Enhancing Reliability In Photonuclear Cross-Section Fitting With Bayesian Neural Networks - Info and Reading Options

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<div class="hd"> <h1> Enhancing Reliability in Photonuclear Cross-Section Fitting with Bayesian Neural Networks </h1> <div class="flex" style="border:0px;padding-bottom:0px;"> </div> <div class="bd" style="border-bottom:1px solid #ced6e0;"> <ul style="margin-top:0px;"> <li> <b> 作者： </b> <a href="https://chinaxiv.org/user/search.htm?field=author&amp;value=Qian-KunSun" style="color:#3060cc;" rel="ugc nofollow"> Qian-KunSun </a> <sup style="margin-left:0px;"> 1,2 </sup> <a href="https://chinaxiv.org/user/search.htm?field=author&amp;value=YueZhang" style="color:#3060cc;" rel="ugc nofollow"> YueZhang </a> <sup style="margin-left:0px;"> 3 </sup> <a href="https://chinaxiv.org/user/search.htm?field=author&amp;value=Zi-RuiHao" style="color:#3060cc;" rel="ugc nofollow"> Zi-RuiHao </a> <sup style="margin-left:0px;"> 3 </sup> <a href="https://chinaxiv.org/user/search.htm?field=author&amp;value=Hong-WeiWang" style="color:#3060cc;" rel="ugc nofollow"> Hong-WeiWang </a> <sup style="margin-left:0px;"> 1,2,3 </sup> <a href="https://chinaxiv.org/user/search.htm?field=author&amp;value=Gong-TaoFan" style="color:#3060cc;" rel="ugc nofollow"> Gong-TaoFan </a> <sup style="margin-left:0px;"> 1,2,3 </sup> <a href="https://chinaxiv.org/user/search.htm?field=author&amp;value=Hang-HuaXu" style="color:#3060cc;" rel="ugc nofollow"> Hang-HuaXu </a> <sup style="margin-left:0px;"> 3 </sup> <a href="https://chinaxiv.org/user/search.htm?field=author&amp;value=Long-XiangLiu" style="color:#3060cc;" rel="ugc nofollow"> Long-XiangLiu </a> <sup style="margin-left:0px;"> 3 </sup> <a href="https://chinaxiv.org/user/search.htm?field=author&amp;value=ShengJin" style="color:#3060cc;" rel="ugc nofollow"> ShengJin </a> <sup style="margin-left:0px;"> 1,2 </sup> <a href="https://chinaxiv.org/user/search.htm?field=author&amp;value=Yu-XuanYang" style="color:#3060cc;" rel="ugc nofollow"> Yu-XuanYang </a> <sup style="margin-left:0px;"> 1,4 </sup> <a href="https://chinaxiv.org/user/search.htm?field=author&amp;value=Kai-JieChen" style="color:#3060cc;" rel="ugc nofollow"> Kai-JieChen </a> <sup style="margin-left:0px;"> 1,5 </sup> <a href="https://chinaxiv.org/user/search.htm?field=author&amp;value=Zhen-WeiWang" style="color:#3060cc;" rel="ugc nofollow"> Zhen-WeiWang </a> <sup style="margin-left:0px;"> 1,2 </sup> </li> <li> <b> 作者单位： </b> <div style="margin-left:70px;margin-top:-26px;"> <div> 1. <a href="https://chinaxiv.org/user/search.htm?field=affication&amp;value=Shanghai%20Institute%20of%20Applied%20Physics,%20Chinese%20Academy%20of%20Sciences,%20Shanghai%20201800,%20China" style="color:#3060cc;" rel="ugc nofollow"> Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800, China </a> </div> <div> 2. <a href="https://chinaxiv.org/user/search.htm?field=affication&amp;value=University%20of%20Chinese%20Academy%20of%20Sciences,%20Beijing%20100049,%20China" style="color:#3060cc;" rel="ugc nofollow"> University of Chinese Academy of Sciences, Beijing 100049, China </a> </div> <div> 3. <a href="https://chinaxiv.org/user/search.htm?field=affication&amp;value=Shanghai%20Advanced%20Research%20Institute,%20Chinese%20Academy%20of%20Sciences,%20Shanghai%20201210,%20China" style="color:#3060cc;" rel="ugc nofollow"> Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai 201210, China </a> </div> <div> 4. <a href="https://chinaxiv.org/user/search.htm?field=affication&amp;value=School%20of%20Physics%20and%20Microelectronics,%20Zhengzhou%20university,%20Zhengzhou%20450001,%20China" style="color:#3060cc;" rel="ugc nofollow"> School of Physics and Microelectronics, Zhengzhou university, Zhengzhou 450001, China </a> </div> <div> 5. <a href="https://chinaxiv.org/user/search.htm?field=affication&amp;value=School%20of%20Physical%20Science%20and%20Technology,%20ShanghaiTech%20University,%20Shanghai%20201210,%20China" style="color:#3060cc;" rel="ugc nofollow"> School of Physical Science and Technology, ShanghaiTech University, Shanghai 201210, China </a> </div> </div> </li> <li> <b> 通讯作者： </b> <a href="https://chinaxiv.org/user/search.htm?field=author&amp;value=Qian-KunSun" style="color:#bb3536;" rel="ugc nofollow"> Qian-KunSun </a> Email:[email protected] <a href="https://chinaxiv.org/user/search.htm?field=author&amp;value=YueZhang" style="color:#bb3536;" rel="ugc nofollow"> YueZhang </a> Email:[email protected] <a href="https://chinaxiv.org/user/search.htm?field=author&amp;value=Hong-WeiWang" style="color:#bb3536;" rel="ugc nofollow"> Hong-WeiWang </a> Email:[email