Precision Measurement of the Weak Mixing Angle in Moller Scattering

We report on a precision measurement of the parity-violating asymmetry in fixed target electron-electron (Moller) scattering: A_PV = -131 +/- 14 (stat.) +/- 10 (syst.) parts per billion, leading to the determination of the weak mixing angle \sin^2\theta_W^eff = 0.2397 +/- 0.0010 (stat.) +/- 0.0008 (syst.), evaluated at Q^2 = 0.026 GeV^2. Combining this result with the measurements of \sin^2\theta_W^eff at the Z^0 pole, the running of the weak mixing angle is observed with over 6 sigma significance. The measurement sets constraints on new physics effects at the TeV scale.Comment: 4 pages, 2 postscript figues, submitted to Physical Review Letter

Removing krypton from xenon by cryogenic distillation to the ppq level

The XENON1T experiment aims for the direct detection of dark matter in a cryostat filled with 3.3 tons of liquid xenon. In order to achieve the desired sensitivity, the background induced by radioactive decays inside the detector has to be sufficiently low. One major contributor is the $\beta$-emitter $^{85}$Kr which is an intrinsic contamination of the xenon. For the XENON1T experiment a concentration of natural krypton in xenon $\rm{^{nat}}$Kr/Xe < 200 ppq (parts per quadrillion, 1 ppq = 10$^{-15}$ mol/mol) is required. In this work, the design of a novel cryogenic distillation column using the common McCabe-Thiele approach is described. The system demonstrated a krypton reduction factor of 6.4$\cdot$10$^5$ with thermodynamic stability at process speeds above 3 kg/h. The resulting concentration of $\rm{^{nat}}$Kr/Xe < 26 ppq is the lowest ever achieved, almost one order of magnitude below the requirements for XENON1T and even sufficient for future dark matter experiments using liquid xenon, such as XENONnT and DARWIN

Lowering the radioactivity of the photomultiplier tubes for the XENON1T dark matter experiment

The low-background, VUV-sensitive 3-inch diameter photomultiplier tube R11410 has been developed by Hamamatsu for dark matter direct detection experiments using liquid xenon as the target material. We present the results from the joint effort between the XENON collaboration and the Hamamatsu company to produce a highly radio-pure photosensor (version R11410-21) for the XENON1T dark matter experiment. After introducing the photosensor and its components, we show the methods and results of the radioactive contamination measurements of the individual materials employed in the photomultiplier production. We then discuss the adopted strategies to reduce the radioactivity of the various PMT versions. Finally, we detail the results from screening 216 tubes with ultra-low background germanium detectors, as well as their implications for the expected electronic and nuclear recoil background of the XENON1T experiment.Comment: 10 pages, 5 figure

Search for Two-Neutrino Double Electron Capture of 124^{124}Xe with XENON100

Two-neutrino double electron capture is a rare nuclear decay where two electrons are simultaneously captured from the atomic shell. For $^{124}$Xe this process has not yet been observed and its detection would provide a new reference for nuclear matrix element calculations. We have conducted a search for two-neutrino double electron capture from the K-shell of $^{124}$Xe using 7636 kg$\cdot$d of data from the XENON100 dark matter detector. Using a Bayesian analysis we observed no significant excess above background, leading to a lower 90 % credibility limit on the half-life $T_{1/2}>6.5\times10^{20}$ yr. We also evaluated the sensitivity of the XENON1T experiment, which is currently being commissioned, and find a sensitivity of $T_{1/2}>6.1\times10^{22}$ yr after an exposure of 2 t$\cdot$yr.Comment: 6 pages, 4 figure

Search for Event Rate Modulation in XENON100 Electronic Recoil Data

We have searched for periodic variations of the electronic recoil event rate in the (2-6) keV energy range recorded between February 2011 and March 2012 with the XENON100 detector, adding up to 224.6 live days in total. Following a detailed study to establish the stability of the detector and its background contributions during this run, we performed an un-binned profile likelihood analysis to identify any periodicity up to 500 days. We find a global significance of less than 1 sigma for all periods suggesting no statistically significant modulation in the data. While the local significance for an annual modulation is 2.8 sigma, the analysis of a multiple-scatter control sample and the phase of the modulation disfavor a dark matter interpretation. The DAMA/LIBRA annual modulation interpreted as a dark matter signature with axial-vector coupling of WIMPs to electrons is excluded at 4.8 sigma.Comment: 6 pages, 4 figure

Radio Astronomy

Contains table of contents for Section 4 and reports on nine research projects.National Science Foundation Grant AST 88-19848National Science Foundation Grant AST 90-22501Alfred P. Sloan FellowshipNational Science Foundation Presidential Young Investigator AwardNational Aeronautics and Space Administration Grant NAGW-2310David and Lucile Packard FellowshipSM Systems and Research CorporationNational Aeronautics and Space Administration/Goddard Space Flight Center Contract NAS 5-30791National Aeronautics and Space Administration/Goddard Space Flight Center Grant NAG5-10Leaders for Manufacturing Progra

BIOSCAN-5M:A Multimodal Dataset for Insect Biodiversity

As part of an ongoing worldwide effort to comprehend and monitor insect biodiversity, this paper presents the BIOSCAN-5M Insect dataset to the machine learning community and establish several benchmark tasks. BIOSCAN-5M is a comprehensive dataset containing multi-modal information for over 5 million insect specimens, and it significantly expands existing image-based biological datasets by including taxonomic labels, raw nucleotide barcode sequences, assigned barcode index numbers, geographical, and size information. We propose three benchmark experiments to demonstrate the impact of the multi-modal data types on the classification and clustering accuracy. First, we pretrain a masked language model on the DNA barcode sequences of the BIOSCAN-5M dataset, and demonstrate the impact of using this large reference library on species- and genus-level classification performance. Second, we propose a zero-shot transfer learning task applied to images and DNA barcodes to cluster feature embeddings obtained from self-supervised learning, to investigate whether meaningful clusters can be derived from these representation embeddings. Third, we benchmark multi-modality by performing contrastive learning on DNA barcodes, image data, and taxonomic information. This yields a general shared embedding space enabling taxonomic classification using multiple types of information and modalities. The code repository of the BIOSCAN-5M Insect dataset is available at https://github.com/bioscan-ml/BIOSCAN-5M