<div dir="ltr"><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:5pt"><span style="font-size:18pt;font-family:Times,serif;color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><font size="4" style="color:rgb(34,34,34);font-family:Arial,Helvetica,sans-serif;white-space:normal">Dear all,</font></span></p><div><br></div><div><span style="font-size:large">Here is the information about <span class="gmail-il">next</span> <span class="gmail-il">week</span>'s <span class="gmail-il">theory</span> <span class="gmail-il">seminar</span>:</span><br></div><div><font size="4"><br></font></div><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:5pt"><span style="font-size:18pt;font-family:Times,serif;color:rgb(0,0,0);background-color:transparent;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"></span></p><div><font size="4"><b><u><span class="gmail-il">Theory</span> <span class="gmail-il">seminar</span></u></b><br>Monday November 30,<font color="#000000"> 9:00 AM</font><br></font><div><font size="4"><br><b>Gurtej Kanwar</b> (MIT) will talk about "Ensemble generation for lattice QFT using machine learning".<br><br><u>Abstract:</u></font></div><div><div name="messageBodySection"><p class="MsoNormal" style="margin:0in;font-family:Calibri,sans-serif"><span style="font-family:Arial,Helvetica,sans-serif"><font size="4">Monte Carlo sampling is a powerful method to compute observables in quantum field theories regularized on a discrete spacetime lattice (LQFT), which is necessary for example to study the non-perturbative behavior of QCD in the low-energy regime. The cost of drawing independent samples is a major bottleneck in such studies. I discuss our recent work demonstrating that generative machine-learning models can be used to perform Monte Carlo sampling and produce unbiased estimates of observables in LQFT. This work lays out a framework for exactly encoding translational and gauge symmetries in these models, making training practically viable.</font></span><br></p></div></div><div><font size="4"><br>Bluejeans connection: </font><a href="https://urldefense.proofpoint.com/v2/url?u=https-3A__bluejeans.com_801786278&d=DwMFaQ&c=CJqEzB1piLOyyvZjb8YUQw&r=AIMSQQ81YDyrZuJNGks2qw&m=aT_3J5jjiFmHtFXffqbfPqEY_A73NEWw2ebyFyL_eCA&s=YNm3qgT5e8sJgKfZ9vFA_w--imuXwmeAjg0C4AslLwg&e=" target="_blank"><font size="4">https://bluejeans.com/801786278</font></a><br><font size="4"><br>Happy Thanksgiving weekend!</font><br><font size="4">Astrid, Christos, Filippo</font></div></div></div>