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</div> <div class="control"> <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/2111.11310">arXiv:2111.11310</a> <span> [<a href="https://arxiv.org/pdf/2111.11310">pdf</a>, <a href="https://arxiv.org/format/2111.11310">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Plasma Physics">physics.plasm-ph</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="High Energy Physics - Phenomenology">hep-ph</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.1038/s41586-021-03382-w">10.1038/s41586-021-03382-w <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> The data-driven future of high energy density physics </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/physics?searchtype=author&query=Hatfield%2C+P+W">Peter W. Hatfield</a>, <a href="/search/physics?searchtype=author&query=Gaffney%2C+J+A">Jim A. Gaffney</a>, <a href="/search/physics?searchtype=author&query=Anderson%2C+G+J">Gemma J. Anderson</a>, <a href="/search/physics?searchtype=author&query=Ali%2C+S">Suzanne Ali</a>, <a href="/search/physics?searchtype=author&query=Antonelli%2C+L">Luca Antonelli</a>, <a href="/search/physics?searchtype=author&query=Pree%2C+S+B+d">Suzan Ba艧e臒mez du Pree</a>, <a href="/search/physics?searchtype=author&query=Citrin%2C+J">Jonathan Citrin</a>, <a href="/search/physics?searchtype=author&query=Fajardo%2C+M">Marta Fajardo</a>, <a href="/search/physics?searchtype=author&query=Knapp%2C+P">Patrick Knapp</a>, <a href="/search/physics?searchtype=author&query=Kettle%2C+B">Brendan Kettle</a>, <a href="/search/physics?searchtype=author&query=Kustowski%2C+B">Bogdan Kustowski</a>, <a href="/search/physics?searchtype=author&query=MacDonald%2C+M+J">Michael J. MacDonald</a>, <a href="/search/physics?searchtype=author&query=Mariscal%2C+D">Derek Mariscal</a>, <a href="/search/physics?searchtype=author&query=Martin%2C+M+E">Madison E. Martin</a>, <a href="/search/physics?searchtype=author&query=Nagayama%2C+T">Taisuke Nagayama</a>, <a href="/search/physics?searchtype=author&query=Palmer%2C+C+A+J">Charlotte A. J. Palmer</a>, <a href="/search/physics?searchtype=author&query=Peterson%2C+J+L">J. Luc Peterson</a>, <a href="/search/physics?searchtype=author&query=Rose%2C+S">Steven Rose</a>, <a href="/search/physics?searchtype=author&query=Ruby%2C+J+J">J J Ruby</a>, <a href="/search/physics?searchtype=author&query=Shneider%2C+C">Carl Shneider</a>, <a href="/search/physics?searchtype=author&query=Streeter%2C+M+J+V">Matt J. V. Streeter</a>, <a href="/search/physics?searchtype=author&query=Trickey%2C+W">Will Trickey</a>, <a href="/search/physics?searchtype=author&query=Williams%2C+B">Ben Williams</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="2111.11310v1-abstract-short" style="display: inline;"> The study of plasma physics under conditions of extreme temperatures, densities and electromagnetic field strengths is significant for our understanding of astrophysics, nuclear fusion and fundamental physics. These extreme physical systems are strongly non-linear and very difficult to understand theoretically or optimize experimentally. Here, we argue that machine learning models and data-driven… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2111.11310v1-abstract-full').style.display = 'inline'; document.getElementById('2111.11310v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2111.11310v1-abstract-full" style="display: none;"> The study of plasma physics under conditions of extreme temperatures, densities and electromagnetic field strengths is significant for our understanding of astrophysics, nuclear fusion and fundamental physics. These extreme physical systems are strongly non-linear and very difficult to understand theoretically or optimize experimentally. Here, we argue that machine learning models and data-driven methods are in the process of reshaping our exploration of these extreme systems that have hitherto proven far too non-linear for human researchers. From a fundamental perspective, our understanding can be helped by the way in which machine learning models can rapidly discover complex interactions in large data sets. From a practical point of view, the newest generation of extreme physics facilities can perform experiments multiple times a second (as opposed to ~daily), moving away from human-based control towards automatic control based on real-time interpretation of diagnostic data and updates of the physics model. To make the most of these emerging opportunities, we advance proposals for the community in terms of research design, training, best practices, and support for synthetic diagnostics and data analysis. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2111.11310v1-abstract-full').style.display = 'none'; document.getElementById('2111.11310v1-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> 22 November, 2021; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2021. </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">14 pages, 4 figures. This work was the result of a meeting at the Lorentz Center, University of Leiden, 13th-17th January 2020. This is a preprint of Hatfield et al., Nature, 593, 7859, 351-361 (2021) https://www.nature.com/articles/s41586-021-03382-w</span> </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Journal ref:</span> Nature, 593, 7859, 351-361, 2021 </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/1905.08215">arXiv:1905.08215</a> <span> [<a href="https://arxiv.org/pdf/1905.08215">pdf</a>, <a href="https://arxiv.org/format/1905.08215">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Plasma Physics">physics.plasm-ph</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.1063/1.5091985">10.1063/1.5091985 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> The Blind Implosion-Maker - Automated Inertial Confinement Fusion experiment design </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/physics?searchtype=author&query=Hatfield%2C+P+W">P. W. Hatfield</a>, <a href="/search/physics?searchtype=author&query=Rose%2C+S+J">S. J. Rose</a>, <a href="/search/physics?searchtype=author&query=Scott%2C+R+H+H">R. H. H. Scott</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="1905.08215v1-abstract-short" style="display: inline;"> The design of inertial confinement fusion experiments, alongside improving the development of energy density physics theory and experimental methods, is one of the key challenges in the quest for nuclear fusion as a viable energy source. Recent challenges in achieving a high-yield implosion at the National Ignition Facility (NIF) have led to new interest in considering a much wider design paramete… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1905.08215v1-abstract-full').style.display = 'inline'; document.getElementById('1905.08215v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="1905.08215v1-abstract-full" style="display: none;"> The design of inertial confinement fusion experiments, alongside improving the development of energy density physics theory and experimental methods, is one of the key challenges in the quest for nuclear fusion as a viable energy source. Recent challenges in achieving a high-yield implosion at the National Ignition Facility (NIF) have led to new interest in considering a much wider design parameter space than normally studied. Here we report an algorithmic approach that can produce reasonable ICF designs with minimal assumptions. In particular we use the genetic algorithm metaheuristic, in which `populations' of implosions are simulated, the design of capsule is described by a `genome', natural selection removes poor designs, high quality designs are `mated' with each other based on their yield, and designs undergo `mutations' to introduce new ideas. We show that it takes ~5x10^4 simulations for the algorithm to find an original NIF design. We also link this method to other parts of the design process and look towards a completely automated ICF experiment design process - changing ICF from an experiment design problem to an algorithm design problem. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1905.08215v1-abstract-full').style.display = 'none'; document.getElementById('1905.08215v1-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> 20 May, 2019; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> May 2019. </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">11 pages, 7 figures. The following article has been accepted by Physics of Plasmas. 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