arXiv subjects

Michael Spannowsky

Publications and source records attributed to Michael Spannowsky.

At least 109 records · Page 6Linked to original sources

arXiv2021

Effective connections of $a_μ$, Higgs physics, and the collider frontier

We consider scalar extensions of the SM and their effective field theoretic generalisations to illustrate the phenomenological connection between precision measurements of the anomalous magnetic moment of the muon $a_μ$, precision Higgs measurements, and direct collider sensitivity. To this end, we consider charged BSM scalar sectors of the Zee-Babu type for which we develop a consistent, and complete dimensions-5 and -6 effective field theory extension. This enables us to track generic new physics effects that interact with the SM predominantly via radiative interactions. While the operator space is high dimensional, the intersection of exotics searches at the Large Hadron Collider, Higgs signal strength and anomalous muon magnetic measurements is manageably small. We find that consistency of LHC Higgs observations and $a_μ$ requires a significant deformation of the new states' electroweak properties. Evidence in searches for doubly charged scalars as currently pursued by the LHC experiments can be used to further tension the BSMEFT parameter space and resolve blind directions in the EFT-extended Zee-Babu scenario.

hep-ph↗

arXiv2021

Anomaly detection with Convolutional Graph Neural Networks

We devise an autoencoder based strategy to facilitate anomaly detection for boosted jets, employing Graph Neural Networks (GNNs) to do so. To overcome known limitations of GNN autoencoders, we design a symmetric decoder capable of simultaneously reconstructing edge features and node features. Focusing on latent space based discriminators, we find that such setups provide a promising avenue to isolate new physics and competing SM signatures from sensitivity-limiting QCD jet contributions. We demonstrate the flexibility and broad applicability of this approach using examples of $W$ bosons, top quarks, and exotic hadronically-decaying exotic scalar bosons.

hep-ph↗

arXiv2021

Quantum-inspired event reconstruction with Tensor Networks: Matrix Product States

Tensor Networks are non-trivial representations of high-dimensional tensors, originally designed to describe quantum many-body systems. We show that Tensor Networks are ideal vehicles to connect quantum mechanical concepts to machine learning techniques, thereby facilitating an improved interpretability of neural networks. This study presents the discrimination of top quark signal over QCD background processes using a Matrix Product State classifier. We show that entanglement entropy can be used to interpret what a network learns, which can be used to reduce the complexity of the network and feature space without loss of generality or performance. For the optimisation of the network, we compare the Density Matrix Renormalization Group (DMRG) algorithm to stochastic gradient descent (SGD) and propose a joined training algorithm to harness the explainability of DMRG with the efficiency of SGD.

hep-ph↗

arXiv2021

Quantum Optimisation of Complex Systems with a Quantum Annealer

We perform an in-depth comparison of quantum annealing with several classical optimisation techniques, namely thermal annealing, Nelder-Mead, and gradient descent. We begin with a direct study of the 2D Ising model on a quantum annealer, and compare its properties directly with those of the thermal 2D Ising model. These properties include an Ising-like phase transition that can be induced by either a change in 'quantum-ness' of the theory, or by a scaling the Ising couplings up or down. This behaviour is in accord with what is expected from the physical understanding of the quantum system. We then go on to demonstrate the efficacy of the quantum annealer at minimising several increasingly hard two dimensional potentials. For all the potentials we find the general behaviour that Nelder-Mead and gradient descent methods are very susceptible to becoming trapped in false minima, while the thermal anneal method is somewhat better at discovering the true minimum. However, and despite current limitations on its size, the quantum annealer performs a minimisation very markedly better than any of these classical techniques. A quantum anneal can be designed so that the system almost never gets trapped in a false minimum, and rapidly and successfully minimises the potentials.

quant-ph↗

arXiv2021

A fully differential SMEFT analysis of the golden channel using the method of moments

The Method of Moments is a powerful framework to disentangle the relative contributions of amplitudes of a specific process to its various phase space regions. We apply this method to carry out a fully differential analysis of the Higgs decay channel $h \to 4\ell$ and constrain gauge-Higgs coupling modifications parametrised by dimension-six effective operators. We find that this analysis approach provides very good constraints and minimises degeneracies in the parameter space of the effective theory. By combining the decay $h \to 4\ell$ with Higgs-associated production processes, $Wh$ and $Zh$, we obtain the strongest reported bounds on anomalous gauge-Higgs couplings.

