Gianluca Valentino

Simulations and measurements of beam loss patterns at the CERN Large Hadron Collider

The CERN Large Hadron Collider (LHC) is designed to collide proton beams of unprecedented energy, in order to extend the frontiers of high-energy particle physics. During the first very successful running period in 2010--2013, the LHC was routinely storing protons at 3.5--4 TeV with a total beam energy of up to 146 MJ, and even higher stored energies are foreseen in the future. This puts extraordinary demands on the control of beam losses. An un-controlled loss of even a tiny fraction of the beam could cause a superconducting magnet to undergo a transition into a normal-conducting state, or in the worst case cause material damage. Hence a multi-stage collimation system has been installed in order to safely intercept high-amplitude beam protons before they are lost elsewhere. To guarantee adequate protection from the collimators, a detailed theoretical understanding is needed. This article presents results of numerical simulations of the distribution of beam losses around the LHC that have leaked out of the collimation system. The studies include tracking of protons through the fields of more than 5000 magnets in the 27 km LHC ring over hundreds of revolutions, and Monte-Carlo simulations of particle-matter interactions both in collimators and machine elements being hit by escaping particles. The simulation results agree typically within a factor 2 with measurements of beam loss distributions from the previous LHC run. Considering the complex simulation, which must account for a very large number of unknown imperfections, and in view of the total losses around the ring spanning over 7 orders of magnitude, we consider this an excellent agreement. Our results give confidence in the simulation tools, which are used also for the design of future accelerators.

Automatic Threshold Selection for BLM Signals during LHC Collimator Beam-Based Alignment

The Large Hadron Collider at CERN is the largest high-energy particle accelerator in the world. Proton beams are currently collided at an energy of 4 TeV per beam to investigate the fundamental elements of matter. The collider is equipped with a collimation system to ensure that potentially destructive halo particles are absorbed before they hit vulnerable elements. Beam-based alignment of the collimators is required to ensure that they are positioned for maximum cleaning efficiency. The alignment procedure relies on feedback from Beam Loss Monitors, and is currently being automated to speed it up. This paper describes a method for automatically selecting a threshold for the beam loss signal during alignment, based on an empirical analysis of collimator alignment data over one year of operation. The results achieved with threshold selection during alignments at 4 TeV are presented.

MEASUREMENTS OF THE EFFECT OF COLLISIONS ON TRANSVERSE BEAM HALO DIFFUSION IN THE TEVATRON AND IN THE LHC

Beam-beam forces and collision optics can strongly affect beam lifetime, dynamic aperture, and halo formation in particle colliders. Extensive analytical and numerical si mulations are carried out in the design and operational stage o f a machine to quantify these effects, but experimental data is scarce. The technique of small-step collimator scans was applied to the Fermilab Tevatron collider and to the CERN Large Hadron Collider to study the effect of collisions on transverse beam halo dynamics. We describe the technique and present a summary of the first results on the dependence of the halo diffusion coefficient on betatron amplitude in the Tevatron and in the LHC.

Classification of LHC beam loss spikes using Support Vector Machines

The CERN Large Hadron Colliders (LHC) collimation system is the most complex beam cleaning system ever designed. It requires frequent setups to determine the beam centres and beam sizes at the 86 collimator positions. A collimator jaw is aligned to the beam halo when a clear beam loss spike is detected on a Beam Loss Monitor (BLM) downstream of the collimator. This paper presents a technique for identifying such clear loss spikes with the aid of Support Vector Machines. The training data was gathered from setups held during the first three months of the 2011 LHC run, and the model was tested with data from a machine development period.

Manned sample return mission to phobos: A technology demonstration for human exploration of Mars

In order to reduce the knowledge gap associated with long-duration human exploration of Mars, a manned precursor mission destined for one of the Martian moons is currently considered a feasible option for testing and demonstrating critical technologies within the Martian system. The 2013 Caltech Space Challenge, a student mission design competition held at the California Institute of Technology, addressed the interest in human precursor missions. Two teams of 16 students, with varying backgrounds and nationalities, were allocated five days to design a mission to land at least one human on a Martian moon and return them, along with a sample, safely to Earth with a launch date no later than January 1, 2041. This paper provides an overview of Technology Advancing Phobos Exploration and Return (TAPER-1), the manned Phobos sample return mission devised by Team Explorer. As the first manned mission to the Martian system, TAPER-1 is designed as an opposition class mission to Phobos, carrying four astronauts, with a launch date in April 2033, and a nominal time of flight of 456 days. In addition, this paper demonstrates the feasibility and value of exposing students to the process of rapid mission design.

