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In this article, we document version 0.1 of the PanScales code for parton shower simulations. With the help of a few examples, we discuss basic usage of the code, including tests of logarithmic accuracy of parton showers. We expose some of the numerical techniques underlying the logarithmic tests and include a description of how users can implement their own showers within the framework. Some of the simpler logarithmic tests can be performed in a few minutes on a modern laptop. As an early step towards phenomenology, we also outline some aspects of a preliminary interface to Pythia, for access to its hard matrix elements and its hadronisation modules., Comment: Code available from https://gitlab.com/panscales/panscales-0.X, 23 pages, 5 figures

To explore the interplay of NLO matching and next-to-leading logarithmic (NLL) parton showers, we consider the simplest case of $\gamma^*$ and Higgs-boson decays to $q\bar q$ and $gg$ respectively. Not only should shower NLL accuracy be retained across observables after matching, but for global event-shape observables and the two-jet rate, matching can augment the shower in such a way that it additionally achieves next-to-next-to-double-logarithmic (NNDL) accuracy, a first step on the route towards general NNLL. As a proof-of-concept exploration of this question, we consider direct application of multiplicative matrix-element corrections, as well as simple implementations of MC@NLO and POWHEG-style matching. We find that the first two straightforwardly bring NNDL accuracy, and that this can also be achieved with POWHEG, although particular care is needed in the handover between POWHEG and the shower. Our study involves both analytic and numerical components and we also touch on some phenomenological considerations., Comment: 42 pages, 14 figures; v2: matches published version; v3: corrected typos in eqs. 1.1, 4.1, A.4, no other content affected

A major task in particle physics is the measurement of rare signal processes. These measurements are highly dependent on the classification accuracy of these events in relation to the huge background of other Standard Model processes. Reducing the background by a few tens of percent with the same signal efficiency can already increase the sensitivity considerably. This work demonstrates the importance of incorporating physical information into deep learning-based event selection. The paper includes this information into different methods for classifying events, in particular Boosted Decision Trees, Transformer Architectures (Particle Transformer) and Graph Neural Networks (Particle Net). In addition to the physical information previously proposed for jet tagging, we add particle measures for energy-dependent particle-particle interaction strengths as predicted by the leading order interactions of the Standard Model (SM). We find that the integration of physical information into the attention matrix (transformers) or edges (graphs) notably improves background rejection by $10\%$ to $40\%$ over baseline models (a graph network), with about $10\%$ of this improvement directly attributable to what we call the SM interaction matrix. In a simplified statistical analysis, we find that such architectures can improve the significance of signals by a significant factor compared to a graph network (our base model)., Comment: Version 2 of this paper supersedes arXiv:2211.05143v1. 26 pages, 5 figures

We carry out extensive tests of the next-to-leading logarithmic (NLL) accuracy of the PanScales parton showers, as introduced recently for colour-singlet production in hadron collisions. The tests include comparisons to (semi-)analytic NLL calculations of a wide range of hadron-collider observables: the colour-singlet boson transverse momentum distribution; global and non-global hadronic energy flow variables related to jet vetoes and analogues of jettiness distributions; (sub)jet multiplicities; and observables sensitive to the DGLAP evolution of the incoming momentum fractions. In the tests, we also include an implementation of a standard transverse-momentum ordered dipole shower, to establish the size of missing NLL effects in such showers, which, depending on the observable, can reach $100\%$. This paper, together with arXiv:2205.02237, constitutes the first step towards process-independent NLL-accurate parton showers for hadronic collisions., Comment: 35 pages, 10 figures, v2 (new exploratory phenomenological results of the showers with scale variation)

We formulate PanScales parton showers for hadron collisions so as to achieve next-to-leading logarithmic (NLL) accuracy across a broad set of observables. We do so specifically for colour singlet production. Relative to the existing PanScales final-state showers, the main new question is that of how to redistribute momentum imbalances from initial-state branching across the remainder of the event. We presents tests of the showers at fixed order, including the treatment of full colour for soft-collinear emissions and of spin correlations in both the soft and collinear domains. We also include comparisons to a formulation of a standard dipole shower, the current leading-logarithmic state of the art. A forthcoming companion paper will explore all-order tests of the new showers., Comment: 65 pages, 15 figures; v2 includes additional clarifications and comparisons, as accepted for publication in JHEP

