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Title: Results of the Search for eV-scale sterile neutrinos with 7.5 years of DeepCore data
{"Abstract":["Results of the Search for eV-scale sterile neutrinos with the DeepCore "golden" sample in machine readable format. Allows reproduction of Figure 5 of the publication.\n\n<ul>\n<li> The file "wilks_contour_90pct.csv" contains the 90% contour line in CSV format. The columns "U\\mu4_sq" and "U\\tau4_sq" correspond to the _squared_ elements of the 3+1 mixing matrix, |U_{μ4}|^2 and |U_{τ4}|^2, respectively. The contour was drawn assuming that Wilks' theorem holds with two degrees of freedom. The points are ordered by nearest neighbors. </li>\n<li> The file "expected_sensitivity_90pct.csv" contains the expected sensitivity at 90% CL of the analysis for Asimov data produced at the null hypothesis. The format is identical to that of the result. </li>\n<li> The files "marginalized_umu4_sq.csv" and "marginalized_utau4_sq.csv" contain the marginalized scan of the test statistic over the matrix elements. The column "Metric Difference" refers to the delta chi-square metric used in the analysis. Since this metric is a delta chi-square (rather than a likelihood), it should _not_ be multiplied by two when calculating significances. They allow reproduction of the top and right panels of Figure 5 of the publication. </li>\n<li> The file "real_data_wilks_contours_reprod_mar_2025_best_fit_points.tab" contains the best-fit values of all free nuisance parameters in a |U_{μ4}|^2 and |U_{τ4}|^2 scan. </li>\n<li> The file "real_data_wilks_contours_reprod_mar_2025_metric_diff.tab" contains the \\chi^2 difference between the scan point and the global best-fit in a |U_{μ4}|^2 and |U_{τ4}|^2 scan. </li>\n</ul>"]} more »« less
{"Abstract":["Data and plotting scripts for reproducing plots from "Physics potential of the IceCube Upgrade for atmospheric neutrino oscillations". Please refer to the related publication for a detailed explanation of the sample and analysis.\n<br><br>\nContents: \n<ol>\n<li> <code>README.md</code> contains useful information about the contents of this data release.</li>\n<li> <code>example.py</code> Example script demonstrating how to load the csv files, plot the chi squared map, and extract the 90% sensitivity contours shown in Figures 11 and 15.</li>\n<li> <code>modchi2map_nufitwoSK.csv</code> chi2 map used to produce Figure 11 (left), in which the injected truth point is the best fit point from <a href="http://www.nu-fit.org/sites/default/files/v52.tbl-parameters.pdf">NuFit 5.2 w/o SK (upper panel)</a>, sin<sup>2</sup>(θ<sub>23</sub>)=0.572 and Δm<sup>2</sup><sub>32</sub>=2.43×10<sup>-3</sup> eV<sup>2</sup>.</li>\n<li> <code>modchi2map_nufitwSK.csv</code> chi2 map used to produce Figure 11 (right), in which the injected truth point is the best fit point from <a href="http://www.nu-fit.org/sites/default/files/v52.tbl-parameters.pdf">NuFit 5.2 w/ SK (lower panel)</a>, sin<sup>2</sup>(θ<sub>23</sub>)=0.451 and Δm<sup>2</sup><sub>32</sub>=2.43×10<sup>-3</sup> eV<sup>2</sup>.</li>\n<li> <code>modchi2map_icecube.csv</code> chi2 map used to produce Figure 15, in which the injected truth point is the best fit point from the latest published IceCube DeepCore oscillation result <a href="https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.134.091801">Phys. Rev. Lett. 134, 091801 (2025)</a>, sin<sup>2</sup>(θ<sub>23</sub>)=0.54 and Δm<sup>2</sup><sub>32</sub>=2.40×10<sup>-3</sup> eV<sup>2</sup>.</li>\n</ol>\n\nPlease note: The CSV files are available for download through dataverse in either csv or tab format."]}
