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1. Two-neutrino double electron capture of $^{124}$Xe in the first LUX-ZEPLIN exposure

Author

Aalbers, J., Akerib, D. S., Musalhi, A. K. Al, Alder, F., Amarasinghe, C. S., Ames, A., Anderson, T. J., Angelides, N., Araújo, H. M., Armstrong, J. E., Arthurs, M., Baker, A., Balashov, S., Bang, J., Bargemann, J. W., Barillier, E. E., Beattie, K., Bhatti, A., Biekert, A., Biesiadzinski, T. P., Birch, H. J., Bishop, E., Blockinger, G. M., Boxer, B., Brew, C. A. J., Brás, P., Burdin, S., Buuck, M., Carmona-Benitez, M. C., Carter, M., Chawla, A., Chen, H., Chin, Y. T., Chott, N. I., Converse, M. V., Coronel, R., Cottle, A., Cox, G., Curran, D., Dahl, C. E., David, A., Delgaudio, J., Dey, S., de Viveiros, L., Di Felice, L., Ding, C., Dobson, J. E. Y., Druszkiewicz, E., Dubey, S., Eriksen, S. R., Fan, A., Fearon, N. M., Fieldhouse, N., Fiorucci, S., Flaecher, H., Fraser, E. D., Fruth, T. M. A., Gaitskell, R. J., Geffre, A., Genovesi, J., Ghag, C., Gibbons, R., Gokhale, S., Green, J., van der Grinten, M. G. D., Haiston, J. J., Hall, C. R., Han, S., Hartigan-O'Connor, E., Haselschwardt, S. J., Hernandez, M. A., Hertel, S. A., Heuermann, G., Homenides, G. J., Horn, M., Huang, D. Q., Hunt, D., Jacquet, E., James, R. S., Johnson, J., Kaboth, A. C., Kamaha, A. C., Kannichankandy, M., Khaitan, D., Khazov, A., Khurana, I., Kim, J., Kim, Y. D., Kingston, J., Kirk, R., Kodroff, D., Korley, L., Korolkova, E. V., Kraus, H., Kravitz, S., Kreczko, L., Kudryavtsev, V. A., Leonard, D. S., Lesko, K. T., Levy, C., Lin, J., Lindote, A., Lippincott, W. H., Lopes, M. I., Lorenzon, W., Lu, C., Luitz, S., Majewski, P. A., Manalaysay, A., Mannino, R. L., Maupin, C., McCarthy, M. E., McDowell, G., McKinsey, D. N., McLaughlin, J., McLaughlin, J. B., McMonigle, R., Mizrachi, E., Monte, A., Monzani, M. E., Morrison, E., Mount, B. J., Murdy, M., Murphy, A. St. J., Naylor, A., Nelson, H. N., Neves, F., Nguyen, A., O'Brien, C. L., Olcina, I., Oliver-Mallory, K. C., Orpwood, J., Oyulmaz, K. Y, Palladino, K. J., Palmer, J., Pannifer, N. J., Parveen, N., Patton, S. J., Penning, B., Pereira, G., Perry, E., Pershing, T., Piepke, A., Qie, Y., Reichenbacher, J., Rhyne, C. A., Riffard, Q., Rischbieter, G. R. C., Ritchey, E., Riyat, H. S., Rosero, R., Rushton, T., Rynders, D., Santone, D., Sazzad, A. B. M. R., Schnee, R. W., Sehr, G., Shafer, B., Shaw, S., Shutt, T., Silk, J. J., Silva, C., Sinev, G., Siniscalco, J., Smith, R., Solovov, V. N., Sorensen, P., Soria, J., Stevens, A., Stifter, K., Suerfu, B., Sumner, T. J., Szydagis, M., Tiedt, D. R., Timalsina, M., Tong, Z., Tovey, D. R., Tranter, J., Trask, M., Tripathi, M., Vacheret, A., Vaitkus, A. C., Valentino, O., Velan, V., Wang, A., Wang, J. J., Wang, Y., Watson, J. R., Weeldreyer, L., Whitis, T. J., Wild, K., Williams, M., Wisniewski, W. J., Wolf, L., Wolfs, F. L. H., Woodford, S., Woodward, D., Wright, C. J., Xia, Q., Xu, J., Xu, Y., Yeh, M., Yeum, D., Zha, W., and Zweig, E. A.

Subjects
Nuclear Experiment, Physics - Instrumentation and Detectors
Abstract

The broad physics reach of the LUX-ZEPLIN (LZ) experiment covers rare phenomena beyond the direct detection of dark matter. We report precise measurements of the extremely rare decay of $^{124}$Xe through the process of two-neutrino double electron capture (2$\nu$2EC), utilizing a $1.39\,\mathrm{kg} \times \mathrm{yr}$ isotopic exposure from the first LZ science run. A half-life of $T_{1/2}^{2\nu2\mathrm{EC}} = (1.09 \pm 0.14_{\text{stat}} \pm 0.05_{\text{sys}}) \times 10^{22}\,\mathrm{yr}$ is observed with a statistical significance of $8.3\,\sigma$, in agreement with literature. First empirical measurements of the KK capture fraction relative to other K-shell modes were conducted, and demonstrate consistency with respect to recent signal models at the $1.4\,\sigma$ level., Comment: 15 pages, 3 figures

Published
2024

2. Optimizing Checkpoint-Restart Mechanisms for HPC with DMTCP in Containers at NERSC

Author

Timalsina, Madan, Gerhardt, Lisa, Tyler, Nicholas, Blaschke, Johannes P., and Arndt, William

Subjects
Computer Science - Distributed, Parallel, and Cluster Computing, Computer Science - Software Engineering
Abstract

This paper presents an in-depth examination of checkpoint-restart mechanisms in High-Performance Computing (HPC). It focuses on the use of Distributed MultiThreaded CheckPointing (DMTCP) in various computational settings, including both within and outside of containers. The study is grounded in real-world applications running on NERSC Perlmutter, a state-of-the-art supercomputing system. We discuss the advantages of checkpoint-restart (C/R) in managing complex and lengthy computations in HPC, highlighting its efficiency and reliability in such environments. The role of DMTCP in enhancing these workflows, especially in multi-threaded and distributed applications, is thoroughly explored. Additionally, the paper delves into the use of HPC containers, such as Shifter and Podman-HPC, which aid in the management of computational tasks, ensuring uniform performance across different environments. The methods, results, and potential future directions of this research, including its application in various scientific domains, are also covered, showcasing the critical advancements made in computational methodologies through this study., Comment: 9 pages, 4 figures

Published
2024

3. Just read twice: closing the recall gap for recurrent language models

Author

Arora, Simran, Timalsina, Aman, Singhal, Aaryan, Spector, Benjamin, Eyuboglu, Sabri, Zhao, Xinyi, Rao, Ashish, Rudra, Atri, and Ré, Christopher

Subjects
Computer Science - Computation and Language, Computer Science - Machine Learning
Abstract

Recurrent large language models that compete with Transformers in language modeling perplexity are emerging at a rapid rate (e.g., Mamba, RWKV). Excitingly, these architectures use a constant amount of memory during inference. However, due to the limited memory, recurrent LMs cannot recall and use all the information in long contexts leading to brittle in-context learning (ICL) quality. A key challenge for efficient LMs is selecting what information to store versus discard. In this work, we observe the order in which information is shown to the LM impacts the selection difficulty. To formalize this, we show that the hardness of information recall reduces to the hardness of a problem called set disjointness (SD), a quintessential problem in communication complexity that requires a streaming algorithm (e.g., recurrent model) to decide whether inputted sets are disjoint. We empirically and theoretically show that the recurrent memory required to solve SD changes with set order, i.e., whether the smaller set appears first in-context. Our analysis suggests, to mitigate the reliance on data order, we can put information in the right order in-context or process prompts non-causally. Towards that end, we propose: (1) JRT-Prompt, where context gets repeated multiple times in the prompt, effectively showing the model all data orders. This gives $11.0 \pm 1.3$ points of improvement, averaged across $16$ recurrent LMs and the $6$ ICL tasks, with $11.9\times$ higher throughput than FlashAttention-2 for generation prefill (length $32$k, batch size $16$, NVidia H100). We then propose (2) JRT-RNN, which uses non-causal prefix-linear-attention to process prompts and provides $99\%$ of Transformer quality at $360$M params., $30$B tokens and $96\%$ at $1.3$B params., $50$B tokens on average across the tasks, with $19.2\times$ higher throughput for prefill than FA2.

Published
2024

4. Anvil: An integration of artificial intelligence, sampling techniques, and a combined CAD-CFD tool

Author

Vardhan, Harsh, Timalsina, Umesh, Sandborn, Michael, Hyde, David, Volgyesi, Peter, and Sztipanovits, Janos

Subjects
Computer Science - Computational Engineering, Finance, and Science, Computer Science - Machine Learning, Mathematics - Numerical Analysis
Abstract

In this work, we introduce an open-source integrated CAD-CFD tool, Anvil, which combines FreeCAD for CAD modeling and OpenFOAM for CFD analysis, along with an AI-based optimization method (Bayesian optimization) and other sampling algorithms. Anvil serves as a scientific machine learning tool for shape optimization in three modes: data generation, CFD evaluation, and shape optimization. In data generation mode, it automatically runs CFD evaluations and generates data for training a surrogate model. In optimization mode, it searches for the optimal design under given requirements and optimization metrics. In CFD mode, a single CAD file can be evaluated with a single OpenFOAM run. To use Anvil, experimenters provide a JSON configuration file and a parametric CAD seed design. Anvil can be used to study solid-fluid dynamics for any subsonic flow conditions and has been demonstrated in various simulation and optimization use cases. The open-source code for the tool, installation process, artifacts (such as CAD seed designs and example STL models), experimentation results, and detailed documentation can be found at \url{https://github.com/symbench/Anvil}.

Published
2024

5. 3D Gaze Tracking for Studying Collaborative Interactions in Mixed-Reality Environments

Author

Davalos, Eduardo, Zhang, Yike, S., Ashwin T., Fonteles, Joyce H., Timalsina, Umesh, and Biswas, Guatam

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence
Abstract

This study presents a novel framework for 3D gaze tracking tailored for mixed-reality settings, aimed at enhancing joint attention and collaborative efforts in team-based scenarios. Conventional gaze tracking, often limited by monocular cameras and traditional eye-tracking apparatus, struggles with simultaneous data synchronization and analysis from multiple participants in group contexts. Our proposed framework leverages state-of-the-art computer vision and machine learning techniques to overcome these obstacles, enabling precise 3D gaze estimation without dependence on specialized hardware or complex data fusion. Utilizing facial recognition and deep learning, the framework achieves real-time, tracking of gaze patterns across several individuals, addressing common depth estimation errors, and ensuring spatial and identity consistency within the dataset. Empirical results demonstrate the accuracy and reliability of our method in group environments. This provides mechanisms for significant advances in behavior and interaction analysis in educational and professional training applications in dynamic and unstructured environments., Comment: 9 pages, 8 figures, conference, submitted to ICMI 2024

Published
2024

6. Probing the Scalar WIMP-Pion Coupling with the first LUX-ZEPLIN data

Author

Aalbers, J., Akerib, D. S., Musalhi, A. K. Al, Alder, F., Amarasinghe, C. S., Ames, A., Anderson, T. J., Angelides, N., Araújo, H. M., Armstrong, J. E., Arthurs, M., Baker, A., Balashov, S., Bang, J., Barillier, E. E., Bargemann, J. W., Beattie, K., Benson, T., Bhatti, A., Biekert, A., Biesiadzinski, T. P., Birch, H. J., Bishop, E. J., Blockinger, G. M., Boxer, B., Brew, C. A. J., Brás, P., Burdin, S., Buuck, M., Carmona-Benitez, M. C., Carter, M., Chawla, A., Chen, H., Cherwinka, J. J., Chin, Y. T., Chott, N. I., Converse, M. V., Cottle, A., Cox, G., Curran, D., Dahl, C. E., David, A., Delgaudio, J., Dey, S., deViveiros, L., DiFelice, L., Ding, C., Dobson, J. E. Y., Druszkiewicz, E., Eriksen, S. R., Fan, A., Fearon, N. M., Fiorucci, S., Flaecher, H., Fraser, E. D., Fruth, T. M. A., Gaitskell, R. J., Geffre, A., Genovesi, J., Ghag, C., Gibbons, R., Gokhale, S., Green, J., vanderGrinten, M. G. D., Haiston, J. J., Hall, C. R., Han, S., Hartigan-O'Connor, E., Haselschwardt, S. J., Hernandez, M. A., Hertel, S. A., Heuermann, G., Homenides, G. J., Horn, M., Huang, D. Q., Hunt, D., Jacquet, E., James, R. S., Johnson, J., Kaboth, A. C., Kamaha, A. C., Kannichankandy, M., Khaitan, D., Khazov, A., Khurana, I., DKim, J., Kim, J., Kingston, J., Kirk, R., Kodroff, D., Korley, L., Korolkova, E. V., Kraus, H., Kravitz, S., Kreczko, L., Kudryavtsev, V. A., Leonard, D. S., Lesko, K. T., Levy, C., Lin, J., Lindote, A., Linehan, R., Lippincott, W. H., Lopes, M. I., Lorenzon, W., Lu, C., Luitz, S., Majewski, P. A., Manalaysay, A., Mannino, R. L., Maupin, C., McCarthy, M. E., McDowell, G., McKinsey, D. N., McLaughlin, J., McLaughlin, J. B., McMonigle, R., Miller, E. H., Mizrachi, E., Monte, A., Monzani, M. E., Mendoza, J. D. Morales, Morrison, E., Mount, B. J., Murdy, M., Murphy, A. St. J., Naylor, A., Nelson, H. N., Neves, F., Nguyen, A., Nikoleyczik, J. A., Olcina, I., Oliver-Mallory, K. C., Orpwood, J., Palladino, K. J., Palmer, J., Pannifer, N. J., Parveen, N., Patton, S. J., Penning, B., Pereira, G., Perry, E., Pershing, T., Piepke, A., Qie, Y., Reichenbacher, J., Rhyne, C. A., Riffard, Q., Rischbieter, G. R. C., Riyat, H. S., Rosero, R., Rushton, T., Rynders, D., Santone, D., Sazzad, A. B. M. R., Schnee, R. W., Shaw, S., Shutt, T., Silk, J. J., Silva, C., Sinev, G., Siniscalco, J., Smith, R., Solovov, V. N., Sorensen, P., Soria, J., Stancu, I., Stevens, A., Stifter, K., Suerfu, B., Sumner, T. J., Szydagis, M., Taylor, W. C., Tiedt, D. R., Timalsina, M., Tong, Z., Tovey, D. R., Tranter, J., Trask, M., Tripathi, M., Tronstad, D. R., Vacheret, A., Vaitkus, A. C., Valentino, O., Velan, V., Wang, A., Wang, J. J., Wang, Y., Watson, J. R., Webb, R. C., Weeldreyer, L., Whitis, T. J., Williams, M., Wisniewski, W. J., Wolfs, F. L. H., Woodford, S., Woodward, D., Wright, C. J., Xia, Q., Xiang, X., Xu, J., Yeh, M., and Zweig, E. A.

