Mathis Dubau · Scheme bank
Schemes
The 99 schemes I drew in Tik Z for my thesis, to download as PDF or SVG. Reuse them freely, citing the thesis.
Click a scheme to open it full size; under each one, PDF and SVG download it. To reuse a scheme, cite the thesis
with the figure number shown under it (one click on the box selects all of it for copying):
@phdthesis{Dubau:thesis,
author = "M. Dubau",
title = "{Multivariate study of polarisation states in electroweak vector boson scattering WZ events using ATLAS data at the LHC}",
school = "Universit\'{e} Savoie Mont Blanc",
year = "2026",
doi = "10.17181/cw32k-7w243",
url = "https://repository.cern/records/cw32k-7w243",
type = "PhD thesis"
}
The Standard Model
The Standard Model in Lego bricks: quarks, leptons and bosons, coloured by the interactions they take part in. Thesis Fig. 1.5
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The 18 bricks, one by one
The Higgs potential: the field rolls from the unstable top to the circle of minima and breaks the symmetry. Thesis Fig. 1.2
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The three helicity states of a vector boson: spin − 1 -1 , 0 0 and + 1 +1 along its direction of motion. Thesis Fig. 1.6
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Feynman diagrams
Vertices and scalar scattering
The QED vertex: a photon couples to a fermion–antifermion pair with strength − i Q e -iQe . Thesis Fig. 1.1
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The electroweak vertex: a W or Z boson couples to a pair of fermions. Thesis Fig. C.1
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Quartic scalar interaction, the contact term of scalar scattering. Thesis Fig. A.1(a)
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Scalar scattering through an s-channel Higgs exchange. Thesis Fig. A.1(b)
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Scalar scattering through a t-channel Higgs exchange. Thesis Fig. A.1(c)
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Scalar scattering through a u-channel Higgs exchange. Thesis Fig. A.1(d)
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Vector boson scattering
Vector boson scattering: two quarks radiate a W and a Z that scatter, leaving two forward jets. Thesis Fig. 6.4
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Electroweak ZZjj production through vector boson scattering. Thesis Fig. 6.17(h)
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Corrections to WZjj: NLO QCD and NLO electroweak emissions, virtual and real. Thesis Fig. 6.16
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Backgrounds
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QCD-induced WZjj production, the main irreducible background. Thesis Fig. 6.5(a)
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Another QCD-induced WZjj diagram. Thesis Fig. 6.5(b)
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QCD-induced ZZjj production. Thesis Fig. 6.17(i)
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Triboson production, a background with three leptons. Thesis Fig. 6.17(e)
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Z + jets, a background when a jet fakes the third lepton. Thesis Fig. 6.17(f)
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Z γ \mathrm{Z}\gamma production, a background when the photon converts. Thesis Fig. 6.17(g)
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tZj production, a background with three leptons and jets. Thesis Fig. 6.17(d)
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t t ‾ W \mathrm{t\bar{t}W} production. Thesis Fig. 6.17(b)
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t t ‾ Z \mathrm{t\bar{t}Z} production. Thesis Fig. 6.17(c)
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t t ‾ \mathrm{t\bar{t}} production, a background with a non-prompt lepton. Thesis Fig. 6.17(a)
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Beyond the Standard Model
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The one-loop diagram that gives neutrinos a Majorana mass in the scotogenic model. Thesis Fig. Z.1
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Vector boson scattering and the WZ analysis
History
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Diboson and triboson measurements at LEP, the Tevatron and the LHC over time.
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Vector boson scattering measurements over time, from searches to observations.
