Future Colliders

Abstract:

Monte Carlo simulations are a crucial component when analysing the Standard Model and New physics processes at the Large Hadron Collider (LHC). This paper aims to explore the use of generative models for increasing the statistics of Monte Carlo simulations in the final stage of data analysis by generating synthetic data that follows the same kinematic distributions for a limited set of analysis-specific observables to a high precision. Several state-of-the-art generative machine learning algorithms are adapted to this task, best performance is demonstrated by the normalizing flow architectures, which are capable of fast generation of an arbitrary number of new events. As an example of analysis-specific Monte Carlo simulated data, a well-known benchmark sample containing the Higgs boson production beyond the Standard Model and the corresponding irreducible background is used. The applicability of normalizing flows with different model parameters and numbers of initial events used in training is investigated. The resulting event distributions are compared with the original Monte Carlo distributions using statistical tests and a simplified statistical analysis to evaluate their similarity and quality of reproduction required in a physics analysis environment in a systematic way.Comment: 28 pages, 22 figure

Abstract:

We consider a model where the electroweak symmetry breaking is driven by strong dynamics, resulting in an electroweak doublet scalar condensate, and transmitted to the standard model matter fields via another electroweak doublet scalar. At low energies the effective theory therefore shares features with a type-I two Higgs doublet model. However, important differences arise due to the rich composite spectrum expected to contain new vector resonances accessible at the LHC. We carry out a systematic analysis of the vector resonance signals at LHC and find that the model remains viable, but will be tightly constrained by direct searches as the projected integrated luminosity, around 200 fb(-1), of the current run becomes available.Peer reviewe

Abstract:

The interaction of intense particle bunches with plasma can give rise to plasma wakes capable of sustaining gigavolt-per-metre electric fields, which are orders of magnitude higher than provided by state-of-the-art radio-frequency technology. Plasma wakefields can, therefore, strongly accelerate charged particles and offer the opportunity to reach higher particle energies with smaller and hence more widely available accelerator facilities. However, the luminosity and brilliance demands of high-energy physics and photon science require particle bunches to be accelerated at repetition rates of thousands or even millions per second, which are orders of magnitude higher than demonstrated with plasma-wakefield technology. Here we investigate the upper limit on repetition rates of beam-driven plasma accelerators by measuring the time it takes for the plasma to recover to its initial state after perturbation by a wakefield. The many-nanosecond-level recovery time measured establishes the in-principle attainability of megahertz rates of acceleration in plasmas. The experimental signatures of the perturbation are well described by simulations of a temporally evolving parabolic ion channel, transferring energy from the collapsing wake to the surrounding media. This result establishes that plasma-wakefield modules could be developed as feasible high-repetition-rate energy boosters at current and future particle-physics and photon-science facilities.