Datasets:

alefisico
/

LHC_HH4b_mixeddata

event uint64	luminosityBlock uint32	run uint32	nJet int32	xbW float64	ZHSR bool	SB bool	ZZSR bool	nSelJets int64	weight float64	xW float64	fourTag bool	SR bool	HHSR bool	threeTag bool	passHLT bool	nNotCanJet int32	nCanJet int32	pseudoTagWeight float64	FvT float64	hh bool	ps_hh float64	ps_zz float64	phh float64	tt_vs_mj float64	ptt float64	q_1234 float64	zz bool	q_1423 float64	q_1324 float64	pmj float64	passMinPs bool	zh bool	ps float64	pzz float64	pzh float64	ps_zh float64	year large_string	Jet1_jetId int64	Jet2_jetId int64	Jet3_jetId int64	Jet4_jetId int64	Jet5_jetId int64	Jet6_jetId int64	Jet7_jetId int64	Jet8_jetId int64	Jet9_jetId int64	Jet10_jetId int64	Jet11_jetId int64	Jet12_jetId int64	Jet1_rawFactor float64	Jet2_rawFactor float64	Jet3_rawFactor float64	Jet4_rawFactor float64	Jet5_rawFactor float64	Jet6_rawFactor float64	Jet7_rawFactor float64	Jet8_rawFactor float64	Jet9_rawFactor float64	Jet10_rawFactor float64	Jet11_rawFactor float64	Jet12_rawFactor float64	Jet1_hfsigmaPhiPhi float64	Jet2_hfsigmaPhiPhi float64	Jet3_hfsigmaPhiPhi float64	Jet4_hfsigmaPhiPhi float64	Jet5_hfsigmaPhiPhi float64	Jet6_hfsigmaPhiPhi float64	Jet7_hfsigmaPhiPhi float64	Jet8_hfsigmaPhiPhi float64	Jet9_hfsigmaPhiPhi float64	Jet10_hfsigmaPhiPhi float64	Jet11_hfsigmaPhiPhi float64	Jet12_hfsigmaPhiPhi float64	Jet1_qgl float64	Jet2_qgl float64	Jet3_qgl float64	Jet4_qgl float64	Jet5_qgl float64	Jet6_qgl float64	Jet7_qgl float64	Jet8_qgl float64	Jet9_qgl float64	Jet10_qgl float64	Jet11_qgl float64	Jet12_qgl float64	Jet1_cRegCorr float64	Jet2_cRegCorr float64	Jet3_cRegCorr float64	Jet4_cRegCorr float64	Jet5_cRegCorr float64	Jet6_cRegCorr float64	Jet7_cRegCorr float64	Jet8_cRegCorr float64	Jet9_cRegCorr float64	Jet10_cRegCorr float64	Jet11_cRegCorr float64	Jet12_cRegCorr float64	Jet5_hfcentralEtaStripSize float64	Jet6_hfcentralEtaStripSize float64	Jet7_hfcentralEtaStripSize float64	Jet8_hfcentralEtaStripSize float64	Jet9_hfcentralEtaStripSize float64	Jet10_hfcentralEtaStripSize float64	Jet11_hfcentralEtaStripSize float64	Jet12_hfcentralEtaStripSize float64	Jet2_nMuons float64	Jet4_nMuons float64	Jet5_nMuons float64	Jet6_nMuons float64	Jet7_nMuons float64	Jet8_nMuons float64	Jet9_nMuons float64	Jet10_nMuons float64	Jet11_nMuons float64	Jet12_nMuons float64	Jet1_btagDeepFlavQG float64	Jet2_btagDeepFlavQG float64	Jet3_btagDeepFlavQG float64	Jet4_btagDeepFlavQG float64	Jet5_btagDeepFlavQG float64	Jet6_btagDeepFlavQG float64	Jet7_btagDeepFlavQG float64	Jet8_btagDeepFlavQG float64	Jet9_btagDeepFlavQG float64	Jet10_btagDeepFlavQG float64	Jet11_btagDeepFlavQG float64	Jet12_btagDeepFlavQG float64	Jet1_nElectrons float64	Jet2_nElectrons