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1. The JWST Early-release Science Program for Direct Observations of Exoplanetary Systems II: A 1 to 20 μm Spectrum of the Planetary-mass Companion VHS 1256-1257 b

Author

Miles, BE, Biller, BA, Patapis, P, Worthen, K, Rickman, E, Hoch, KKW, Skemer, A, Perrin, MD, Whiteford, N, Chen, CH, Sargent, B, Mukherjee, S, Morley, CV, Moran, SE, Bonnefoy, M, Petrus, S, Carter, AL, Choquet, E, Hinkley, S, Ward-Duong, K, Leisenring, JM, Millar-Blanchaer, MA, Pueyo, L, Ray, S, Sallum, S, Stapelfeldt, KR, Stone, JM, Wang, JJ, Absil, O, Balmer, WO, Boccaletti, A, Bonavita, M, Booth, M, Bowler, BP, Chauvin, G, Christiaens, V, Currie, T, Danielski, C, Fortney, JJ, Girard, JH, Grady, CA, Greenbaum, AZ, Henning, T, Hines, DC, Janson, M, Kalas, P, Kammerer, J, Kennedy, GM, Kenworthy, MA, Kervella, P, Lagage, PO, Lew, BWP, Liu, MC, Macintosh, B, Marino, S, Marley, MS, Marois, C, Matthews, EC, Matthews, BC, Mawet, D, McElwain, MW, Metchev, S, Meyer, MR, Molliere, P, Pantin, E, Quirrenbach, A, Rebollido, I, Ren, BB, Schneider, G, Vasist, M, Wyatt, MC, Zhou, Y, Briesemeister, ZW, Bryan, ML, Calissendorff, P, Cantalloube, F, Cugno, G, De Furio, M, Dupuy, TJ, Factor, SM, Faherty, JK, Fitzgerald, MP, Franson, K, Gonzales, EC, Hood, CE, Howe, AR, Kraus, AL, Kuzuhara, M, Lagrange, AM, Lawson, K, Lazzoni, C, Liu, P, Llop-Sayson, J, Lloyd, JP, Martinez, RA, Mazoyer, J, Quanz, SP, Redai, JA, Samland, M, Schlieder, JE, Miles, BE [0000-0002-5500-4602], Biller, BA [0000-0003-4614-7035], Patapis, P [0000-0001-8718-3732], Worthen, K [0000-0002-5885-5779], Rickman, E [0000-0003-4203-9715], Hoch, KKW [0000-0002-9803-8255], Skemer, A [0000-0001-6098-3924], Perrin, MD [0000-0002-3191-8151], Whiteford, N [0000-0001-8818-1544], Chen, CH [0000-0002-8382-0447], Sargent, B [0000-0001-9855-8261], Mukherjee, S [0000-0003-1622-1302], Morley, CV [0000-0002-4404-0456], Moran, SE [0000-0002-6721-3284], Bonnefoy, M [0000-0001-5579-5339], Petrus, S [0000-0003-0331-3654], Carter, AL [0000-0001-5365-4815], Choquet, E [0000-0002-9173-0740], Hinkley, S [0000-0001-8074-2562], Ward-Duong, K [0000-0002-4479-8291], Leisenring, JM [0000-0002-0834-6140], Millar-Blanchaer, MA [0000-0001-6205-9233], Ray, S [0000-0003-2259-3911], Sallum, S [0000-0001-6871-6775], Stapelfeldt, KR [0000-0002-2805-7338], Stone, JM [0000-0003-0454-3718], Wang, JJ [0000-0003-0774-6502], Absil, O [0000-0002-4006-6237], Balmer, WO [0000-0001-6396-8439], Boccaletti, A [0000-0001-9353-2724], Bonavita, M [0000-0002-7520-8389], Booth, M [0000-0001-8568-6336], Bowler, BP [0000-0003-2649-2288], Chauvin, G [0000-0003-4022-8598], Christiaens, V [0000-0002-0101-8814], Currie, T [0000-0002-7405-3119], Danielski, C [0000-0002-3729-2663], Fortney, JJ [0000-0002-9843-4354], Girard, JH [0000-0001-8627-0404], Greenbaum, AZ [0000-0002-7162-8036], Henning, T [0000-0002-1493-300X], Hines, DC [0000-0003-4653-6161], Janson, M [0000-0001-8345-593X], Kalas, P [0000-0002-6221-5360], Kammerer, J [0000-0003-2769-0438], Kennedy, GM [0000-0001-6831-7547], Kenworthy, MA [0000-0002-7064-8270], Kervella, P [0000-0003-0626-1749], Lew, BWP [0000-0003-1487-6452], Liu, MC [0000-0003-2232-7664], Macintosh, B [0000-0003-1212-7538], Marino, S [0000-0002-5352-2924], Marley, MS [0000-0002-5251-2943], Marois, C [0000-0002-4164-4182], Matthews, EC [0000-0003-0593-1560], Matthews, BC [0000-0003-3017-9577], Mawet, D [0000-0002-8895-4735], McElwain, MW [0000-0003-0241-8956], Metchev, S [0000-0003-3050-8203], Meyer, MR [0000-0003-1227-3084], Molliere, P [0000-0003-4096-7067], Pantin, E [0000-0001-6472-2844], Rebollido, I [0000-0002-4388-6417], Ren, BB [0000-0003-1698-9696], Schneider, G [0000-0002-4511-5966], Vasist, M [0000-0002-4511-3602], Wyatt, MC [0000-0001-9064-5598], Zhou, Y [0000-0003-2969-6040], Briesemeister, ZW [0000-0002-1764-2494], Bryan, ML [0000-0002-6076-5967], Calissendorff, P [0000-0002-5335-0616], Cantalloube, F [0000-0002-3968-3780], Cugno, G [0000-0001-7255-3251], De Furio, M [0000-0003-1863-4960], Dupuy, TJ [0000-0001-9823-1445], Factor, SM [0000-0002-8332-8516], Faherty, JK [0000-0001-6251-0573], Fitzgerald, MP [0000-0002-0176-8973], Franson, K [0000-0003-4557-414X], Gonzales, EC [0000-0003-4636-6676], Hood, CE [0000-0003-1150-7889], Howe, AR [0000-0002-4884-7150], Kraus, AL [0000-0001-9811-568X], Kuzuhara, M [0000-0002-4677-9182], Lawson, K [0000-0002-6964-8732], Lazzoni, C [0000-0001-7819-9003], Liu, P [0000-0001-7047-0874], Llop-Sayson, J [0000-0002-3414-784X], Martinez, RA [0000-0001-6301-896X], Mazoyer, J [0000-0002-9133-3091], Quanz, SP [0000-0003-3829-7412], Redai, JA [0000-0002-4489-3168], Samland, M [0000-0001-9992-4067], Schlieder, JE [0000-0001-5347-7062], and Apollo - University of Cambridge Repository

