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CMS Thesis Award Winners for 2024
No full textIt's with great pride that the CMS Collaboration announces the winners of the 2024 CMS PhD Thesis Award. After a rigorous evaluation of a remarkable pool of 19 nominees, we are delighted to honour Congqiao Li, Christina Wenlu Wang, and Ho Fung Tsoi for their exceptional work. The awards were presented during a dedicated ceremony during the September 2025 CMS Week at CERN. Each winner then presented their thesis work to the collaboration
Minimum bias and underlaying event measurements at the LHC with tje ATLAS detector
No full textThis talk reports recent measurements relating to minibias and underlying events as well as multi parton interactions at the LHC. These measurements provide important insights to understand Quantum Chromodynamics at the soft regime and hadronization scales
Wasserstein normalized autoencoder for anomaly detection
No full textA novel anomaly detection algorithm is presented. The Wasserstein normalized autoencoder (WNAE) is a normalized probabilistic model that minimizes the Wasserstein distance between the learned probability distribution---a Boltzmann distribution where the energy is the reconstruction error of the autoencoder---and the distribution of the training data. This algorithm has been developed and applied to the identification of semivisible jets---conical sprays of visible standard model particles and invisible dark matter states---with the CMS experiment at the CERN LHC. Trained on jets of particles from simulated standard model processes, the WNAE is shown to learn the probability distribution of the input data in a fully unsupervised fashion, such that it effectively identifies new physics jets as anomalies. The model consistently demonstrates stable, convergent training and achieves strong classification performance across a wide range of signals, improving upon standard normalized autoencoders, while remaining agnostic to the signal. The WNAE directly tackles the problem of outlier reconstruction, a common failure mode of autoencoders in anomaly detection tasks.A novel anomaly detection algorithm is presented. The Wasserstein normalized autoencoder (WNAE) is a normalized probabilistic model that minimizes the Wasserstein distance between the learned probability distribution -- a Boltzmann distribution where the energy is the reconstruction error of the autoencoder -- and the distribution of the training data. This algorithm has been developed and applied to the identification of semivisible jets -- conical sprays of visible standard model particles and invisible dark matter states -- with the CMS experiment at the CERN LHC. Trained on jets of particles from simulated standard model processes, the WNAE is shown to learn the probability distribution of the input data in a fully unsupervised fashion, such that it effectively identifies new physics jets as anomalies. The model consistently demonstrates stable, convergent training and achieves strong classification performance across a wide range of signals, improving upon standard normalized autoencoders, while remaining agnostic to the signal. The WNAE directly tackles the problem of outlier reconstruction, a common failure mode of autoencoders in anomaly detection tasks
Search for a resonance decaying into a scalar particle and a Higgs boson in the final state with two bottom quarks and two photons with 199 fb of data collected at =13 TeV and =13.6 TeV with the ATLAS detector
No full textA search for the resonant production of a heavy scalar decaying into a Higgs boson and a lighter scalar , through the process , where the two photons are consistent with the Higgs boson decay, is performed. The search is conducted using integrated luminosities of 140 fb and 58.6 fb of proton-proton collision data at centre-of-mass energies of 13 TeV and 13.6 TeV respectively, recorded with the ATLAS detector at the Large Hadron Collider. The search is performed over the mass ranges of 170 1000 GeV and 15 500 GeV. No significant excess over the Standard Model background prediction is observed and limits at 95% confidence level are set on the cross-section times branching ratio at 13 TeV, ranging from 9 fb to 0.06 fb.A search for the resonant production of a heavy scalar decaying into a Higgs boson and a lighter scalar , through the process , where the two photons are consistent with the Higgs boson decay, is performed. The search is conducted using integrated luminosities of 140 fb and 58.6 fb of proton-proton collision data at centre-of-mass energies of 13 TeV and 13.6 TeV respectively, recorded with the ATLAS detector at the Large Hadron Collider. The search is performed over the mass ranges of 170 1000 GeV and 15 500 GeV. No significant excess over the Standard Model background prediction is observed and limits at 95% confidence level are set on the cross-section times branching ratio at 13 TeV, ranging from 9 fb to 0.06 fb
High-Energy Evolution of Power-Suppressed Amplitudes
No full textWe present a new class of evolution equations which govern the high-energy behavior of power-suppressed scattering amplitudes. The equations can be viewed as a renormalization group flow with respect to the relevant effective field theory cutoff. A distinct feature of the method is in the use of a multidimensional cutoff to separate the relevant scales in problems characterized by a complex factorization structure. By adjusting the renormalization group variables to the geometry of the effective theory modes, our method naturally extends to a broad spectrum of physical problems including massive, massless, small, and wide angle scattering. We present applications to the benchmark processes of electron-positron forward annihilation and light quark mediated Higgs boson production/decays
Timing response characterization of MALTA monolithic pixel detectors
No full textThe MALTA monolithic active pixel detector has been developed to meet the stringent demands of future high-energy physics experiments. To assess its capabilities, we performed fast-timing studies to define a figure of merit for this family of detectors. Conventional laser techniques are hindered by reflections from the sensor's metal layers, which restrict material penetration. We developed a triggered micro-X-ray system designed for precise timing measurements, that employs a micro-X-ray source that generates X-rays from a Cu-Cr target, synchronized with an external trigger signal. After validating the system with an LGAD, we used it to evaluate the timing performance of MALTA and MALTA2 pixel detector prototypes, providing insights into their operational characteristics
