Recent experimental measurements in the Large Hadron Collider (LHC) have shown a clear correlation between beam-beam resonance driving terms and beam losses, with a characteristic bunch-by-bunch signature. This observation creates interesting conditions to study diffusive processes. Over the past few decades, early chaos indicators, frequency map analysis and dynamic aperture studies have been commonly used to study particle stability in circular machines. However, the underlying mechanisms driving particles to large amplitudes in the presence of high order resonances is still an open question. Leveraging on years of development on particle tracking tools, this paper presents full-fledged 6-dimensional bunch-by-bunch beam loss simulations in the LHC. The computed loss rates are shown to be in agreement with experimental observations from LHC Run 3.

Since the start of the Large Hadron Collider (LHC), dust-induced beam loss events resulted in more than hundred premature beam aborts and more than ten dipole quenches during proton physics operation. The events are presumably caused by micrometer-sized dust grains, which are attracted by the proton beams and consequently give rise to beam losses due to inelastic proton-nucleus collisions. Besides the events which trigger dumps or quenches, a large number of smaller dust events has been detected by the beam loss monitors every year. Although these events are not detrimental for physics operation, they are still carefully scrutinized as they give a better understanding about the correlation with beam parameters, about the long-term evolution of event rates, and about possible correlations with shutdown activities and the installation of new equipment. In this contribution, we present a summary of observations from the first three runs of the LHC.

Xsuite is a modular simulation package bringing to a single flexible and modern framework capabilities of different tools developed at CERN in the past decades notably MAD-X Sixtrack Sixtracklib COMBI and PyHEADTAIL. The suite consists of a set of Python modules (Xobjects, Xpart, Xtrack, Xcoll, Xfields, Xdeps) that can be flexibly combined together and with other accelerator-specific and general-purpose python tools to study complex simulation scenarios. Different computing platforms are supported including conventional CPUs as well as GPUs from different vendors. The code allows for symplectic modeling of the particle dynamics combined with the effect of synchrotron radiation impedances feedbacks space charge electron cloud beam-beam beamstrahlung and electron lenses. For collimation studies beam-matter interaction is simulated using the K2 scattering model or interfacing Xsuite with the BDSIM/Geant4 library and with the FLUKA code. Methods are made available to compute and optimize the accelerator lattice functions, chromatic properties and equilibrium beam sizes. By now the tool has reached a mature stage of development and is used for simulations studies by a large and diverse user community.

Recent experimental measurements in the Large Hadron Collider (LHC) have shown a clear correlation between beam-beam resonance driving terms and beam losses, with a characteristic bunch-by-bunch signature. This observation creates interesting conditions to study diffusive processes. Over the past few decades, early chaos indicators, frequency map analysis and dynamic aperture studies have been commonly used to study particle stability in circular machines. However, the underlying mechanisms driving particles to large amplitudes in the presence of high order resonances is still an open question. Leveraging on years of development on particle tracking tools, this paper presents full-fledged 6-dimensional bunch-by-bunch beam loss simulations in the LHC. The computed loss rates are shown to be in agreement with experimental observations from LHC Run 3.