Subjects
The Solar System, Exoplanets, and Astrobiology, 5109 Space Sciences, 51 Physical Sciences
Abstract

We present the highest fidelity spectrum to date of a planetary-mass object. VHS 1256 b is a M Jup widely separated (∼8″, a = 150 au), young, planetary-mass companion that shares photometric colors and spectroscopic features with the directly imaged exoplanets HR 8799c, d, and e. As an L-to-T transition object, VHS 1256 b exists along the region of the color–magnitude diagram where substellar atmospheres transition from cloudy to clear. We observed VHS 1256 b with JWST's NIRSpec IFU and MIRI MRS modes for coverage from 1 to 20 μm at resolutions of ∼1000–3700. Water, methane, carbon monoxide, carbon dioxide, sodium, and potassium are observed in several portions of the JWST spectrum based on comparisons from template brown dwarf spectra, molecular opacities, and atmospheric models. The spectral shape of VHS 1256 b is influenced by disequilibrium chemistry and clouds. We directly detect silicate clouds, the first such detection reported for a planetary-mass companion.

Published
2023

2. Analysis of community connectivity in spatial transcriptomics data

Author

Juan Xie, Kyeong Joo Jung, Carter Allen, Yuzhou Chang, Subhadeep Paul, Zihai Li, Qin Ma, and Dongjun Chung

Subjects
spatial transcriptomics, analysis of community connectivity, stochastic block model, Bayesian models, network analysis, Applied mathematics. Quantitative methods, T57-57.97, Probabilities. Mathematical statistics, QA273-280
Abstract

