{"id":{"repo_id":"cambridge","oai_identifier":"oai:www.repository.cam.ac.uk:1810/339884"},"canonical_url":"https://search.dev.ndltd.org/etd/cambridge/oai:www.repository.cam.ac.uk:1810/339884","repository":{"repo_id":"cambridge","name":"Cambridge University","base_url":"https://api.repository.cam.ac.uk/server/oai/request"},"display":{"title":"Determination of the CKM ratio $|V_{ub}|/|V_{cb}|$ using semileptonic $B_c^{+}$ decays at LHCb","abstract":"This thesis reports the first search for $B_c^{+} \\to D^{(*)0}\\mu^+ \\nu_{\\mu}$ decays using proton-proton collision data collected by the LHCb experiment operating at the Large Hadron Collider at CERN. The measurement makes use of a data sample collected between 2016 and 2018 at a centre-of-mass energy of 13 TeV, corresponding to an integrated luminosity of $5.1\\,\\textrm{fb}^{-1}$. The semi-exclusive signal $B_c^{+} \\to D^{(*)0}\\mu^+ \\nu_{\\mu}$ branching fraction is measured relative to the normalisation decay, $B_c^{+} \\to J/\\psi \\,\\mu^+ \\nu_{\\mu}$. The branching fraction ratio is found to be $\\begin{align*}\\frac{\\mathcal{B}(B_c^{+} \\to D^{(*)0}\\mu^+ \\nu_{\\mu})}{\\mathcal{B}(B_c^{+} \\to J/\\psi\\,\\mu^+ \\nu_{\\mu})} &= 0.0405 \\pm 0.0082 \\pm 0.0065 \\pm 0.0004,\\end{align*}$ and is exploited to extract the first-ever measurement of the CKM ratio, $|V_{ub}|/|V_{cb}|$, using semileptonic $B_c^{+}$ decays, $\\begin{align*}\\frac{|V_{ub}|}{|V_{cb}|} = 0.200 \\pm 0.020 \\pm 0.041 \\pm 0.001.\\end{align*}$ In both results, the first uncertainty is statistical, the second is systematic, and the third is due to external measurements of the $D^{0} \\to K^{-}\\pi^{+}$ and $J/\\psi \\to \\mu^{+}\\mu^{-}$ decay branching fractions. This proof-of-concept measurement demonstrates the potential for CKM metrology with the rare $B_{c}^+$ meson. In addition, this thesis details the development of a novel deep learning architecture to perform calorimetric shower reconstruction at high energy particle physics experiments. A bespoke network, exploiting recent developments in image recognition and geometric deep learning, is designed to achieve one-shot 2D cluster reconstruction capable of learning an arbitrary detector-plane geometry. The performance of the detection network is assessed using a standalone dataset inspired by the LHCb Electromagnetic Calorimeter layout.","abstract_html":"This thesis reports the first search for <span class=\"etd-inline-math\">B<sub>c</sub><sup>+</sup> \\to D<sup>(*)0</sup>&mu;<sup>+</sup> \\nu<sub>&mu;</sub></span> decays using proton-proton collision data collected by the LHCb experiment operating at the Large Hadron Collider at CERN. The measurement makes use of a data sample collected between 2016 and 2018 at a centre-of-mass energy of 13 TeV, corresponding to an integrated luminosity of <span class=\"etd-inline-math\">5.1 \\textrm{fb}<sup>-1</sup></span>. The semi-exclusive signal <span class=\"etd-inline-math\">B<sub>c</sub><sup>+</sup> \\to D<sup>(*)0</sup>&mu;<sup>+</sup> \\nu<sub>&mu;</sub></span> branching fraction is measured relative to the normalisation decay, <span class=\"etd-inline-math\">B<sub>c</sub><sup>+</sup> \\to J/\\psi  &mu;<sup>+</sup> \\nu<sub>&mu;</sub></span>. The branching fraction ratio is found to be <span class=\"etd-inline-math\">\\begin{align*}\\frac{\\mathcal{B}(B<sub>c</sub><sup>+</sup> \\to D<sup>(*)0</sup>&mu;<sup>+</sup> \\nu<sub>&mu;</sub>)}{\\mathcal{B}(B<sub>c</sub><sup>+</sup> \\to J/\\psi &mu;<sup>+</sup> \\nu<sub>&mu;</sub>)} &amp;= 0.0405 \\pm 0.0082 \\pm 0.0065 \\pm 0.0004,\\end{align*}</span> and is exploited to extract the first-ever measurement of the CKM ratio, <span class=\"etd-inline-math\">|V<sub>ub</sub>|/|V<sub>cb</sub>|</span>, using semileptonic <span class=\"etd-inline-math\">B<sub>c</sub><sup>+</sup></span> decays, <span class=\"etd-inline-math\">\\begin{align*}\\frac{|V<sub>ub</sub>|}{|V<sub>cb</sub>|} = 0.200 \\pm 0.020 \\pm 0.041 \\pm 0.001.