float64	Jet3_nElectrons float64	Jet4_nElectrons float64	Jet5_nElectrons float64	Jet6_nElectrons float64	Jet7_nElectrons float64	Jet8_nElectrons float64	Jet9_nElectrons float64	Jet10_nElectrons float64	Jet11_nElectrons float64	Jet12_nElectrons float64	Jet1_btagDeepB float64	Jet2_btagDeepB float64	Jet3_btagDeepB float64	Jet4_btagDeepB float64	Jet5_btagDeepB float64	Jet6_btagDeepB float64	Jet7_btagDeepB float64	Jet8_btagDeepB float64	Jet9_btagDeepB float64	Jet10_btagDeepB float64	Jet11_btagDeepB float64	Jet12_btagDeepB float64	Jet6_hfadjacentEtaStripsSize float64	Jet7_hfadjacentEtaStripsSize float64	Jet8_hfadjacentEtaStripsSize float64	Jet9_hfadjacentEtaStripsSize float64	Jet10_hfadjacentEtaStripsSize float64	Jet11_hfadjacentEtaStripsSize float64	Jet12_hfadjacentEtaStripsSize float64	Jet1_btagDeepFlavB float64	Jet2_btagDeepFlavB float64	Jet3_btagDeepFlavB float64	Jet4_btagDeepFlavB float64	Jet5_btagDeepFlavB float64	Jet6_btagDeepFlavB float64	Jet7_btagDeepFlavB float64	Jet8_btagDeepFlavB float64	Jet9_btagDeepFlavB float64	Jet10_btagDeepFlavB float64	Jet11_btagDeepFlavB float64	Jet12_btagDeepFlavB float64	Jet1_neEmEF float64	Jet2_neEmEF float64	Jet3_neEmEF float64	Jet4_neEmEF float64	Jet5_neEmEF float64	Jet6_neEmEF float64	Jet7_neEmEF float64	Jet8_neEmEF float64	Jet9_neEmEF float64	Jet10_neEmEF float64	Jet11_neEmEF float64	Jet12_neEmEF float64	Jet1_pt float64	Jet2_pt float64	Jet3_pt float64	Jet4_pt float64	Jet5_pt float64	Jet6_pt float64	Jet7_pt float64	Jet8_pt float64	Jet9_pt float64	Jet10_pt float64	Jet11_pt float64	Jet12_pt float64	Jet1_muonIdx2 int64	Jet2_muonIdx2 int64	Jet3_muonIdx2 int64	Jet4_muonIdx2 int64	Jet5_muonIdx2 int64	Jet6_muonIdx2 int64	Jet7_muonIdx2 int64	Jet8_muonIdx2 int64	Jet9_muonIdx2 int64	Jet10_muonIdx2 int64	Jet11_muonIdx2 int64	Jet12_muonIdx2 int64	Jet1_cleanmask int64	Jet2_cleanmask int64	Jet3_cleanmask int64	Jet4_cleanmask int64	Jet5_cleanmask int64	Jet6_cleanmask int64	Jet7_cleanmask int64	Jet8_cleanmask int64	Jet9_cleanmask int64	Jet10_cleanmask int64	Jet11_cleanmask int64	Jet1_btagCSVV2 float64	Jet2_btagCSVV2 float64	Jet3_btagCSVV2 float64	Jet4_btagCSVV2 float64	Jet5_btagCSVV2 float64	Jet6_btagCSVV2 float64	Jet7_btagCSVV2 float64	Jet8_btagCSVV2 float64	Jet9_btagCSVV2 float64	Jet10_btagCSVV2 float64	Jet11_btagCSVV2 float64	Jet12_btagCSVV2 float64	Jet1_puIdDisc float64	Jet2_puIdDisc float64	Jet3_puIdDisc float64	Jet4_puIdDisc float64	Jet5_puIdDisc float64	Jet6_puIdDisc float64	Jet7_puIdDisc float64	Jet8_puIdDisc float64	Jet9_puIdDisc float64	Jet10_puIdDisc float64	Jet11_puIdDisc float64	Jet12_puIdDisc float64	Jet1_phi float64	Jet2_phi float64	Jet3_phi float64	Jet4_phi float64	Jet5_phi float64	Jet6_phi float64	Jet7_phi