Month: October 2023

by Luca Bottero Our interests center around the intriguing domain of Continual Learning, a subset of machine learning focused on training models to adapt and evolve over time. This involves enabling these models to learn from new data while retaining previously acquired knowledge. In today’s fast-paced world, characterized by constant changes in data and knowledge, Continual Learning assumes primary importance. Traditional machine learning models often encounter challenges when confronted with novel information, a phenomenon commonly referred to as catastrophic forgetting. Continual Learning presents a remedy to this issue by facilitating continuous learning, rendering models adaptable, efficient, and adept at handling evolving data environments. Currently, we are working in a project that applies these Continual Learning techniques to gravitational wave interferometer data. We aspire to develop adaptive models that can learn from new experimental runs while retaining knowledge learned from prior detections. In a world characterized by relentless technological advancements and cease- less data generation, the concept of Continual Learning remains pivotal. The Turin...

by Beatrice Villata Tumor treatment can be achieved with radiotherapy techniques by irradiating the target volumes with ionizing radiation. Conventionally, photons are the selected particles for the treatment, but in recent years interest in the use of charged particles has been steadily growing in medical physics. The energy deposition of particle therapy allows to spare the organ at risk around the target volume. At the same time, the energy deposition of particle therapy is greatly influenced by range uncertainties provoked by motion or variations in tissue density along the path, requiring precise treatment planning and monitoring techniques to ensure accurate and effective therapy delivery.One way to achieve this is by analyzing the secondary particles created in the interactions between the charged particles and the tissues. Prompt gammas are candidates for this technique because their creation occurs instantaneously on the interaction site and can escape the patient. For these reasons, prompt gammas are not affected by washout effects and can be easily...