911 research outputs found

    Photon collider search strategy for sleptons and dark matter at the LHC

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    We propose a search strategy using the LHC as a photon collider to open sensitivity to scalar lepton (slepton ~\tilde{\ell}) production with masses around 15 to 60 GeV above that of neutralino dark matter χ~10\tilde{\chi}^0_1. This region is favored by relic abundance and muon (g2)μ(g-2)_\mu arguments. However, conventional searches are hindered by the irreducible diboson background. We overcome this obstruction by measuring initial state kinematics and the missing momentum four-vector in proton-tagged ultraperipheral collisions using forward detectors. We demonstrate sensitivity beyond LEP for slepton masses of up to 220 GeV for 15Δm(~,χ~10)60 15 \lesssim \Delta m(\tilde{\ell}, \tilde{\chi}^0_1) \lesssim 60 GeV with 100 fb1^{-1} of 13 TeV proton collisions. We encourage the LHC collaborations to open this forward frontier for discovering new physics.Comment: 4 pages + bibliography, 3 figure

    Shadows of Universalism: The Untold Story of Human Rights around 1948

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    How did the idea of self-determination get written into human rights after World War II? And by whom? In this article, Lydia H. Liu reopens the history of how the postwar norms of human rights were radically transformed by an unexpected clash with the classical standard of civilization in international law. She analyzes the drafting of the document of the Universal Declaration of Human Rights as well as the UN debates surrounding it to explore the translingual forging of universalism in the multiple temporalities of global history

    Design Guidelines for Prompt Engineering Text-to-Image Generative Models

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    Text-to-image generative models are a new and powerful way to generate visual artwork. However, the open-ended nature of text as interaction is double-edged; while users can input anything and have access to an infinite range of generations, they also must engage in brute-force trial and error with the text prompt when the result quality is poor. We conduct a study exploring what prompt keywords and model hyperparameters can help produce coherent outputs. In particular, we study prompts structured to include subject and style keywords and investigate success and failure modes of these prompts. Our evaluation of 5493 generations over the course of five experiments spans 51 abstract and concrete subjects as well as 51 abstract and figurative styles. From this evaluation, we present design guidelines that can help people produce better outcomes from text-to-image generative models
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