\\end{align*}</span> In both results, the first uncertainty is statistical, the second is systematic, and the third is due to external measurements of the <span class=\"etd-inline-math\">D<sup>0</sup> \\to K<sup>-</sup>&pi;<sup>+</sup></span> and <span class=\"etd-inline-math\">J/\\psi \\to &mu;<sup>+</sup>&mu;<sup>-</sup></span> decay branching fractions. This proof-of-concept measurement demonstrates the potential for CKM metrology with the rare <span class=\"etd-inline-math\">B<sub>c</sub><sup>+</sup></span> meson. In addition, this thesis details the development of a novel deep learning architecture to perform calorimetric shower reconstruction at high energy particle physics experiments. A bespoke network, exploiting recent developments in image recognition and geometric deep learning, is designed to achieve one-shot 2D cluster reconstruction capable of learning an arbitrary detector-plane geometry. The performance of the detection network is assessed using a standalone dataset inspired by the LHCb Electromagnetic Calorimeter layout.","abstract_has_math":true,"creators":["Delaney, Blaise"],"institution":"University of Cambridge","degree_name":"Doctor of Philosophy (PhD)","degree_level":"Doctoral","degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Gibson, Valerie"],"committee_chairs":[],"committee_members":[],"year":2022,"date_issued":"2022-01-30","date_published":"2022-01-30","updated_at":"2026-07-22T22:24:03Z","subjects":["B physics","Calorimetry","CERN","CKM","Geometric deep learning","LHC","LHCb","Semileptonic"],"languages":["eng"],"rights":[],"rights_urls":["https://creativecommons.org/licenses/by-nc-nd/4.0/"],"identifier_entries":[]},"links":{"outbound_url":"https://doi.org/10.17863/CAM.87305","outbound_label":"DOI","outbound_source":"dc:identifier.doi"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Gibson, Valerie"]},{"key":"dc:contributor.sponsor","label":"Sponsor","values":["Funded by the Science and Technology Facilities Council (STFC)."]},{"key":"dc:creator","label":"Author","values":["Delaney, Blaise"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.issued","label":"Date","values":["2022-01-30"]},{"key":"dc:publisher.institution","label":"Dc Publisher Institution","values":["University of Cambridge"]},{"key":"dc:relation.isreferencedby.uri","label":"Dc Relation Isreferencedby URI","values":["https://www.repository.cam.ac.uk/handle/1810/339884"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"dc:type.qualificationlevel","label":"Dc Type Qualificationlevel","values":["Doctoral"]},{"key":"dc:type.qualificationname","label":"Dc Type Qualificationname","values":["Doctor of Philosophy (PhD)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["B physics","Calorimetry","CERN","CKM","Geometric deep learning","LHC","LHCb","Semileptonic"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["https://creativecommons.org/licenses/by-nc-nd/4.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.doi","label":"DOI","values":["10.17863/CAM.87305"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://apollo8-f-pro.lib.cam.ac.uk/bitstreams/ac865eb6-d935-46e7-bb06-0e9c0e60e3e0/download"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["This thesis reports the first search for $B_c^{+} \\to D^{(*)0}\\mu^+ \\nu_{\\mu}$ decays using proton-proton collision data collected by the LHCb experiment operating at the Large Hadron Collider at CERN. The measurement makes use of a data sample collected between 2016 and 2018 at a centre-of-mass energy of 13 TeV, corresponding to an integrated luminosity of $5.1\\,\\textrm{fb}^{-1}$. The semi-exclusive signal $B_c^{+} \\to D^{(*)0}\\mu^+ \\nu_{\\mu}$ branching fraction is measured relative to the normalisation decay, $B_c^{+} \\to J/\\psi \\,\\mu^+ \\nu_{\\mu}$. The branching fraction ratio is found to be $\\begin{align*}\\frac{\\mathcal{B}(B_c^{+} \\to D^{(*)0}\\mu^+ \\nu_{\\mu})}{\\mathcal{B}(B_c^{+} \\to J/\\psi\\,\\mu^+ \\nu_{\\mu})} &= 0.0405 \\pm 0.0082 \\pm 0.0065 \\pm 0.0004,\\end{align*}$ and is exploited to extract the first-ever measurement of the CKM ratio, $|V_{ub}|/|V_{cb}|$, using semileptonic $B_c^{+}$ decays, $\\begin{align*}\\frac{|V_{ub}|}{|V_{cb}|} = 0.200 \\pm 0.020 \\pm 0.041 \\pm 0.001.