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Greetings everyone, </div>
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Tomorrow, o</span><span style="font-size: 14.67px; color: black;">n Monday, </span>
<span style="font-size: 11pt; color: rgb(0, 0, 0); background-color: white;">May 12</span><span style="font-size: 14.67px; color: black;"><sup>th</sup>, 2025 at 1:00PM EDT,
</span><span style="font-size: 11pt; color: black;">we will have a virtual seminar given by
</span><span style="font-size: 11pt; color: black; background-color: white;">Yi Chen of Vanderbilt University</span><span style="font-size: 11pt; color: rgb(0, 0, 0); background-color: white;"> on the following Zoom link: </span></div>
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<span style="background-color: rgb(255, 255, 255);"><a href="https://jlab-org.zoomgov.com/j/1619803255?pwd=AgMEd0JYWBs0MZa4LvbDa5ZecSO6EK.1" target="_blank" id="OWAb0ca894f-9199-a081-48ae-e20639bcad1a" class="x_OWAAutoLink" title="https://jlab-org.zoomgov.com/j/1619803255?pwd=AgMEd0JYWBs0MZa4LvbDa5ZecSO6EK.1" rel="noopener noreferrer" style="margin: 0px; background-color: rgb(255, 255, 255); text-align: left;" data-ogsb="rgb(255, 255, 255)" data-ogsc="" data-auth="NotApplicable" data-olk-copy-source="MessageBody" data-linkindex="0">https://jlab-org.zoomgov.com/j/1619803255?pwd=AgMEd0JYWBs0MZa4LvbDa5ZecSO6EK.1</a></span></div>
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<span style="background-color: white;">Although it’s not an in-person seminar, you can also join your colleagues for a remote streaming of the seminar in CEBAF Center F324-325.</span></div>
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Please see below for the title and abstract. </div>
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<span style="color: black;"><b><u>Theory Seminar</u></b>:<b> </b></span><span style="color: rgb(0, 0, 0); background-color: white;">May 12</span><span style="color: black;"><sup>th</sup>, 1pm EDT (virtual) </span></div>
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<b><u>Speaker</u></b>: Yi Chen (Vanderbilt University) </div>
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<span style="font-size: 11pt; color: black;"><b><u>Title</u></b>:<b> </b></span><span style="font-size: 14.6667px; color: rgb(0, 0, 0); background-color: white;">Systematic studies of complex systems with the Bayesian framework: ultrarelativistic heavy-ion
collisions as an example </span></div>
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<span style="font-family: Calibri, Helvetica, sans-serif; font-size: 11pt; color: black;"><b><u>Abstract</u></b>:
</span><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 11pt; color: black; line-height: 1.284;">As the complexity of the systems we seek to study increases, extracting their specific properties becomes increasingly challenging. Bayesian
parameter extraction is a robust statistical technique that uses Bayes' theorem to estimate model parameters by incorporating both prior information and observed data. This technique not only facilitates parameter estimation but also extends to a variety of
advanced applications, including model comparison, model combination, sensitivity analysis, experimental design, and more.</span></p>
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<span style="line-height: 1.284;">Ultrarelativistic heavy ion collisions are a prime example of such complex systems. These collisions, occurring at nearly the speed of light, generate extreme conditions that resembles the state of the universe microseconds
after the big bang, and they produce a wealth of intriguing phenomena. Over the past decades, extensive measurements have been conducted on these collisions, resulting in an ever-growing volume of data. Interpreting this large volume of data cohesively presents
a unique challenge. In this seminar, I will use a recent study that employs Bayesian parameter extraction to investigate ultrarelativistic heavy ion collisions as an example. I will discuss the methodology, techniques involved, and the insights gained from
this exercise.</span></div>
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<span style="line-height: 1.284;">Furthermore, I will explore various applications of Bayesian analysis beyond parameter extraction. These applications demonstrate the versatility of Bayesian methods and their potential to contribute to diverse fields of study,
from physics to other scientific fields and beyond.</span></div>
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See you tomorrow!</div>
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Kind regards, </div>
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Joe, Zheng-Yang, Gloria and Adam</div>
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