IntroductionThe advent of high throughput spatial transcriptomics (HST) has allowed for unprecedented characterization of spatially distinct cell communities within a tissue sample. While a wide range of computational tools exist for detecting cell communities in HST data, none allow for the characterization of community connectivity, i.e., the relative similarity of cells within and between found communities—an analysis task that can elucidate cellular dynamics in important settings such as the tumor microenvironment.MethodsTo address this gap, we introduce the analysis of community connectivity (ACC), which facilitates understanding of the relative similarity of cells within and between communities. We develop a Bayesian multi-layer network model called BANYAN for the integration of spatial and gene expression information to achieve ACC.ResultsWe demonstrate BANYAN's ability to recover community connectivity structure via a simulation study based on real sagittal mouse brain HST data. Next, we use BANYAN to implement ACC across a wide range of real data scenarios, including 10 × Visium data of melanoma brain metastases and invasive ductal carcinoma, and NanoString CosMx data of human-small-cell lung cancer, each of which reveals distinct cliques of interacting cell sub-populations. An R package banyan is available at https://github.com/dongjunchung/banyan.

Published
2024
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3. Ground-based transmission spectroscopy with FORS2: A featureless optical transmission spectrum and detection of H2O for the ultra-hot Jupiter WASP-103b

Author

Wilson, J, Gibson, NP, Nikolov, N, Constantinou, S, Madhusudhan, N, Goyal, J, Barstow, JK, Carter, AL, De Mooij, EJW, Drummond, B, Mikal-Evans, T, Helling, C, Mayne, NJ, Sing, DK, Constantinou, Savvas [0000-0001-6839-4569], Nikku, Madhusudhan [0000-0002-4869-000X], and Apollo - University of Cambridge Repository

Subjects
stars: individual (WASP-103), Astrophysics::Cosmology and Extragalactic Astrophysics, Astrophysics::Earth and Planetary Astrophysics, methods: data analysis, planetary systems, Astrophysics::Galaxy Astrophysics, techniques: spectroscopic
Abstract

We report ground-based transmission spectroscopy of the highly irradiated and ultra-short period hot-Jupiter WASP-103b covering the wavelength range $\approx$ 400-600 nm using the FORS2 instrument on the Very Large Telescope. The light curves show significant time-correlated noise which is mainly invariant in wavelength and which we model using a Gaussian process. The precision of our transmission spectrum is improved by applying a common-mode correction derived from the white light curve, reaching typical uncertainties in transit depth of $\approx$ 2x10$^{-4}$ in wavelength bins of 15 nm. After correction for flux contamination from a blended companion star, our observations reveal a featureless spectrum across the full range of the FORS2 observations and we are unable to confirm the Na absorption previously inferred using Gemini/GMOS or the strong Rayleigh scattering observed using broad-band light curves. We performed a Bayesian atmospheric retrieval on the full optical-infrared transmission spectrum using the additional data from Gemini/GMOS, HST/WFC3 and Spitzer observations and recover evidence for H$_2$O absorption at the 4.0$\sigma$ level. However, our observations are not able to completely rule out the presence of Na, which is found at 2.0$\sigma$ in our retrievals. This may in part be explained by patchy/inhomogeneous clouds or hazes damping any absorption features in our FORS2 spectrum, but an inherently small scale height also makes this feature challenging to probe from the ground. Our results nonetheless demonstrate the continuing potential of ground-based observations for investigating exoplanet atmospheres and emphasise the need for the application of consistent and robust statistical techniques to low-resolution spectra in the presence of instrumental systematics.

