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ANTARES is currently the largest undersea neutrino telescope, located in the Mediterranean Sea and taking data since 2007. It consists of a 3D array of photo sensors, instrumenting about 10Mt of seawater to detect Cherenkov light induced by…
Multifragmentation reactions are dominating processes for the decomposition of highly excited nuclei leading to the fragment production in heavy-ion collisions. At high energy reactions strange particles are abundantly produced. We present…
The breakthrough in Deep Learning neural networks has transformed the use of AI and machine learning technologies for the analysis of very large experimental datasets. These datasets are typically generated by large-scale experimental…
The advent of Industry 4.0 has precipitated the incorporation of Artificial Intelligence (AI) methods within industrial contexts, aiming to realize intelligent manufacturing, operation as well as maintenance, also known as industrial…
We report a novel manifestation of spin-vorticity interplay in relativistic heavy-ion collisions. Using $^{16}$O+$^{197}$Au at $\sqrt{s_{\rm NN}}=7.7$ GeV as a test case, we show that the $\Lambda$ hyperon exhibits a clear dual-polarization…
Strangeness production in Au+Au collisions has been measured via the yields of K+ and K- at 6, 8 AGeV and of anti-Lambda at 10.8 AGeV beam kinetic energy in experiment E917. By varying the collision centrality and beam energy, a systematic…
Artificial intelligence (AI) and high-performance computing (HPC) are rapidly becoming the engines of modern science. However, their joint effect on discovery has yet to be quantified at scale. Drawing on metadata from over five million…
In the field of computational physics and material science, the efficient sampling of rare events occurring at atomic scale is crucial. It aids in understanding mechanisms behind a wide range of important phenomena, including protein…
A novel, unorthodox picture of the dynamics of heavy ion collisions is developed using the concept of Hagedorn states. A prescription of the bootstrap of Hagedorn states respecting the conserved quantum numbers baryon number B, strangeness…
Quantum sensors leverage matter's quantum properties to enable measurements with unprecedented spatial and spectral resolution. Among these sensors, those utilizing nitrogen-vacancy (NV) centers in diamond offer the distinct advantage of…
The design of alloys is a multi-scale problem that requires a holistic approach that involves retrieving relevant knowledge, applying advanced computational methods, conducting experimental validations, and analyzing the results, a process…
Neutrino experiments study the least understood of the Standard Model particles by observing their direct interactions with matter or searching for ultra-rare signals. The study of neutrinos typically requires overcoming large backgrounds,…
The lack of evidence for new interactions and particles at the Large Hadron Collider has motivated the high-energy physics community to explore model-agnostic data-analysis approaches to search for new physics. Autoencoders are unsupervised…
Hypernuclear research will be one of the main topics addressed by the PANDA experiment at the planned Facility for Anti-proton and Ion Research FAIR at Darmstadt, Germany. A copious production of Xi-hyperons at a dedicated internal target…
The systematics of strangeness enhancement is calculated using the HIJING and VENUS models and compared to recent data on $\,pp\,$, $\,pA\,$ and $\,AA\,$ collisions at CERN/SPS energies ($200A\,\, GeV\,$). The HIJING model is used to…
We review the progress in understanding the strange particle yields in nuclear collisions and their role in signalling quark-gluon plasma formation. We report on new insights into the formation mechanisms of strange particles during…
The dynamics of exotic hypernuclei in heavy-ion collisions has been investigated thoroughly with a microscopic transport model. All possible channels on hyperon ($\Lambda$, $\Sigma$ and $\Xi$) production near threshold energies are…
Bringing artificial intelligence (AI) alongside next-generation X-ray imaging detectors, including CCDs and DEPFET sensors, enhances their sensitivity to achieve many of the flagship science cases targeted by future X-ray observatories,…
The prediction of neutron stars properties is strictly connected to the employed nuclear interactions. The appearance of hyperons in the inner core of the star is strongly dependent on the details of the underlying hypernuclear force. We…
This paper focuses on the analysis of the application effectiveness of the integration of deep learning and computer vision technologies. Deep learning achieves a historic breakthrough by constructing hierarchical neural networks, enabling…