<h1 id="summary">Summary</h1> <p>Title: Data Release for A search for extremely-high-energy neutrinos and first constraints on the ultra-high-energy cosmic-ray proton fraction with IceCube</p> <p>The IceCube observatory analyzed 12.6 years of data in search of extremely-high-energy (EHE) neutrinos above 5 PeV. The resultant limit of the search (Fig 1), and the effective area of the event selection (Fig 7), are provided in this data release.</p> <h1 id="contents">Contents</h1> <ul> <li><p>README file: this file</p> </li> <li><p><code>differential_limit_and_sensitivity.csv</code>: a comma separated value file, giving the observed experimental differential limit, and sensitivity, of the search as a function of neutrino energy. This is the content of Fig 1 in the paper. The first column is the neutrino energy in GeV. The second column is the limit in units of GeV/cm2/s/sr. The third column is the sensitivity in units of GeV/cm2/s/sr.</p> </li> <li><p><code>effective_area.csv</code>: a comma separated value file, giving the effective area of the search as a function of energy. This is the content of Fig 7 in the paper. The first column is the neutrino energy in GeV. The second column is the total effective area of the search, summed across neutrino flavors, and averaged across neutrinos and antineutrinos, in meters-squared. The third column is the effective area of the search for the average of electron neutrino and electron antineutrinos in units of meters-squared. The fourth column is the same as the third, but for muon-flavor neutrinos. The fifth column is the same as the third and fourth, but for tau-flavor neutrinos.</p> </li> <li><p><code>demo.py</code>: a short python script to demonstrate how to read the files. Run like <code>python demo.py</code>. A standard base python installation is sufficient, as the only dependencies are numpy and matplotlib.</p> </li> </ul> <h1 id="contacts">Contacts</h1> <p>For any questions about this data release, please write to analysis@icecube.wisc.edu</p>
{"Abstract":["Data files were used in support of the research paper titled \u201cMitigating RF Jamming Attacks at the Physical Layer with Machine Learning<\/em>" which has been submitted to the IET Communications journal.<\/p>\n\n---------------------------------------------------------------------------------------------<\/p>\n\nAll data was collected using the SDR implementation shown here: https://github.com/mainland/dragonradio/tree/iet-paper. Particularly for antenna state selection, the files developed for this paper are located in 'dragonradio/scripts/:'<\/p>\n\n'ModeSelect.py': class used to defined the antenna state selection algorithm<\/li>'standalone-radio.py': SDR implementation for normal radio operation with reconfigurable antenna<\/li>'standalone-radio-tuning.py': SDR implementation for hyperparameter tunning<\/li>'standalone-radio-onmi.py': SDR implementation for omnidirectional mode only<\/li><\/ul>\n\n---------------------------------------------------------------------------------------------<\/p>\n\nAuthors: Marko Jacovic, Xaime Rivas Rey, Geoffrey Mainland, Kapil R. Dandekar\nContact: krd26@drexel.edu<\/p>\n\n---------------------------------------------------------------------------------------------<\/p>\n\nTop-level directories and content will be described below. Detailed descriptions of experiments performed are provided in the paper.