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Events and selection
A WZjj vector boson scattering event in ATLAS. Thesis Fig. 6.15
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Discriminant plane
Output of the signal-versus-background network: background near 0, WZjj-EW near 1. Thesis Fig. 6.19(a)
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The discriminant plane: background bottom left, the targeted polarisation state top right. Thesis Fig. 6.23
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Output of a polarisation network for the targeted state and the others. Thesis Fig. 6.19(b)
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Binning the discriminant plane: 1 1 , 2 × 2 2\times2 or 3 × 3 3\times3 bins. Thesis Fig. G.1(a)
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The four polarisation states of the WZ pair, longitudinal (0) or transverse (T). Thesis Fig. G.1(b)
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Statistics
From a p p -value to a significance Z Z : the tail of a unit Gaussian. Thesis Fig. O.1
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A profile-likelihood scan and the intervals read where − 2 Δ ln L -2\Delta\ln L crosses 1 1 and 2.71 2.71 . Thesis Fig. O.2
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Machine learning
Neural networks
An artificial neuron: weighted inputs, a sum and an activation. Thesis Fig. 4.1
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A fully connected neural network with two hidden layers. Thesis Fig. 4.2
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Under- and overfitting: training and validation loss against the epochs. Thesis Fig. 4.5
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A ROC curve: background rejection against signal efficiency. Thesis Fig. 4.8
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Training a network: forward pass, loss against the truth, back-propagation.
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The ReLU activation. Thesis Fig. 4.4(a)
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The sigmoid activation. Thesis Fig. 4.4(b)
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The softmax activation. Thesis Fig. 4.4(c)
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The softplus activation. Thesis Fig. 5.13
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Decision trees
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A decision tree and the cuts it makes. Thesis Fig. 4.9(a)
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The regions a decision tree cuts the plane into. Thesis Fig. 4.9(b)
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Boosting: each weak tree learns from the residuals of the previous ones. Thesis Fig. 4.10
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Active learning
The active-learning loop: a network chooses which points the expensive oracle computes. Thesis Fig. Z.2
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Simulation
A simulated proton–proton collision: hard scattering, parton showers, underlying event and hadronisation. Thesis Fig. 4.13
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CERN and the LHC
Accelerators
The CERN accelerator complex, from LINAC 4 to the LHC. Thesis Fig. 2.3
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The injection chain: the magnet cycles of the PS Booster, PS and SPS that fill the LHC. Thesis Fig. 2.4(a)
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The LHC ring and its eight sectors, with the four large experiments. Thesis Fig. 2.5
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An LHC fill: injection, ramp, squeeze, stable beams and dump. Thesis Fig. 2.4(b)
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The LHC timeline, from Run 1 to the High-Luminosity LHC. Thesis Fig. 2.6
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Coordinates
The LHC ring and the ATLAS axes. Thesis Fig. 3.2(a)
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The ATLAS coordinate system and the pseudorapidity η \eta . Thesis Fig. 3.2(b)
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The ATLAS detector
Whole detector
Electromagnetic showers of electrons and photons in the ATLAS calorimeter. Thesis Fig. 5.1
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Hadronic showers in the ATLAS calorimeters. Thesis Fig. 6.7(a)
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A muon crossing the whole of ATLAS. Thesis Fig. 6.7(b)
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Inner detector
Quarter view of the ATLAS Inner Detector: pixels, strips and straw tubes. Thesis Fig. 3.3(b)
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Quarter view of the ITk and HGTD, which reach | η | = 4 |\eta| = 4 at the HL-LHC. Thesis Fig. 3.16(b)
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A pixel sensor and its bump-bonded readout. Thesis Fig. 3.4(a)
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An IBL pixel sensor. Thesis Fig. 3.4(b)
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An SCT strip sensor. Thesis Fig. 3.4(c)
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A TRT straw: ionisation and transition radiation in a gas-filled tube. Thesis Fig. 3.5
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An ITk strip sensor. Thesis Fig. 3.17(a)
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An HGTD low-gain avalanche sensor, which times each track. Thesis Fig. 3.17(b)
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Calorimeters
Quarter view of the ATLAS calorimeters. Thesis Fig. 3.6(b)
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The accordion geometry of the ATLAS liquid-argon electromagnetic calorimeter. Thesis Fig. 3.7(a)