Published
2020

4. The transiting exoplanet community early release science program for JWST

Author

Bean, JL, Stevenson, KB, Batalha, NM, Berta-Thompson, Z, Kreidberg, L, Crouzet, N, Benneke, B, Line, MR, Sing, DK, Wakeford, HR, Knutson, HA, Kempton, EMR, Désert, JM, Crossfield, I, Batalha, NE, De Wit, J, Parmentier, V, Harrington, J, Moses, JI, Lopez-Morales, M, Alam, MK, Blecic, J, Bruno, G, Carter, AL, Chapman, JW, Decin, L, Dragomir, D, Evans, TM, Fortney, JJ, Fraine, JD, Gao, P, Muñoz, AG, Gibson, NP, Goyal, JM, Heng, K, Hu, R, Kendrew, S, Kilpatrick, BM, Krick, J, Lagage, PO, Lendl, M, Louden, T, Madhusudhan, N, Mandell, AM, Mansfield, M, May, EM, Morello, G, Morley, CV, Nikolov, N, Redfield, S, Roberts, JE, Schlawin, E, Spake, JJ, Todorov, KO, Tsiaras, A, Venot, O, Waalkes, WC, Wheatley, PJ, Zellem, RT, Angerhausen, D, Barrado, D, Carone, L, Casewell, SL, Cubillos, PE, Damiano, M, Borro, MDV, Drummond, B, Edwards, B, Endl, M, Espinoza, N, France, K, Gizis, JE, Greene, TP, Henning, TK, Hong, Y, Ingalls, JG, Iro, N, Irwin, PGJ, Kataria, T, Lahuis, F, Leconte, J, Lillo-Box, J, Lines, S, Lothringer, JD, Mancini, L, Marchis, F, Mayne, N, Palle, E, Rauscher, E, Roudier, G, Shkolnik, EL, Southworth, J, Swain, MR, Taylor, J, Teske, J, Tinetti, G, Tremblin, P, Tucker, GS, Boekel, RV, Waldmann, IP, Bean, JL [0000-0003-4733-6532], and Apollo - University of Cambridge Repository

Subjects
planets and satellites: atmospheres, Astrophysics::Instrumentation and Methods for Astrophysics, Astrophysics::Cosmology and Extragalactic Astrophysics, Astrophysics::Earth and Planetary Astrophysics, methods: observational, planets and satellites: individual (WASP-79b, WASP-43b, WASP-18b)
Abstract

The James Webb Space Telescope (JWST) presents the opportunity to transform our understanding of planets and the origins of life by revealing the atmospheric compositions, structures, and dynamics of transiting exoplanets in unprecedented detail. However, the high-precision, time-series observations required for such investigations have unique technical challenges, and prior experience with other facilities indicates that there will be a steep learning curve when JWST becomes operational. In this paper we describe the science objectives and detailed plans of the Transiting Exoplanet Community Early Release Science (ERS) Program, which is a recently approved program for JWST observations early in Cycle 1. The goal of this project, for which the obtained data will have no exclusive access period, is to accelerate the acquisition and diffusion of technical expertise for transiting exoplanet observations with JWST, while also providing a compelling set of representative datasets that will enable immediate scientific breakthroughs. The Transiting Exoplanet Community ERS Program will exercise the time-series modes of all four JWST instruments that have been identified as the consensus highest priorities, observe the full suite of transiting planet characterization geometries (transits, eclipses, and phase curves), and target planets with host stars that span an illustrative range of brightnesses. The observations in this program were defined through an inclusive and transparent process that had participation from JWST instrument experts and international leaders in transiting exoplanet studies. Community engagement in the project will be centered on a two-phase Data Challenge that culminates with the delivery of planetary spectra, time-series instrument performance reports, and open-source data analysis toolkits in time to inform the agenda for Cycle 2 of the JWST mission.

Published
2018

5. Geostatistical interpolation can reliably extend coverage of a very high-resolution model of temperature-dependent sex determination

Author

Carter, AL, Kearney, MR, Hartley, S, Porter, WP, Nelson, NJ, Carter, AL, Kearney, MR, Hartley, S, Porter, WP, and Nelson, NJ

Abstract

AIM: Recognition that statistical models do not always reliably predict habitat suitability under future climate scenarios is leading increasingly to explicit incorporation of the physiological constraints that underlie species’ distributions into spatially explicit predictions. However, computational intensity constrains the use of high‐resolution, process‐explicit models. We examined whether geostatistical analysis can effectively interpolate a biophysical model, reducing the computational investment typically required for using mechanistic methods to inform physiological predictions. LOCATION: New Zealand [40°40′00″ S 174°00′00″ E]. METHODS: We used a spatially explicit, mechanistic microclimate model to predict hourly temperatures at five soil depths under two scenarios of climate warming. Using the predicted soil temperatures as input to a biophysical model of temperature‐dependent embryonic development, we estimated incubation temperatures and corresponding hatchling sex ratios for tuatara, a reptile with temperature‐dependent sex determination, at a submetre horizontal spatial resolution. We then applied ordinary kriging, a robust method of geostatistical interpolation, to estimate predictions throughout the full extent of our study location, an additional 480,000+ microsites, and validated the interpolation against an independent set of predictions. RESULTS: Ordinary kriging accurately predicted spatial variability in incubation temperatures. Mean predictions were similar between methods, and error in the geospatial model generally decreased with increasing soil depth. Error was higher for the geospatial model of the ‘maximum warming’, compared with the ‘minimum warming’, scenario of climate change. MAIN CONCLUSIONS: Our results show that ordinary kriging can be a reliable method for interpolating variability in high‐resolution predictions. However, the effects of error on the accuracy of interpolated predictions will become more severe as values approach a