<\/p>\n\n---------------------------------------------------------------------------------------------<\/p>\n\nclassifier_training: files used for training classifiers that are integrated into SDR platform<\/p>\n\n'logs-8-18' directory contains OTA SDR collected log files for each jammer type and under normal operation (including congested and weaklink states)<\/li>'classTrain.py' is the main parser for training the classifiers<\/li>'trainedClassifiers' contains the output classifiers generated by 'classTrain.py'<\/li><\/ul>\n\npost_processing_classifier: contains logs of online classifier outputs and processing script<\/p>\n\n'class' directory contains .csv logs of each RTE and OTA experiment for each jamming and operation scenario<\/li>'classProcess.py' parses the log files and provides classification report and confusion matrix for each multi-class and binary classifiers for each observed scenario - found in 'results->classifier_performance'<\/li><\/ul>\n\npost_processing_mgen: contains MGEN receiver logs and parser<\/p>\n\n'configs' contains JSON files to be used with parser for each experiment<\/li>'mgenLogs' contains MGEN receiver logs for each OTA and RTE experiment described. Within each experiment logs are separated by 'mit' for mitigation used, 'nj' for no jammer, and 'noMit' for no mitigation technique used. File names take the form *_cj_* for constant jammer, *_pj_* for periodic jammer, *_rj_* for reactive jammer, and *_nj_* for no jammer. Performance figures are found in 'results->mitigation_performance'<\/li><\/ul>\n\nray_tracing_emulation: contains files related to Drexel area, Art Museum, and UAV Drexel area validation RTE studies.<\/p>\n\nDirectory contains detailed 'readme.txt' for understanding.<\/li>Please note: the processing files and data logs present in 'validation' folder were developed by Wolfe et al. and should be cited as such, unless explicitly stated differently. \n\tS. Wolfe, S. Begashaw, Y. Liu and K. R. Dandekar, "Adaptive Link Optimization for 802.11 UAV Uplink Using a Reconfigurable Antenna," MILCOM 2018 - 2018 IEEE Military Communications Conference (MILCOM), 2018, pp. 1-6, doi: 10.1109/MILCOM.2018.8599696.<\/li><\/ul>\n\t<\/li><\/ul>\n\nresults: contains results obtained from study<\/p>\n\n'classifier_performance' contains .txt files summarizing binary and multi-class performance of online SDR system. Files obtained using 'post_processing_classifier.'<\/li>'mitigation_performance' contains figures generated by 'post_processing_mgen.'<\/li>'validation' contains RTE and OTA performance comparison obtained by 'ray_tracing_emulation->validation->matlab->outdoor_hover_plots.m'<\/li><\/ul>\n\ntuning_parameter_study: contains the OTA log files for antenna state selection hyperparameter study<\/p>\n\n'dataCollect' contains a folder for each jammer considered in the study, and inside each folder there is a CSV file corresponding to a different configuration of the learning parameters of the reconfigurable antenna. The configuration selected was the one that performed the best across all these experiments and is described in the paper.<\/li>'data_summary.txt'this file contains the summaries from all the CSV files for convenience.<\/li><\/ul>"]}
{"Abstract":["A biodiversity dataset graph: DataONE<\/p>\n\nThe intended use of this archive is to facilitate meta-analysis of the Data Observation Network for Earth (DataONE, [1]). DataONE is a distributed infrastructure that provides information about earth observation data. <\/p>\n\nThis dataset provides versioned snapshots of the DataONE network as tracked by Preston [2] between 17 October 2018 and 7 July 2019. <\/p>\n\nThe archive consists of 256 individual parts (e.g., preston-00.tar.gz, preston-01.tar.gz, ...) to allow for parallel file downloads. The archive contains three types of files: index files, provenance files and data files. Only two index and provenance files are included and have been individually included in this dataset publication. Index files provide a way to links provenance files in time to eestablish a versioning mechanism. Provenance files describe how, when and where the DataONE meta-data files were retrieved. For more information, please visit https://preston.guoda.bio or https://doi.org/10.5281/zenodo.1410543). <\/p>\n\nTo retrieve and verify the downloaded