float64	Jet8_phi float64	Jet9_phi float64	Jet10_phi float64	Jet11_phi float64	Jet12_phi float64	Jet1_partonFlavour int64	Jet2_partonFlavour int64	Jet3_partonFlavour int64	Jet4_partonFlavour int64	Jet5_partonFlavour int64	Jet6_partonFlavour int64	Jet7_partonFlavour int64	Jet8_partonFlavour int64	Jet9_partonFlavour int64	Jet10_partonFlavour int64	Jet11_partonFlavour int64	Jet12_partonFlavour int64	Jet1_hfsigmaEtaEta float64	Jet2_hfsigmaEtaEta float64	Jet3_hfsigmaEtaEta float64	Jet4_hfsigmaEtaEta float64	Jet5_hfsigmaEtaEta float64	Jet6_hfsigmaEtaEta float64	Jet7_hfsigmaEtaEta float64	Jet8_hfsigmaEtaEta float64	Jet9_hfsigmaEtaEta float64	Jet10_hfsigmaEtaEta float64	Jet11_hfsigmaEtaEta float64	Jet12_hfsigmaEtaEta float64	Jet1_chHEF float64	Jet2_chHEF float64	Jet3_chHEF float64	Jet4_chHEF float64	Jet5_chHEF float64	Jet6_chHEF float64	Jet7_chHEF float64	Jet8_chHEF float64	Jet9_chHEF float64	Jet10_chHEF float64	Jet11_chHEF float64	Jet12_chHEF float64	Jet1_btagDeepCvB float64	Jet2_btagDeepCvB float64	Jet3_btagDeepCvB float64	Jet4_btagDeepCvB float64	Jet5_btagDeepCvB float64	Jet6_btagDeepCvB float64	Jet7_btagDeepCvB float64	Jet8_btagDeepCvB float64	Jet9_btagDeepCvB float64	Jet10_btagDeepCvB float64	Jet11_btagDeepCvB float64	Jet12_btagDeepCvB float64	Jet1_eta float64	Jet2_eta float64	Jet3_eta float64	Jet4_eta float64	Jet5_eta float64	Jet6_eta float64	Jet7_eta float64	Jet8_eta float64	Jet9_eta float64	Jet10_eta float64	Jet11_eta float64	Jet12_eta float64	Jet1_nConstituents float64	Jet2_nConstituents float64	Jet3_nConstituents float64	Jet4_nConstituents float64	Jet5_nConstituents float64	Jet6_nConstituents float64	Jet7_nConstituents float64	Jet8_nConstituents float64	Jet9_nConstituents float64	Jet10_nConstituents float64	Jet11_nConstituents float64	Jet12_nConstituents float64	Jet1_btagDeepFlavCvB float64	Jet2_btagDeepFlavCvB float64	Jet3_btagDeepFlavCvB float64	Jet4_btagDeepFlavCvB float64	Jet5_btagDeepFlavCvB float64	Jet6_btagDeepFlavCvB float64	Jet7_btagDeepFlavCvB float64	Jet8_btagDeepFlavCvB float64	Jet9_btagDeepFlavCvB float64	Jet10_btagDeepFlavCvB float64	Jet11_btagDeepFlavCvB float64	Jet12_btagDeepFlavCvB float64	Jet1_chFPV0EF float64	Jet2_chFPV0EF float64	Jet3_chFPV0EF float64	Jet4_chFPV0EF float64	Jet5_chFPV0EF float64	Jet6_chFPV0EF float64	Jet7_chFPV0EF float64	Jet8_chFPV0EF float64	Jet9_chFPV0EF float64	Jet10_chFPV0EF float64	Jet11_chFPV0EF float64	Jet12_chFPV0EF float64	Jet1_muonSubtrFactor float64	Jet2_muonSubtrFactor float64	Jet3_muonSubtrFactor float64	Jet4_muonSubtrFactor float64	Jet5_muonSubtrFactor float64	Jet6_muonSubtrFactor float64	Jet7_muonSubtrFactor float64	Jet8_muonSubtrFactor float64	Jet9_muonSubtrFactor float64	Jet10_muonSubtrFactor