Published
2018

6. Treatment with soluble CD24 attenuates COVID-19-associated systemic immunopathology

Author

No-Joon Song, Carter Allen, Anna E. Vilgelm, Brian P. Riesenberg, Kevin P. Weller, Kelsi Reynolds, Karthik B. Chakravarthy, Amrendra Kumar, Aastha Khatiwada, Zequn Sun, Anjun Ma, Yuzhou Chang, Mohamed Yusuf, Anqi Li, Cong Zeng, John P. Evans, Donna Bucci, Manuja Gunasena, Menglin Xu, Namal P. M. Liyanage, Chelsea Bolyard, Maria Velegraki, Shan-Lu Liu, Qin Ma, Martin Devenport, Yang Liu, Pan Zheng, Carlos D. Malvestutto, Dongjun Chung, and Zihai Li

Subjects
COVID-19, CD24Fc, Soluble CD24, Immunophenotyping, Cytokine score, Diseases of the blood and blood-forming organs, RC633-647.5, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Abstract Background Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) causes coronavirus disease 2019 (COVID-19) through direct lysis of infected lung epithelial cells, which releases damage-associated molecular patterns and induces a pro-inflammatory cytokine milieu causing systemic inflammation. Anti-viral and anti-inflammatory agents have shown limited therapeutic efficacy. Soluble CD24 (CD24Fc) blunts the broad inflammatory response induced by damage-associated molecular patterns via binding to extracellular high mobility group box 1 and heat shock proteins, as well as regulating the downstream Siglec10-Src homology 2 domain–containing phosphatase 1 pathway. A recent randomized phase III trial evaluating CD24Fc for patients with severe COVID-19 (SAC-COVID; NCT04317040) demonstrated encouraging clinical efficacy. Methods Using a systems analytical approach, we studied peripheral blood samples obtained from patients enrolled at a single institution in the SAC-COVID trial to discern the impact of CD24Fc treatment on immune homeostasis. We performed high dimensional spectral flow cytometry and measured the levels of a broad array of cytokines and chemokines to discern the impact of CD24Fc treatment on immune homeostasis in patients with COVID-19. Results Twenty-two patients were enrolled, and the clinical characteristics from the CD24Fc vs. placebo groups were matched. Using high-content spectral flow cytometry and network-level analysis, we found that patients with severe COVID-19 had systemic hyper-activation of multiple cellular compartments, including CD8+ T cells, CD4+ T cells, and CD56+ natural killer cells. Treatment with CD24Fc blunted this systemic inflammation, inducing a return to homeostasis in NK and T cells without compromising the anti-Spike protein antibody response. CD24Fc significantly attenuated the systemic cytokine response and diminished the cytokine coexpression and network connectivity linked with COVID-19 severity and pathogenesis. Conclusions Our data demonstrate that CD24Fc rapidly down-modulates systemic inflammation and restores immune homeostasis in SARS-CoV-2-infected individuals, supporting further development of CD24Fc as a novel therapeutic against severe COVID-19.

Published
2022
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7. Define and visualize pathological architectures of human tissues from spatially resolved transcriptomics using deep learning

Author

Yuzhou Chang, Fei He, Juexin Wang, Shuo Chen, Jingyi Li, Jixin Liu, Yang Yu, Li Su, Anjun Ma, Carter Allen, Yu Lin, Shaoli Sun, Bingqiang Liu, José Javier Otero, Dongjun Chung, Hongjun Fu, Zihai Li, Dong Xu, and Qin Ma

Subjects
Spatial transcriptomics, Deep learning, Tissue architecture visualization and identification, Biotechnology, TP248.13-248.65
Abstract