Subjects
High Energy Physics - Experiment
Abstract

Weakly interacting massive particles (WIMPs) may interact with a virtual pion that is exchanged between nucleons. This interaction channel is important to consider in models where the spin-independent isoscalar channel is suppressed. Using data from the first science run of the LUX-ZEPLIN dark matter experiment, containing 60 live days of data in a 5.5~tonne fiducial mass of liquid xenon, we report the results on a search for WIMP-pion interactions. We observe no significant excess and set an upper limit of $1.5\times10^{-46}$~cm$^2$ at a 90\% confidence level for a WIMP mass of 33~GeV/c$^2$ for this interaction.

Published
2024

7. The Data Acquisition System of the LZ Dark Matter Detector: FADR

Author

Aalbers, J., Akerib, D. S., Musalhi, A. K. Al, Alder, F., Amarasinghe, C. S., Ames, A., Anderson, T. J., Angelides, N., Araújo, H. M., Armstrong, J. E., Arthurs, M., Baker, A., Balashov, S., Bang, J., Barillier, E. E., Bargemann, J. W., Beattie, K., Benson, T., Bhatti, A., Biekert, A., Biesiadzinski, T. P., Birch, H. J., Bishop, E., Blockinger, G. M., Boxer, B., Brew, C. A. J., Brás, P., Buckley, J. H., Burdin, S., Buuck, M., Carmona-Benitez, M. C., Carter, M., Chawla, A., Chen, H., Cherwinka, J. J., Chin, Y. T., Chott, N. I., Converse, M. V., Cottle, A., Cox, G., Curran, D., Dahl, C. E., David, A., Delgaudio, J., Dey, S., de Viveiros, L., Di Felice, L., Dimino, T., Ding, C., Dobson, J. E. Y., Druszkiewicz, E., Eriksen, S. R., Fan, A., Fearon, N. M., Fieldhouse, N., Fiorucci, S., Flaecher, H., Fraser, E. D., Fruth, T. M. A., Gaitskell, R. J., Geffre, A., Gelfand, R., Genovesi, J., Ghag, C., Gibbons, R., Gokhale, S., Green, J., van der Grinten, M. G. D., Haiston, J. J., Hall, C. R., Han, S., Hartigan-O'Connor, E., Haselschwardt, S. J., Hernandez, M. A., Hertel, S. A., Heuermann, G., Homenides, G. J., Horn, M., Huang, D. Q., Hunt, D., Jacquet, E., James, R. S., Johnson, J., Kaboth, A. C., Kamaha, A. C., Kannichankandy, M., Khaitan, D., Khazov, A., Khurana, I., Kim, J., Kim, Y. D., Kingston, J., Kirk, R., Kodroff, D., Korley, L., Korolkova, E. V., Koyuncu, M., Kraus, H., Kravitz, S., Kreczko, L., Kudryavtsev, V. A., Leonard, D. S., Lesko, K. T., Levy, C., Lin, J., Lindote, A., Linehan, R., Lippincott, W. H., Loniewski, C., Lopes, M. I., Lorenzon, W., Lu, C., Luitz, S., Majewski, P. A., Manalaysay, A., Mannino, R. L., Maupin, C., McCarthy, M. E., McDowell, G., McKinsey, D. N., McLaughlin, J., Mclaughlin, J. B., McMonigle, R., Miller, E. H., Mizrachi, E., Monte, A., Monzani, M. E., Moongweluwan, M., Mendoza, J. D. Morales, Morrison, E., Mount, B. J., Murdy, M., Murphy, A. St. J., Naylor, A., Nelson, H. N., Neves, F., Nguyen, A., Nikoleyczik, J. A., Oh, H., Olcina, I., Olevitch, M. A., Oliver-Mallory, K. C., Orpwood, J., Palladino, K. J., Palmer, J., Pannifer, N. J., Parveen, N., Patton, S. J., Penning, B., Pereira, G., Perry, E., Pershing, T., Piepke, A., Qie, Y., Reichenbacher, J., Rhyne, C. A., Riffard, Q., Rischbieter, G. R. C., Riyat, H. S., Rosero, R., Rushton, T., Rynders, D., Santone, D., Sarkis, R., Sazzad, A. B. M. R., Schnee, R. W., Shaw, S., Shutt, T., Silk, J. J., Silva, C., Sinev, G., Siniscalco, J., Skulski, W., Smith, R., Solovov, V. N., Sorensen, P., Soria, J., Stancu, I., Stevens, A., Stifter, K., Suerfu, B., Sumner, T. J., Szydagis, M., Taylor, W. C., Tiedt, D. R., Timalsina, M., Tong, Z., Tovey, D. R., Tranter, J., Trask, M., Tripathi, M., Tronstad, D. R., Vacheret, A., Vaitkus, A. C., Vaitkus, J., Valentino, O., Velan, V., Wang, A., Wang, J. J., Wang, Y., Watson, J. R., Webb, R. C., Weeldreyer, L., Whitis, T. J., Williams, M., Wisniewski, W. J., Wolfs, F. L. H., Wolfs, J. D., Woodford, S., Woodward, D., Wright, C. J., Xia, Q., Xiang, X., Xu, J., Yeh, M., and Yin, J.

Subjects
Physics - Instrumentation and Detectors, High Energy Physics - Experiment
Abstract

The Data Acquisition System (DAQ) for the LUX-ZEPLIN (LZ) dark matter detector is described. The signals from 745 PMTs, distributed across three subsystems, are sampled with 100-MHz 32-channel digitizers (DDC-32s). A basic waveform analysis is carried out on the on-board Field Programmable Gate Arrays (FPGAs) to extract information about the observed scintillation and electroluminescence signals. This information is used to determine if the digitized waveforms should be preserved for offline analysis. The system is designed around the Kintex-7 FPGA. In addition to digitizing the PMT signals and providing basic event selection in real time, the flexibility provided by the use of FPGAs allows us to monitor the performance of the detector and the DAQ in parallel to normal data acquisition. The hardware and software/firmware of this FPGA-based Architecture for Data acquisition and Realtime monitoring (FADR) are discussed and performance measurements are described., Comment: 18 pages, 24 figures

Published
2024

8. Effect of substrate and thickness on spin-wave propagation properties in ferrimagnetic thulium iron garnet thin films

Author

Timalsina, Rupak, Giri, Bharat, Wang, Haohan, Erickson, Adam, Sarin, Suchit, Lamichhane, Suvechhya, Liou, Sy-Hwang, Shield, Jeffery E., Xu, Xiaoshan, and Laraoui, Abdelghani

Subjects
Condensed Matter - Materials Science, Condensed Matter - Mesoscale and Nanoscale Physics
Abstract

Rare-earth iron garnets have distinctive spin-wave (SW) properties such as low magnetic damping and long SW coherence length making them ideal candidates for magnonics. Among them, thulium iron garnet (TmIG) is a ferrimagnetic insulator with unique magnetic properties including perpendicular magnetic anisotropy (PMA) and topological hall effect at room temperature when grown down to a few nanometers, extending its application to magnon spintronics. Here, the SW propagation properties of TmIG films (thickness of 7 - 34 nm) grown on GGG and sGGG substrates are studied at room temperature. Magnetic measurements show in-plane magnetic anisotropy for TmIG films grown on GGG and out-of-plane magnetic anisotropy for films grown on sGGG substrates with PMA. SW electrical transmission spectroscopy measurements on TmIG /GGG films unveil magnetostatic surface spin waves (MSSWs) propagating up to 80 um with a SW group velocity of 3 - 8 km/s. Intriguingly, these MSSWs exhibit nonreciprocal propagation, opening new applications in SW functional devices. TmIG films grown on sGGG substrates exhibit forward volume spin waves with a reciprocal propagation behavior up to 32 um.

Published
2024

9. The Design, Implementation, and Performance of the LZ Calibration Systems

Author

Aalbers, J., Akerib, D. S., Musalhi, A. K. Al, Alder, F., Amarasinghe, C. S., Ames, A., Anderson, T. J., Angelides, N., Araújo, H. M., Armstrong, J. E., Arthurs, M., Baker, A., Balashov, S., Bang, J., Barillier, E. E., Bargemann, J. W., Beattie, K., Benson, T., Bhatti, A., Biekert, A., Biesiadzinski, T. P., Birch, H. J., Bishop, E., Blockinger, G. M., Boxer, B., Brew, C. A. J., Brás, P., Burdin, S., Buuck, M., Carmona-Benitez, M. C., Carter, M., Chawla, A., Chen, H., Cherwinka, J. J., Chin, Y. T., Chott, N. I., Converse, M. V., Cottle, A., Cox, G., Curran, D., Dahl, C. E., David, A., Delgaudio, J., Dey, S., de Viveiros, L., Di Felice, L., Ding, C., Dobson, J. E. Y., Druszkiewicz, E., Eriksen, S. R., Fan, A., Fearon, N. M., Fieldhouse, N., Fiorucci, S., Flaecher, H., Fraser, E. D., Fruth, T. M. A., Gaitskell, R. J., Geffre, A., Genovesi, J., Ghag, C., Gibbons, R., Gokhale, S., Green, J., van der Grinten, M. G. D., Haiston, J. J., Hall, C. R., Han, S., Hartigan-O'Connor, E., Haselschwardt, S. J., Hernandez, M. A., Hertel, S. A., Heuermann, G., Homenides, G. J., Horn, M., Huang, D. Q., Hunt, D., Jacquet, E., James, R. S., Johnson, J., Kaboth, A. C., Kamaha, A. C., Kannichankandy, M., Khaitan, D., Khazov, A., Khurana, I., Kim, J., Kim, Y. D., Kingston, J., Kirk, R., Kodroff, D., Korley, L., Korolkova, E. V., Kraus, H., Kravitz, S., Kreczko, L., Kudryavtsev, V. A., Leonard, D. S., Lesko, K. T., Levy, C., Lin, J., Lindote, A., Linehan, R., Lippincott, W. H., Lopes, M. I., Lorenzon, W., Lu, C., Luitz, S., Majewski, P. A., Manalaysay, A., Mannino, R. L., Maupin, C., McCarthy, M. E., McDowell, G., McKinsey, D. N., McLaughlin, J., Mclaughlin, J. B., McMonigle, R., Miller, E. H., Mizrachi, E., Monte, A., Monzani, M. E., Mendoza, J. D. Morales, Morrison, E., Mount, B. J., Murdy, M., Murphy, A. St. J., Naylor, A., Nelson, H. N., Neves, F., Nguyen, A., Nikoleyczik, J. A., Olcina, I., Oliver-Mallory, K. C., Orpwood, J., Palladino, K. J., Palmer, J., Pannifer, N. J., Parveen, N., Patton, S. J., Penning, B., Pereira, G., Perry, E., Pershing, T., Piepke, A., Qie, Y., Reichenbacher, J., Rhyne, C. A., Riffard, Q., Rischbieter, G. R. C., Riyat, H. S., Rosero, R., Rushton, T., Rynders, D., Santone, D., Sazzad, A. B. M. R., Schnee, R. W., Shaw, S., Shutt, T., Silk, J. J., Silva, C., Sinev, G., Siniscalco, J., Smith, R., Solovov, V. N., Sorensen, P., Soria, J., Stancu, I., Stevens, A., Stifter, K., Suerfu, B., Sumner, T. J., Szydagis, M., Taylor, W. C., Tiedt, D. R., Timalsina, M., Tong, Z., Tovey, D. R., Tranter, J., Trask, M., Tripathi, M., Tronstad, D. R., Vacheret, A., Vaitkus, A. C., Valentino, O., Velan, V., Wang, A., Wang, J. J., Wang, Y., Watson, J. R., Webb, R. C., Weeldreyer, L., Whitis, T. J., Williams, M., Wisniewski, W. J., Wolfs, F. L. H., Woodford, S., Woodward, D., Wright, C. J., Xia, Q., Xiang, X., Xu, J., and Yeh, M.