DataONE biodiversity dataset graph, first concatenate all the downloaded preston-*.tar.gz files (e.g., cat preston-*.tar.gz > preston.tar.gz). Then, extract the archives into a "data" folder. Alternatively, you can use the preston[2] command-line tool to "clone" this dataset using:<\/p>\n\n$$ java -jar preston.jar clone --remote https://zenodo.org/record/3277312/files<\/p>\n\nAfter that, verify the index of the archive by reproducing the following result:<\/p>\n\n$$ java -jar preston.jar history\n<0659a54f-b713-4f86-a917-5be166a14110> <http://purl.org/pav/hasVersion> <hash://sha256/8c67e0741d1c90db54740e08d2e39d91dfd73566ea69c1f2da0d9ab9780a9a9f> .\n<hash://sha256/3ed3acaca7ac57f546d0b8877c1927ab5e08c23eccaa8219600c59c77a72c685> <http://purl.org/pav/previousVersion> <hash://sha256/8c67e0741d1c90db54740e08d2e39d91dfd73566ea69c1f2da0d9ab9780a9a9f> .\n<hash://sha256/857753997a7595a1b372b05641b58a25d9408b7ff08d557ce1fe8b73e4bd383f> <http://purl.org/pav/previousVersion> <hash://sha256/3ed3acaca7ac57f546d0b8877c1927ab5e08c23eccaa8219600c59c77a72c685> .\n<hash://sha256/7ee0376f4c3f7aeeda36927a5211395e5da8201e810e8c7e638a0fe23d001e88> <http://purl.org/pav/previousVersion> <hash://sha256/857753997a7595a1b372b05641b58a25d9408b7ff08d557ce1fe8b73e4bd383f> .\n<hash://sha256/68b4974d8ab7c4c7a7a4305065839b60ba460aaa862590b34c67877738feba90> <http://purl.org/pav/previousVersion> <hash://sha256/7ee0376f4c3f7aeeda36927a5211395e5da8201e810e8c7e638a0fe23d001e88> .\n<hash://sha256/060a76d56255bf9482c951748c91291fddeeb20f180632132be1344e081b2372> <http://purl.org/pav/previousVersion> <hash://sha256/68b4974d8ab7c4c7a7a4305065839b60ba460aaa862590b34c67877738feba90> .\n<hash://sha256/29357bdfab4548025f8a5743301f5c3c9146fa436c39e3c9e019fb9409ac9c42> <http://purl.org/pav/previousVersion> <hash://sha256/060a76d56255bf9482c951748c91291fddeeb20f180632132be1344e081b2372> .\n<hash://sha256/3669cd95100d1d533eb8953ff4ec5092cbd8addb8879b3e6262191148a8a3ebb> <http://purl.org/pav/previousVersion> <hash://sha256/29357bdfab4548025f8a5743301f5c3c9146fa436c39e3c9e019fb9409ac9c42> .\n<hash://sha256/8dc1663299359d271cb1b4c14ad521d0f1be67743689dd18016543dc1e097efb> <http://purl.org/pav/previousVersion> <hash://sha256/3669cd95100d1d533eb8953ff4ec5092cbd8addb8879b3e6262191148a8a3ebb> .\n<hash://sha256/dc4903e8afee651db1d9bf509f20503bf9c8e89679c4bcffb46d5b97440cb6de> <http://purl.org/pav/previousVersion> <hash://sha256/8dc1663299359d271cb1b4c14ad521d0f1be67743689dd18016543dc1e097efb> .<\/p>\n\nTo check the integrity of the extracted archive, confirm that each line produce by the command "preston verify" produces lines as shown below, with each line including "CONTENT_PRESENT_VALID_HASH". Depending on hardware capacity, this may take a while.<\/p>\n\n$ java -jar preston.jar verify\nhash://sha256/e55c1034d985740926564e94decd6dc7a70f779a33e7deb931553739cda16945 file:/home/preston/preston-dataone/data/e5/5c/e55c1034d985740926564e94decd6dc7a70f779a33e7deb931553739cda16945 OK CONTENT_PRESENT_VALID_HASH 21580\nhash://sha256/d0ddcc2111b6134a570bcc7d89375920ef4d754130cecc0727c79d2b05a9f81f file:/home/preston/preston-dataone/data/d0/dd/d0ddcc2111b6134a570bcc7d89375920ef4d754130cecc0727c79d2b05a9f81f OK CONTENT_PRESENT_VALID_HASH 2035\nhash://sha256/472de9d1c9fd7e044aac409abfbfff9f12c6b69359df995d431009580ffb0f53 file:/home/preston/preston-dataone/data/47/2d/472de9d1c9fd7e044aac409abfbfff9f12c6b69359df995d431009580ffb0f53 OK CONTENT_PRESENT_VALID_HASH 1935\nhash://sha256/b29879462cd43862129c5cf9b149c41ecd33ffef284a4dbea4ac1c0f90108687 file:/home/preston/preston-dataone/data/b2/98/b29879462cd43862129c5cf9b149c41ecd33ffef284a4dbea4ac1c0f90108687 OK CONTENT_PRESENT_VALID_HASH 1553<\/p>\n\nNote that a copy of the java program "preston", preston.jar, is included in this publication. The program runs on java 8+ virtual machine using "java -jar preston.jar", or in short "preston". <\/p>\n\nFiles in this data publication:<\/p>\n\nREADME - this file<\/p>\n\npreston.jar - executable java jar containing preston[2] v0.1.1.