hep-ph↗

arXiv2021

Searching for QCD Instantons at Hadron Colliders

QCD instantons are arguably the best motivated yet unobserved nonperturbative effects predicted by the Standard Model. A discovery and detailed study of instanton-generated processes at colliders would provide a new window into the phenomenological exploration of QCD and a vastly improved fundamental understanding of its non-perturbative dynamics. Building on the optical theorem, we numerically calculate the total instanton cross-section from the elastic scattering amplitude, also including quantum effects arising from resummed perturbative exchanges between hard gluons in the initial state, thereby improving in accuracy on previous results. Although QCD instanton processes are predicted to be produced with a large scattering cross-section at small centre-of-mass partonic energies, discovering them at hadron colliders is a challenging task that requires dedicated search strategies. We evaluate the sensitivity of high-luminosity LHC runs, as well as low-luminosity LHC and Tevatron runs. We find that LHC low-luminosity runs in particular, which do not suffer from large pileup and trigger thresholds, show a very good sensitivity for discovering QCD instanton-generated processes.

hep-ph↗

arXiv2021

Exploring instantons with spin-lattice systems

Instanton processes are present in a variety of quantum field theories relevant to high energy as well as condensed matter physics. While they have led to important theoretical insights and physical applications, their underlying features often remain elusive due to the complicated computational treatment. Here, we address this problem by studying topological as well as non-topological instantons using Monte Carlo methods on lattices of interacting spins. As a proof of principle, we systematically construct instanton solutions in $O(3)$ non-linear sigma models with a Dzyaloshinskii-Moriya interaction in $(1 + 1)$ and $(1 + 2)$ dimensions, thereby resembling an example of a chiral magnet. We demonstrate that, due to their close correspondence, Monte Carlo techniques in spin-lattice systems are well suited to describe topologically non-trivial field configurations in these theories. In particular, by means of simulated annealing, we demonstrate how to obtain domain walls, merons and critical instanton solutions.

hep-th↗

arXiv2021

Combine and Conquer: Event Reconstruction with Bayesian Ensemble Neural Networks

Ensemble learning is a technique where multiple component learners are combined through a protocol. We propose an Ensemble Neural Network (ENN) that uses the combined latent-feature space of multiple neural network classifiers to improve the representation of the network hypothesis. We apply this approach to construct an ENN from Convolutional and Recurrent Neural Networks to discriminate top-quark jets from QCD jets. Such ENN provides the flexibility to improve the classification beyond simple prediction combining methods by linking different sources of error correlations, hence improving the representation between data and hypothesis. In combination with Bayesian techniques, we show that it can reduce epistemic uncertainties and the entropy of the hypothesis by simultaneously exploiting various kinematic correlations of the system, which also makes the network less susceptible to a limitation in training sample size.

hep-ph↗

arXiv2021

The Emergence of Electroweak Skyrmions through Higgs Bosons

Skyrmions are extended field configurations, initially proposed to describe baryons as topological solitons in an effective field theory of mesons. We investigate and confirm the existence of skyrmions within the electroweak sector of the Standard Model and study their properties. We find that the interplay of the electroweak sector with a dynamical Higgs field and the Skyrme term leads to a non-trivial vacuum structure with the skyrmion and perturbative vacuum sectors separated by a finite energy barrier. We identify dimension-8 operators that stabilise the electroweak skyrmion as a spatially localised soliton field configuration with finite size. Such operators are induced generically by a wide class of UV models. To calculate the skyrmion energy and radius we use a neural network method. Electroweak skyrmions are non-topological solitons but are exponentially long lived, and we find that the electroweak skyrmion is a viable dark matter candidate. While the skyrmion production cross section at collider experiments is suppressed, measuring the size of the Skyrme term in multi-Higgs-production processes at high-energy colliders is a promising avenue to probe the existence of electroweak skyrmions.

hep-ph↗

arXiv2021

Elvet -- a neural network-based differential equation and variational problem solver