Subjects
Physics - Instrumentation and Detectors, High Energy Physics - Experiment
Abstract

LUX-ZEPLIN (LZ) is a tonne-scale experiment searching for direct dark matter interactions and other rare events. It is located at the Sanford Underground Research Facility (SURF) in Lead, South Dakota, USA. The core of the LZ detector is a dual-phase xenon time projection chamber (TPC), designed with the primary goal of detecting Weakly Interacting Massive Particles (WIMPs) via their induced low energy nuclear recoils. Surrounding the TPC, two veto detectors immersed in an ultra-pure water tank enable reducing background events to enhance the discovery potential. Intricate calibration systems are purposely designed to precisely understand the responses of these three detector volumes to various types of particle interactions and to demonstrate LZ's ability to discriminate between signals and backgrounds. In this paper, we present a comprehensive discussion of the key features, requirements, and performance of the LZ calibration systems, which play a crucial role in enabling LZ's WIMP-search and its broad science program. The thorough description of these calibration systems, with an emphasis on their novel aspects, is valuable for future calibration efforts in direct dark matter and other rare-event search experiments.

Published
2024
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10. Constraints On Covariant WIMP-Nucleon Effective Field Theory Interactions from the First Science Run of the LUX-ZEPLIN Experiment

Author

Aalbers, J., Akerib, D. S., Musalhi, A. K. Al, Alder, F., Amarasinghe, C. S., Ames, A., Anderson, T. J., Angelides, N., Araújo, H. M., Armstrong, J. E., Arthurs, M., Baker, A., Balashov, S., Bang, J., Barillier, E. E., Bargemann, J. W., Beattie, K., Benson, T., Bhatti, A., Biekert, A., Biesiadzinski, T. P., Birch, H. J., Bishop, E. J., Blockinger, G. M., Boxer, B., Brew, C. A. J., Brás, P., Burdin, S., Buuck, M., Carmona-Benitez, M. C., Carter, M., Chawla, A., Chen, H., Cherwinka, J. J., Chin, Y. T., Chott, N. I., Converse, M. V., Cottle, A., Cox, G., Curran, D., Dahl, C. E., David, A., Delgaudio, J., Dey, S., de Viveiros, L., Di Felice, L., Ding, C., Dobson, J. E. Y., Druszkiewicz, E., Eriksen, S. R., Fan, A., Fearon, N. M., Fiorucci, S., Flaecher, H., Fraser, E. D., Fruth, T. M. A., Gaitskell, R. J., Geffre, A., Genovesi, J., Ghag, C., Gibbons, R., Gokhale, S., Green, J., van der Grinten, M. G. D., Haiston, J. H., Hall, C. R., Han, S., Hartigan-O'Connor, E., Haselschwardt, S. J., Hernandez, M. A., Hertel, S. A., Heuermann, G., Homenides, G. J., Horn, M., Huang, D. Q., Hunt, D., Ignarra, C. M., Jacquet, E., James, R. S., Johnson, J., Kaboth, A. C., Kamaha, A. C., Kannichankandy, M., Khaitan, D., Khazov, A., Khurana, I., Kim, J., Kingston, J., Kirk, R., Kodroff, D., Korley, L., Korolkova, E. V., Kraus, H., Kravitz, S., Kreczko, L., Kudryavtsev, V. A., Lee, J., Leonard, D. S., Lesko, K. T., Levy, C., Lin, J., Lindote, A., Linehan, R., Lippincott, W. H., Lopes, M. I., Lorenzon, W., Lu, C., Luitz, S., Majewski, P. A., Manalaysay, A., Mannino, R. L., Maupin, C., McCarthy, M. E., McDowell, G., McKinsey, D. N., McLaughlin, J., McLaughlin, J. B., McMonigle, R., Miller, E. H., Mizrachi, E., Monte, A., Monzani, M. E., Mendoza, J. D. Morales, Morrison, E., Mount, B. J., Murdy, M., Murphy, A. St. J., Naylor, A., Nelson, H. N., Neves, F., Nguyen, A., Nikoleyczik, J. A., Olcina, I., Oliver-Mallory, K. C., Orpwood, J., Palladino, K. J., Palmer, J., Pannifer, N. J., Parveen, N., Patton, S. J., Penning, B., Pereira, G., Perry, E., Pershing, T., Piepke, A., Qie, Y., Reichenbacher, J., Rhyne, C. A., Riffard, Q., Rischbieter, G. R. C., Riyat, H. S., Rosero, R., Rushton, T., Rynders, D., Santone, D., Sazzad, A. B. M. R., Schnee, R. W., Shaw, S., Shutt, T., Silk, J. J., Silva, C., Sinev, G., Siniscalco, J., Smith, R., Solovov, V. N., Sorensen, P., Soria, J., Stancu, I., Stevens, A., Stifter, K., Suerfu, B., Sumner, T. J., Szydagis, M., Taylor, W. C., Tiedt, D. R., Timalsina, M., Tong, Z., Tovey, D. R., Tranter, J., Trask, M., Tripathi, M., Tronstad, D. R., Vacheret, A., Vaitkus, A. C., Valentino, O., Velan, V., Wang, A., Wang, J. J., Wang, Y., Watson, J. R., Webb, R. C., Weeldreyer, L., Whitis, T. J., Williams, M., Wisniewski, W. J., Wolfs, F. L. H., Woodford, S., Woodward, D., Wright, C. J., Xia, Q., Xiang, X., Xu, J., Yeh, M., and Zweig, E. A.

Subjects
High Energy Physics - Experiment
Abstract

The first science run of the LUX-ZEPLIN (LZ) experiment, a dual-phase xenon time project chamber operating in the Sanford Underground Research Facility in South Dakota, USA, has reported leading limits on spin-independent WIMP-nucleon interactions and interactions described from a non-relativistic effective field theory (NREFT). Using the same 5.5~t fiducial mass and 60 live days of exposure we report on the results of a relativistic extension to the NREFT. We present constraints on couplings from covariant interactions arising from the coupling of vector, axial currents, and electric dipole moments of the nucleon to the magnetic and electric dipole moments of the WIMP which cannot be described by recasting previous results described by an NREFT. Using a profile-likelihood ratio analysis, in an energy region between 0~keV$_\text{nr}$ to 270~keV$_\text{nr}$, we report 90% confidence level exclusion limits on the coupling strength of five interactions in both the isoscalar and isovector bases., Comment: 7 pages, 4 figures

Published
2024

11. Simple linear attention language models balance the recall-throughput tradeoff

Author

Arora, Simran, Eyuboglu, Sabri, Zhang, Michael, Timalsina, Aman, Alberti, Silas, Zinsley, Dylan, Zou, James, Rudra, Atri, and Ré, Christopher

Subjects
Computer Science - Computation and Language, Computer Science - Machine Learning
Abstract

Recent work has shown that attention-based language models excel at recall, the ability to ground generations in tokens previously seen in context. However, the efficiency of attention-based models is bottle-necked during inference by the KV-cache's aggressive memory consumption. In this work, we explore whether we can improve language model efficiency (e.g. by reducing memory consumption) without compromising on recall. By applying experiments and theory to a broad set of architectures, we identify a key tradeoff between a model's state size and recall ability. We show that efficient alternatives to attention (e.g. H3, Mamba, RWKV) maintain a fixed-size recurrent state, but struggle at recall. We propose BASED a simple architecture combining linear and sliding window attention. By varying BASED window size and linear attention feature dimension, we can dial the state size and traverse the pareto frontier of the recall-memory tradeoff curve, recovering the full quality of attention on one end and the small state size of attention-alternatives on the other. We train language models up to 1.3b parameters and show that BASED matches the strongest sub-quadratic models (e.g. Mamba) in perplexity and outperforms them on real-world recall-intensive tasks by 6.22 accuracy points. Implementations of linear attention are often less efficient than optimized standard attention implementations. To make BASED competitive, we develop IO-aware algorithms that enable 24x higher throughput on language generation than FlashAttention-2, when generating 1024 tokens using 1.3b parameter models. Code for this work is provided at: https://github.com/HazyResearch/based.

Published
2024

12. New constraints on ultraheavy dark matter from the LZ experiment

Author

Aalbers, J., Akerib, D. S., Musalhi, A. K. Al, Amarasinghe, C. S., Ames, A., Anderson, T. J., Angelides, N., Araújo, H. M., Armstrong, J. E., Arthurs, M., Baker, A., Balashov, S., Bang, J., Bargemann, J. W., Baxter, A., Beattie, K., Benson, T., Bhatti, A., Biekert, A., Biesiadzinski, T. P., Birch, H. J., Bishop, E., Blockinger, G. M., Boxer, B., Brew, C. A. J., Brás, P., Burdin, S., Buuck, M., Carmona-Benitez, M. C., Carter, M., Chawla, A., Chen, H., Cherwinka, J. J., Chott, N. I., Converse, M. V., Cottle, A., Cox, G., Curran, D., Dahl, C. E., David, A., Delgaudio, J., Dey, S., de Viveiros, L., Ding, C., Dobson, J. E. Y., Druszkiewicz, E., Eriksen, S. R., Fan, A., Fearon, N. M., Fiorucci, S., Flaecher, H., Fraser, E. D., Fruth, T. M. A., Gaitskell, R. J., Geffre, A., Genovesi, J., Ghag, C., Gibbons, R., Gokhale, S., Green, J., van der Grinten, M. G. D., Hall, C. R., Han, S., Hartigan-O'Connor, E., Haselschwardt, S. J., Hertel, S. A., Heuermann, G., Homenides, G. J., Horn, M., Huang, D. Q., Hunt, D., Ignarra, C. M., Jacquet, E., James, R. S., Johnson, J., Kaboth, A. C., Kamaha, A. C., Khaitan, D., Khazov, A., Khurana, I., Kim, J., Kingston, J., Kirk, R., Kodroff, D., Korley, L., Korolkova, E. V., Kraus, H., Kravitz, S., Kreczko, L., Krikler, B., Kudryavtsev, V. A., Lee, J., Leonard, D. S., Lesko, K. T., Levy, C., Lin, J., Lindote, A., Linehan, R., Lippincott, W. H., Lopes, M. I., Asamar, E. Lopez, Lorenzon, W., Lu, C., Luitz, S., Majewski, P. A., Manalaysay, A., Mannino, R. L., Maupin, C., McCarthy, M. E., McDowell, G., McKinsey, D. N., McLaughlin, J., McMonigle, R., Miller, E. H., Mizrachi, E., Monte, A., Monzani, M. E., Mendoza, J. D. Morales, Morrison, E., Mount, B. J., Murdy, M., Murphy, A. St. J., Naylor, A., Nedlik, C., Nelson, H. N., Neves, F., Nguyen, A., Nikoleyczik, J. A., Olcina, I., Oliver-Mallory, K. C., Orpwood, J., Palladino, K. J., Palmer, J., Pannifer, N. J., Parveen, N., Patton, S. J., Penning, B., Pereira, G., Perry, E., Pershing, T., Piepke, A., Qie, Y., Reichenbacher, J., Rhyne, C. A., Riffard, Q., Rischbieter, G. R. C., Riyat, H. S., Rosero, R., Rushton, T., Rynders, D., Santone, D., Sazzad, A. B. M. R., Schnee, R. W., Shaw, S., Shutt, T., Silk, J. J., Silva, C., Sinev, G., Smith, R., Solovov, V. N., Sorensen, P., Soria, J., Stancu, I., Stevens, A., Stifter, K., Suerfu, B., Sumner, T. J., Szydagis, M., Taylor, W. C., Tiedt, D. R., Timalsina, M., Tong, Z., Tovey, D. R., Tranter, J., Trask, M., Tripathi, M., Tronstad, D. R., Turner, W., Vacheret, A., Vaitkus, A. C., Velan, V., Wang, A., Wang, J. J., Wang, Y., Watson, J. R., Webb, R. C., Weeldreyer, L., Whitis, T. J., Williams, M., Wisniewski, W. J., Wolfs, F. L. H., Woodford, S., Woodward, D., Wright, C. J., Xia, Q., Xiang, X., Xu, J., Yeh, M., and Zweig, E. A.

Subjects
High Energy Physics - Experiment, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

Searches for dark matter with liquid xenon time projection chamber experiments have traditionally focused on the region of the parameter space that is characteristic of weakly interacting massive particles, ranging from a few GeV/$c^2$ to a few TeV/$c^2$. Models of dark matter with a mass much heavier than this are well motivated by early production mechanisms different from the standard thermal freeze-out, but they have generally been less explored experimentally. In this work, we present a re-analysis of the first science run (SR1) of the LZ experiment, with an exposure of $0.9$ tonne$\times$year, to search for ultraheavy particle dark matter. The signal topology consists of multiple energy deposits in the active region of the detector forming a straight line, from which the velocity of the incoming particle can be reconstructed on an event-by-event basis. Zero events with this topology were observed after applying the data selection calibrated on a simulated sample of signal-like events. New experimental constraints are derived, which rule out previously unexplored regions of the dark matter parameter space of spin-independent interactions beyond a mass of 10$^{17}$ GeV/$c^2$., Comment: 9 pages, 7 figures

Published
2024
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16. Zoology: Measuring and Improving Recall in Efficient Language Models

Author

Arora, Simran, Eyuboglu, Sabri, Timalsina, Aman, Johnson, Isys, Poli, Michael, Zou, James, Rudra, Atri, and Ré, Christopher

Subjects
Computer Science - Computation and Language, Computer Science - Machine Learning
Abstract

Attention-free language models that combine gating and convolutions are growing in popularity due to their efficiency and increasingly competitive performance. To better understand these architectures, we pretrain a suite of 17 attention and "gated-convolution" language models, finding that SoTA gated-convolution architectures still underperform attention by up to 2.1 perplexity points on the Pile. In fine-grained analysis, we find 82% of the gap is explained by each model's ability to recall information that is previously mentioned in-context, e.g. "Hakuna Matata means no worries Hakuna Matata it means no" $\rightarrow$ "??". On this task, termed "associative recall", we find that attention outperforms gated-convolutions by a large margin: a 70M parameter attention model outperforms a 1.4 billion parameter gated-convolution model on associative recall. This is surprising because prior work shows gated convolutions can perfectly solve synthetic tests for AR capability. To close the gap between synthetics and real language, we develop a new formalization of the task called multi-query associative recall (MQAR) that better reflects actual language. We perform an empirical and theoretical study of MQAR that elucidates differences in the parameter-efficiency of attention and gated-convolution recall. Informed by our analysis, we evaluate simple convolution-attention hybrids and show that hybrids with input-dependent sparse attention patterns can close 97.4% of the gap to attention, while maintaining sub-quadratic scaling. Our code is accessible at: https://github.com/HazyResearch/zoology.