float64	Jet11_muonSubtrFactor float64	Jet12_muonSubtrFactor float64	Jet1_bRegCorr float64	Jet2_bRegCorr float64	Jet3_bRegCorr float64	Jet4_bRegCorr float64	Jet5_bRegCorr float64	Jet6_bRegCorr float64	Jet7_bRegCorr float64	Jet8_bRegCorr float64	Jet9_bRegCorr float64	Jet10_bRegCorr float64	Jet11_bRegCorr float64	Jet12_bRegCorr float64	Jet1_area float64	Jet2_area float64	Jet3_area float64	Jet4_area float64	Jet5_area float64	Jet6_area float64	Jet7_area float64	Jet8_area float64	Jet9_area float64	Jet10_area float64	Jet11_area float64	Jet12_area float64	Jet1_cRegRes float64	Jet2_cRegRes float64	Jet3_cRegRes float64	Jet4_cRegRes float64	Jet5_cRegRes float64	Jet6_cRegRes float64	Jet7_cRegRes float64	Jet8_cRegRes float64	Jet9_cRegRes float64	Jet10_cRegRes float64	Jet11_cRegRes float64	Jet12_cRegRes float64	Jet1_hadronFlavour int64	Jet2_hadronFlavour int64	Jet3_hadronFlavour int64	Jet4_hadronFlavour int64	Jet5_hadronFlavour int64	Jet6_hadronFlavour int64	Jet7_hadronFlavour int64	Jet8_hadronFlavour int64	Jet9_hadronFlavour int64	Jet10_hadronFlavour int64	Jet11_hadronFlavour int64	Jet12_hadronFlavour int64	Jet1_muonIdx1 int64	Jet2_muonIdx1 int64	Jet3_muonIdx1 int64	Jet4_muonIdx1 int64	Jet5_muonIdx1 int64	Jet6_muonIdx1 int64	Jet7_muonIdx1 int64	Jet8_muonIdx1 int64	Jet9_muonIdx1 int64	Jet10_muonIdx1 int64	Jet11_muonIdx1 int64	Jet12_muonIdx1 int64	Jet1_electronIdx2 int64	Jet2_electronIdx2 int64	Jet3_electronIdx2 int64	Jet4_electronIdx2 int64	Jet5_electronIdx2 int64	Jet6_electronIdx2 int64	Jet7_electronIdx2 int64	Jet8_electronIdx2 int64	Jet9_electronIdx2 int64	Jet10_electronIdx2 int64	Jet11_electronIdx2 int64	Jet12_electronIdx2 int64	Jet1_neHEF float64	Jet2_neHEF float64	Jet3_neHEF float64	Jet4_neHEF float64	Jet5_neHEF float64	Jet6_neHEF float64	Jet7_neHEF float64	Jet8_neHEF float64	Jet9_neHEF float64	Jet10_neHEF float64	Jet11_neHEF float64	Jet12_neHEF float64	Jet1_btagDeepFlavCvL float64	Jet2_btagDeepFlavCvL float64	Jet3_btagDeepFlavCvL float64	Jet4_btagDeepFlavCvL float64	Jet5_btagDeepFlavCvL float64	Jet6_btagDeepFlavCvL float64	Jet7_btagDeepFlavCvL float64	Jet8_btagDeepFlavCvL float64	Jet9_btagDeepFlavCvL float64	Jet10_btagDeepFlavCvL float64	Jet11_btagDeepFlavCvL float64	Jet12_btagDeepFlavCvL float64	Jet1_mass float64	Jet2_mass float64	Jet3_mass float64	Jet4_mass float64	Jet5_mass float64	Jet6_mass float64	Jet7_mass float64	Jet8_mass float64	Jet9_mass float64	Jet10_mass float64	Jet11_mass float64	Jet12_mass float64	Jet2_muEF float64	Jet4_muEF float64	Jet5_muEF float64	Jet6_muEF float64	Jet7_muEF float64	Jet8_muEF float64	Jet9_muEF float64	Jet10_muEF float64	Jet11_muEF float64	Jet12_muEF float64	Jet1_btagDeepCvL float64	Jet2_btagDeepCvL float64	