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<button class="button is-small is-link">Go</button> </div> </div> </form> </div> </div> <ol class="breathe-horizontal" start="1"> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2203.11226">arXiv:2203.11226</a> <span> [<a href="https://arxiv.org/pdf/2203.11226">pdf</a>, <a href="https://arxiv.org/format/2203.11226">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Cosmology and Nongalactic Astrophysics">astro-ph.CO</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Instrumentation and Methods for Astrophysics">astro-ph.IM</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="High Energy Physics - Experiment">hep-ex</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="High Energy Physics - Phenomenology">hep-ph</span> </div> </div> <p class="title is-5 mathjax"> Snowmass2021 Cosmic Frontier CF6 White Paper: Multi-Experiment Probes for Dark Energy -- Transients </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/hep-ph?searchtype=author&query=Kim%2C+A+G">Alex G. Kim</a>, <a href="/search/hep-ph?searchtype=author&query=Palmese%2C+A">Antonella Palmese</a>, <a href="/search/hep-ph?searchtype=author&query=Pereira%2C+M+E+S">Maria E. S. Pereira</a>, <a href="/search/hep-ph?searchtype=author&query=Aldering%2C+G">Greg Aldering</a>, <a href="/search/hep-ph?searchtype=author&query=Andrade-Oliveira%2C+F">Felipe Andrade-Oliveira</a>, <a href="/search/hep-ph?searchtype=author&query=Annis%2C+J">James Annis</a>, <a href="/search/hep-ph?searchtype=author&query=Bailey%2C+S">Stephen Bailey</a>, <a href="/search/hep-ph?searchtype=author&query=BenZvi%2C+S">Segev BenZvi</a>, <a href="/search/hep-ph?searchtype=author&query=Braga-Neto%2C+U">Ulysses Braga-Neto</a>, <a href="/search/hep-ph?searchtype=author&query=Courbin%2C+F">Fr茅d茅ric Courbin</a>, <a href="/search/hep-ph?searchtype=author&query=Garcia%2C+A">Alyssa Garcia</a>, <a href="/search/hep-ph?searchtype=author&query=Jeffery%2C+D">David Jeffery</a>, <a href="/search/hep-ph?searchtype=author&query=Narayan%2C+G">Gautham Narayan</a>, <a href="/search/hep-ph?searchtype=author&query=Perlmutter%2C+S">Saul Perlmutter</a>, <a href="/search/hep-ph?searchtype=author&query=Soares-Santos%2C+M">Marcelle Soares-Santos</a>, <a href="/search/hep-ph?searchtype=author&query=Treu%2C+T">Tommaso Treu</a>, <a href="/search/hep-ph?searchtype=author&query=Wang%2C+L">Lifan Wang</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2203.11226v2-abstract-short" style="display: inline;"> This invited Snowmass 2021 White Paper highlights the power of joint-analysis of astronomical transients in advancing HEP Science and presents research activities that can realize the opportunities that come with current and upcoming projects. Transients of interest include gravitational wave events, neutrino events, strongly-lensed quasars and supernovae, and Type~Ia supernovae specifically. Thes… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2203.11226v2-abstract-full').style.display = 'inline'; document.getElementById('2203.11226v2-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2203.11226v2-abstract-full" style="display: none;"> This invited Snowmass 2021 White Paper highlights the power of joint-analysis of astronomical transients in advancing HEP Science and presents research activities that can realize the opportunities that come with current and upcoming projects. Transients of interest include gravitational wave events, neutrino events, strongly-lensed quasars and supernovae, and Type~Ia supernovae specifically. These transients can serve as probes of cosmological distances in the Universe and as cosmic laboratories of extreme strong-gravity, high-energy physics. Joint analysis refers to work that requires significant coordination from multiple experiments or facilities so encompasses Multi-Messenger Astronomy and optical transient discovery and distributed follow-up programs. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2203.11226v2-abstract-full').style.display = 'none'; document.getElementById('2203.11226v2-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 4 October, 2022; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 21 March, 2022; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> March 2022. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">Minor updates to align with the feedback from the Snowmass Community Summer Study Workshop</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2203.08056">arXiv:2203.08056</a> <span> [<a href="https://arxiv.org/pdf/2203.08056">pdf</a>, <a href="https://arxiv.org/ps/2203.08056">ps</a>, <a href="https://arxiv.org/format/2203.08056">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="High Energy Physics - Phenomenology">hep-ph</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Cosmology and Nongalactic Astrophysics">astro-ph.CO</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Instrumentation and Methods for Astrophysics">astro-ph.IM</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Machine Learning">cs.LG</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Machine Learning">stat.ML</span> </div> </div> <p class="title is-5 mathjax"> Machine Learning and Cosmology </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/hep-ph?searchtype=author&query=Dvorkin%2C+C">Cora Dvorkin</a>, <a href="/search/hep-ph?searchtype=author&query=Mishra-Sharma%2C+S">Siddharth Mishra-Sharma</a>, <a href="/search/hep-ph?searchtype=author&query=Nord%2C+B">Brian Nord</a>, <a href="/search/hep-ph?searchtype=author&query=Villar%2C+V+A">V. Ashley Villar</a>, <a href="/search/hep-ph?searchtype=author&query=Avestruz%2C+C">Camille Avestruz</a>, <a href="/search/hep-ph?searchtype=author&query=Bechtol%2C+K">Keith Bechtol</a>, <a href="/search/hep-ph?searchtype=author&query=%C4%86iprijanovi%C4%87%2C+A">Aleksandra 膯iprijanovi膰</a>, <a href="/search/hep-ph?searchtype=author&query=Connolly%2C+A+J">Andrew J. Connolly</a>, <a href="/search/hep-ph?searchtype=author&query=Garrison%2C+L+H">Lehman H. Garrison</a>, <a href="/search/hep-ph?searchtype=author&query=Narayan%2C+G">Gautham Narayan</a>, <a href="/search/hep-ph?searchtype=author&query=Villaescusa-Navarro%2C+F">Francisco Villaescusa-Navarro</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2203.08056v1-abstract-short" style="display: inline;"> Methods based on machine learning have recently made substantial inroads in many corners of cosmology. Through this process, new computational tools, new perspectives on data collection, model development, analysis, and discovery, as well as new communities and educational pathways have emerged. Despite rapid progress, substantial potential at the intersection of cosmology and machine learning rem… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2203.08056v1-abstract-full').style.display = 'inline'; document.getElementById('2203.08056v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2203.08056v1-abstract-full" style="display: none;"> Methods based on machine learning have recently made substantial inroads in many corners of cosmology. Through this process, new computational tools, new perspectives on data collection, model development, analysis, and discovery, as well as new communities and educational pathways have emerged. Despite rapid progress, substantial potential at the intersection of cosmology and machine learning remains untapped. In this white paper, we summarize current and ongoing developments relating to the application of machine learning within cosmology and provide a set of recommendations aimed at maximizing the scientific impact of these burgeoning tools over the coming decade through both technical development as well as the fostering of emerging communities. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2203.08056v1-abstract-full').style.display = 'none'; document.getElementById('2203.08056v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 15 March, 2022; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> March 2022. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">Contribution to Snowmass 2021. 32 pages</span> 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