Effect of a resonant excitation on the evolution of the beam emittance and halo population

Collimation with hollow electron beams or lenses (HEL) is currently one of the most promising concepts for active halo control in HL-LHC. In previous studies it has been shown that the halo can be efficiently removed with a hollow electron lens. Equally important as an efficient removal of the halo, is to demonstrate that the core stays unperturbed. In the case of an ideal hollow electron lens without bends, the field at the location of the beam core vanishes and the core thus remains unperturbed. In reality, the field at the beam core does not vanish entirely due to imperfections in the electron beam profile and the electron lens bends necessary to guide the electron in and out of the proton aperture. In particular, in the case of a pulsed operation of the electron lens the non-vanishing residual field induces noise on the proton beam. To identify the most sensitive pulsing patterns for the resonant mode and derive tolerances on the profile imperfections, a first MD (MD1415) was carried out on 24.08.2016 [1] and a second MD on 17.09.2017. In this note we present the results of the second MD (MD2167), which focused on confirming a part of the results of the first MD and testing in addition a resonant excitation for which no effect on the beam core is expected and the effect of random uniform noise in addition.

Machine Learning Applied at the LHC for Beam Loss Pattern Classification

Beam losses at the LHC are constantly monitored because they can heavily impact the performance of the machine. One of the highest risks is to quench the LHC superconducting magnets in the presence of losses leading to a long machine downtime in order to recover cryogenic conditions. Smaller losses are more likely to occur and have an impact on the machine performance, reducing the luminosity production or reducing the lifetime of accelerator systems due to radiation effects, such as magnets. Understanding the characteristics of the beam loss, such as the beam and the plane, is crucial in order to correct them. Regularly during the year, dedicated loss map measurements are performed in order to validate the beam halo cleaning of the collimation system. These loss maps have the particular advantage that they are performed in well controlled conditions and can therefore be used by a machine learning algorithm to classify the type of losses during the LHC machine cycle. This study shows the result of the beam loss classification and its retrospective application to beam loss data from the 2017 run.

Image mosaicing of tunnel wall images using high level features

This paper proposes a novel approach for position offset correction of images taken from a moving robotic platform in tunnel environments using image mosaicing. An image mosaic is formed by combining multiple images which capture overlapping components of a scene into a larger image. Unlike current image mosaicing methods, which use low-level features such as corners, our method uses binary edges as high-level features for image registration via template matching. This is necessary since such low-level features are absent or rare in tunnel environments. A shading correction algorithm is applied as a pre-processing step to adjust the uneven illumination present in this environment. This technique is simple and efficient while being robust to small camera rotations and small variations in camera distance from the wall. Experimental results show that our method contributes to good image mosaicing results with a low computational complexity, which is attractive for real-time image-based inspection applications.

Observation of channeling in bent crystals at the CERN LHC

The feasibility of crystal-assisted collimation is being investigated for improvements of the LHC collimation system, as a part of the future high luminosity upgrade of the CERN LHC (HL-LHC). Two high-accuracy goniometers, each equipped with one bent silicon crystal, were installed in the betatron cleaning insertion of the LHC in 2014. During dedicated tests in 2015, bent crystals were approached to the circulating the beams to test their usage as a first stage in a crystal-based system, both with proton and Pb ion beams. Tests were performed with protons at injection energy (450 GeV/c) and at flat top (6.5 TeV/c), and with ions at injection energy (450 Z GeV/c). A reduction of losses immediately downstream of the crystals was observed in optimum channeling orientation, demonstrating for the first time channeling at these energies. Halo cleaning efficiency of the crystal-based collimation system was also measured.

Anomaly Detection for Beam Loss Maps in the Large Hadron Collider

Asian Committee for Future Accelerators (ACFA),The American Physical Society Division of Physics of Beams APS-DB and the United States National Science Foundation (Plasma Physics and Accelerator Science),The International Union of Pure and Applied Physics (IUPAP)