arXiv subjects

Andrea Wulzer

Publications and source records attributed to Andrea Wulzer.

At least 19 recordsLinked to original sources

arXiv2025

Quark mixing from muon collider neutrinos

A high energy muon collider naturally produces a collimated beam of neutrinos for a fixed-target experiment at a dedicated far-forward facility. The high intensity and energy of the beam makes it ideally suited for astonishingly precise measurements of neutrino scattering on nucleons in the deeply inelastic regime, enabling the determination of the Cabibbo--Kobayashi--Maskawa~(CKM) quark mixing matrix. We assess the floor to the attainable sensitivity set by irreducible sources of uncertainties from the imperfect knowledge of the parton distribution (PDF) and fragmentation functions, showing that a strong improvement is possible well above current standards. As a by-product, our analysis also outlines extraordinary perspectives for a combined determination of the PDF. The results demonstrate the potential of a parasitic neutrino experiment at the muon collider, motivating detailed future studies.

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arXiv2025

Flavor physics at high-energy muon colliders

Flavor-breaking interactions due to heavy new physics can be probed at a 10 TeV muon collider in the high-energy production of quarks and leptons. The high collision energy mitigates the suppression of the new interactions, offering sensitivity to interaction scales well above 100 TeV both in the lepton and in the quark sector. We investigate all possible deformations of the Standard Model that produce quadratic growth with energy of the four-fermion scattering amplitudes at the muon collider, and we derive sensitivity projections. Electroweak radiation emission gives access to new observable final states like for instance the production of a charged pair of fermions by the emission of at least one W boson. This, combined with jet flavor tagging, improves the sensitivity and the ability to disentangle different interactions. Currently, the best probes of flavor-breaking new physics are high-intensity low-energy measurements of lepton or hadron decays or oscillations. The high-energy probes at the muon collider, of the interactions containing a muon bilinear, are competitive with current bounds and strongly superior for some class of transitions. The sensitivity extends to operators involving the top quark that cannot be tested at low energy. In addition, muon collider probes are generically less exposed to experimental or theoretical mismodeling uncertainties as they do not target the observation of extremely rare phenomena, nor they rely on extremely accurate measurements and theoretical predictions: the energy enhancement makes the putative effects relatively easy to observe. Muon collider measurements offer a novel pathway towards the exploration of flavor physics at the energy rather than at the intensity frontier.

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arXiv2025

Quantifying EFT Uncertainties in LHC Searches

Effective Field Theory (EFT) is a general framework to parametrize the low-energy approximation to a UV model that is widely used in model-independent searches for new physics. The use of EFTs at the LHC can suffer from a 'validity' issue, since new physics amplitudes often grow with energy and the kinematic regions with the most sensitivity to new physics have the largest theoretical uncertainties. We propose a method to account for these uncertainties with the aim of producing robust model-independent results with a well-defined statistical interpretation. In this approach, one must specify the new operators being studied as well as the new physics cutoff $M$, the energy scale where the EFT approximation breaks down. At energies below $M$, the EFT uncertainties are accounted for by adding additional higher dimensional operators with coefficients that are treated as nuisance parameters. The size of the nuisances are governed by a prior likelihood function that incorporates information about dimensional analysis, naturalness, and the scale $M$. At energies above $M$, our method incorporates the lack of predictivity of the EFT, and we show that this is crucial to obtain consistent results. We perform a number of tests of this method in a simple toy model, illustrating its performance in analyses aimed at new physics exclusion as well as for discovery. The method is conveniently implemented by the technique of event reweighting and is easily ported to realistic LHC analyses. We find that the procedure converges quickly with the number of nuisance parameters and is conservative when compared to UV models. The paper gives a precise meaning and offers a principled and practical solution to the widely debated 'EFT validity issue'.

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arXiv2024

Why detect forward muons at a muon collider

We survey the opportunities offered by the detection of the forward muons that accompany the creation of neutral effective vector bosons at a muon collider, in different kinematic regimes. Vectors with relatively low energy produce the Higgs boson and the extended muon angular coverage enables studies of the Higgs properties, such as the measurement of the inclusive production cross section and of the branching ratio to invisible final states. New heavy particles could be produced by vectors of higher energy, through Higgs portal interactions. If the new particles are invisible, the detection of the forward muons is essential in order to search for this scenario. The angular correlations of the forward muons are sensitive to the quantum interference between the vector boson helicity amplitudes and can be exploited for the characterisation of vector boson scattering and fusion processes. This is illustrated by analysing the CP properties of the Higgs coupling to the Z boson. Our findings provide a physics case and a set of benchmarks for the design of a dedicated forward muon detector.