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Sampling in liquid argon: lead absorbers, argon gaps and readout electrodes. Thesis Fig. 3.8(a)
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Sampling in the Tile calorimeter: steel and scintillator, read through wavelength-shifting fibres. Thesis Fig. 3.8(b)
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A Tile calorimeter module. Thesis Fig. 3.7(b)
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A forward calorimeter electrode: a rod in a tube, with a thin liquid-argon gap. Thesis Fig. 3.9
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Muon spectrometer
Quarter view of the ATLAS muon spectrometer. Thesis Fig. 3.10(b)
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A monitored drift tube: the muon ionises the gas and the electrons drift to the anode wire. Thesis Fig. 3.11(a)
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A cathode strip chamber. Thesis Fig. 3.11(b)
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A resistive plate chamber. Thesis Fig. 3.12(a)
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A thin gap chamber. Thesis Fig. 3.12(b)
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A Micromegas chamber of the New Small Wheel. Thesis Fig. 3.11(c)
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Trigger and luminosity
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The ATLAS trigger and data acquisition chain. Thesis Fig. 3.14
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LUCID, the luminosity monitor: Cherenkov light in quartz read by photomultipliers. Thesis Fig. 3.15
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Reconstruction
Tracks
The perigee parameters of a track. Thesis Fig. 5.3
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Track reconstruction in the inner detector. Thesis Fig. 5.4
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Electrons and photons
Electron and photon reconstruction in ATLAS, step by step. Thesis Fig. 5.2
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Superclusters: a seed cluster gathers its satellites, for electrons and converted photons. Thesis Fig. 5.6
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Electron or photon? How the ambiguity is resolved. Thesis Fig. 5.7
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The electron and photon energy calibration chain. Thesis Fig. 5.8
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Calorimeter isolation: the energy in a cone around the electron, its core removed. Thesis Fig. 5.10
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The calorimeter and track variables used to identify electrons.
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A forward electron shower and its cluster moments. Thesis Fig. 5.11
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Decorrelation: a variable replaced by its residual from a linear fit in p T p_{\text{T}} . Thesis Fig. 5.16
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The forward-electron calibration and identification workflow. Thesis Fig. 5.18
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Jets, muons, taus and missing momentum
k t k_t and anti-k t k_t jet clustering: anti-k t k_t grows round jets around the hard particles. Thesis Fig. 6.9(a)
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The ATLAS jet energy calibration chain. Thesis Fig. 6.10
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Missing transverse momentum: minus the vector sum of every reconstructed object. Thesis Fig. 6.12
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The k t k_t clustering algorithm, step by step. Thesis Fig. 6.9(b)
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A b-jet: the b hadron flies before decaying at a secondary vertex. Thesis Fig. 6.11(a)
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A τ \tau lepton decaying to a lepton at a displaced vertex. Thesis Fig. 6.11(b)
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Prompt and non-prompt leptons: a lepton from a secondary vertex is displaced from the primary one. Thesis Fig. 5.5
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Muon momentum corrections: the simulation is matched to the data on the Z peak. Thesis Fig. 6.6
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Particle flow: tracks are matched to calorimeter clusters and their expected energy is subtracted. Thesis Fig. 6.8
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Drawn with the thesis, not printed in it
Show the 9 schemes
What the signal region is made of: the WZjj signal and each background.
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The information budget: what the inputs x x tell about the label y y , I ( x ; y ) I(x;y) , and what is left, H ( y | x ) H(y|x) .
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A cross-entropy gives a lower bound on the mutual information: I ( x ; y ) ≥ H ( y ) − C E ( q ) I(x;y) \geq H(y) - \mathrm{CE}(q) .
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The toy model used to check the information measurements against the analytic truth.
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Ionisation: a charged particle passing by knocks an electron out of the atom.
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Bremsstrahlung: an electron deflected by the nucleus radiates a photon.
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Photoelectric effect: a photon is absorbed and ejects a bound electron.
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Compton scattering: a photon scatters off an atomic electron and loses energy.
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Pair creation: near a nucleus, a photon turns into an electron–positron pair.
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