Published
2023

17. First Constraints on WIMP-Nucleon Effective Field Theory Couplings in an Extended Energy Region From LUX-ZEPLIN

Author

LZ Collaboration, Aalbers, J., Akerib, D. S., Musalhi, A. K. Al, Alder, F., Amarasinghe, C. S., Ames, A., Anderson, T. J., Angelides, N., Araújo, H. M., Armstrong, J. E., Arthurs, M., Baker, A., Balashov, S., Bang, J., Bargemann, J. W., Baxter, A., Beattie, K., Benson, T., Bhatti, A., Biekert, A., Biesiadzinski, T. P., Birch, H. J., Bishop, E., Blockinger, G. M., Boxer, B., Brew, C. A. J., Brás, P., Burdin, S., Buuck, M., Carmona-Benitez, M. C., Carter, M., Chawla, A., Chen, H., Cherwinka, J. J., Chott, N. I., Converse, M. V., Cottle, A., Cox, G., Curran, D., Dahl, C. E., David, A., Delgaudio, J., Dey, S., de Viveiros, L., Ding, C., Dobson, J. E. Y., Druszkiewicz, E., Eriksen, S. R., Fan, A., Fearon, N. M., Fiorucci, S., Flaecher, H., Fraser, E. D., Fruth, T. M. A., Gaitskell, R. J., Geffre, A., Genovesi, J., Ghag, C., Gibbons, R., Gokhale, S., Green, J., van der Grinten, M. G. D., Hall, C. R., Han, S., Hartigan-O'Connor, E., Haselschwardt, S. J., Hertel, S. A., Heuermann, G., Homenides, G. J., Horn, M., Huang, D. Q., Hunt, D., Ignarra, C. M., Jacquet, E., James, R. S., Johnson, J., Kaboth, A. C., Kamaha, A. C., Khaitan, D., Khazov, A., Khurana, I., Kim, J., Kingston, J., Kirk, R., Kodroff, D., Korley, L., Korolkova, E. V., Kraus, H., Kravitz, S., Kreczko, L., Krikler, B., Kudryavtsev, V. A., Lee, J., Leonard, D. S., Lesko, K. T., Levy, C., Lin, J., Lindote, A., Linehan, R., Lippincott, W. H., Lopes, M. I., Asamar, E. Lopez, Lorenzon, W., Lu, C., Luitz, S., Majewski, P. A., Manalaysay, A., Mannino, R. L., Maupin, C., McCarthy, M. E., McDowell, G., McKinsey, D. N., McLaughlin, J., Miller, E. H., Mizrachi, E., Monte, A., Monzani, M. E., Mendoza, J. D. Morales, Morrison, E., Mount, B. J., Murdy, M., Murphy, A. St. J., Naylor, A., Nedlik, C., Nelson, H. N., Neves, F., Nguyen, A., Nikoleyczik, J. A., Olcina, I., Oliver-Mallory, K. C., Orpwood, J., Palladino, K. J., Palmer, J., Pannifer, N., Parveen, N., Patton, S. J., Penning, B., Pereira, G., Perry, E., Pershing, T., Piepke, A., Qie, Y., Reichenbacher, J., Rhyne, C. A., Riffard, Q., Rischbieter, G. R. C., Riyat, H. S., Rosero, R., Rushton, T., Rynders, D., Santone, D., Sazzad, A. B. M. R., Schnee, R. W., Shaw, S., Shutt, T., Silk, J. J., Silva, C., Sinev, G., Smith, R., Solovov, V. N., Sorensen, P., Soria, J., Stancu, I., Stevens, A., Stifter, K., Suerfu, B., Sumner, T. J., Szydagis, M., Taylor, W. C., Tiedt, D. R., Timalsina, M., Tong, Z., Tovey, D. R., Tranter, J., Trask, M., Tripathi, M., Tronstad, D. R., Turner, W., Vacheret, A., Vaitkus, A. C., Velan, V., Wang, A., Wang, J. J., Wang, Y., Watson, J. R., Webb, R. C., Weeldreyer, L., Whitis, T. J., Williams, M., Wisniewski, W. J., Wolfs, F. L. H., Woodford, S., Woodward, D., Wright, C. J., Xia, Q., Xiang, X., Xu, J., Yeh, M., and Zweig, E. A.

Subjects
High Energy Physics - Experiment, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

Following the first science results of the LUX-ZEPLIN (LZ) experiment, a dual-phase xenon time projection chamber operating from the Sanford Underground Research Facility in Lead, South Dakota, USA, we report the initial limits on a model-independent non-relativistic effective field theory describing the complete set of possible interactions of a weakly interacting massive particle (WIMP) with a nucleon. These results utilize the same 5.5 t fiducial mass and 60 live days of exposure collected for the LZ spin-independent and spin-dependent analyses while extending the upper limit of the energy region of interest by a factor of 7.5 to 270 keVnr. No significant excess in this high energy region is observed. Using a profile-likelihood ratio analysis, we report 90% confidence level exclusion limits on the coupling of each individual non-relativistic WIMP-nucleon operator for both elastic and inelastic interactions in the isoscalar and isovector bases., Comment: 17 pages 11 figures

Published
2023
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18. Laughing Hyena Distillery: Extracting Compact Recurrences From Convolutions

Author

Massaroli, Stefano, Poli, Michael, Fu, Daniel Y., Kumbong, Hermann, Parnichkun, Rom N., Timalsina, Aman, Romero, David W., McIntyre, Quinn, Chen, Beidi, Rudra, Atri, Zhang, Ce, Re, Christopher, Ermon, Stefano, and Bengio, Yoshua

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Electrical Engineering and Systems Science - Signal Processing
Abstract

Recent advances in attention-free sequence models rely on convolutions as alternatives to the attention operator at the core of Transformers. In particular, long convolution sequence models have achieved state-of-the-art performance in many domains, but incur a significant cost during auto-regressive inference workloads -- naively requiring a full pass (or caching of activations) over the input sequence for each generated token -- similarly to attention-based models. In this paper, we seek to enable $\mathcal O(1)$ compute and memory cost per token in any pre-trained long convolution architecture to reduce memory footprint and increase throughput during generation. Concretely, our methods consist in extracting low-dimensional linear state-space models from each convolution layer, building upon rational interpolation and model-order reduction techniques. We further introduce architectural improvements to convolution-based layers such as Hyena: by weight-tying the filters across channels into heads, we achieve higher pre-training quality and reduce the number of filters to be distilled. The resulting model achieves 10x higher throughput than Transformers and 1.5x higher than Hyena at 1.3B parameters, without any loss in quality after distillation.

Published
2023

19. Detection of Iron in Nanoclustered Cytochrome C Proteins Using Nitrogen-Vacancy Magnetic Relaxometry

Author

Lamichhane, Suvechhya, Timalsina, Rupak, Schultz, Cody, Fescenko, Ilja, Ambal, Kapildeb, Liou, Sy-Hwang, Lai, Rebecca Y., and Laraoui, Abdelghani

Subjects
Physics - Biological Physics, Quantum Physics
Abstract

Nitrogen-vacancy (NV) magnetometry offers an alternative tool to detect iron levels in neurons and cells with a favorable combination of magnetic sensitivity and spatial resolution. Here we employ NV-T1 relaxometry to detect Fe in cytochrome C (Cyt-C) nanoclusters. Cyt-C is a water-soluble protein that contains a single heme group and plays a vital role in the electron transport chain of mitochondria. Under ambient conditions, the heme group remains in the Fe+3 paramagnetic state. We perform NV-T1 relaxometry on a functionalized diamond chip and vary the concentration of Cyt-C from 6 uM to 54 uM, resulting in a decrease of T1 from 1.2 ms to 150 us, respectively. This reduction is attributed to spin-noise originating from the intracellular Fe spins in the Cyt-C. We perform relaxometry imaging of Cyt-C proteins on a nanostructured diamond chip by varying the density of adsorbed iron from 1.44 x 10^6 to 1.7 x 10^7 per um^2.

Published
2023

20. Mapping of Spin-Wave Transport in Thulium Iron Garnet Thin Films Using Diamond Quantum Microscopy

Author

Timalsina, Rupak, Wang, Haohan, Giri, Bharat, Erickson, Adam, Xu, Xiaoshan, and Laraoui, Abdelghani

Subjects
Condensed Matter - Mesoscale and Nanoscale Physics
Abstract

Spin waves, collective dynamic magnetic excitations, offer crucial insights into magnetic material properties. Rare-earth iron garnets offer an ideal spin-wave (SW) platform with long propagation length, short wavelength, gigahertz frequency, and applicability to magnon spintronic platforms. Of particular interest, thulium iron garnet (TmIG) has attracted a huge interest recently due to its successful growth down to a few nanometers, observed topological Hall effect and spin orbit torque-induced switching effects. However, there is no direct spatial measurement of its SW properties. This work uses diamond nitrogen vacancy (NV) magnetometry in combination with SW electrical transmission spectroscopy to study SW transport properties in TmIG thin films. NV magnetometry allows probing spin waves at the sub-micrometer scale, seen by the amplification of the local microwave magnetic field due to the coupling of NV spin qubits with the stray magnetic field produced by the microwave-excited spin waves. By monitoring the NV spin resonances, the SW properties in TmIG thin films are measured as function of the applied magnetic field, including their amplitude, decay length (~ 50 um), and wavelength (0.8 - 2 um). These results pave the way for studying spin qubit-magnon interactions in rare-earth magnetic insulators, relevant to quantum magnonics applications.

Published
2023
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21. A search for new physics in low-energy electron recoils from the first LZ exposure

Author

The LZ Collaboration, Aalbers, J., Akerib, D. S., Musalhi, A. K. Al, Alder, F., Amarasinghe, C. S., Ames, A., Anderson, T. J., Angelides, N., Araújo, H. M., Armstrong, J. E., Arthurs, M., Baker, A., Balashov, S., Bang, J., Bargemann, J. W., Baxter, A., Beattie, K., Beltrame, P., Benson, T., Bhatti, A., Biekert, A., Biesiadzinski, T. P., Birch, H. J., Blockinger, G. M., Boxer, B., Brew, C. A. J., Brás, P., Burdin, S., Buuck, M., Carmona-Benitez, M. C., Chan, C., Chawla, A., Chen, H., Cherwinka, J. J., Chott, N. I., Converse, M. V., Cottle, A., Cox, G., Curran, D., Dahl, C. E., David, A., Delgaudio, J., Dey, S., de Viveiros, L., Ding, C., Dobson, J. E. Y., Druszkiewicz, E., Eriksen, S. R., Fan, A., Fearon, N. M., Fiorucci, S., Flaecher, H., Fraser, E. D., Fruth, T. M. A., Gaitskell, R. J., Geffre, A., Genovesi, J., Ghag, C., Gibbons, R., Gokhale, S., Green, J., van der Grinten, M. G. D., Hall, C. R., Han, S., Hartigan-O'Connor, E., Haselschwardt, S. J., Huang, D. Q., Hertel, S. A., Heuermann, G., Horn, M., Hunt, D., Ignarra, C. M., Jahangir, O., James, R. S., Johnson, J., Kaboth, A. C., Kamaha, A. C., Khaitan, D., Khazov, A., Khurana, I., Kim, J., Kingston, J., Kirk, R., Kodroff, D., Korley, L., Korolkova, E. V., Kraus, H., Kravitz, S., Kreczko, L., Krikler, B., Kudryavtsev, V. A., Leason, E. A., Lee, J., Leonard, D. S., Lesko, K. T., Levy, C., Lin, J., Lindote, A., Linehan, R., Lippincott, W. H., Liu, X., Lopes, M. I., Asamar, E. Lopez, Lorenzon, W., Lu, C., Lucero, D., Luitz, S., Majewski, P. A., Manalaysay, A., Mannino, R. L., Maupin, C., McCarthy, M. E., McDowell, G., McKinsey, D. N., McLaughlin, J., Miller, E. H., Mizrachi, E., Monte, A., Monzani, M. E., Mendoza, J. D. Morales, Morrison, E., Mount, B. J., Murdy, M., Murphy, A. St. J., Naim, D., Naylor, A., Nedlik, C., Nelson, H. N., Neves, F., Nguyen, A., Nikoleyczik, J. A., Olcina, I., Oliver-Mallory, K. C., Orpwood, J., Palladino, K. J., Palmer, J., Parveen, N., Patton, S. J., Penning, B., Pereira, G., Perry, E., Pershing, T., Piepke, A., Poudel, S., Qie, Y., Reichenbacher, J., Rhyne, C. A., Riffard, Q., Rischbieter, G. R. C., Riyat, H. S., Rosero, R., Rushton, T., Rynders, D., Santone, D., Sazzad, A. B. M. R., Schnee, R. W., Shaw, S., Shutt, T., Silk, J. J., Silva, C., Sinev, G., Smith, R., Solovov, V. N., Sorensen, P., Soria, J., Stancu, I., Stevens, A., Stifter, K., Suerfu, B., Sumner, T. J., Szydagis, M., Taylor, W. C., Temples, D. J., Tiedt, D. R., Timalsina, M., Tong, Z., Tovey, D. R., Tranter, J., Trask, M., Tripathi, M., Tronstad, D. R., Turner, W., Vacheret, A., Vaitkus, A. C., Wang, A., Wang, J. J., Wang, Y., Watson, J. R., Webb, R. C., Weeldreyer, L., Whitis, T. J., Williams, M., Wisniewski, W. J., Wolfs, F. L. H., Woodford, S., Woodward, D., Wright, C. J., Xia, Q., Xiang, X., Xu, J., Yeh, M., and Zweig, E. A.