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arXiv2024

Low-virtuality splitting in the Standard Model

When the available collision energy is much above the mass of the particles involved, scattering amplitudes feature kinematic configurations that are enhanced by the much lower virtuality of some intermediate particle. Such configurations generally factorise in terms of a hard scattering amplitude with exactly on-shell intermediate particle, times universal factors. In the case of real radiation emission, such factors are splitting amplitudes that describe the creation or the annihilation -- for initial or final state splittings -- of the low-virtuality particle and the creation of the real radiation particles. We compute at tree-level the amplitudes describing all the splittings that take place in the Standard Model when the collision energy is much above the electroweak scale. Unlike previous results, our splitting amplitudes fully describe the low-virtuality kinematic regime, which includes the region of collinear splitting, of soft emission, and combinations thereof. The splitting amplitudes are compactly represented as little-group tensors in an improved bi-spinor formalism for massive spin-1 particles that automatically incorporates the Goldstone Boson Equivalence Theorem. Simple explicit expressions are obtained using a suitably defined infinite-momentum helicity basis representation of the spinor variables. Our results, combined with the known virtual contributions, could enable systematic predictions of the leading electroweak radiation effects in high-energy scattering processes, with particularly promising phenomenological applications to the physics of future colliders with very high energy such as a muon collider.

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arXiv2023

Boosting likelihood learning with event reweighting

Extracting maximal information from experimental data requires access to the likelihood function, which however is never directly available for complex experiments like those performed at high energy colliders. Theoretical predictions are obtained in this context by Monte Carlo events, which do furnish an accurate but abstract and implicit representation of the likelihood. Strategies based on statistical learning are currently being developed to infer the likelihood function explicitly by training a continuous-output classifier on Monte Carlo events. In this paper, we investigate the usage of Monte Carlo events that incorporate the dependence on the parameters of interest by reweighting. This enables more accurate likelihood learning with less training data and a more robust learning scheme that is more suited for automation and extensive deployment. We illustrate these advantages in the context of LHC precision probes of new Effective Field Theory interactions.

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arXiv2023

Goodness of fit by Neyman-Pearson testing

The Neyman-Pearson strategy for hypothesis testing can be employed for goodness of fit if the alternative hypothesis is selected from data by exploring a rich parametrised family of models, while controlling the impact of statistical fluctuations. The New Physics Learning Machine (NPLM) methodology has been developed as a concrete implementation of this idea, to target the detection of new physical effects in the context of high energy physics collider experiments. In this paper we conduct a comparison of this approach to goodness of fit with others, in particular with classifier-based strategies that share strong similarities with NPLM. From our comparison, NPLM emerges as the more sensitive test to small departures of the data from the expected distribution and not biased towards detecting specific types of anomalies. These features make it suited for agnostic searches for new physics at collider experiments. Its deployment in other scientific and industrial scenarios should be investigated.

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arXiv2023

Invisible Higgs from forward muons at a muon collider

We propose to probe the Higgs boson decay to invisible particles at a muon collider by observing the forward muons that are produced in association with the Higgs in the Z-boson fusion channel. An excellent sensitivity is possible in line of principle, owing to the large number of produced Higgs bosons, provided a forward muon detector is installed. We find that the resolution on the measurement of the muon energy and angle will be the main factor limiting the actual sensitivity. This poses tight requirements on the forward muon detector design.

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arXiv2023

A fast and flexible machine learning approach to data quality monitoring

We present a machine learning based approach for real-time monitoring of particle detectors. The proposed strategy evaluates the compatibility between incoming batches of experimental data and a reference sample representing the data behavior in normal conditions by implementing a likelihood-ratio hypothesis test. The core model is powered by recent large-scale implementations of kernel methods, nonparametric learning algorithms that can approximate any continuous function given enough data. The resulting algorithm is fast, efficient and agnostic about the type of potential anomaly in the data. We show the performance of the model on multivariate data from a drift tube chambers muon detector.

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arXiv2023

Fast kernel methods for Data Quality Monitoring as a goodness-of-fit test

We here propose a machine learning approach for monitoring particle detectors in real-time. The goal is to assess the compatibility of incoming experimental data with a reference dataset, characterising the data behaviour under normal circumstances, via a likelihood-ratio hypothesis test. The model is based on a modern implementation of kernel methods, nonparametric algorithms that can learn any continuous function given enough data. The resulting approach is efficient and agnostic to the type of anomaly that may be present in the data. Our study demonstrates the effectiveness of this strategy on multivariate data from drift tube chamber muon detectors.

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arXiv2023

The collider landscape: which collider for establishing the SM instability?

Capabilities of future colliders are usually discussed assuming specific hypothetical new physics. We consider the opposite possibility: that no new physics is accessible, and we want to learn if the unnatural Standard Model is part of a vast landscape. We argue that a main step in this direction would be establishing the possible instability scale of the Higgs potential. This primarily needs reducing the uncertainty on the strong coupling and on the top quark mass. We show that the top quark mass can be measured well enough via a $t \bar t$ threshold scan with low $10^{33}\,{\rm cm}^{-2}{\rm sec}^{-1}$ luminosity, that seems achievable at a `small' $e^+ e^-$ collider in the LEP tunnel, or at the first low-energy stage of a muon collider.