Jet3_btagDeepCvL float64	Jet4_btagDeepCvL float64	Jet5_btagDeepCvL float64	Jet6_btagDeepCvL float64	Jet7_btagDeepCvL float64	Jet8_btagDeepCvL float64	Jet9_btagDeepCvL float64	Jet10_btagDeepCvL float64	Jet11_btagDeepCvL float64	Jet12_btagDeepCvL float64	Jet1_electronIdx1 int64	Jet2_electronIdx1 int64	Jet3_electronIdx1 int64	Jet4_electronIdx1 int64	Jet5_electronIdx1 int64	Jet6_electronIdx1 int64	Jet7_electronIdx1 int64	Jet8_electronIdx1 int64	Jet9_electronIdx1 int64	Jet10_electronIdx1 int64	Jet11_electronIdx1 int64	Jet12_electronIdx1 int64	Jet1_bRegRes float64	Jet2_bRegRes float64	Jet3_bRegRes float64	Jet4_bRegRes float64	Jet5_bRegRes float64	Jet6_bRegRes float64	Jet7_bRegRes float64	Jet8_bRegRes float64	Jet9_bRegRes float64	Jet10_bRegRes float64	Jet11_bRegRes float64	Jet12_bRegRes float64	Jet1_puId int64	Jet2_puId int64	Jet3_puId int64	Jet4_puId int64	Jet5_puId int64	Jet6_puId int64	Jet7_puId int64	Jet8_puId int64	Jet9_puId int64	Jet10_puId int64	Jet11_puId int64	Jet12_puId int64	Jet1_genJetIdx int64	Jet2_genJetIdx int64	Jet3_genJetIdx int64	Jet4_genJetIdx int64	Jet5_genJetIdx int64	Jet6_genJetIdx int64	Jet7_genJetIdx int64	Jet8_genJetIdx int64	Jet9_genJetIdx int64	Jet10_genJetIdx int64	Jet11_genJetIdx int64	Jet12_genJetIdx int64	Jet1_chEmEF float64	Jet3_chEmEF float64	Jet4_chEmEF float64	Jet5_chEmEF float64	Jet6_chEmEF float64	Jet7_chEmEF float64	Jet8_chEmEF float64	Jet9_chEmEF float64	Jet10_chEmEF float64	Jet11_chEmEF float64	Jet12_chEmEF float64	CanJet1_phi float64	CanJet2_phi float64	CanJet3_phi float64	CanJet4_phi float64	CanJet1_pt float64	CanJet2_pt float64	CanJet3_pt float64	CanJet4_pt float64	CanJet1_eta float64	CanJet2_eta float64	CanJet3_eta float64	CanJet4_eta float64	CanJet1_mass float64	CanJet2_mass float64	CanJet3_mass float64	CanJet4_mass float64	NotCanJet1_phi float64	NotCanJet2_phi float64	NotCanJet3_phi float64	NotCanJet4_phi float64	NotCanJet5_phi float64	NotCanJet6_phi float64	NotCanJet7_phi float64	NotCanJet8_phi float64	NotCanJet1_isSelJet int64	NotCanJet2_isSelJet int64	NotCanJet1_mass float64	NotCanJet2_mass float64	NotCanJet3_mass float64	NotCanJet4_mass float64	NotCanJet5_mass float64	NotCanJet6_mass float64	NotCanJet7_mass float64	NotCanJet8_mass float64	NotCanJet1_pt float64	NotCanJet2_pt float64	NotCanJet3_pt float64	NotCanJet4_pt float64	NotCanJet5_pt float64	NotCanJet6_pt float64	NotCanJet7_pt float64	NotCanJet8_pt float64	NotCanJet1_eta float64	NotCanJet2_eta float64	NotCanJet3_eta float64	NotCanJet4_eta float64	NotCanJet5_eta float64	NotCanJet6_eta float64	NotCanJet7_eta float64	NotCanJet8_eta float64	jcmWeight float64
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End of preview. Expand in Data Studio