Spatially resolved transcriptomics provides a new way to define spatial contexts and understand the pathogenesis of complex human diseases. Although some computational frameworks can characterize spatial context via various clustering methods, the detailed spatial architectures and functional zonation often cannot be revealed and localized due to the limited capacities of associating spatial information. We present RESEPT, a deep-learning framework for characterizing and visualizing tissue architecture from spatially resolved transcriptomics. Given inputs such as gene expression or RNA velocity, RESEPT learns a three-dimensional embedding with a spatial retained graph neural network from spatial transcriptomics. The embedding is then visualized by mapping into color channels in an RGB image and segmented with a supervised convolutional neural network model. Based on a benchmark of 10x Genomics Visium spatial transcriptomics datasets on the human and mouse cortex, RESEPT infers and visualizes the tissue architecture accurately. It is noteworthy that, for the in-house AD samples, RESEPT can localize cortex layers and cell types based on pre-defined region- or cell-type-enriched genes and furthermore provide critical insights into the identification of amyloid-beta plaques in Alzheimer's disease. Interestingly, in a glioblastoma sample analysis, RESEPT distinguishes tumor-enriched, non-tumor, and regions of neuropil with infiltrating tumor cells in support of clinical and prognostic cancer applications.

Published
2022
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8. Network-Based Discovery of Opioid Use Vulnerability in Rats Using the Bayesian Stochastic Block Model

Author

Carter Allen, Brittany N. Kuhn, Nazzareno Cannella, Ayteria D. Crow, Analyse T. Roberts, Veronica Lunerti, Massimo Ubaldi, Gary Hardiman, Leah C. Solberg Woods, Roberto Ciccocioppo, Peter W. Kalivas, and Dongjun Chung

Subjects
clustering, community detection, Bayesian model, opioid use disorder, network analysis, stochastic block model, Psychiatry, RC435-571
Abstract

Opioid use disorder is a psychological condition that affects over 200,000 people per year in the U.S., causing the Centers for Disease Control and Prevention to label the crisis as a rapidly spreading public health epidemic. The behavioral relationship between opioid exposure and development of opioid use disorder (OUD) varies greatly between individuals, implying existence of sup-populations with varying degrees of opioid vulnerability. However, effective pre-clinical identification of these sub-populations remains challenging due to the complex multivariate measurements employed in animal models of OUD. In this study, we propose a novel non-linear network-based data analysis workflow that employs seven behavioral traits to identify opioid use sub-populations and assesses contributions of behavioral variables to opioid vulnerability and resiliency. Through this analysis workflow we determined how behavioral variables across heroin taking, refraining and seeking interact with one another to identify potentially heroin resilient and vulnerable behavioral sub-populations. Data were collected from over 400 heterogeneous stock rats in two geographically distinct locations. Rats underwent heroin self-administration training, followed by a progressive ratio and heroin-primed reinstatement test. Next, rats underwent extinction training and a cue-induced reinstatement test. To enter the analysis workflow, we integrated data from different cohorts of rats and removed possible batch effects. We then constructed a rat-rat similarity network based on their behavioral patterns and implemented community detection on this similarity network using a Bayesian degree-corrected stochastic block model to uncover sub-populations of rats with differing levels of opioid vulnerability. We identified three statistically distinct clusters corresponding to distinct behavioral sub-populations, vulnerable, resilient and intermediate for heroin use, refraining and seeking. We implement this analysis workflow as an open source R package, named mlsbm.

Published
2021
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9. The Sudbury Neutrino Observatory