protected] </li> <li> <b> 提交时间： </b> 2024-11-19 12:05:40 </li> </ul> </div> <div class="bd" style="margin-top:15px;"> <div style="line-height:24px;color:#333;"> <b> 摘要: </b> This study investigates photonuclear reaction $(\gamma,n)$ cross-sections using Bayesian neural network (BNN) analysis. After determining the optimal network architecture, which features two hidden layers, each with 50 hidden nodes, training was conducted for 30,000 iterations to ensure comprehensive data capture. By analyzing the distribution of absolute errors positively correlated with the cross-section for the isotope $^{159}$Tb, as well as the relative errors unrelated to the cross-section, we confirmed that the network effectively captured the data features without overfitting. Comparison with the TENDL-2021 Database demonstrated the BNN’s reliability in fitting photonuclear cross-sections with lower average errors. The predictions for nuclei with single and double giant dipole resonance peak cross-sections, the accurate determination of the photoneutron reaction threshold in the low-energy region, and the precise description of trends in the high-energy cross-sections further demonstrate the network’s generalization ability on the validation set. This can be attributed to the consistency of the training data. By using consistent training sets from different laboratories, Bayesian neural networks can predict nearby unknown cross-sections based on existing laboratory data, thereby estimating the potential differences between other laboratories’ existing data and their own measurement results. Experimental measurements of photonuclear reactions on the newly constructed SLEGS beamline will contribute to clarifying the differences in cross-sections within the existing data. </div> <div class="brdge"> <span class="spankwd"> <a href="https://chinaxiv.org/user/search.htm?field=keywords&amp;value=Photoneutron%20reaction" rel="ugc nofollow"> Photoneutron reaction </a> </span> <span class="spankwd"> <a href="https://chinaxiv.org/user/search.htm?field=keywords&amp;value=%20Bayesian%20neural%20network" rel="ugc nofollow"> Bayesian neural network </a> </span> <span class="spankwd"> <a href="https://chinaxiv.org/user/search.htm?field=keywords&amp;value=%20Machine%20learning" rel="ugc nofollow"> Machine learning </a> </span> <span class="spankwd"> <a href="https://chinaxiv.org/user/search.htm?field=keywords&amp;value=%20Gamma%20source" rel="ugc nofollow"> Gamma source </a> </span> <span class="spankwd"> <a href="https://chinaxiv.org/user/search.htm?field=keywords&amp;value=%20SLEGS" rel="ugc nofollow"> SLEGS </a> </span> </div> <ul> <li> <b> 来自： </b> 孙乾坤 </li> <li> <b> 分类： </b> <a href="https://chinaxiv.org/user/search.htm?field=domain&amp;value=2" rel="ugc nofollow"> 物理学 </a> &gt;&gt; <a href="https://chinaxiv.org/user/search.htm?field=subject&amp;value=40" rel="ugc nofollow"> 核物理学 </a> </li> <li> <b> 说明： </b> <span> 已被Nuclear Science and Techniques期刊接收 </span> </li> <li> <b> 投稿状态： </b> <a rel="ugc nofollow"> 已被期刊接收 </a> </li> <li> <b> 引用： </b> <a href="https://chinaxiv.org/abs/202411.00202" rel="ugc nofollow"> <font color="#0000FF"> ChinaXiv:202411.00202 </font> </a> (或此版本 <a href="https://chinaxiv.org/abs/202411.00202v1" rel="ugc nofollow"> <font color="#0000FF"> ChinaXiv:202411.00202V1 </font> </a> ) <br /> <a href="http://dx.doi.org/10.12074/202411.00202" style="color:#0000FF;margin-left:45px;" rel="ugc nofollow"> <font color="#0000FF"> DOI:10.12074/202411.00202 </font> </a> <br /> <a href="https://www.cstr.cn/CSTR:32003.36.ChinaXiv.202411.00202" style="margin-left:45px;" rel="ugc nofollow"> <font color="#0000FF"> CSTR:32003.36.ChinaXiv.202411.00202 </font> </a> </li> <li> <b> 科创链TXID： </b> <a href="https://sciencechain.ac.cn/realTimeNetwork/transaction/197016ef-a392-4705-b927-8824ed0ffe4c" rel="ugc nofollow"> <font color="#0000FF"> 197016ef-a392-4705-b927-8824ed0ffe4c </font> </a> </li> <li> <b> 推荐引用方式： </b> <span> Qian-KunSun,YueZhang,Zi-RuiHao,Hong-WeiWang,Gong-TaoFan,Hang-HuaXu,Long-XiangLiu,ShengJin,Yu-XuanYang,Kai-JieChen,Zhen-WeiWang.Enhancing Reliability in Photonuclear Cross-Section Fitting with Bayesian Neural Networks.中国科学院科技论文预发布平台.[DOI:10.12074/202411.00202] </span> </li> </ul> </div> <div class="ft"> <h4> <span> 版本历史 </span> </h4> <table style="font-size:14px;"> <tr> <td> <b> [V1] </b> </td> <td> 2024-11-19 12:05:40 </td> <td> ChinaXiv:202411.00202V1 </td> <td> <a class="btn" href="https://chinaxiv.org/user/download.htm?uuid=072f2abe-6c7f-411b-8f31-349b029a85c3" rel="ugc nofollow"> 下载全文 </a> </td> </tr> </table> </div> </div>

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