CMS Open Data: HH → 4b Multijet Background Modelling and Hemisphere-Mixed Dataset

🚀 Quickstart Tutorial Notebook

An interactive end-to-end tutorial is provided in notebooks/quickstart.ipynb:

1-Click Run in Colab: Click the Open In Colab badge above to launch and execute directly in your browser without downloading 14.5 GB locally.
Hands-on Demonstrations: Fast HTTP Parquet loading with pandas/polars, inspecting feature categories across simulation (623 cols), collision data (276 cols), and synthetic mixed data (191 cols), plotting jet kinematic distributions ((p_T, \eta, \phi)), visualizing DeepJet (b)-tagging domain shifts, and training a machine learning reweighting baseline.

1. Overview & Physics Challenge

This dataset contains flat tabular (Apache Parquet) collision data and simulated physics processes released by the CMS Collaboration on the CERN Open Data Portal (Record cms-93965).

It is prepared for machine-learning-based background modelling, density ratio estimation, and domain-adaptation reweighting in multijet searches for di-Higgs production in the four-bottom-quark final state:

$\mathrm{pp} \to HH \to (b\bar{b})(b\bar{b})$

recorded with the CMS detector at the CERN Large Hadron Collider (LHC) during Run 2 (2016–2018) at center-of-mass energy (\sqrt{s} = 13\text{ TeV}).

The Background Challenge

In the all-hadronic 4b final state, the dominant background arises from non-resonant quantum chromodynamic (QCD) multijet production. First-principles Monte Carlo simulations cannot model non-resonant multijet events with sufficient precision, and leading-order cross sections are computationally intractable. Consequently, particle physicists employ data-driven methods by transferring kinematic properties from an orthogonal, high-statistics source domain (three-tag events, 3b) into the target domain (four-tag events, 4b).

Furthermore, collision data in the signal-sensitive mass window (the Signal Region, SR) must remain strictly blinded to avoid confirmation bias. To provide an authentic, signal-free benchmark with an unblinded ground truth, this dataset provides synthetic 4b collision data generated via hemisphere mixing.

2. Machine Learning Task Formulation (Domain Adaptation & Density Ratio Estimation)

This benchmark presents a canonical, real-world machine learning problem: high-dimensional density ratio extrapolation under domain shift.

flowchart LR
    subgraph Source_Domain ["Source Domain: Sideband (SB)"]
        D3b_SB["3b Collision Data (SB)"]
        D4b_SB["4b Mixed Pseudo-Data (SB)"]
    end

    subgraph Learning ["Model Learning"]
        direction TB
        Reweighter["Train Reweight Classifier w_θ(x)<br>p(x|4b) / p(x|3b)"]
    end

    subgraph Target_Domain ["Target Domain: Signal Region (SR)"]
        D3b_SR["3b Collision Data (SR)"]
        Pred_SR["Predicted 4b Background (SR)"]
        GroundTruth_SR["Replica 0 Mixed Ground Truth (SR)"]
    end

    D3b_SB --> Reweighter
    D4b_SB --> Reweighter
    Reweighter -.->|"Extrapolate w_θ"| D3b_SR
    D3b_SR --> Pred_SR
    Pred_SR <-->|"Evaluate Transfer Error"| GroundTruth_SR

Formal Problem Definition

Let (\mathbf{x} \in \mathcal{X} \subset \mathbb{R}^d) denote an event feature vector. The feature space is partitioned into two disjoint kinematic regions:

Source Domain ((\mathcal{X}_{\mathrm{src}})): The Sideband (SB) ring.
Target Domain ((\mathcal{X}_{\mathrm{tgt}})): The Signal Region (SR) disk centered at candidate Higgs masses ((m_{H_1}, m_{H_2}) \approx (125, 120)\text{ GeV}).

Participants have access to:

Control data: (\mathcal{D}{3b}) available in both (\mathcal{X}{\mathrm{src}}) and (\mathcal{X}_{\mathrm{tgt}}).
Target data in the Source Domain: (\mathcal{D}_{4b}^{\mathrm{src}}) (both real collision data and synthetic mixed data).
Resonant background simulation: (\mathcal{D}_{t\bar{t}}) in both domains (subtracted to isolate the QCD multijet continuum).
Downstream signal template: (\mathcal{D}{HH}) in (\mathcal{X}{\mathrm{tgt}}).

The Objective: Learn a density ratio operator (w_\theta(\mathbf{x}) = \frac{p(\mathbf{x} \mid 4b)}{p(\mathbf{x} \mid 3b)}) strictly using data in (\mathcal{X}{\mathrm{src}}), and apply it to control data in (\mathcal{X}{\mathrm{tgt}}) to predict the target distribution:

$\hat{p}_{4b}(\mathbf{x} \mid \mathbf{x} \in \mathcal{X}_{\mathrm{tgt}}) = w_\theta(\mathbf{x}) \cdot p_{3b}(\mathbf{x} \mid \mathbf{x} \in \mathcal{X}_{\mathrm{tgt}})$

The predicted distribution is evaluated against the unblinded synthetic ground truth (Replica 0) in the Signal Region.

3. Dataset Splits and Statistics

The dataset totals approximately 14.54 GB across 202 Parquet files and up to 623 feature columns.