Normalizing flows are a class of generative models that enable exact likelihood evaluation. While these models have already found various applications in particle physics, normalizing flows are not flexible enough to model many of the peripheral features of collision events. Using the framework of Nielsen et al. (2020), we introduce several surjective and stochastic transform layers to a baseline normalizing flow to improve modelling of permutation symmetry, varying dimensionality and discrete features, which are all commonly encountered in particle physics events. We assess their efficacy in the context of the generation of a matrix element-level process, and in the context of anomaly detection in detector-level LHC events., Comment: 29 pages, 15 figures

This manual describes the PYTHIA 8.3 event generator, the most recent version of an evolving physics tool used to answer fundamental questions in particle physics. The program is most often used to generate high-energy-physics collision "events", i.e. sets of particles produced in association with the collision of two incoming high-energy particles, but has several uses beyond that. The guiding philosophy is to produce and reproduce properties of experimentally obtained collisions as accurately as possible. The program includes a wide ranges of reactions within and beyond the Standard Model, and extending to heavy ion physics. Emphasis is put on phenomena where strong interactions play a major role. The manual contains both pedagogical and practical components. All included physics models are described in enough detail to allow the user to obtain a cursory overview of used assumptions and approximations, enabling an informed evaluation of the program output. A number of the most central algorithms are described in enough detail that the main results of the program can be reproduced independently, allowing further development of existing models or the addition of new ones. Finally, a chapter dedicated fully to the user is included towards the end, providing pedagogical examples of standard use cases, and a detailed description of a number of external interfaces. The program code, the online manual, and the latest version of this print manual can be found on the PYTHIA web page: https://www.pythia.org/, Comment: 315 pages, 19 figures. The program code is available at https://www.pythia.org/

First-principle simulations are at the heart of the high-energy physics research program. They link the vast data output of multi-purpose detectors with fundamental theory predictions and interpretation. This review illustrates a wide range of applications of modern machine learning to event generation and simulation-based inference, including conceptional developments driven by the specific requirements of particle physics. New ideas and tools developed at the interface of particle physics and machine learning will improve the speed and precision of forward simulations, handle the complexity of collision data, and enhance inference as an inverse simulation problem., Comment: Review article based on a Snowmass 2021 contribution

We introduce a simple procedure that resolves the long-standing question of how to account for single-logarithmic spin-correlation effects in parton showers not just in the collinear limit, but also in the soft wide-angle limit, at leading colour. We discuss its implementation in the context of the PanScales family of parton showers, where it complements our earlier treatment of the purely collinear spin correlations. Comparisons to fixed-order matrix elements help validate our approach up to third order in the strong coupling, and an appendix demonstrates the small size of residual subleading-colour effects. To help probe wide-angle soft spin correlation effects, we introduce a new declustering-based non-global spin-sensitive observable, the first of its kind. Our showers provide a reference for its single-logarithmic resummation. The work in this paper represents the last step required for final-state massless showers to satisfy the broad PanScales next-to-leading logarithmic accuracy goals., Comment: 26 pages, 12 figures

We propose a framework for high-energy interactions in which resonance decays and electroweak branching processes are interleaved with the QCD evolution in a single common sequence of decreasing resolution scales. The interleaved treatment of resonance decays allows for a new treatment of finite-width effects in parton showers. At scales above their offshellness, resonances participate explicitly as incoming and outgoing states in branching processes, while they are effectively "integrated out" of the description at lower scales. We implement this formalism, together with a full set of antenna functions for branching processes involving electroweak (W/Z/H) bosons in the Vincia shower module in Pythia 8.3, and study some of the consequences., Comment: 38 pages, 15 figures