<\/p>\n\npreston-[00-ff].tar.gz - preston archives containing DataONE meta-data files, their provenance and a provenance index.<\/p>\n\n2a5de79372318317a382ea9a2cef069780b852b01210ef59e06b640a3539cb5a - preston index file\n2aecaf289def0e23a27058bf7715f226ef9189905f0be13228174825633125cf - preston index file\n3d38b70198e448674be6a63d14b9817f3a956f48bba7418fa7baa086a56c05b7 - preston index file\n66ad3e5e904740f1e835ac6718dda4279e0c24b204ea0d1113cda1352a5072ba - preston index file\n8bf062872ce958545d361e9d53a552ffb025ac29ab875caad1157c0995d34f66 - preston index file\nd9378616636be3686bbabd5bf29d50f0ef0e5ceb5ddd7dfce47f7e755b596b7d - preston index file\nda26fa6e7371385ed3f61af9a766221c833060d59dfd4869bbd7110f95f288db - preston index file\ne4103a75627857de3ee2e317429108611c244fc448c01d1d7bf652115c3b8a55 - preston index file\neb368fedb8f100210dd968edcf80f4d13cab3dd64135a6ab744102cf15e68c94 - preston index file\nff92b6c06ae5286bd2f1db679e0fcc4da294acb9bc01b2e9522378d99218c2e3 - preston index file<\/p>\n\n[1] DataONE, https://www.dataone.org\n[2] https://preston.guoda.bio, https://doi.org/10.5281/zenodo.1410543 . DataONE was crawled via Preston with "preston update -u https://dataone.org".<\/p>\n\nThis work is funded in part by grant NSF OAC 1839201 from the National Science Foundation<\/p>"]}
{"Abstract":["A biodiversity dataset graph: BHL<\/p>\n\nThe intended use of this archive is to facilitate (meta-)analysis of the Biodiversity Heritage Library (BHL). The Biodiversity Heritage Library improves research methodology by collaboratively making biodiversity literature openly available to the world as part of a global biodiversity community.<\/p>\n\nThis dataset provides versioned snapshots of the BHL network as tracked by Preston [2] between 2019-05-19 and 2020-05-09 using "preston update -u https://biodiversitylibrary.org".<\/p>\n\nThe archive consists of 256 individual parts (e.g., preston-00.tar.gz, preston-01.tar.gz, ...) to allow for parallel file downloads. The archive contains three types of files: index files, provenance logs and data files. In addition, index files have been individually included in this dataset publication to facilitate remote access. Index files provide a way to links provenance files in time to establish a versioning mechanism. Provenance files describe how, when, what and where the BHL content was retrieved. For more information, please visit https://preston.guoda.bio or https://doi.org/10.5281/zenodo.1410543 . <\/p>\n\nTo retrieve and verify the downloaded BHL biodiversity dataset graph, first concatenate all the downloaded preston-*.tar.gz files (e.g., cat preston-*.tar.gz > preston.tar.gz). Then, extract the archives into a "data" folder. Alternatively, you can use the preston[2] command-line tool to "clone" this dataset using:<\/p>\n\n$$ java -jar preston.jar clone --remote https://zenodo.org/record/3849560/files<\/p>\n\nAfter that, verify the index of the archive by reproducing the following provenance log history:<\/p>\n\n$$ java -jar preston.jar history\n<0659a54f-b713-4f86-a917-5be166a14110> <http://purl.org/pav/hasVersion> <hash://sha256/89926f33157c0ef057b6de73f6c8be0060353887b47db251bfd28222f2fd801a> .\n<hash://sha256/41b19aa9456fc709de1d09d7a59c87253bc1f86b68289024b7320cef78b3e3a4> <http://purl.org/pav/previousVersion> <hash://sha256/89926f33157c0ef057b6de73f6c8be0060353887b47db251bfd28222f2fd801a> .\n<hash://sha256/7582d5ba23e0d498ca4f55c29408c477d0d92b4fdcea139e8666f4d78c78a525> <http://purl.org/pav/previousVersion> <hash://sha256/41b19aa9456fc709de1d09d7a59c87253bc1f86b68289024b7320cef78b3e3a4> .