Subjects
High Energy Physics - Experiment, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

The LUX-ZEPLIN (LZ) experiment is a dark matter detector centered on a dual-phase xenon time projection chamber. We report searches for new physics appearing through few-keV-scale electron recoils, using the experiment's first exposure of 60 live days and a fiducial mass of 5.5t. The data are found to be consistent with a background-only hypothesis, and limits are set on models for new physics including solar axion electron coupling, solar neutrino magnetic moment and millicharge, and electron couplings to galactic axion-like particles and hidden photons. Similar limits are set on weakly interacting massive particle (WIMP) dark matter producing signals through ionized atomic states from the Migdal effect., Comment: 13 pages, 10 figures. See https://tinyurl.com/LZDataReleaseRun1ER for a data release related to this paper

Published
2023
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22. Time-resolved interactome profiling deconvolutes secretory protein quality control dynamics

Author

Madison T Wright, Bibek Timalsina, Valeria Garcia Lopez, Jake N Hermanson, Sarah Garcia, and Lars Plate

Subjects
Temporal Proteomics, Thyroglobulin, Hypothyroidism, Proteostasis, Bioorthogonal Protein Labeling, Biology (General), QH301-705.5, Medicine (General), R5-920
Abstract

Abstract Many cellular processes are governed by protein–protein interactions that require tight spatial and temporal regulation. Accordingly, it is necessary to understand the dynamics of these interactions to fully comprehend and elucidate cellular processes and pathological disease states. To map de novo protein–protein interactions with time resolution at an organelle-wide scale, we developed a quantitative mass spectrometry method, time-resolved interactome profiling (TRIP). We apply TRIP to elucidate aberrant protein interaction dynamics that lead to the protein misfolding disease congenital hypothyroidism. We deconvolute altered temporal interactions of the thyroid hormone precursor thyroglobulin with pathways implicated in hypothyroidism pathophysiology, such as Hsp70-/90-assisted folding, disulfide/redox processing, and N-glycosylation. Functional siRNA screening identified VCP and TEX264 as key protein degradation components whose inhibition selectively rescues mutant prohormone secretion. Ultimately, our results provide novel insight into the temporal coordination of protein homeostasis, and our TRIP method should find broad applications in investigating protein-folding diseases and cellular processes.

Published
2024
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23. Introduction

Author

Breed, Ananda, primary, Pells, Kirrily, additional, Marambio, Helena-Ulrike, additional, and Timalsina, Rajib, additional

Published
2024
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25. Sample-Efficient and Surrogate-Based Design Optimization of Underwater Vehicle Hulls

Author

Vardhan, Harsh, Hyde, David, Timalsina, Umesh, Volgyesi, Peter, and Sztipanovits, Janos

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Physics - Applied Physics, Physics - Fluid Dynamics, Statistics - Applications, Statistics - Machine Learning
Abstract

Physics simulations like computational fluid dynamics (CFD) are a computational bottleneck in computer-aided design (CAD) optimization processes. To overcome this bottleneck, one requires either an optimization framework that is highly sample-efficient, or a fast data-driven proxy (surrogate model) for long-running simulations. Both approaches have benefits and limitations. Bayesian optimization is often used for sample efficiency, but it solves one specific problem and struggles with transferability; alternatively, surrogate models can offer fast and often more generalizable solutions for CFD problems, but gathering data for and training such models can be computationally demanding. In this work, we leverage recent advances in optimization and artificial intelligence (AI) to explore both of these potential approaches, in the context of designing an optimal unmanned underwater vehicle (UUV) hull. Our study finds that the Bayesian Optimization-Lower Condition Bound (BO-LCB) algorithm is the most sample-efficient optimization framework and has the best convergence behavior of those considered. Subsequently, we show that our DNN-based surrogate model predicts drag force on test data in tight agreement with CFD simulations, with a mean absolute percentage error (MAPE) of 1.85%. Combining these results, we demonstrate a two-orders-of-magnitude speedup (with comparable accuracy) for the design optimization process when the surrogate model is used. To our knowledge, this is the first study applying Bayesian optimization and DNN-based surrogate modeling to the problem of UUV design optimization, and we share our developments as open-source software.

Published
2023
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26. Tetrahedralization of Hexahedral Mesh

Author

Timalsina, Aman, Knepley, Matthew, Barth, Timothy J., Series Editor, Griebel, Michael, Series Editor, Keyes, David E., Series Editor, Nieminen, Risto M., Series Editor, Roose, Dirk, Series Editor, Schlick, Tamar, Series Editor, Ruiz-Gironés, Eloi, editor, Sevilla, Rubén, editor, and Moxey, David, editor

Published
2024
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27. Nitrogen-vacancy magnetometry of individual Fe-triazole spin crossover nanorods

Author

Lamichhane, Suvechhya, McElveen, Kayleigh A, Erickson, Adam, Fescenko, Ilja, Sun, Shuo, Timalsina, Rupak, Guo, Yinsheng, Liou, Sy-Hwang, Lai, Rebecca Y., and Laraoui, Abdelghani

Subjects
Condensed Matter - Mesoscale and Nanoscale Physics, Physics - Chemical Physics, Quantum Physics
Abstract

[Fe(Htrz)2(trz)](BF4) (Fe-triazole) spin crossover molecules show thermal, electrical, and optical switching between high spin (HS) and low spin (LS) states, making them promising candidates for molecular spintronics. The LS and HS transitions originate from the electronic configurations of Fe(II), and are considered to be diamagnetic and paramagnetic respectively. The Fe(II) LS state has six paired electrons in the ground states with no interaction with the magnetic field and a diamagnetic behavior is usually observed. While the bulk magnetic properties of Fe-triazole compounds are widely studied by standard magnetometry techniques their properties at the individual level are missing. Here we use nitrogen vacancy (NV) based magnetometry to study the magnetic properties of the Fe-triazole LS state of nanoparticle clusters and individual nanorods of size varying from 20 to 1000 nm. Scanning electron microscopy (SEM) and Raman spectroscopy are performed to determine the size of the nanoparticles/nanorods and to confirm their respective spin state. The magnetic field patterns produced by the nanoparticles/nanorods are imaged by NV magnetic microscopy as a function of applied magnetic field (up to 350 mT) and correlated with SEM and Raman. We found that in most of the nanorods the LS state is slightly paramagnetic, possibly originating from the surface oxidation and/or the greater Fe(III) presence along the nanorod edges. NV measurements on the Fe-triazole LS state nanoparticle clusters revealed both diamagnetic and paramagnetic behavior. Our results highlight the potential of NV quantum sensors to study the magnetic properties of spin crossover molecules and molecular magnets.

Published
2023
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28. An efficient and low-cost method to create high-density nitrogen-vacancy centers in CVD diamond for sensing applications

Author

Karki, Prem Bahadur, Timalsina, Rupak, Dowran, Mohammadjavad, Aregbesola, Ayodimeji E., Laraoui, Abdelghani, and Ambal, Kapildeb

Subjects
Condensed Matter - Mesoscale and Nanoscale Physics, Condensed Matter - Materials Science, Condensed Matter - Other Condensed Matter
Abstract

The negatively charged Nitrogen-Vacancy (NV-) center in diamond is one of the most versatile and robust quantum sensors suitable for quantum technologies, including magnetic field and temperature sensors. For precision sensing applications, densely packed NV- centers within a small volume are preferable due to benefiting from 1/N^1/2 sensitivity enhancement (N is the number of sensing NV centers) and efficient excitation of NV centers. However, methods for quickly and efficiently forming high concentrations of NV- centers are in development stage. We report an efficient, low-cost method for creating high-density NV- centers production from a relatively low nitrogen concentration based on high-energy photons from Ar+ plasma. This study was done on type-IIa, single crystal, CVD-grown diamond substrates with an as-grown nitrogen concentration of 1 ppm. We estimate an NV- density of ~ 0.57 ppm (57%) distributed homogeneously over 200 um deep from the diamond surface facing the plasma source based on optically detected magnetic resonance and fluorescence confocal microscopy measurements. The created NV-s have a spin-lattice relaxation time (T1) of 5 ms and a spin-spin coherence time (T2) of 4 us. We measure a DC magnetic field sensitivity of ~ 104 nT Hz^-1/2, an AC magnetic field sensitivity of ~ 0.12 pT Hz^-1/2, and demonstrate real-time magnetic field sensing at a rate over 10 mT s-1 using an active sample volume of 0.2 um3.

Published
2023
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29. Background Determination for the LUX-ZEPLIN (LZ) Dark Matter Experiment

Author

Aalbers, J., Akerib, D. S., Musalhi, A. K. Al, Alder, F., Alsum, S. K., Amarasinghe, C. S., Ames, A., Anderson, T. J., Angelides, N., Araújo, H. M., Armstrong, J. E., Arthurs, M., Baker, A., Bang, J., Bargemann, J. W., Baxter, A., Beattie, K., Beltrame, P., Bernard, E. P., Bhatti, A., Biekert, A., Biesiadzinski, T. P., Birch, H. J., Blockinger, G. M., Boxer, B., Brew, C. A. J., Brás, P., Burdin, S., Buuck, M., Cabrita, R., Carmona-Benitez, M. C., Chan, C., Chawla, A., Chen, H., Chiang, A. P. S., Chott, N. I., Converse, M. V., Cottle, A., Cox, G., Creaner, O., Dahl, C. E., David, A., Dey, S., de Viveiros, L., Ding, C., Dobson, J. E. Y., Druszkiewicz, E., Eriksen, S. R., Fan, A., Fearon, N. M., Fiorucci, S., Flaecher, H., Fraser, E. D., Fruth, T., Gaitskell, R. J., Genovesi, J., Ghag, C., Gibbons, R., Gilchriese, M. G. D., Gokhale, S., Green, J., van der Grinten, M. G. D., Gwilliam, C. B., Hall, C. R., Han, S., Hartigan-O'Connor, E., Haselschwardt, S. J., Hertel, S. A., Heuermann, G., Horn, M., Huang, D. Q., Hunt, D., Ignarra, C. M., Jacobsen, R. G., Jahangir, O., James, R. S., Johnson, J., Kaboth, A. C., Kamaha, A. C., Khaitan, D., Khurana, I., Kirk, R., Kodroff, D., Korley, L., Korolkova, E. V., Kraus, H., Kravitz, S., Kreczko, L., Krikler, B., Kudryavtsev, V. A., Leason, E. A., Lee, J., Leonard, D. S., Lesko, K. T., Levy, C., Lin, J., Lindote, A., Linehan, R., Lippincott, W. H., Liu, X., Lopes, M. I., Asamar, E. Lopez, Paredes, B. López, Lorenzon, W., Lu, C., Luitz, S., Majewski, P. A., Manalaysay, A., Mannino, R. L., Marangou, N., McCarthy, M. E., McKinsey, D. N., McLaughlin, J., Miller, E. H., Mizrachi, E., Monte, A., Monzani, M. E., Mendoza, J. D. Morales, Morrison, E., Mount, B. J., Murdy, M., Murphy, A. St. J., Naim, D., Naylor, A., Nedlik, C., Nelson, H. N., Neves, F., Nguyen, A., Nikoleyczik, J. A., Olcina, I., Oliver-Mallory, K. C., Orpwood, J., Palladino, K. J., Palmer, J., Parveen, N., Patton, S. J., Penning, B., Pereira, G., Perry, E., Pershing, T., Piepke, A., Porzio, D., Poudel, S., Qie, Y., Reichenbacher, J., Rhyne, C. A., Riffard, Q., Rischbieter, G. R. C., Riyat, H. S., Rosero, R., Rossiter, P., Rushton, T., Santone, D., Sazzad, A. B. M. R., Schnee, R. W., Shaw, S., Shutt, T., Silk, J. J., Silva, C., Sinev, G., Smith, R., Solmaz, M., Solovov, V. N., Sorensen, P., Soria, J., Stancu, I., Stevens, A., Stifter, K., Suerfu, B., Sumner, T. J., Swanson, N., Szydagis, M., Taylor, R., Taylor, W. C., Temples, D. J., Terman, P. A., Tiedt, D. R., Timalsina, M., Tong, Z., Tovey, D. R., Tranter, J., Trask, M., Tripathi, M., Tronstad, D. R., Turner, W., Utku, U., Vaitkus, A. C., Wang, A., Wang, J. J., Wang, W., Wang, Y., Watson, J. R., Webb, R. C., Whitis, T. J., Williams, M., Wolfs, F. L. H., Woodford, S., Woodward, D., Wright, C. J., Xia, Q., Xiang, X., Xu, J., and Yeh, M.

