Leandro G. Almeida

Substructure of high-p_T Jets at the LHC

We study high-p{sub T} jets from QCD and from highly boosted massive particles such as tops, W, Z, and Higgs bosons, and argue that infrared-safe observables can help reduce QCD backgrounds. Jets from QCD are characterized by different patterns of energy flow compared to the products of highly boosted heavy particle decays, and we employ a variety of jet shapes, observables restricted to energy flow within a jet, to explore this difference. Results from Monte Carlo generators and arguments based on perturbation theory support the discriminating power of the shapes we refer to as planar flow and angularities. We emphasize that for massive jets, these and other observables can be analyzed perturbatively.

α-synuclein assemblies sequester neuronal α3-Na+/K+-ATPase and impair Na+ gradient

Extracellular α‐synuclein (α‐syn) assemblies can be up‐taken by neurons; however, their interaction with the plasma membrane and proteins has not been studied specifically. Here we demonstrate that α‐syn assemblies form clusters within the plasma membrane of neurons. Using a proteomic‐based approach, we identify the α3‐subunit of Na+/K+‐ATPase (NKA) as a cell surface partner of α‐syn assemblies. The interaction strength depended on the state of α‐syn, fibrils being the strongest, oligomers weak, and monomers none. Mutations within the neuron‐specific α3‐subunit are linked to rapid‐onset dystonia Parkinsonism (RDP) and alternating hemiplegia of childhood (AHC). We show that freely diffusing α3‐NKA are trapped within α‐syn clusters resulting in α3‐NKA redistribution and formation of larger nanoclusters. This creates regions within the plasma membrane with reduced local densities of α3‐NKA, thereby decreasing the efficiency of Na+ extrusion following stimulus. Thus, interactions of α3‐NKA with extracellular α‐syn assemblies reduce its pumping activity as its mutations in RDP/AHC.

Comparing and counting logs in direct and effective methods of QCD resummation

A bstractWe compare methods to resum logarithms in event shape distributions as they have been used in perturbative QCD directly and in effective field theory. We demonstrate that they are equivalent. In showing this equivalence, we are able to put standard soft-collinear effective theory (SCET) formulae for cross sections in momentum space into a novel form more directly comparable with standard QCD formulae, and endow the QCD formulae with dependence on separated hard, jet, and soft scales, providing potential ways to improve estimates of theoretical uncertainty. We show how to compute cross sections in momentum space to keep them as accurate as the corresponding expressions in Laplace space. In particular, we point out that that care is required in truncating differential distributions at NkLL accuracy to ensure they match the accuracy of the corresponding cumulant or Laplace transform. We explain how to avoid such mismatches at NkLL accuracy, and observe why they can also be avoided by working to NkLL′ accuracy.

Playing tag with ANN: boosted top identification with pattern recognition

A bstractMany searches for physics beyond the Standard Model at the Large Hadron Collider (LHC) rely on top tagging algorithms, which discriminate between boosted hadronic top quarks and the much more common jets initiated by light quarks and gluons. We note that the hadronic calorimeter (HCAL) effectively takes a “digital image” of each jet, with pixel intensities given by energy deposits in individual HCAL cells. Viewed in this way, top tagging becomes a canonical pattern recognition problem. With this motivation, we present a novel top tagging algorithm based on an Artificial Neural Network (ANN), one of the most popular approaches to pattern recognition. The ANN is trained on a large sample of boosted tops and light quark/gluon jets, and is then applied to independent test samples. The ANN tagger demonstrated excellent performance in a Monte Carlo study: for example, for jets with pT in the 1100-1200 GeV range, 60% top-tag efficiency can be achieved with a 4% mis-tag rate. We discuss the physical features of the jets identified by the ANN tagger as the most important for classification, as well as correlations between the ANN tagger and some of the familiar top-tagging observables and algorithms.

Three-particle templates for a boosted Higgs boson

We explore the ability of three-particle templates to distinguish color neutral objects from QCD background. This method is particularly useful to identify the standard model Higgs, as well as other massive neutral particles. Simple cut-based analysis in the overlap distributions of the signal and background is shown to provide a significant rejection power. By combining with other discriminating variables, such as planar flow, and several variables that depend on the partonic template, three-particle templates are used to characterize the influence of gluon emission and color flow in collider events. The performance of the method is discussed for the case of a highly boosted Higgs in association with a leptonically-decaying W boson.

Study of the standard model Higgs boson partial widths and branching fractions

The discovery of the Higgs boson, with a mass known to be better than the percent level, enables precision Higgs boson analyses for the first time. Toward this goal, we define an expansion formalism of the Higgs boson partial widths and branching fractions that facilitates such studies. This expansion yields the observables as a perturbative expansion around reference values of Standard Model input observables (quark masses, QCD coupling constant, etc.). We compute the coefficients of the expansion using state-of- the-art results. We also study the various sources of uncertainties in computing the partial widths and branching fractions more precisely. We discuss the impact of these results with efforts to discern new physics through precision Higgs boson studies. With the discovery of the Higgs boson (1), particle physics is entering a new era of precision studies of the Higgs sector. The observables are many and include the Higgs boson mass, its total decay width, its spin, its decay branching fractions to Standard Model (SM) particles, its possible decay branching fractions to other exotic final states, and its various production rates at colliders. All of these observables will be studied carefully in time. The theory under primary consideration in this article is the Standard Model. The subpercent-level determination of the Higgs boson mass now enables a complete set of input observables whereby any perturbative high-energy observ- able involving the Higgs boson can be predicted. In this article, our focus is on the careful exposition of the decay partial widths and branching fractions of a SM Higgs boson with mass near 126 GeV. Our goal is to provide state-of-the-art formulas that can be used in any precision electroweak analysis to investigate compatibility of the data with the SM predictions in these most fundamental and sensitive observables. Other calculations exist in the literature, 1 most notably from the computer program HDECAY (2); however, we wish to provide an independent calculation that includes the latest advances and allows us to vary the renormalization scale in all parts of the computations. This flexibility will be useful in later discussions regarding uncertainties. We also aim to detail the errors that each input into the computation propagates to the final answer for each observable (3). In some cases, these uncertainties are large, and constitute a limitation to how sensitive experimental measurements can be in determining the underlying theory parameters. Finally, we discuss some implications for physics beyond the SM sensitivities in precision Higgs studies.