We present Elvet, a Python package for solving differential equations and variational problems using machine learning methods. Elvet can deal with any system of coupled ordinary or partial differential equations with arbitrary initial and boundary conditions. It can also minimize any functional that depends on a collection of functions of several variables while imposing constraints on them. The solution to any of these problems is represented as a neural network trained to produce the desired function.

cs.LG↗

arXiv2021

EFT Diagrammatica: UV Roots of the CP-conserving SMEFT

Effective Field Theories are an established framework to bridge the gap between UV and low energy theories. In the context of the Standard Model, the bottom-up approach extends its operator set and thus equips us to astutely probe its observables while encapsulating indirect evidence of unknown high scale theories. While the top-down approach, on the other hand, employs functional techniques to integrate out the heavy fields from a BSM Lagrangian leading to a set of SMEFT operators. An intricate interplay of the two approaches enhances the efficacy of the SMEFT in making meaningful predictions while providing a platform for conducting a coherent comparison of new physics scenarios. However, while the bottom-up approach fails to indicate the origin of the effective operators, the top-down approach is highly dependent on the specific model assumptions of the UV theory. We, for the first time, are proposing a diagrammatic approach to establish selection criteria for the allowed heavy field representations corresponding to each SMEFT operator. This, in turn, paves the way to construct observable driven new physics models. While we take a predominantly minimalistic approach, we also highlight the necessity for non-minimal interactions for certain operators.

hep-ph↗

arXiv2021

ATLAS Violating CP Effectively

CP violation beyond the Standard Model (SM) is a crucial missing piece for explaining the observed matter-antimatter symmetry in the Universe. Recently, the ATLAS experiment at the Large Hadron Collider has performed an analysis of electroweak $Zjj$ production, thereby excluding the SM locally at 95\% confidence level in the measurement of CP-sensitive observables. We take the excess' interpretation in terms of anomalous gauge-Higgs interactions at face value and discuss further steps that are required to scrutinize its origin. In particular, we discuss the relevance of multi-boson production using adapted angular observables to show how they can be used to directly tension the reported $Zjj$ excess in a more comprehensive analysis. To connect the excess to a concrete UV scenario for which the underlying assumptions of the $Zjj$ analysis are valid, we identify vector-like leptons as a candidate theory consistent with the observed CP-odd Wilson coefficient hierarchy observed by ATLAS. We perform a complete one-loop matching calculation to motivate further model-specific and correlated new physics searches. In parallel, we provide estimates of the sensitivity reach of the LHC's high luminosity phase for this particular scenario of CP-violation in light of electroweak precision and Run-2 Higgs data. These provide strong constraints on the model's CP-even low-energy phenomenology, but also inform the size of the CP-odd SM deformation indirectly via our model hypothesis.

hep-ph↗

arXiv2021

Cosmological bubble friction in local equilibrium

In first-order cosmological phase transitions, the asymptotic velocity of expanding bubbles is of crucial relevance for predicting observables like the spectrum of stochastic gravitational waves, or for establishing the viability of mechanisms explaining fundamental properties of the universe such as the observed baryon asymmetry. In these dynamic phase transitions, it is generally accepted that subluminal bubble expansion requires out-of-equilibrium interactions with the plasma which are captured by friction terms in the equations of motion for the scalar field. This has been disputed in works pointing out subluminal velocities in local equilibrium arising either from hydrodynamic effects in deflagrations or from the entropy change across the bubble wall in general situations. We argue that both effects are related and can be understood from the conservation of the entropy of the degrees of freedom in local equilibrium, leading to subluminal speeds for both deflagrations and detonations. The friction effect arises from the background field dependence of the entropy density in the plasma, and can be accounted for by simply imposing local conservation of stress-energy and including field dependent thermal contributions to the effective potential. We illustrate this with explicit calculations of dynamic and static bubbles for a first-order electroweak transition in a Standard Model extension with additional scalar fields.

hep-ph↗

arXiv2021

Precision SMEFT bounds from the VBF Higgs at high transverse momentum

We study the production of Higgs bosons at high transverse momenta via vector-boson fusion (VBF) in the Standard Model Effective Field Theory (SMEFT). We find that contributions from four independent operator combinations dominate in this limit. These are the same `high energy primaries' that control high energy diboson processes, including Higgs-strahlung. We perform detailed collider simulations for the diphoton decay mode of the Higgs boson as well as the three final states arising from the ditau channel. Using the quadratic growth of the SMEFT contributions relative to the Standard Model (SM) contribution, we project very stringent bounds on these operators that far surpass the corresponding bounds from the LEP experiment.