Subjects
High Energy Physics - Experiment, Physics - Instrumentation and Detectors
Abstract

The LUX-ZEPLIN experiment recently reported limits on WIMP-nucleus interactions from its initial science run, down to $9.2\times10^{-48}$ cm$^2$ for the spin-independent interaction of a 36 GeV/c$^2$ WIMP at 90% confidence level. In this paper, we present a comprehensive analysis of the backgrounds important for this result and for other upcoming physics analyses, including neutrinoless double-beta decay searches and effective field theory interpretations of LUX-ZEPLIN data. We confirm that the in-situ determinations of bulk and fixed radioactive backgrounds are consistent with expectations from the ex-situ assays. The observed background rate after WIMP search criteria were applied was $(6.3\pm0.5)\times10^{-5}$ events/keV$_{ee}$/kg/day in the low-energy region, approximately 60 times lower than the equivalent rate reported by the LUX experiment., Comment: 25 pages, 15 figures

Published
2022
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30. Data efficient surrogate modeling for engineering design: Ensemble-free batch mode deep active learning for regression

Author

Vardhan, Harsh, Timalsina, Umesh, Volgyesi, Peter, and Sztipanovits, Janos

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Computer Science - Software Engineering, Mathematics - Numerical Analysis
Abstract

In a computer-aided engineering design optimization problem that involves notoriously complex and time-consuming simulator, the prevalent approach is to replace these simulations with a data-driven surrogate that approximates the simulator's behavior at a much cheaper cost. The main challenge in creating an inexpensive data-driven surrogate is the generation of a sheer number of data using these computationally expensive numerical simulations. In such cases, Active Learning (AL) methods have been used that attempt to learn an input--output behavior while labeling the fewest samples possible. The current trend in AL for a regression problem is dominated by the Bayesian framework that needs training an ensemble of learning models that makes surrogate training computationally tedious if the underlying learning model is Deep Neural Networks (DNNs). However, DNNs have an excellent capability to learn highly nonlinear and complex relationships even for a very high dimensional problem. To leverage the excellent learning capability of deep networks along with avoiding the computational complexity of the Bayesian paradigm, in this work we propose a simple and scalable approach for active learning that works in a student-teacher manner to train a surrogate model. By using this proposed approach, we are able to achieve the same level of surrogate accuracy as the other baselines like DBAL and Monte Carlo sampling with up to 40 % fewer samples. We empirically evaluated this method on multiple use cases including three different engineering design domains:finite element analysis, computational fluid dynamics, and propeller design., Comment: 23 pages, 12 figures

Published
2022

31. How do Regeneration status, Vegetation Diversity, Stand Structure, and Carbon Stock vary across Ecological Regions of Nepal?

Author

Santosh Ayer, Aman Prabhakar, Kishor Adhikari, Subrat Poudel, Sandhya Basnet, Manisha Timalsina, Medha Giri, Prashant Tarami Magar, Saru Lamichane, and Anija Singh

Subjects
Sustainable forest management, Vegetation diversity, Carbon sequestration, Biodiversity conservation, Ecology, QH540-549.5
Abstract

This study compared the regeneration status, vegetation diversity, stand structure, and carbon stock of two community-managed forests located in different ecological regions of Nepal. A total of 61 concentric sample plots were investigated by using systematic random sampling with 1 % sampling intensity. The phytosociological parameters of trees and regeneration density were calculated using standard techniques. The aboveground tree carbon was estimated using a non-destructive method. Correlation analysis was performed to assess the variation of carbon stock with biomass, stand density, tree diameter at breast height (DBH), tree height, basal area, and seedling density. Janata community forest had higher regeneration than the Hazare community forest, with a bell-shaped distribution of DBH in Janata and an interrupted curve in Hazare community forest. Both forests were dominated by Shorea robusta. Hazare had higher Shannon diversity index, Simpson's index, and evenness index, while Janata community forest had higher carbon stock. The observed differences in the studied parameters between the two community forests can be attributed to the difference in ecological factors such as temperature, rainfall, soil nutrient availability, and management practices. Future studies focusing on investigating the underlying factors driving the observed patterns and relationships, such as the effects of disturbance, climate, and management practices on forest structure and function are also needed. These findings have important implications for forest management and conservation policies, especially in the context of climate change mitigation and biodiversity conservation.

Published
2024
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32. Ageing well in Nepal? : exploring the health and social care needs of older adults : a qualitative study in Dhading district of Nepal

Author

Timalsina, Laxmi, Simkhada, Padam, and Sah, Rajeeb

Subjects
Older adults, Senior citizens, Nepal
Abstract

Ageing and older adult care is a new endeavour in Nepal. The attitude and assumptions toward older adults in Nepalese society make it very difficult to derive a clear concept of ageing well. Moreover, there are other factors that act as barriers towards meeting older adults' health and social care needs, such as structural barriers, lack of actual documentation and database, trained manpower, passiveness and lack of concerns from governmental bodies at the local level. Therefore, this research study aims to explore the ageing experiences of older adults residing in the Dhading district of Nepal and develop recommendations for improving the local health and social care and welfare needs of this population. In order to address the key research, aim and objectives, this study has employed a qualitative research approach. The research used purposive sampling to select a total of 54 participants. Semi-structured interviews were used to collect data from 20 older adults over the age of 65 years and 10 stakeholders involved in addressing the health and social care needs of the older adults. In addition, the research collected data using four focus group discussions, each with six participants. This research study found that older adults considered old age as a natural process. The findings show that ageing well and the need for health and social care is multifaceted and interrelated. Older adults consider physical health and functional ability as the key to ageing well. Older adults view ageing both positively and negatively as it provides opportunities as well as many challenges. They place greater emphasis on the fulfilment of basic needs and good physical health as being the key to ageing well. The meaning of ageing well and the components associated with older adults' well-being differed for every individual. Similarly, this research also found that empowerment for older adults comes with good health, education attainment, financial security, family support and social security. The findings from this study suggest an urgent need for older adult care policies to be adopted which could address the concerns of ageing well and the health and social care needs of Nepalese older adults.

Published
2023

33. AIM Photonics Design Enablement: A Design-Assembly-Test Platform Advancing the Silicon-Photonics Ecosystem.

Author

Amit Dikshit, Jin Wallner, M. Jobayer Hossain, M. Rakib Uddin, Javery Mann, Anthony Aiello, Lewis G. Carpenter, Yukta Timalsina, Colin McDonough, Nick Fahrenkopf, Gerald Leake, Christopher Baiocco, Christopher Striemer, Maria Halepis, Daniel Coleman, Amir Begovic, Hao Yang, Michael Zylstra, Jerome Jahn, Jordan Goldstein, Christopher V. Poulton, Todd H. Stievater, Nathan F. Tyndall, Michael Fanto, and David Harame

Published
2024

34. Nanoscale imaging of antiferromagnetic domains in epitaxial films of Cr2O3 via scanning diamond magnetic probe microscopy

Author

Erickson, Adam, Shah, Syed Qamar Abbas, Mahmood, Ather, Fescenko, Ilja, Timalsina, Rupak, Binek, Christian, and Laraoui, Abdelghani

Subjects
Condensed Matter - Materials Science, Condensed Matter - Mesoscale and Nanoscale Physics
Abstract

We report direct imaging of boundary magnetization associated with antiferromagnetic domains in magnetoelectric epitaxial Cr2O3 thin films using diamond nitrogen vacancy microscopy. We found a correlation between magnetic domain size and structural grain size which we associate with the domain formation process. We performed field cooling, i.e., cooling from above to below the N\'eel temperature in the presence of magnetic field, which resulted in the selection of one of the two otherwise degenerate 180 degree domains. Lifting of such a degeneracy is achievable with a magnetic field alone due to the Zeeman energy of a weak parasitic magnetic moment in Cr2O3 films that originates from defects and the imbalance of the boundary magnetization of opposing interfaces. This boundary magnetization couples to the antiferromagnetic order parameter enabling selection of its orientation. Nanostructuring the Cr2O3 film with mesa structures revealed reversible edge magnetic states with the direction of magnetic field during field cooling.

Published
2022
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35. Tetrahedralization of a Hexahedral Mesh

Author

Timalsina, Aman and Knepley, Matthew G.

Subjects
Computer Science - Computational Geometry, Mathematics - Numerical Analysis
Abstract

Two important classes of three-dimensional elements in computational meshes are hexahedra and tetrahedra. While several efficient methods exist that convert a hexahedral element to a tetrahedral elements, the existing algorithm for tetrahedralization of a hexahedral complex is the marching tetrahedron algorithm which limits pre-selection of face divisions. We generalize a procedure for tetrahedralizing triangular prisms to tetrahedralizing cubes, and combine it with certain heuristics to design an algorithm that can triangulate any hexahedra., Comment: The previous version had an error in the proof of Observation 2.1, which has since been rectified in this version. Formatting and title changed

Published
2022

36. First Dark Matter Search Results from the LUX-ZEPLIN (LZ) Experiment

Author

Aalbers, J., Akerib, D. S., Akerlof, C. W., Musalhi, A. K. Al, Alder, F., Alqahtani, A., Alsum, S. K., Amarasinghe, C. S., Ames, A., Anderson, T. J., Angelides, N., Araújo, H. M., Armstrong, J. E., Arthurs, M., Azadi, S., Bailey, A. J., Baker, A., Balajthy, J., Balashov, S., Bang, J., Bargemann, J. W., Barry, M. J., Barthel, J., Bauer, D., Baxter, A., Beattie, K., Belle, J., Beltrame, P., Bensinger, J., Benson, T., Bernard, E. P., Bhatti, A., Biekert, A., Biesiadzinski, T. P., Birch, H. J., Birrittella, B., Blockinger, G. M., Boast, K. E., Boxer, B., Bramante, R., Brew, C. A. J., Brás, P., Buckley, J. H., Bugaev, V. V., Burdin, S., Busenitz, J. K., Buuck, M., Cabrita, R., Carels, C., Carlsmith, D. L., Carlson, B., Carmona-Benitez, M. C., Cascella, M., Chan, C., Chawla, A., Chen, H., Cherwinka, J. J., Chott, N. I., Cole, A., Coleman, J., Converse, M. V., Cottle, A., Cox, G., Craddock, W. W., Creaner, O., Curran, D., Currie, A., Cutter, J. E., Dahl, C. E., David, A., Davis, J., Davison, T. J. R., Delgaudio, J., Dey, S., de Viveiros, L., Dobi, A., Dobson, J. E. Y., Druszkiewicz, E., Dushkin, A., Edberg, T. K., Edwards, W. R., Elnimr, M. M., Emmet, W. T., Eriksen, S. R., Faham, C. H., Fan, A., Fayer, S., Fearon, N. M., Fiorucci, S., Flaecher, H., Ford, P., Francis, V. B., Fraser, E. D., Fruth, T., Gaitskell, R. J., Gantos, N. J., Garcia, D., Geffre, A., Gehman, V. M., Genovesi, J., Ghag, C., Gibbons, R., Gibson, E., Gilchriese, M. G. D., Gokhale, S., Gomber, B., Green, J., Greenall, A., Greenwood, S., van der Grinten, M. G. D., Gwilliam, C. B., Hall, C. R., Hans, S., Hanzel, K., Harrison, A., Hartigan-O'Connor, E., Haselschwardt, S. J., Hertel, S. A., Heuermann, G., Hjemfelt, C., Hoff, M. D., Holtom, E., Hor, J. Y-K., Horn, M., Huang, D. Q., Hunt, D., Ignarra, C. M., Jacobsen, R. G., Jahangir, O., James, R. S., Jeffery, S. N., Ji, W., Johnson, J., Kaboth, A. C., Kamaha, A. C., Kamdin, K., Kasey, V., Kazkaz, K., Keefner, J., Khaitan, D., Khaleeq, M., Khazov, A., Khurana, I., Kim, Y. D., Kocher, C. D., Kodroff, D., Korley, L., Korolkova, E. V., Kras, J., Kraus, H., Kravitz, S., Krebs, H. J., Kreczko, L., Krikler, B., Kudryavtsev, V. A., Kyre, S., Landerud, B., Leason, E. A., Lee, C., Lee, J., Leonard, D. S., Leonard, R., Lesko, K. T., Levy, C., Li, J., Liao, F. -T., Liao, J., Lin, J., Lindote, A., Linehan, R., Lippincott, W. H., Liu, R., Liu, X., Liu, Y., Loniewski, C., Lopes, M. I., Asamar, E. Lopez, Paredes, B. López, Lorenzon, W., Lucero, D., Luitz, S., Lyle, J. M., Majewski, P. A., Makkinje, J., Malling, D. C., Manalaysay, A., Manenti, L., Mannino, R. L., Marangou, N., Marzioni, M. F., Maupin, C., McCarthy, M. E., McConnell, C. T., McKinsey, D. N., McLaughlin, J., Meng, Y., Migneault, J., Miller, E. H., Mizrachi, E., Mock, J. A., Monte, A., Monzani, M. E., Morad, J. A., Mendoza, J. D. Morales, Morrison, E., Mount, B. J., Murdy, M., Murphy, A. St. J., Naim, D., Naylor, A., Nedlik, C., Nehrkorn, C., Neves, F., Nguyen, A., Nikoleyczik, J. A., Nilima, A., O'Dell, J., O'Neill, F. G., O'Sullivan, K., Olcina, I., Olevitch, M. A., Oliver-Mallory, K. C., Orpwood, J., Pagenkopf, D., Pal, S., Palladino, K. J., Palmer, J., Pangilinan, M., Parveen, N., Patton, S. J., Pease, E. K., Penning, B., Pereira, C., Pereira, G., Perry, E., Pershing, T., Peterson, I. B., Piepke, A., Podczerwinski, J., Porzio, D., Powell, S., Preece, R. M., Pushkin, K., Qie, Y., Ratcliff, B. N., Reichenbacher, J., Reichhart, L., Rhyne, C. A., Richards, A., Riffard, Q., Rischbieter, G. R. C., Rodrigues, J. P., Rodriguez, A., Rose, H. J., Rosero, R., Rossiter, P., Rushton, T., Rutherford, G., Rynders, D., Saba, J. S., Santone, D., Sazzad, A. B. M. R., Schnee, R. W., Scovell, P. R., Seymour, D., Shaw, S., Shutt, T., Silk, J. J., Silva, C., Sinev, G., Skarpaas, K., Skulski, W., Smith, R., Solmaz, M., Solovov, V. N., Sorensen, P., Soria, J., Stancu, I., Stark, M. R., Stevens, A., Stiegler, T. M., Stifter, K., Studley, R., Suerfu, B., Sumner, T. J., Sutcliffe, P., Swanson, N., Szydagis, M., Tan, M., Taylor, D. J., Taylor, R., Taylor, W. C., Temples, D. J., Tennyson, B. P., Terman, P. A., Thomas, K. J., Tiedt, D. R., Timalsina, M., To, W. H., Tomás, A., Tong, Z., Tovey, D. R., Tranter, J., Trask, M., Tripathi, M., Tronstad, D. R., Tull, C. E., Turner, W., Tvrznikova, L., Utku, U., Va'vra, J., Vacheret, A., Vaitkus, A. C., Verbus, J. R., Voirin, E., Waldron, W. L., Wang, A., Wang, B., Wang, J. J., Wang, W., Wang, Y., Watson, J. R., Webb, R. C., White, A., White, D. T., White, J. T., White, R. G., Whitis, T. J., Williams, M., Wisniewski, W. J., Witherell, M. S., Wolfs, F. L. H., Wolfs, J. D., Woodford, S., Woodward, D., Worm, S. D., Wright, C. J., Xia, Q., Xiang, X., Xiao, Q., Xu, J., Yeh, M., Yin, J., Young, I., Zarzhitsky, P., Zuckerman, A., and Zweig, E. A.