We propose a new method to define anomaly scores and apply this to particle physics collider events. Anomalies can be either rare, meaning that these events are a minority in the normal dataset, or different, meaning they have values that are not inside the dataset. We quantify these two properties using an ensemble of One-Class Deep Support Vector Data Description models, which quantifies differentness, and an autoregressive flow model, which quantifies rareness. These two parameters are then combined into a single anomaly score using different combination algorithms. We train the models using a dataset containing only simulated collisions from the Standard Model of particle physics and test it using various hypothetical signals in four different channels and a secret dataset where the signals are unknown to us. The anomaly detection method described here has been evaluated in a summary paper [1] where it performed very well compared to a large number of other methods. The method is simple to implement and is applicable to other datasets in other fields as well., Comment: 7 pages, 5 figures; improved text

Insight into the electroweak (EW) and Higgs sectors can be achieved through measurements of vector boson scattering (VBS) processes. The scattering of EW bosons are rare processes that are precisely predicted in the Standard Model (SM) and are closely related to the Higgs mechanism. Modifications to VBS processes are also predicted in models of physics beyond the SM (BSM), for example through changes to the Higgs boson couplings to gauge bosons and the resonant production of new particles. In this review, experimental results and theoretical developments of VBS at the Large Hadron Collider, its high luminosity upgrade, and future colliders are presented., Comment: Journal version with additional discussion and references. 56 pages (including toc and refs.), 71 image files, eight tables, and many references. VBSCan@Snowmass review

As part of a programme to develop parton showers with controlled logarithmic accuracy, we consider the question of collinear spin correlations within the PanScales family of parton showers. We adapt the well-known Collins-Knowles spin-correlation algorithm to PanScales antenna and dipole showers, using an approach with similarities to that taken by Richardson and Webster. To study the impact of spin correlations, we develop Lund-declustering based observables that are sensitive to spin-correlation effects both within and between jets and extend the MicroJets collinear single-logarithmic resummation code to include spin correlations. Together with a 3-point energy correlation observable proposed recently by Chen, Moult and Zhu, this provides a powerful set of constraints for validating the logarithmic accuracy of our shower results. The new observables and their resummation further open the pathway to phenomenological studies of these important quantum mechanical effects., Comment: 30 pages + appendices, 21 figures; v2: matches published version

We explore the use of autoregressive flows, a type of generative model with tractable likelihood, as a means of efficient generation of physical particle collider events. The usual maximum likelihood loss function is supplemented by an event weight, allowing for inference from event samples with variable, and even negative event weights. To illustrate the efficacy of the model, we perform experiments with leading-order top pair production events at an electron collider with importance sampling weights, and with next-to-leading-order top pair production events at the LHC that involve negative weights., Comment: 26 pages, 7 figures

We present a first implementation of collinear electroweak radiation in the Vincia parton shower. Due to the chiral nature of the electroweak theory, explicit spin dependence in the shower algorithm is required. We thus use the spinor-helicity formalism to compute helicity-dependent branching kernels, taking special care to deal with the gauge relics that may appear in computation that involve longitudinal polarizations of the massive electroweak vector bosons. These kernels are used to construct a shower algorithm that includes all possible collinear final-state electroweak branchings, including those induced by the Yang-Mills triple vector boson coupling and all Higgs couplings, as well as vector boson emissions from the initial state. We incorporate a treatment of features particular to the electroweak theory, such as the effects of bosonic interference and recoiler effects, as well as a preliminary description of the overlap between electroweak branchings and resonance decays. Some qualifying results on electroweak branching spectra at high energies, as well as effects on LHC physics are presented. Possible future improvements are discussed, including treatment of soft and spin effects, as well as issues unique to the electroweak sector., Comment: 23 pages, 7 figures

We present algorithms that interleave photon radiation from the final state and the initial state with the QCD evolution in the antenna-based Vincia parton shower. One of the algorithms incorporates the complete soft and collinear structure associated with photon emission, but may be computationally expensive, while the other approximates the soft structure at a lower cost. Radiation from fermions and W bosons is included, and a strategy for photon radiation off leptons below the hadronization scale is set up. We show results of the application of the shower algorithms to Drell-Yan and WW production at the LHC, showing the impact of the inclusion of the full soft structure and treatment of radiation off W bosons., Comment: 12 pages, 3 figures

