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Dear all, </div>
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On Wednesday, November 13<sup>th</sup>, 2024 at 1pm EST, we will have a cake seminar given by Alex Gnech of ODU in CC L102 and on the following Zoom link: </div>
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<a href="https://jlab-org.zoomgov.com/j/1619211940?pwd=Sk0WFJqWsKqjWsZhcFao7VjNHdzIxf.1" id="LPlnk">https://jlab-org.zoomgov.com/j/1619211940?pwd=Sk0WFJqWsKqjWsZhcFao7VjNHdzIxf.1</a></div>
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Attendance in person is highly encouraged. Please see below for the title and abstract. </div>
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<b><u>Cake Seminar</u></b>:<b> </b>Wednesday, November 13<sup>th</sup>, 2024 at 1pm EST</div>
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<b><u>Speaker</u></b>: Alex Gnech (ODU) </div>
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<b><u>Title</u></b>:<b> </b>Studying nuclear structure via neural-network quantum states </div>
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<span style="color: rgb(0, 0, 0);"><b><u>Abstract</u></b>: </span><span style="color: rgb(36, 36, 36);">Neural-networks and machine learning techniques are nowadays explored to approach long standing problems that belongs to low-energy nuclear physics in innovative
ways. In this Cake Seminar we will present the application of neural-networks to solve the nuclear many-body problem. We will introduce a variational Monte Carlo method based on a new, highly-expressive, neural-network quantum state ansatz that permits to
solve the many-body schrödinger equation in a systematical and improvable way. In particular we will focus on the computation of ground-state properties of atomic nuclei with up to A= 20 nucleons, using as input a leading order pionless effective field theory
Hamiltonian. Finally we will present the first calculation of electromagnetic properties as well as electroweak transitions computed using the neural-network quantum state wave functions. </span></div>
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See you on Wednesday. </div>
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Best regards, </div>
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Joe, Zheng-Yang & Gloria</div>
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