\n<hash://sha256/a70774061ccded1a45389b9e6063eb3abab3d42813aa812391f98594e7e26687> <http://purl.org/pav/previousVersion> <hash://sha256/7582d5ba23e0d498ca4f55c29408c477d0d92b4fdcea139e8666f4d78c78a525> .\n<hash://sha256/007e065ba4b99867751d688754aa3d33fa96e6e03133a2097e8a368d613cd93a> <http://purl.org/pav/previousVersion> <hash://sha256/a70774061ccded1a45389b9e6063eb3abab3d42813aa812391f98594e7e26687> .\n<hash://sha256/4fb4b4d8f1ae2961311fb0080e817adb2faa746e7eae15249a3772fbe2d662a1> <http://purl.org/pav/previousVersion> <hash://sha256/007e065ba4b99867751d688754aa3d33fa96e6e03133a2097e8a368d613cd93a> .\n<hash://sha256/67cc329e74fd669945f503917fbb942784915ab7810ddc41105a82ebe6af5482> <http://purl.org/pav/previousVersion> <hash://sha256/4fb4b4d8f1ae2961311fb0080e817adb2faa746e7eae15249a3772fbe2d662a1> .\n<hash://sha256/e46cd4b0d7fdb51ea789fa3c5f7b73591aca62d2d8f913346d71aa6cf0745c9f> <http://purl.org/pav/previousVersion> <hash://sha256/67cc329e74fd669945f503917fbb942784915ab7810ddc41105a82ebe6af5482> .\n<hash://sha256/9215d543418a80510e78d35a0cfd7939cc59f0143d81893ac455034b5e96150a> <http://purl.org/pav/previousVersion> <hash://sha256/e46cd4b0d7fdb51ea789fa3c5f7b73591aca62d2d8f913346d71aa6cf0745c9f> .\n<hash://sha256/1448656cc9f339b4911243d7c12f3ba5366b54fff3513640306682c50f13223d> <http://purl.org/pav/previousVersion> <hash://sha256/9215d543418a80510e78d35a0cfd7939cc59f0143d81893ac455034b5e96150a> .\n<hash://sha256/7ee6b16b7a5e9b364776427d740332d8552adf5041d48018eeb3c0e13ccebf27> <http://purl.org/pav/previousVersion> <hash://sha256/1448656cc9f339b4911243d7c12f3ba5366b54fff3513640306682c50f13223d> .\n<hash://sha256/34ccd7cf7f4a1ea35ac6ae26a458bb603b2f6ee8ad36e1a58aa0261105d630b1> <http://purl.org/pav/previousVersion> <hash://sha256/7ee6b16b7a5e9b364776427d740332d8552adf5041d48018eeb3c0e13ccebf27> .<\/p>\n\nTo check the integrity of the extracted archive, confirm that each line produce by the command "preston verify" produces lines as shown below, with each line including "CONTENT_PRESENT_VALID_HASH". Depending on hardware capacity, this may take a while.<\/p>\n\n$ java -jar preston.jar verify\nhash://sha256/e0c131ebf6ad2dce71ab9a10aa116dcedb219ae4539f9e5bf0e57b84f51f22ca file:/home/preston/preston-bhl/data/e0/c1/e0c131ebf6ad2dce71ab9a10aa116dcedb219ae4539f9e5bf0e57b84f51f22ca OK CONTENT_PRESENT_VALID_HASH 49458087 hash://sha256/e0c131ebf6ad2dce71ab9a10aa116dcedb219ae4539f9e5bf0e57b84f51f22ca\nhash://sha256/1a57e55a780b86cff38697cf1b857751ab7b389973d35113564fe5a9a58d6a99 file:/home/preston/preston-bhl/data/1a/57/1a57e55a780b86cff38697cf1b857751ab7b389973d35113564fe5a9a58d6a99 OK CONTENT_PRESENT_VALID_HASH 25745 hash://sha256/1a57e55a780b86cff38697cf1b857751ab7b389973d35113564fe5a9a58d6a99\nhash://sha256/85efeb84c1b9f5f45c7a106dd1b5de43a31b3248a211675441ff584a7154b61c file:/home/preston/preston-bhl/data/85/ef/85efeb84c1b9f5f45c7a106dd1b5de43a31b3248a211675441ff584a7154b61c OK CONTENT_PRESENT_VALID_HASH 519892 hash://sha256/85efeb84c1b9f5f45c7a106dd1b5de43a31b3248a211675441ff584a7154b61c\nhash://sha256/251e5032afce4f1e44bfdc5a8f0316ca1b317e8af41bdbf88163ab5bd2b52743 file:/home/preston/preston-bhl/data/25/1e/251e5032afce4f1e44bfdc5a8f0316ca1b317e8af41bdbf88163ab5bd2b52743 OK CONTENT_PRESENT_VALID_HASH 787414 hash://sha256/251e5032afce4f1e44bfdc5a8f0316ca1b317e8af41bdbf88163ab5bd2b52743<\/p>\n\nNote that a copy of the java program "preston", preston.jar, is included in this publication. The program runs on java 8+ virtual machine using "java -jar preston.jar", or in short "preston".