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1. Update on Glueballs

   https://doi.org/10.22323/1.466.0004  

   Morningstar, Colin (February 2025, Sissa Medialab)

   The recent BESIII announcement of a pseudoscalar glueball candidate makes an update on glueballs from lattice QCD timely. A brief review of how glueballs are studied in lattice QCD is given, and the reasons that glueballs are difficult to study both in lattice QCD with dynamical quarks and in experiments are outlined. Recent glueball studies in lattice QCD are then presented, and an exploratory investigation of the scalar glueball using glueball, meson, and meson-meson operators is summarized, suggesting that no scalar state below 2 GeV or so can be considered to be predominantly a glueball state. 

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2. Abstractions for Reconfigurable Hybrid Network Update and A Consistent Update Approach

   Wand, Weitao; Das, Sushovan; Ng, T. S. (August 2021, ACM SIGCOMM 2021 Workshop on Optical Systems (OptSys'21))

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3. Sparse Exact Factorization Update

   https://doi.org/10.1109/ia354616.2021.00012  

   Chen, Jinhao; Davis, Timothy A.; Lourenco, Christopher; Moreno-Centeno, Erick (November 2021, 2021 IEEE/ACM 11th Workshop on Irregular Applications: Architectures and Algorithms (IA3))

   To meet the growing need for extended or exact precision solvers, an efficient framework based on Integer-Preserving Gaussian Elimination (IPGE) has been recently developed, which includes dense/sparse LU/Cholesky factorizations and dense LU/Cholesky factorization updates for column and/or row replacement. This paper discusses our ongoing work developing the sparse LU/Cholesky column/row-replacement update and the sparse rank-l update/downdate. We first present some basic background for the exact factorization framework based on IPGE. Then we give our proposed algorithms along with some implementation and data-structure details. Finally, we provide some experimental results showcasing the performance of our update algorithms. Specifically, we show that updating these exact factorizations can typically be 10x to 100x faster than (re-)factorizing the matrices from scratch. 

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4. texas-skew-update-2021

   https://doi.org/10.18738/T8/SVLCOQ  

   Cleveland, Theodore G.; null (January 2021, Texas Data Repository)

   A permanent copy of a data repository resulting from project 0-6977 Update Texas Skew Coefficients, including interim reports and the final report (as pdf and source) When the data are final this sentence will be deleted 

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5. Towards Optimal Tradeoff Between Data Freshness and Update Cost in Information-update Systems

   https://doi.org/10.1109/ICCCN54977.2022.9868923  

   Liu, Z.; Li, B.; Zheng, Z.; Hou, Y. T.; Ji, B. (April 2023, IEEE internet of things journal)