new: 2402.07661 (#231)

iml-wg · Nov 27, 2024 · 6bc2d9f · 6bc2d9f
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diff --git a/HEPML.bib b/HEPML.bib
@@ -3424,6 +3424,24 @@ @article{Kim:2024rpd
     year = "2024"
 }
 
+
+% February 12, 2024
+@article{Romao:2024gjx,
+    author = "Rom\~ao, Jorge Crispim and Crispim Rom\~ao, Miguel",
+    title = "{Combining evolutionary strategies and novelty detection to go beyond the alignment limit of the Z3 3HDM}",
+    eprint = "2402.07661",
+    archivePrefix = "arXiv",
+    primaryClass = "hep-ph",
+    reportNumber = "IPPP/24/04, CFTP/24-002",
+    doi = "10.1103/PhysRevD.109.095040",
+    journal = "Phys. Rev. D",
+    volume = "109",
+    number = "9",
+    pages = "095040",
+    year = "2024"
+}
+
+
 % February 12, 2024
 @article{Lin:2024eiz,
     author = "Lin, Joshua and Luo, Di and Yao, Xiaojun and Shanahan, Phiala E.",

diff --git a/HEPML.tex b/HEPML.tex
@@ -201,7 +201,7 @@
 		\\\textit{This is the task of removing detector distortions.  In contrast to parameter estimation, the goal is not to infer model parameters, but instead, the undistorted phase space probability density.  This is often also called deconvolution.}
 		\item \textbf{Domain adaptation}~\cite{Glazier:2024ogg,Kelleher:2024jsh,Kelleher:2024rmb,Zhao:2024ely,Algren:2023qnb,Schreck:2023pzs,Camaiani:2022kul,Nachman:2021opi,Diefenbacher:2020rna,Cranmer:2015bka,Andreassen:2019nnm,Rogozhnikov:2016bdp}
 		\\\textit{Morphing simulations to look like data is a form of domain adaptation.}
-		\item \textbf{BSM}~\cite{Heimel:2024drk,Maselek:2024qyp,Yang:2024bqw,Florez:2024lrr,Saito:2024fmr,Schofbeck:2024zjo,Hammad:2024hhm,Ahmed:2024uaz,Choudhury:2024mox,Baruah:2024gwy,Ahmed:2024oxg,Catena:2024fjn,Bhattacharya:2024sxl,vanBeekveld:2024cby,Barman:2024xlc,Arganda:2023qni,Franz:2023gic,Mandal:2023mck,Chhibra:2023tyf,vanBeekveld:2023ney,Dennis:2023kfe,Anisha:2023xmh,Castro:2022zpq,GomezAmbrosio:2022mpm,deSouza:2022uhk,Romao:2020ojy,Brehmer:2019xox,Brehmer:2018hga,Brehmer:2018eca,Brehmer:2018kdj,Hollingsworth:2020kjg,Andreassen:2020nkr}
+		\item \textbf{BSM}~\cite{Heimel:2024drk,Maselek:2024qyp,Yang:2024bqw,Florez:2024lrr,Saito:2024fmr,Schofbeck:2024zjo,Hammad:2024hhm,Ahmed:2024uaz,Choudhury:2024mox,Baruah:2024gwy,Ahmed:2024oxg,Catena:2024fjn,Bhattacharya:2024sxl,vanBeekveld:2024cby,Barman:2024xlc,Romao:2024gjx,Arganda:2023qni,Franz:2023gic,Mandal:2023mck,Chhibra:2023tyf,vanBeekveld:2023ney,Dennis:2023kfe,Anisha:2023xmh,Castro:2022zpq,GomezAmbrosio:2022mpm,deSouza:2022uhk,Romao:2020ojy,Brehmer:2019xox,Brehmer:2018hga,Brehmer:2018eca,Brehmer:2018kdj,Hollingsworth:2020kjg,Andreassen:2020nkr}
 		\\\textit{This category is for parameter estimation when the parameter is the signal strength of new physics.}
 		\item \textbf{Differentiable Simulation}~\cite{Heller:2024onk,Chung:2024vfg,Heimel:2024wph,BarhamAlzas:2024ggt,Smith:2023ssh,Aehle:2023wwi,Kagan:2023gxz,Shenoy:2023ros,Napolitano:2023jhg,Lei:2022dvn,Nachman:2022jbj,MODE:2022znx,Heinrich:2022xfa}
 		\\\textit{Coding up a simulation using a differentiable programming language like TensorFlow, PyTorch, or JAX.}

diff --git a/README.md b/README.md
@@ -1932,6 +1932,7 @@ This review was built with the help of the HEP-ML community, the [INSPIRE REST A
 * [Higgs couplings in SMEFT via Zh production at the HL-LHC](https://arxiv.org/abs/2403.03001) (2024)
 * [The impact of CP-violating phases on DM observables in the cpMSSM](https://arxiv.org/abs/2402.08814) (2024)
 * [Current status of the light neutralino thermal dark matter in the phenomenological MSSM](https://arxiv.org/abs/2402.07991) (2024)
+* [Combining evolutionary strategies and novelty detection to go beyond the alignment limit of the Z3 3HDM](https://arxiv.org/abs/2402.07661) [[DOI](https://doi.org/10.1103/PhysRevD.109.095040)] (2024)
 * [LHC Study of Third-Generation Scalar Leptoquarks with Machine-Learned Likelihoods](https://arxiv.org/abs/2309.05407) [[DOI](https://doi.org/10.1103/PhysRevD.109.055032)] (2023)
 * [Tip of the Red Giant Branch Bounds on the Neutrino Magnetic Dipole Moment Revisited](https://arxiv.org/abs/2307.13050) (2023)
 * [Pinning down the leptophobic $Z^\prime$ in leptonic final states with Deep Learning](https://arxiv.org/abs/2307.01118) [[DOI](https://doi.org/10.1016/j.physletb.2023.138417)] (2023)

diff --git a/docs/index.md b/docs/index.md
@@ -2134,6 +2134,7 @@ const expandElements = shouldExpand => {
     * [Higgs couplings in SMEFT via Zh production at the HL-LHC](https://arxiv.org/abs/2403.03001) (2024)
     * [The impact of CP-violating phases on DM observables in the cpMSSM](https://arxiv.org/abs/2402.08814) (2024)
     * [Current status of the light neutralino thermal dark matter in the phenomenological MSSM](https://arxiv.org/abs/2402.07991) (2024)
+    * [Combining evolutionary strategies and novelty detection to go beyond the alignment limit of the Z3 3HDM](https://arxiv.org/abs/2402.07661) [[DOI](https://doi.org/10.1103/PhysRevD.109.095040)] (2024)
     * [LHC Study of Third-Generation Scalar Leptoquarks with Machine-Learned Likelihoods](https://arxiv.org/abs/2309.05407) [[DOI](https://doi.org/10.1103/PhysRevD.109.055032)] (2023)
     * [Tip of the Red Giant Branch Bounds on the Neutrino Magnetic Dipole Moment Revisited](https://arxiv.org/abs/2307.13050) (2023)
     * [Pinning down the leptophobic $Z^\prime$ in leptonic final states with Deep Learning](https://arxiv.org/abs/2307.01118) [[DOI](https://doi.org/10.1016/j.physletb.2023.138417)] (2023)