An aggregation-removal model for the formation and size determination of post-synaptic scaffold domains

The formation and stability of synapses are key questions in neuroscience. Post-synaptic domains have been classically conceived as resulting from local insertion and turnover of proteins at the synapse. However, insertion is likely to occur outside the post-synaptic domains and advances in single-molecule imaging have shown that proteins diffuse in the plane of the membrane prior to their accumulation at synapses. We quantitatively investigated this scenario using computer simulations and mathematical analysis, taking for definiteness the specific case of inhibitory synapse components, i.e., the glycine receptor (GlyR) and the associated gephyrin scaffolding protein. The observed domain sizes of scaffold clusters can be explained by a dynamic balance between the aggregation of gephyrin proteins diffusing while bound to GlyR and their turnover at the neuron membrane. We also predict the existence of extrasynaptic clusters with a characteristic size distribution that significantly contribute to the size fluctuations of synaptic domains. New super-resolution data for gephyrin proteins established the existence of extrasynaptic clusters the sizes of which are consistent with the model predictions in a range of model parameters. At a general level, our results highlight aggregation with removal as a non-equilibrium phase separation which produces structures of tunable size.

Data in support of the identification of neuronal and astrocyte proteins interacting with extracellularly applied oligomeric and fibrillar α-synuclein assemblies by mass spectrometry.

α-Synuclein (α-syn) is the principal component of Lewy bodies, the pathophysiological hallmark of individuals affected by Parkinson disease (PD). This neuropathologic form of α-syn contributes to PD progression and propagation of α-syn assemblies between neurons. The data we present here support the proteomic analysis used to identify neuronal proteins that specifically interact with extracellularly applied oligomeric or fibrillar α-syn assemblies (conditions 1 and 2, respectively) (doi: 10.15252/embj.201591397[1]). α-syn assemblies and their cellular partner proteins were pulled down from neuronal cell lysed shortly after exposure to exogenous α-syn assemblies and the associated proteins were identified by mass spectrometry using a shotgun proteomic-based approach. We also performed experiments on pure cultures of astrocytes to identify astrocyte-specific proteins interacting with oligomeric or fibrillar α-syn (conditions 3 and 4, respectively). For each condition, proteins interacting selectively with α-syn assemblies were identified by comparison to proteins pulled-down from untreated cells used as controls. The mass spectrometry data, the database search and the peak lists have been deposited to the ProteomeXchange Consortium database via the PRIDE partner repository with the dataset identifiers PRIDE: PXD002256 to PRIDE: PXD002263 and doi: 10.6019/PXD002256 to 10.6019/PXD002263.

Continuous rearrangement of the postsynaptic gephyrin scaffolding domain: a super-resolution quantified and energetic approach

Synaptic function and plasticity requires a delicate balance between overall structural stability and the continuous rearrangement of the components that make up the presynaptic active zone and the postsynaptic density (PSD). Photoactivated localization microscopy (PALM) has provided a detailed view of the nanoscopic structure and organization of some of these synaptic elements. Still lacking, are tools to address the morphing and stability of such complexes at super-resolution. We describe an approach to quantify morphological changes and energetic states of multimolecular assemblies over time. With this method, we studied the scaffold protein gephyrin, which forms postsynaptic clusters that play a key role in the stabilization of receptors at inhibitory synapses. Postsynaptic gephyrin clusters exhibit an internal microstructure composed of nanodomains. We found, that within the PSD, gephyrin molecules continuously undergo spatial reorganization. This dynamic behavior depends on neuronal activity and cytoskeleton integrity. The proposed approach also allowed access to the effective energy responsible for the tenacity of the PSD despite molecular instability. Significant statement Super-resolution microscopy has become an important tool for the study of biological systems, allowing detailed, nano-scale structural reconstruction, single molecule tracking, particle counting, and interaction studies. However, quantification tools that take full advantage of the information provided by this technology are still lacking. We describe a novel quantification method to obtain information related to the size, directionality, dynamics, and stability of clustered structures from super-resolution microscopy. With this method, we studied the stability of gephyrin clusters, the main inhibitory scaffold protein. We found that gephyrin molecules continuously undergo reorganization based on neuronal activity and changes in the cytoskeleton.

Substructure of high-pTjets at the LHC

We study high-p{sub T} jets from QCD and from highly boosted massive particles such as tops, W, Z, and Higgs bosons, and argue that infrared-safe observables can help reduce QCD backgrounds. Jets from QCD are characterized by different patterns of energy flow compared to the products of highly boosted heavy particle decays, and we employ a variety of jet shapes, observables restricted to energy flow within a jet, to explore this difference. Results from Monte Carlo generators and arguments based on perturbation theory support the discriminating power of the shapes we refer to as planar flow and angularities. We emphasize that for massive jets, these and other observables can be analyzed perturbatively.