Author

Boger, J, Hahn, RL, Rowley, JK, Carter, AL, Hollebone, B, Kessler, D, Blevis, I, Dalnoki-Veress, F, DeKok, A, Farine, J, Grant, DR, Hargrove, CK, Laberge, G, Levine, I, McFarlane, K, Mes, H, Noble, AT, Novikov, VM, O'Neill, M, Shatkay, M, Shewchuk, C, Sinclair, D, Clifford, ETH, Deal, R, Earle, ED, Gaudette, E, Milton, G, Sur, B, Bigu, J, Cowan, JHM, Cluff, DL, Hallman, ED, Haq, RU, Hewett, J, Hykawy, JG, Jonkmans, G, Michaud, R, Roberge, A, Roberts, J, Saettler, E, Schwendener, MH, Seifert, H, Sweezey, D, Tafirout, R, Virtue, CJ, Beck, DN, Chan, YD, Chen, X, Dragowsky, MR, Dycus, FW, Gonzalez, J, Isaac, MCP, Kajiyama, Y, Koehler, GW, Lesko, KT, Moebus, MC, Norman, EB, Okada, CE, Poon, AWP, Purgalis, P, Schuelke, A, Smith, AR, Stokstad, RG, Turner, S, Zlimen, I, Anaya, JM, Bowles, TJ, Brice, SJ, Esch, EI, Fowler, MM, Goldschmidt, A, Hime, A, McGirt, AF, Miller, GG, Teasdale, WA, Wilhelmy, JB, Wouters, JM, Anglin, JD, Bercovitch, M, Davidson, WF, Storey, RS, Biller, S, Black, RA, Boardman, RJ, Bowler, MG, Cameron, J, Cleveland, B, Ferraris, AP, Doucas, G, Heron, H, Howard, C, Jelley, NA, Knox, AB, Lay, M, Locke, W, Lyon, J, Majerus, S, Moorhead, M, Omori, M, Tanner, NW, Taplin, RK, Thorman, M, Wark, DL, West, N, Barton, JC, Trent, PT, Kouzes, R, Lowry, MM, Bell, AL, Bonvin, E, Boulay, M, Dayon, M, Duncan, F, Erhardt, LS, Evans, HC, Ewan, GT, Ford, R, Hallin, A, Hamer, A, Hart, PM, Harvey, PJ, Haslip, D, Hearns, CAW, Heaton, R, Hepburn, JD, Jillings, CJ, Korpach, EP, Lee, HW, Leslie, JR, Liu, MQ, Mak, HB, McDonald, AB, MacArthur, JD, McLatchie, W, Moffat, BA, Noel, S, Radcliffe, TJ, Robertson, BC, Skensved, P, Stevenson, RL, Zhu, X, Gil, S, Heise, J, Helmer, RL, Komar, RJ, Nally, CW, Ng, HS, Waltham, CE, Allen, RC, Buhler, G, Chen, HH, Aardsma, G, Andersen, T, Cameron, K, Chon, MC, Hanson, RH, Jagam, P, Karn, J, Law, J, Ollerhead, RW, Simpson, JJ, Tagg, N, Wang, JX, Alexander, C, Beier, EW, Cook, JC, Cowen, DF, Frank, ED, Frati, W, Keener, PT, Klein, JR, Mayers, G, McDonald, DS, Neubauer, MS, Newcomer, FM, Pearce, RJ, Van de Water, RG, Van Berg, R, Wittich, P, Ahmad, QR, Beck, JM, Browne, MC, Burritt, TH, Doe, PJ, Duba, CA, Elliott, SR, Franklin, JE, Germani, JV, Green, P, Hamian, AA, Heeger, KM, Howe, M, Drees, RM, Myers, A, Robertson, RGH, Smith, MWE, Steiger, TD, Van Wechel, T, Wilkerson, JF, and Collaboration, SNO

Subjects
Nuclear and High Energy Physics, Physics - Instrumentation and Detectors, Physics::Instrumentation and Detectors, Solar neutrino, Astrophysics::High Energy Astrophysical Phenomena, FOS: Physical sciences, Astrophysics, 7. Clean energy, 01 natural sciences, High Energy Physics - Experiment, High Energy Physics - Experiment (hep-ex), High Energy Physics - Phenomenology (hep-ph), 0103 physical sciences, Nuclear Experiment (nucl-ex), Nuclear Experiment, 010306 general physics, Neutrino oscillation, Instrumentation, Physics, Standard solar model, Sudbury Neutrino Observatory, 010308 nuclear & particles physics, Astrophysics (astro-ph), High Energy Physics::Phenomenology, Instrumentation and Detectors (physics.ins-det), High Energy Physics - Phenomenology, Neutrino detector, High Energy Physics::Experiment, Neutrino, Electron neutrino, Lepton
Abstract

The Sudbury Neutrino Observatory is a second generation water Cherenkov detector designed to determine whether the currently observed solar neutrino deficit is a result of neutrino oscillations. The detector is unique in its use of D2O as a detection medium, permitting it to make a solar model-independent test of the neutrino oscillation hypothesis by comparison of the charged- and neutral-current interaction rates. In this paper the physical properties, construction, and preliminary operation of the Sudbury Neutrino Observatory are described. Data and predicted operating parameters are provided whenever possible., 58 pages, 12 figures, submitted to Nucl. Inst. Meth. Uses elsart and epsf style files. For additional information about SNO see http://www.sno.phy.queensu.ca . This version has some new references

Published
2000

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