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arXiv2022

Truncation, validity, uncertainties

The truncation of the standard-model effective field theory, its validity and the associated uncertainties have been discussed in meetings of the LHC EFT WG. Proposals were made by participants to address these issues. No consensus was reached and no formal recommendation is therefore put forward at this time. None of the proposals has been approved or validated and further work is needed to establish a prescription. This note aims at summarizing the proposals and points of debate.

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arXiv2022

The physics case of a 3 TeV muon collider stage

In the path towards a muon collider with center of mass energy of 10 TeV or more, a stage at 3 TeV emerges as an appealing option. Reviewing the physics potential of such muon collider is the main purpose of this document. In order to outline the progression of the physics performances across the stages, a few sensitivity projections for higher energy are also presented. There are many opportunities for probing new physics at a 3 TeV muon collider. Some of them are in common with the extensively documented physics case of the CLIC 3 TeV energy stage, and include measuring the Higgs trilinear coupling and testing the possible composite nature of the Higgs boson and of the top quark at the 20 TeV scale. Other opportunities are unique of a 3 TeV muon collider, and stem from the fact that muons are collided rather than electrons. This is exemplified by studying the potential to explore the microscopic origin of the current $g$-2 and $B$-physics anomalies, which are both related with muons.

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arXiv2022

Learning new physics efficiently with nonparametric methods

We present a machine learning approach for model-independent new physics searches. The corresponding algorithm is powered by recent large-scale implementations of kernel methods, nonparametric learning algorithms that can approximate any continuous function given enough data. Based on the original proposal by D'Agnolo and Wulzer (arXiv:1806.02350), the model evaluates the compatibility between experimental data and a reference model, by implementing a hypothesis testing procedure based on the likelihood ratio. Model-independence is enforced by avoiding any prior assumption about the presence or shape of new physics components in the measurements. We show that our approach has dramatic advantages compared to neural network implementations in terms of training times and computational resources, while maintaining comparable performances. In particular, we conduct our tests on higher dimensional datasets, a step forward with respect to previous studies.

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arXiv2022

Learning from Radiation at a Very High Energy Lepton Collider

We study the potential of lepton collisions with about $10\text{ TeV}$ center of mass energy to probe Electroweak, Higgs and Top short-distance physics at the $100\text{ TeV}$ scale, pointing out the interplay with the long-distance ($100\text{ GeV}$) phenomenon of Electroweak radiation. On one hand, we find that sufficiently accurate theoretical predictions require the resummed inclusion of radiation effects, which we perform at the double logarithmic order. On the other hand, we notice that short-distance physics does influence the emission of Electroweak radiation. Therefore the investigation of the radiation pattern can enhance the sensitivity to new short-distance physical laws. We illustrate these aspects by studying Effective Field Theory contact interactions in di-fermion and di-boson production, and comparing cross-section measurements that require or that exclude the emission of massive Electroweak bosons. The combination of the two types of measurements is found to enhance the sensitivity to the new interactions. Based on these results, we perform sensitivity projections to Higgs and Top Compositeness and to minimal $Z'$ new physics scenarios at future muon colliders.

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arXiv2021

Learning New Physics from an Imperfect Machine

We show how to deal with uncertainties on the Standard Model predictions in an agnostic new physics search strategy that exploits artificial neural networks. Our approach builds directly on the specific Maximum Likelihood ratio treatment of uncertainties as nuisance parameters for hypothesis testing that is routinely employed in high-energy physics. After presenting the conceptual foundations of our method, we first illustrate all aspects of its implementation and extensively study its performances on a toy one-dimensional problem. We then show how to implement it in a multivariate setup by studying the impact of two typical sources of experimental uncertainties in two-body final states at the LHC.

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arXiv2021

Learning Multivariate New Physics

We discuss a method that employs a multilayer perceptron to detect deviations from a reference model in large multivariate datasets. Our data analysis strategy does not rely on any prior assumption on the nature of the deviation. It is designed to be sensitive to small discrepancies that arise in datasets dominated by the reference model. The main conceptual building blocks were introduced in Ref. [1]. Here we make decisive progress in the algorithm implementation and we demonstrate its applicability to problems in high energy physics. We show that the method is sensitive to putative new physics signals in di-muon final states at the LHC. We also compare our performances on toy problems with the ones of alternative methods proposed in the literature.

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arXiv2021

High-energy EFT probes with fully differential Drell-Yan measurements

We study the potential of fully-differential measurements of high-energy dilepton cross-sections at the LHC to probe heavy new physics encapsulated in dimension-6 interaction operators. The assessment is performed in the seven-dimensional parameter space of operators that induce energy-growing corrections to the Standard Model partonic cross-sections at the interference level, and in the two-dimensional subspace associated with the W and Y parameters. A considerable sensitivity improvement is found relative to single-differential measurements, owing to the possibility of probing at the interference level more directions in the seven-dimensional parameter space. The reduction of parton distribution function uncertainties in the fully-differential fit is also found to play a significant role. The results are interpreted in the minimal Z' new-physics model, providing a concrete illustration of the advantages of the fully-differential analysis. We find that high-energy dilepton measurements can extend the Z' exclusion and discovery potential well beyond the reach of direct searches in a large region of the parameter space.

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