hep-ph↗

arXiv2021

Unsupervised Event Classification with Graphs on Classical and Photonic Quantum Computers

Photonic Quantum Computers provides several benefits over the discrete qubit-based paradigm of quantum computing. By using the power of continuous-variable computing we build an anomaly detection model to use on searches for New Physics. Our model uses Gaussian Boson Sampling, a $\#$P-hard problem and thus not efficiently accessible to classical devices. This is used to create feature vectors from graph data, a natural format for representing data of high-energy collision events. A simple K-means clustering algorithm is used to provide a baseline method of classification. We then present a novel method of anomaly detection, combining the use of Gaussian Boson Sampling and a quantum extension to K-means known as Q-means. This is found to give equivalent results compared to the classical clustering version while also reducing the $\mathcal{O}$ complexity, with respect to the sample's feature-vector length, from $\mathcal{O}(N)$ to $\mathcal{O}(\mbox{log}(N))$. Due to the speed of the sampling algorithm and the feasibility of near-term photonic quantum devices, anomaly detection at the trigger level can become practical in future LHC runs.

hep-ph↗

arXiv2021

Extended Higgs sectors, effective field theory and Higgs phenomenology

We consider the phenomenological implications of charged scalar extensions of the SM Higgs sector in addition to EFT couplings of this new state to SM matter. We perform a detailed investigation of modifications of loop-induced decays of the 125 GeV Higgs boson, which receives corrections from the propagating charged scalars alongside one-loop EFT operator insertions and demonstrate that the interplay of $H\to γγ$ and $H\to Zγ$ decays can be used to clarify the additional states phenomenology in case a discovery is made in the future. In parallel, EFT interactions of the charged Higgs can lead to a decreased sensitivity to the virtual presence of charged Higgs states, which can significantly weaken the constraints that are naively expected from the precisely measured $H\to γγ$ branching ratio. Again $H\to Zγ$ measurements provide complementary sensitivity that can be exploited in the future.

hep-ph↗

arXiv2020

Sensing Higgs cascade decays through memory

Beyond the Standard Model scenarios with extensions of the Higgs sector typically predict new resonances that can undergo a series of cascade decays to detectable Standard Model particles. On one hand, sensitivity to such signatures will contribute to the full reconstruction of the extended Higgs potential if a new physics discovery will be made. On the other hand, such cascade decays could be dominant decay channels, thus being potentially the best motivated signatures to achieve a new physics discovery in the first place. In this work, we show how the long short-term memory that is encoded in the cascade decays' phenomenology can be exploited in discriminating the signal from the background, where no such information is present. In parallel, we demonstrate for theoretically motivated scenarios that such an approach provides improved sensitivity compared to more standard analyses, where only information about the signal's final state kinematics is included.

hep-ph↗

arXiv2020

Classifying Standard Model Extensions Effectively with Precision Observables

Effective theories are well established theoretical frameworks to describe the effect of energetically widely separated UV models on observables at lower energy scales. Due to the complexity of the effective theory when taking all the Standard Model symmetries and degrees of freedoms into account, tensioning the entire system in a completely agnostic way against experimental measurements results in constraints on the Wilson Coefficients of the effective operators that either bears little information or challenge intrinsic assumptions imposed on the effective field theory framework. In general, a specific high-scale extension of the Standard Model only induces a subset of all possible operators. Thus, by investigating which operators are induced by different classes of the Standard Model extensions and comparing to which precision observables they contribute, we show that it is possible to obtain an improved understanding of which UV model is realised in nature. We consider 15 UV models which are single scalar field extensions of the Standard Model and compute their dimension-6 operators after integrating out the heavy scalars up to 1-loop level. Only very few of these scenarios remain indistinguishable, while most of the models can be phenomenologically separated from one another. Most of these scenarios possess their own characteristic operator signature. Following the approach outlined here, a comparative analysis of a wide range of models will allow to assess at what level the effective field theory series can be truncated and which experimental measurements to prioritise.

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