Barroso, Javier A. Acevedo, Cañameras, Raoul, Cornen, Claude, Dhanasingham, Birendra, Glazebrook, Karl, Martinez, Michael N., Ryczanowski, Dan, Savary, Elodie, Góis-Silva, Filipe, Ureña-López, L. Arturo, Wiesner, Matthew P., Wilde, Joshua, Calçada, Gabriel Valim, Cabanac, Rémi, Pan, Yue, Sierra, Isaac, Despali, Giulia, Cavalcante-Gomes, Micaele V., Macmillan, Christine, Maresca, Jacob, Grudskaia, Aleksandra, O'Donnell, Jackson H., Paic, Eric, Niemiec, Anna, de la Bella, Lucia F., Bromley, Jane, Williams, Devon M., More, Anupreeta, and Levine, Benjamin C.

Subjects
Astrophysics - Astrophysics of Galaxies, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

We investigate the ability of human 'expert' classifiers to identify strong gravitational lens candidates in Dark Energy Survey like imaging. We recruited a total of 55 people that completed more than 25$\%$ of the project. During the classification task, we present to the participants 1489 images. The sample contains a variety of data including lens simulations, real lenses, non-lens examples, and unlabeled data. We find that experts are extremely good at finding bright, well-resolved Einstein rings, whilst arcs with $g$-band signal-to-noise less than $\sim$25 or Einstein radii less than $\sim$1.2 times the seeing are rarely recovered. Very few non-lenses are scored highly. There is substantial variation in the performance of individual classifiers, but they do not appear to depend on the classifier's experience, confidence or academic position. These variations can be mitigated with a team of 6 or more independent classifiers. Our results give confidence that humans are a reliable pruning step for lens candidates, providing pure and quantifiably complete samples for follow-up studies., Comment: 16 pages, 20 Figures

Published
2023
Full Text
View/download PDF

198. The eROSITA Final Equatorial-Depth Survey (eFEDS) -- Splashback radius of X-ray galaxy clusters using galaxies from HSC survey

Author

Rana, Divya, More, Surhud, Miyatake, Hironao, Grandis, Sebastian, Klein, Matthias, Bulbul, Esra, Chiu, I-Non, Miyazaki, Satoshi, and Bahcall, Neta

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Astrophysics of Galaxies
Abstract

We present the splashback radius measurements around the SRG/eROSITA eFEDS X-ray selected galaxy clusters by cross-correlating them with HSC S19A photometric galaxies. The X-ray selection is expected to be less affected by systematics related to projection that affects optical cluster finder algorithms. We use a nearly volume-limited sample of 109 galaxy clusters selected in 0.5-2.0 keV band having luminosity $L_X > 10^{43.5}\,{\rm erg s^{-1} h^{-2}}$ within the redshift $z<0.75$ and obtain measurements of the projected cross-correlation with a signal-to-noise of $17.43$. We model our measurements to infer a three-dimensional profile and find that the steepest slope is sharper than $-3$ and associate the location with the splashback radius. We infer the value of the 3D splashback radius $r_{\rm sp} = 1.45^{+0.30}_{-0.26}\,{\rm h^{-1} Mpc}$. We also measure the weak lensing signal of the galaxy clusters and obtain halo mass $\log[M_{\rm 200m}/{\rm h^{-1}M_\odot}] = 14.52 \pm 0.06$ using the HSC-S16A shape catalogue data at the median redshift $z=0.46$ of our cluster sample. We compare our $r_{\rm sp}$ values with the spherical overdensity boundary $r_{\rm 200m} = 1.75 \pm 0.08\,{\rm h^{-1} Mpc}$ based on the halo mass which is consistent within $1.2\sigma$ with the $\Lambda$CDM predictions. Our constraints on the splashback radius, although broad, are the best measurements thus far obtained for an X-ray selected galaxy cluster sample., Comment: 15 pages, 10 figures

Published
2023
Full Text
View/download PDF

199. The cosmic web of X-ray active galactic nuclei seen through the eROSITA Final Equatorial Depth Survey (eFEDS)

Author

Comparat, Johan, Luo, Wentao, Merloni, Andrea, More, Surhud, Salvato, Mara, Krumpe, Mirko, Miyaji, Takamitsu, Brandt, William, Georgakakis, Antonis, Akiyama, Masayuki, Buchner, Johannes, Dwelly, Tom, Kawaguchi, Toshihiro, Liu, Teng, Nagao, Tohru, Nandra, Kirpal, Silverman, John, Toba, Yoshiki, Anderson, Scott F., and Kollmeier, Juna

Subjects
Astrophysics - Astrophysics of Galaxies, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

Which galaxies in the general population turn into active galactic nuclei (AGNs) is a keystone of galaxy formation and evolution. Thanks to SRG/eROSITA's contiguous 140 square degree pilot survey field, we constructed a large, complete, and unbiased soft X-ray flux-limited ($F_X>6.5\times 10^{-15}$ erg s$^{-1}$ cm$^{-2}$) AGN sample at low redshift, $0.05

Published
2023
Full Text
View/download PDF

200. MAntRA: A framework for model agnostic reliability analysis

Author

Mathpati, Yogesh Chandrakant, More, Kalpesh Sanjay, Tripura, Tapas, Nayek, Rajdip, and Chakraborty, Souvik

Subjects
Statistics - Methodology, Computer Science - Machine Learning, Statistics - Machine Learning
Abstract

We propose a novel model agnostic data-driven reliability analysis framework for time-dependent reliability analysis. The proposed approach -- referred to as MAntRA -- combines interpretable machine learning, Bayesian statistics, and identifying stochastic dynamic equation to evaluate reliability of stochastically-excited dynamical systems for which the governing physics is \textit{apriori} unknown. A two-stage approach is adopted: in the first stage, an efficient variational Bayesian equation discovery algorithm is developed to determine the governing physics of an underlying stochastic differential equation (SDE) from measured output data. The developed algorithm is efficient and accounts for epistemic uncertainty due to limited and noisy data, and aleatoric uncertainty because of environmental effect and external excitation. In the second stage, the discovered SDE is solved using a stochastic integration scheme and the probability failure is computed. The efficacy of the proposed approach is illustrated on three numerical examples. The results obtained indicate the possible application of the proposed approach for reliability analysis of in-situ and heritage structures from on-site measurements.

Published
2022

Catalog

Books, media, physical & digital resources
See catalog results