\\end{align*}$ In both results, the first uncertainty is statistical, the second is systematic, and the third is due to external measurements of the $D^{0} \\to K^{-}\\pi^{+}$ and $J/\\psi \\to \\mu^{+}\\mu^{-}$ decay branching fractions. This proof-of-concept measurement demonstrates the potential for CKM metrology with the rare $B_{c}^+$ meson. In addition, this thesis details the development of a novel deep learning architecture to perform calorimetric shower reconstruction at high energy particle physics experiments. A bespoke network, exploiting recent developments in image recognition and geometric deep learning, is designed to achieve one-shot 2D cluster reconstruction capable of learning an arbitrary detector-plane geometry. The performance of the detection network is assessed using a standalone dataset inspired by the LHCb Electromagnetic Calorimeter layout."]},{"key":"dc:format.checksum.md5","label":"Dc Format Checksum Md5","values":["5fe95f3d5de85105d3b1137acfea8343"]},{"key":"dc:title","label":"Title","values":["Determination of the CKM ratio $|V_{ub}|/|V_{cb}|$ using semileptonic $B_c^{+}$ decays at LHCb"]}]}],"canonical_facts":{"dc:contributor.advisor":["Gibson, Valerie"],"dc:contributor.sponsor":["Funded by the Science and Technology Facilities Council (STFC)."],"dc:creator":["Delaney, Blaise"],"dc:date.issued":["2022-01-30"],"dc:description.abstract":["This thesis reports the first search for $B_c^{+} \\to D^{(*)0}\\mu^+ \\nu_{\\mu}$ decays using proton-proton collision data collected by the LHCb experiment operating at the Large Hadron Collider at CERN. The measurement makes use of a data sample collected between 2016 and 2018 at a centre-of-mass energy of 13 TeV, corresponding to an integrated luminosity of $5.1\\,\\textrm{fb}^{-1}$. The semi-exclusive signal $B_c^{+} \\to D^{(*)0}\\mu^+ \\nu_{\\mu}$ branching fraction is measured relative to the normalisation decay, $B_c^{+} \\to J/\\psi \\,\\mu^+ \\nu_{\\mu}$. The branching fraction ratio is found to be $\\begin{align*}\\frac{\\mathcal{B}(B_c^{+} \\to D^{(*)0}\\mu^+ \\nu_{\\mu})}{\\mathcal{B}(B_c^{+} \\to J/\\psi\\,\\mu^+ \\nu_{\\mu})} &= 0.0405 \\pm 0.0082 \\pm 0.0065 \\pm 0.0004,\\end{align*}$ and is exploited to extract the first-ever measurement of the CKM ratio, $|V_{ub}|/|V_{cb}|$, using semileptonic $B_c^{+}$ decays, $\\begin{align*}\\frac{|V_{ub}|}{|V_{cb}|} = 0.200 \\pm 0.020 \\pm 0.041 \\pm 0.001.\\end{align*}$ In both results, the first uncertainty is statistical, the second is systematic, and the third is due to external measurements of the $D^{0} \\to K^{-}\\pi^{+}$ and $J/\\psi \\to \\mu^{+}\\mu^{-}$ decay branching fractions. This proof-of-concept measurement demonstrates the potential for CKM metrology with the rare $B_{c}^+$ meson. In addition, this thesis details the development of a novel deep learning architecture to perform calorimetric shower reconstruction at high energy particle physics experiments. A bespoke network, exploiting recent developments in image recognition and geometric deep learning, is designed to achieve one-shot 2D cluster reconstruction capable of learning an arbitrary detector-plane geometry. The performance of the detection network is assessed using a standalone dataset inspired by the LHCb Electromagnetic Calorimeter layout."],"dc:format.checksum.md5":["5fe95f3d5de85105d3b1137acfea8343"],"dc:identifier.doi":["10.17863/CAM.87305"],"dc:identifier.uri":["https://apollo8-f-pro.lib.cam.ac.uk/bitstreams/ac865eb6-d935-46e7-bb06-0e9c0e60e3e0/download"],"dc:language":["eng"],"dc:publisher.institution":["University of Cambridge"],"dc:relation.isreferencedby.uri":["https://www.repository.cam.ac.uk/handle/1810/339884"],"dc:rights":["https://creativecommons.org/licenses/by-nc-nd/4.0/"],"dc:subject":["B physics","Calorimetry","CERN","CKM","Geometric deep learning","LHC","LHCb","Semileptonic"],"dc:title":["Determination of the CKM ratio $|V_{ub}|/|V_{cb}|$ using semileptonic $B_c^{+}$ decays at LHCb"],"dc:type":["Thesis"],"dc:type.qualificationlevel":["Doctoral"],"dc:type.qualificationname":["Doctor of Philosophy (PhD)"]},"updated_at":"2026-07-22T22:24:03Z"}