Subjects
High Energy Physics - Experiment, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

The LUX-ZEPLIN experiment is a dark matter detector centered on a dual-phase xenon time projection chamber operating at the Sanford Underground Research Facility in Lead, South Dakota, USA. This Letter reports results from LUX-ZEPLIN's first search for weakly interacting massive particles (WIMPs) with an exposure of 60~live days using a fiducial mass of 5.5 t. A profile-likelihood ratio analysis shows the data to be consistent with a background-only hypothesis, setting new limits on spin-independent WIMP-nucleon, spin-dependent WIMP-neutron, and spin-dependent WIMP-proton cross sections for WIMP masses above 9 GeV/c$^2$. The most stringent limit is set for spin-independent scattering at 36 GeV/c$^2$, rejecting cross sections above 9.2$\times 10^{-48}$ cm$^2$ at the 90% confidence level., Comment: 9 pages, 8 figures. See https://doi.org/10.1103/PhysRevLett.131.041002 for a data release related to this paper

Published
2022
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37. How to Train Your HiPPO: State Space Models with Generalized Orthogonal Basis Projections

Author

Gu, Albert, Johnson, Isys, Timalsina, Aman, Rudra, Atri, and Ré, Christopher

Subjects
Computer Science - Machine Learning
Abstract

Linear time-invariant state space models (SSM) are a classical model from engineering and statistics, that have recently been shown to be very promising in machine learning through the Structured State Space sequence model (S4). A core component of S4 involves initializing the SSM state matrix to a particular matrix called a HiPPO matrix, which was empirically important for S4's ability to handle long sequences. However, the specific matrix that S4 uses was actually derived in previous work for a particular time-varying dynamical system, and the use of this matrix as a time-invariant SSM had no known mathematical interpretation. Consequently, the theoretical mechanism by which S4 models long-range dependencies actually remains unexplained. We derive a more general and intuitive formulation of the HiPPO framework, which provides a simple mathematical interpretation of S4 as a decomposition onto exponentially-warped Legendre polynomials, explaining its ability to capture long dependencies. Our generalization introduces a theoretically rich class of SSMs that also lets us derive more intuitive S4 variants for other bases such as the Fourier basis, and explains other aspects of training S4, such as how to initialize the important timescale parameter. These insights improve S4's performance to 86% on the Long Range Arena benchmark, with 96% on the most difficult Path-X task.

Published
2022

40. Antibiotic dispensing practices among informal healthcare providers in low-income and middle-income countries: a scoping review protocol

Author

Genevieve C Gore, Madhukar Pai, Poshan Thapa, Giorgia Sulis, Buna Bhandari, Sumanth Gandra, Surbhi Sheokand, Prachi Shukla, Nitin Mudgal, Meera Tandan, Diwash Timalsina, Shweta Bohora, Swostika Thapaliya, Anupama Bhusal, and Chandrashekhar Joshi

Subjects
Medicine
Abstract

Introduction The rise of antimicrobial resistance represents a critical threat to global health, exacerbated by the excessive and inappropriate dispensing and use of antimicrobial drugs, notably antibiotics, which specifically target bacterial infections. The surge in antibiotic consumption globally is particularly concerning in low-income and middle-income countries (LMICs), where informal healthcare providers (IPs) play a vital role in the healthcare landscape. Often the initial point of contact for healthcare-seeking individuals, IPs play a crucial role in delivering primary care services in these regions. Despite the prevalent dispensing of antibiotics by IPs in many LMICs, as highlighted by existing research, there remains a gap in the comprehensive synthesis of antibiotic dispensing practices and the influencing factors among IPs. Hence, this scoping review seeks to map and consolidate the literature regarding antibiotic dispensing and its drivers among IPs in LMICs.Methods and analysis This review will follow the Joanna Briggs Institute guideline for scoping review. A comprehensive search across nine electronic databases (MEDLINE, EMBASE, SCOPUS, Global Health, CINAHL, Web of Science, LILACS, AJOL and IMSEAR) will be performed, supplemented by manual searches of reference lists of eligible publications. The search strategy will impose no constraints on study design, methodology, publication date or language. The study selection process will be reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews. The findings on antibiotic dispensing and its patterns will be synthesised and reported descriptively using tables, visuals and a narrative summary. Additionally, factors influencing antibiotic dispensing will be elucidated through both inductive and deductive content analysis methods.Ethics and dissemination Ethical approval is not required for scoping reviews. The findings will be disseminated through peer-reviewed publications and presentations at relevant conferences.

Published
2024
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41. A Next-Generation Liquid Xenon Observatory for Dark Matter and Neutrino Physics

Author

Aalbers, J., Abe, K., Aerne, V., Agostini, F., Maouloud, S. Ahmed, Akerib, D. S., Akimov, D. Yu., Akshat, J., Musalhi, A. K. Al, Alder, F., Alsum, S. K., Althueser, L., Amarasinghe, C. S., Amaro, F. D., Ames, A., Anderson, T. J., Andrieu, B., Angelides, N., Angelino, E., Angevaare, J., Antochi, V. C., Martin, D. Antón, Antunovic, B., Aprile, E., Araújo, H. M., Armstrong, J. E., Arneodo, F., Arthurs, M., Asadi, P., Baek, S., Bai, X., Bajpai, D., Baker, A., Balajthy, J., Balashov, S., Balzer, M., Bandyopadhyay, A., Bang, J., Barberio, E., Bargemann, J. W., Baudis, L., Bauer, D., Baur, D., Baxter, A., Baxter, A. L., Bazyk, M., Beattie, K., Behrens, J., Bell, N. F., Bellagamba, L., Beltrame, P., Benabderrahmane, M., Bernard, E. P., Bertone, G. F., Bhattacharjee, P., Bhatti, A., Biekert, A., Biesiadzinski, T. P., Binau, A. R., Biondi, R., Biondi, Y., Birch, H. J., Bishara, F., Bismark, A., Blanco, C., Blockinger, G. M., Bodnia, E., Boehm, C., Bolozdynya, A. I., Bolton, P. D., Bottaro, S., Bourgeois, C., Boxer, B., Brás, P., Breskin, A., Breur, P. A., Brew, C. A. J., Brod, J., Brookes, E., Brown, A., Brown, E., Bruenner, S., Bruno, G., Budnik, R., Bui, T. K., Burdin, S., Buse, S., Busenitz, J. K., Buttazzo, D., Buuck, M., Buzulutskov, A., Cabrita, R., Cai, C., Cai, D., Capelli, C., Cardoso, J. M. R., Carmona-Benitez, M. C., Cascella, M., Catena, R., Chakraborty, S., Chan, C., Chang, S., Chauvin, A., Chawla, A., Chen, H., Chepel, V., Chott, N. I., Cichon, D., Chavez, A. Cimental, Cimmino, B., Clark, M., Co, R. T., Colijn, A. P., Conrad, J., Converse, M. V., Costa, M., Cottle, A., Cox, G., Creaner, O., Garcia, J. J. Cuenca, Cussonneau, J. P., Cutter, J. E., Dahl, C. E., D'Andrea, V., David, A., Decowski, M. P., Dent, J. B., Deppisch, F. F., de Viveiros, L., Di Gangi, P., Di Giovanni, A., Di Pede, S., Dierle, J., Diglio, S., Dobson, J. E. Y., Doerenkamp, M., Douillet, D., Drexlin, G., Druszkiewicz, E., Dunsky, D., Eitel, K., Elykov, A., Emken, T., Engel, R., Eriksen, S. R., Fairbairn, M., Fan, A., Fan, J. J., Farrell, S. J., Fayer, S., Fearon, N. M., Ferella, A., Ferrari, C., Fieguth, A., Fiorucci, S., Fischer, H., Flaecher, H., Flierman, M., Florek, T., Foot, R., Fox, P. J., Franceschini, R., Fraser, E. D., Frenk, C. S., Frohlich, S., Fruth, T., Fulgione, W., Fuselli, C., Gaemers, P., Gaior, R., Gaitskell, R. J., Galloway, M., Gao, F., Garcia, I. Garcia, Genovesi, J., Ghag, C., Ghosh, S., Gibson, E., Gil, W., Giovagnoli, D., Girard, F., Glade-Beucke, R., Glück, F., Gokhale, S., de Gouvêa, A., Gráf, L., Grandi, L., Grigat, J., Grinstein, B., van der Grinten, M. G. D., Grössle, R., Guan, H., Guida, M., Gumbsheimer, R., Gwilliam, C. B., Hall, C. R., Hall, L. J., Hammann, R., Han, K., Hannen, V., Hansmann-Menzemer, S., Harata, R., Hardin, S. P., Hardy, E., Hardy, C. A., Harigaya, K., Harnik, R., Haselschwardt, S. J., Hernandez, M., Hertel, S. A., Higuera, A., Hils, C., Hochrein, S., Hoetzsch, L., Hoferichter, M., Hood, N., Hooper, D., Horn, M., Howlett, J., Huang, D. Q., Huang, Y., Hunt, D., Iacovacci, M., Iaquaniello, G., Ide, R., Ignarra, C. M., Iloglu, G., Itow, Y., Jacquet, E., Jahangir, O., Jakob, J., James, R. S., Jansen, A., Ji, W., Ji, X., Joerg, F., Johnson, J., Joy, A., Kaboth, A. C., Kamaha, A. C., Kanezaki, K., Kar, K., Kara, M., Kato, N., Kavrigin, P., Kazama, S., Keaveney, A. W., Kellerer, J., Khaitan, D., Khazov, A., Khundzakishvili, G., Khurana, I., Kilminster, B., Kleifges, M., Ko, P., Kobayashi, M., Kodroff, D., Koltmann, G., Kopec, A., Kopmann, A., Kopp, J., Korley, L., Kornoukhov, V. N., Korolkova, E. V., Kraus, H., Krauss, L. M., Kravitz, S., Kreczko, L., Kudryavtsev, V. A., Kuger, F., Kumar, J., Paredes, B. López, LaCascio, L., Laine, Q., Landsman, H., Lang, R. F., Leason, E. A., Lee, J., Leonard, D. S., Lesko, K. T., Levinson, L., Levy, C., Li, I., Li, S. C., Li, T., Liang, S., Liebenthal, C. S., Lin, J., Lin, Q., Lindemann, S., Lindner, M., Lindote, A., Linehan, R., Lippincott, W. H., Liu, X., Liu, K., Liu, J., Loizeau, J., Lombardi, F., Long, J., Lopes, M. I., Asamar, E. Lopez, Lorenzon, W., Lu, C., Luitz, S., Ma, Y., Machado, P. A. N., Macolino, C., Maeda, T., Mahlstedt, J., Majewski, P. A., Manalaysay, A., Mancuso, A., Manenti, L., Manfredini, A., Mannino, R. L., Marangou, N., March-Russell, J., Marignetti, F., Undagoitia, T. Marrodán, Martens, K., Martin, R., Martinez-Soler, I., Masbou, J., Masson, D., Masson, E., Mastroianni, S., Mastronardi, M., Matias-Lopes, J. A., McCarthy, M. E., McFadden, N., McGinness, E., McKinsey, D. N., McLaughlin, J., McMichael, K., Meinhardt, P., Menéndez, J., Meng, Y., Messina, M., Midha, R., Milisavljevic, D., Miller, E. H., Milosevic, B., Milutinovic, S., Mitra, S. A., Miuchi, K., Mizrachi, E., Mizukoshi, K., Molinario, A., Monte, A., Monteiro, C. M. B., Monzani, M. E., Moore, J. S., Morå, K., Morad, J. A., Mendoza, J. D. Morales, Moriyama, S., Morrison, E., Morteau, E., Mosbacher, Y., Mount, B. J., Mueller, J., Murphy, A. St. J., Murra, M., Naim, D., Nakamura, S., Nash, E., Navaieelavasani, N., Naylor, A., Nedlik, C., Nelson, H. N., Neves, F., Newstead, J. L., Ni, K., Nikoleyczik, J. A., Niro, V., Oberlack, U. G., Obradovic, M., Odgers, K., O'Hare, C. A. J., Oikonomou, P., Olcina, I., Oliver-Mallory, K., Oranday, A., Orpwood, J., Ostrovskiy, I., Ozaki, K., Paetsch, B., Pal, S., Palacio, J., Palladino, K. J., Palmer, J., Panci, P., Pandurovic, M., Parlati, A., Parveen, N., Patton, S. J., Pěč, V., Pellegrini, Q., Penning, B., Pereira, G., Peres, R., Perez-Gonzalez, Y., Perry, E., Pershing, T., Petrossian-Byrne, R., Pienaar, J., Piepke, A., Pieramico, G., Pierre, M., Piotter, M., Pizella, V., Plante, G., Pollmann, T., Porzio, D., Qi, J., Qie, Y., Qin, J., Raj, N., Silva, M. Rajado, Ramanathan, K., García, D. Ramírez, Ravanis, J., Redard-Jacot, L., Redigolo, D., Reichard, S., Reichenbacher, J., Rhyne, C. A., Richards, A., Riffard, Q., Rischbieter, G. R. C., Rocchetti, A., Rosenfeld, S. L., Rosero, R., Rupp, N., Rushton, T., Saha, S., Sanchez, L., Sanchez-Lucas, P., Santone, D., Santos, J. M. F. dos, Sarnoff, I., Sartorelli, G., Sazzad, A. B. M. R., Scheibelhut, M., Schnee, R. W., Schrank, M., Schreiner, J., Schulte, P., Schulte, D., Eissing, H. Schulze, Schumann, M., Schwemberger, T., Schwenk, A., Schwetz, T., Lavina, L. Scotto, Scovell, P. R., Sekiya, H., Selvi, M., Semenov, E., Semeria, F., Shagin, P., Shaw, S., Shi, S., Shockley, E., Shutt, T. A., Si-Ahmed, R., Silk, J. J., Silva, C., Silva, M. C., Simgen, H., Šimkovic, F., Sinev, G., Singh, R., Skulski, W., Smirnov, J., Smith, R., Solmaz, M., Solovov, V. N., Sorensen, P., Soria, J., Sparmann, T. J., Stancu, I., Steidl, M., Stevens, A., Stifter, K., Strigari, L. E., Subotic, D., Suerfu, B., Suliga, A. M., Sumner, T. J., Szabo, P., Szydagis, M., Takeda, A., Takeuchi, Y., Tan, P. -L., Taricco, C., Taylor, W. C., Temples, D. J., Terliuk, A., Terman, P. A., Thers, D., Thieme, K., Thümmler, Th., Tiedt, D. R., Timalsina, M., To, W. H., Toennies, F., Tong, Z., Toschi, F., Tovey, D. R., Tranter, J., Trask, M., Trinchero, G. C., Tripathi, M., Tronstad, D. R., Trotta, R., Tsai, Y. D., Tunnell, C. D., Turner, W. G., Ueno, R., Urquijo, P., Utku, U., Vaitkus, A., Valerius, K., Vassilev, E., Vecchi, S., Velan, V., Vetter, S., Vincent, A. C., Vittorio, L., Volta, G., von Krosigk, B., von Piechowski, M., Vorkapic, D., Wagner, C. E. M., Wang, A. M., Wang, B., Wang, Y., Wang, W., Wang, J. J., Wang, L. -T., Wang, M., Watson, J. R., Wei, Y., Weinheimer, C., Weisman, E., Weiss, M., Wenz, D., West, S. M., Whitis, T. J., Williams, M., Wilson, M. J., Winkler, D., Wittweg, C., Wolf, J., Wolf, T., Wolfs, F. L. H., Woodford, S., Woodward, D., Wright, C. J., Wu, V. H. S., Wu, P., Wüstling, S., Wurm, M., Xia, Q., Xiang, X., Xing, Y., Xu, J., Xu, Z., Xu, D., Yamashita, M., Yamazaki, R., Yan, H., Yang, L., Yang, Y., Ye, J., Yeh, M., Young, I., Yu, H. B., Yu, T. T., Yuan, L., Zavattini, G., Zerbo, S., Zhang, Y., Zhong, M., Zhou, N., Zhou, X., Zhu, T., Zhu, Y., Zhuang, Y., Zopounidis, J. P., Zuber, K., and Zupan, J.