<\/p>\n\nFiles in this data publication:<\/p>\n\n--- start of file descriptions ---<\/p>\n\n-- description of archive and its contents (this file) --\nREADME<\/p>\n\n-- executable java jar containing preston[2] v0.1.15. --\npreston.jar<\/p>\n\n-- preston archives containing BHL data files, associated provenance logs and a provenance index --\npreston-[00-ff].tar.gz<\/p>\n\n-- individual provenance index files --\n2a5de79372318317a382ea9a2cef069780b852b01210ef59e06b640a3539cb5a\n2b1104cb7749e818c9afca78391b2d0099bbb0a32f2b348860a335cd2f8f6800\n4081bc59dff58d63f6a86c623cb770f01e9a355a42495b205bcb538cd526190f\n47a2816f8b5600b24487093adcddfea12434cc4f270f3ab09d9215fbdd546cd2\n6f99a1388823fca745c9e22ac21e2da909a219aa1ace55170fa9248c0276903c\n7ae46d7cd9b5a0f5889ba38bac53c82e591b0bdf8b605f5e48c0dce8fb7b717f\n82903464889fea7c53f53daedf4e41fa31092f82619edeb3415eb2b473f74af3\n9e8c86243df39dd4fe82a3f814710eccf73aa9291d050415408e346fa2b09e70\na8308fbf4530e287927c471d881ce0fc852f16543d46e1ee26f1caba48815f3a\nbcec6df2ea7f74e9a6e2830d0072e6b2fbe65323d9ddb022dd6e1349c23996e2\ncfe47c25ec0210ac73c06b407beb20d9c58355cb15bae427fdc7541870ca2e4e\nf73fc9e70bce8f21f0c96b8ef0903749d8f223f71343ab5a8910968f99c9b8b6<\/p>\n\n--- end of file descriptions ---<\/p>\n\n\nReferences<\/p>\n\n[1] Biodiversity Heritage Library (BHL, https://biodiversitylibrary.org) accessed from 2019-05-19 to 2020-05-09 with provenance hash://sha256/34ccd7cf7f4a1ea35ac6ae26a458bb603b2f6ee8ad36e1a58aa0261105d630b1.\n[2] https://preston.guoda.bio, https://doi.org/10.5281/zenodo.1410543 .<\/p>\n\n\nThis work is funded in part by grant NSF OAC 1839201 from the National Science Foundation.<\/p>"]}
Collaboration, IceCube, and Collaboration, IceCube. Results of the Search for eV-scale sterile neutrinos with 7.5 years of DeepCore data. Web. doi:10.7910/dvn/qkl28z.
Collaboration, IceCube, & Collaboration, IceCube. Results of the Search for eV-scale sterile neutrinos with 7.5 years of DeepCore data. https://doi.org/10.7910/dvn/qkl28z
@article{osti_10668196,
place = {Country unknown/Code not available},
title = {Results of the Search for eV-scale sterile neutrinos with 7.5 years of DeepCore data},
url = {https://par.nsf.gov/biblio/10668196},
DOI = {10.7910/dvn/qkl28z},
abstractNote = {{"Abstract":["Results of the Search for eV-scale sterile neutrinos with the DeepCore "golden" sample in machine readable format. Allows reproduction of Figure 5 of the publication.\n\n\n The file "wilks_contour_90pct.csv" contains the 90% contour line in CSV format. The columns "U\\mu4_sq" and "U\\tau4_sq" correspond to the _squared_ elements of the 3+1 mixing matrix, |U_{μ4}|^2 and |U_{τ4}|^2, respectively. The contour was drawn assuming that Wilks' theorem holds with two degrees of freedom. The points are ordered by nearest neighbors. \n The file "expected_sensitivity_90pct.csv" contains the expected sensitivity at 90% CL of the analysis for Asimov data produced at the null hypothesis. The format is identical to that of the result. \n The files "marginalized_umu4_sq.csv" and "marginalized_utau4_sq.csv" contain the marginalized scan of the test statistic over the matrix elements. The column "Metric Difference" refers to the delta chi-square metric used in the analysis. Since this metric is a delta chi-square (rather than a likelihood), it should _not_ be multiplied by two when calculating significances. They allow reproduction of the top and right panels of Figure 5 of the publication. \n The file "real_data_wilks_contours_reprod_mar_2025_best_fit_points.tab" contains the best-fit values of all free nuisance parameters in a |U_{μ4}|^2 and |U_{τ4}|^2 scan. \n The file "real_data_wilks_contours_reprod_mar_2025_metric_diff.tab" contains the \\chi^2 difference between the scan point and the global best-fit in a |U_{μ4}|^2 and |U_{τ4}|^2 scan. \n"]}},
journal = {},
publisher = {Harvard Dataverse},
author = {Collaboration, IceCube and Collaboration, IceCube},
}
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