We present a study for the generation of events from a physical process with deep generative models. The simulation of physical processes requires not only the production of physical events, but also to ensure these events occur with the correct frequencies. We investigate the feasibility of learning the event generation and the frequency of occurrence with Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs) to produce events like Monte Carlo generators. We study three processes: a simple two-body decay, the processes $e^+e^-\to Z \to l^+l^-$ and $p p \to t\bar{t} $ including the decay of the top quarks and a simulation of the detector response. We find that the tested GAN architectures and the standard VAE are not able to learn the distributions precisely. By buffering density information of encoded Monte Carlo events given the encoder of a VAE we are able to construct a prior for the sampling of new events from the decoder that yields distributions that are in very good agreement with real Monte Carlo events and are generated several orders of magnitude faster. Applications of this work include generic density estimation and sampling, targeted event generation via a principal component analysis of encoded ground truth data, anomaly detection and more efficient importance sampling, e.g. for the phase space integration of matrix elements in quantum field theories., Comment: 22 pages, 9 figures

We present a formalism for a fully coherent QED parton shower. The complete multipole structure of photonic radiation is incorporated in a single branching kernel. The regular on-shell 2 to 3 kinematic picture is kept intact by dividing the radiative phase space into sectors, allowing for a definition of the ordering variable that is similar to QCD antenna showers. A modified version of the Sudakov veto algorithm is discussed that increases performance at the cost of the introduction of weighted events. Due to the absence of a soft singularity, the formalism for photon splitting is very similar to the QCD analogon of gluon splitting. However, since no color structure is available to guide the selection of a spectator, a weighted selection procedure from all available spectators is introduced., Comment: 33 pages, 12 figures. Added subsection 4.3 and some comments and references per reviewer request. Version accepted by JHEP

We present a way to analyze the distribution produced by a Monte Carlo algorithm. We perform these analyses on several versions of the Sudakov veto algorithm, adding a cutoff, a second variable and competition between emission channels. The analysis allows us to prove that multiple, seemingly different competition algorithms, including those that are currently implemented in most parton showers, lead to the same result. Finally, we test their performance and show that there are significantly faster alternatives to the commonly used algorithms., Comment: 16 pages, 1 figure

RGIsearch is a C++ program that searches for invariants of a user-defined set of renormalization group equations. Based on the general shape of the $\beta$-functions of quantum field theories, RGIsearch searches for several types of invariants that require different methods. Additionally, it supports the computation of invariants up to two-loop level. A manual for the program is given, including the settings and set-up of the program, as well as a test case.

We stress the potential usefulness of renormalization group invariants. Especially particular combinations thereof could for instance be used as probes into patterns of supersymmetry breaking in the MSSM at inaccessibly high energies. We search for these renormalization group invariants in two systematic ways: on the one hand by making use of symmetry arguments and on the other by means of a completely automated exhaustive search through a large class of candidate invariants. At the one-loop level, we find all known invariants for the MSSM and in fact several more, and extend our results to the more constrained pMSSM and dMSSM, leading to even more invariants. Extending our search to the two-loop level we find that the number of invariants is considerably reduced.

Calculation of amplitudes in perturbative quantum field theory involve large loop integrals. The complexity of those integrals, in combination with the large number of Feynman diagrams, make the calculations very difficult. Reduction methods proved to be very helpful, lowering the number of integrals that need to be actually calculated. Especially, the reduction at the integrand level technique, improves the speed and set-up of these calculations. In this article we demonstrate, by counting the numbers of tensor structures and independent coefficients, how to write such relations at the integrand level for one- and two-loop amplitudes. We clarify their connection to the so-called spurious terms at one loop and discuss their structure in the two-loop case. This method is also applicable to higher loops, and the results obtained apply to both planar and non-planar diagrams.