Subjects
Physics - Instrumentation and Detectors, Astrophysics - Cosmology and Nongalactic Astrophysics, High Energy Physics - Experiment, Nuclear Experiment
Abstract

The nature of dark matter and properties of neutrinos are among the most pressing issues in contemporary particle physics. The dual-phase xenon time-projection chamber is the leading technology to cover the available parameter space for Weakly Interacting Massive Particles (WIMPs), while featuring extensive sensitivity to many alternative dark matter candidates. These detectors can also study neutrinos through neutrinoless double-beta decay and through a variety of astrophysical sources. A next-generation xenon-based detector will therefore be a true multi-purpose observatory to significantly advance particle physics, nuclear physics, astrophysics, solar physics, and cosmology. This review article presents the science cases for such a detector., Comment: 77 pages, 40 figures, 1262 references

Published
2022
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42. Cosmogenic production of $^{37}$Ar in the context of the LUX-ZEPLIN experiment

Author

Aalbers, J., Akerib, D. S., Musalhi, A. K. Al, Alder, F., Alsum, S. K., Amarasinghe, C. S., Ames, A., Anderson, T. J., Angelides, N., Araújo, H. M., Armstrong, J. E., Arthurs, M., Bai, X., Baker, A., Balajthy, J., Balashov, S., Bang, J., Bargemann, J. W., Bauer, D., Baxter, A., Beattie, K., Bernard, E. P., Bhatti, A., Biekert, A., Biesiadzinski, T. P., Birch, H. J., Blockinger, G. M., Bodnia, E., Boxer, B., Brew, C. A. J., Brás, P., Burdin, S., Busenitz, J. K., Buuck, M., Cabrita, R., Carmona-Benitez, M. C., Cascella, M., Chan, C., Chawla, A., Chen, H., Chott, N. I., Cole, A., Converse, M. V., Cottle, A., Cox, G., Creaner, O., Cutter, J. E., Dahl, C. E., David, A., de Viveiros, L., Dobson, J. E. Y., Druszkiewicz, E., Eriksen, S. R., Fan, A., Fayer, S., Fearon, N. M., Fiorucci, S., Flaecher, H., Fraser, E. D., Fruth, T., Gaitskell, R. J., Genovesi, J., Ghag, C., Gibson, E., Gilchriese, M. G. D., Gokhale, S., van der Grinten, M. G. D., Gwilliam, C. B., Hall, C. R., Haselschwardt, S. J., Hertel, S. A., Horn, M., Huang, D. Q., Hunt, D., Ignarra, C. M., Jahangir, O., James, R. S., Ji, W., Johnson, J., Kaboth, A. C., Kamaha, A. C., Kamdin, K., Khaitan, D., Khazov, A., Khurana, I., Kodroff, D., Korley, L., Korolkova, E. V., Kraus, H., Kravitz, S., Kreczko, L., Kudryavtsev, V. A., Leason, E. A., Leonard, D. S., Lesko, K. T., Levy, C., Lee, J., Lin, J., Lindote, A., Linehan, R., Lippincott, W. H., Liu, X., Lopes, M. I., Asamar, E. Lopez, Lopez-Paredes, B., Lorenzon, W., Luitz, S., Majewski, P. A., Manalaysay, A., Manenti, L., Mannino, R. L., Marangou, N., McCarthy, M. E., McKinsey, D. N., McLaughlin, J., Miller, E. H., Mizrachi, E., Monte, A., Monzani, M. E., Morad, J. A., Mendoza, J. D. Morales, Morrison, E., Mount, B. J., Murphy, A. St. J., Naim, D., Naylor, A., Nedlik, C., Nelson, H. N., Neves, F., Nikoleyczik, J. A., Nilima, A., Olcina, I., Oliver-Mallory, K., Pal, S., Palladino, K. J., Palmer, J., Parveen, N., Patton, S. J., Pease, E. K., Penning, B., Pereira, G., Perry, E., Pershing, J., Piepke, A., Porzio, D., Qie, Y., Reichenbacher, J., Rhyne, C. A., Richards, A., Riffard, Q., Riffard, %Q., Rischbieter, G. R. C., Rosero, R., Rossiter, P., Rushton, T., Santone, D., Sazzad, A. B. M. R., Schnee, R. W., Scovell, P. R., Shaw, S., Shutt, T. A., Silk, J. J., Silva, C., Sinev, G., Smith, R., Solmaz, M., Solovov, V. N., Sorensen, P., Soria, J., Stancu, I., Stevens, A., Stifter, K., Suerfu, B., Sumner, T. J., Swanson, N., Szydagis, M., Taylor, W. C., Taylor, R., Temples, D. J., Terman, P. A., Tiedt, D. R., Timalsina, M., To, W. H., Tong, Z., Tovey, D. R., Trask, M., Tripathi, M., Tronstad, D. R., Turner, W., Utku, U., Vaitkus, A., Wang, B., Wang, Y., Wang, J. J., Wang, W., Watson, J. R., Webb, R. C., White, R. G., Whitis, T. J., Williams, M., Wolfs, F. L. H., Woodford, S., Woodward, D., Wright, C. J., Xia, Q., Xiang, X., Xu, J., and Yeh, M.

Subjects
High Energy Physics - Experiment, Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics, High Energy Physics - Phenomenology
Abstract

We estimate the amount of $^{37}$Ar produced in natural xenon via cosmic ray-induced spallation, an inevitable consequence of the transportation and storage of xenon on the Earth's surface. We then calculate the resulting $^{37}$Ar concentration in a 10-tonne payload~(similar to that of the LUX-ZEPLIN experiment) assuming a representative schedule of xenon purification, storage and delivery to the underground facility. Using the spallation model by Silberberg and Tsao, the sea level production rate of $^{37}$Ar in natural xenon is estimated to be 0.024~atoms/kg/day. Assuming the xenon is successively purified to remove radioactive contaminants in 1-tonne batches at a rate of 1~tonne/month, the average $^{37}$Ar activity after 10~tonnes are purified and transported underground is 0.058--0.090~$\mu$Bq/kg, depending on the degree of argon removal during above-ground purification. Such cosmogenic $^{37}$Ar will appear as a noticeable background in the early science data, while decaying with a 35~day half-life. This newly-noticed production mechanism of $^{37}$Ar should be considered when planning for future liquid xenon-based experiments.

Published
2022
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43. Team-based Learning versus Problem-based Learning among First-year Medical Students in Biochemistry: A Quasi-experimental Study

Author

Smita Pakhmode, Manju Chandankhede, Amruta Dashputra, Madhur Gupta, Swati Panbude, and Dilip R Timalsina

Subjects
active teaching learning method, critical thinking skills, knowledge retention, learning gain, medical education, Medicine
Abstract

Introduction: Team-based Learning (TBL) and Problem-based Learning (PBL), both active teaching methodologies, are known for improving problem-solving abilities, clinical reasoning, and motivating students for self-directed studies. Although both active methods, TBL and PBL, differ in methodology and required resources, it is always a challenge to choose active methods that are more feasible and effective in the undergraduate medical curriculum. Aim: To compare two active teaching strategies, viz., the effectiveness of TBL vs. PBL in first-year Bachelor of Medicine, Bachelor of Surgery (MBBS) students in terms of learning outcomes, development of critical thinking skills, and retention of knowledge. Materials and Methods: This quasi-experimental study was conducted at Department of Biochemistry, NKP Salve Medical College and RC Nagpur, Maharashtra, India from August 2017 to October 2017. A total of 150 first-year MBBS students were included in the study. TBL and PBL were performed following the protocols of their respective methodologies, and scores for learning gain and critical thinking were compared between the TBL and PBL groups. Student perception regarding the procedures was collected using a prevalidated structured questionnaire. The retention of knowledge was assessed by comparing scores from a pretest and a test conducted two months later. Data were statistically analysed using the Wilcoxon signed-rank test and the Mann-Whitney U test. Results: In the present study, the mean age of the participating students was 20±2 years. Post-test results, obtained just after the intervention, demonstrated a significant learning gain in students using both methods, with a statistically higher gain in TBL (p-value

Published
2023
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44. Effects of Pore Fluid’s pH on the Physico-Mechanical Behavior of High Plasticity Silt

Author

Bhim Kumar Dahal, Santosh Pokhrel, Saroj Basnet, Uttam Dahal, Shivam Kumar Sah, Sneha Neopane, Sinam Adhikari, and Susmita Timalsina

Subjects
pollution, water quality, ph, acidity, soil mechanics, alkalinity, Ecology, QH540-549.5
Abstract

Acid rain and water pollution are alarming threats, necessitating the study of their influences in different environmental aspects. This study investigates the effects of pore water’s pH on the behavior of high plasticity silt. Samples with varied pore fluid pH were tested for Atterberg limits, unconfined compressive strength on the 9th, 18th, and 27th curing days. Particle size distribution and zeta potential were assessed on the 27th day on strength tested samples. The test showed that the soil properties change with the pH of the pore fluid and the days the sample were cured for. The particle size distribution revealed that higher silt and clay fractions were present in acidic and alkaline conditions respectively. Liquid limit varied irregularly with different pH conditions. On all test days, the plastic limit increased under acidic and alkaline conditions compared to neutral conditions. The Unconfined compressive strength and zeta potential were observed to be low in the acidic and alkaline conditions compared to the neutral condition. The result infers that the dissolution of cementitious elements in acidic and alkaline conditions reduces the long-term strength of the soil. These findings encourage geotechnical engineers to evaluate the pH characteristics of the pore fluids during geotechnical analysis.

Published
2023
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