Split / Config Name	Data Origin	Kinematic Domain	Event Count	Features	Description & ML Workflow Role
`data_3b`	Real Collisions	Source (SB) + Target (SR)	~2.57M	276	High-statistics source domain (3b) to be reweighted into 4b.
`mixeddata_4b`	Hemisphere Mixed	Source (SB) + Target (SR)	~2.99M	191	Synthetic 4b collision data. For standard benchmark comparisons, use 1 replica (e.g. Replica 0) as the target real data.
`ttbar_3b`	Simulation	Source (SB) + Target (SR)	~1.20M	623	Top-quark pair production ((t\bar{t})) in the 3b category (subtracted during reweighting).
`ttbar_4b`	Simulation	Source (SB) + Target (SR)	~130k	623	Top-quark pair production ((t\bar{t})) in the 4b category.
`GluGluToHHTo4B_cHHH1`	Simulation	Target (SR)	~150k	623	Standard Model di-Higgs signal template ((\kappa_\lambda = 1)) for sensitivity benchmarking.
`ZH4b`	Simulation	Target (SR)	~100k	623	Standard Model Electroweak candle ((ZH \to b\bar{b}b\bar{b})).
`ZZ4b`	Simulation	Target (SR)	~100k	623	Standard Model Electroweak candle ((ZZ \to b\bar{b}b\bar{b})).

4. Synthetic Data via Hemisphere Mixing & Benchmark Protocol

Evaluating density estimation or domain adaptation on real physical collision data faces a fundamental hurdle: events in the target Signal Region (SR) must remain blinded.

To overcome this, synthetic 4b events are generated using empirical hemisphere mixing:

Spatial Bisection: Each collision event is partitioned into two spatial hemispheres ((H^+) and (H^-)) across the plane orthogonal to the transverse thrust axis (\hat{\mathbf{t}}).
Empirical Library Query: An empirical library containing hundreds of thousands of hemispheres is constructed from real 4b collision data.
Nearest-Neighbor Recombination: Each hemisphere of a base event is independently replaced by its closest kinematic match queried from the library using a (k)-d tree under a normalized Mahalanobis metric.

flowchart TD
    A["Observed 4b Collision Event"] --> B["Compute Transverse Thrust Axis"]
    B --> C["Bisect into Hemispheres H+ and H-"]
    C --> D["Query Nearest-Neighbor from 4b Library (k-d Tree)"]
    D --> E["Recombine Matches into Synthetic 4b Event"]
    E --> F["Resonant Signals Destroyed<br>Fidelity & Detector Effects Preserved"]

📌 Benchmark Guideline: Using 1 Mixed Replica as Real Data

For benchmark evaluations, domain-adaptation comparisons, and model scoring, users should use only ONE of the mixed data samples (e.g., Replica 0, files ending with *_0.parquet) as the pseudo-data target representing real collision data.

The dataset contains 16 statistically independent replicas in total, but standard model evaluation and reporting should treat a single replica (e.g., Replica 0) as the observed dataset.

5. Feature Schema & Observable Dictionary

The columnar schema organizes detector measurements, composite invariant masses, and event weights:

📊 Expand Detailed Observable Dictionary and Units

Observable Category	Sample Feature Names	Physical Units	Description
Leading Jet Kinematics	`Jet1_pt`, `Jet2_pt`, `Jet3_pt`, `Jet4_pt`	GeV	Transverse momentum of the 4 leading reconstructed jets ((p_T > 40\text{ GeV})).
	`Jet1_eta`, `Jet2_eta`, `Jet3_eta`, `Jet4_eta`	Dimensionless	Pseudorapidity (\eta = -\ln\tan(\theta/2)) ((
	`Jet1_phi`, `Jet2_phi`, `Jet3_phi`, `Jet4_phi`	Radians	Azimuthal angle (\phi \in [-\pi, \pi]).
	`Jet1_mass`, `Jet2_mass`, `Jet3_mass`, `Jet4_mass`	GeV	Reconstructed jet invariant mass.
CMS Flavour Tagging	`Jet1_btagDeepFlavB` ... `Jet4_btagDeepFlavB`	[0, 1]	CMS DeepJet neural network probability that the jet originated from a bottom quark ((b)).
	`Jet1_btagDeepFlavQG` ... `Jet4_btagDeepFlavQG`	[0, 1]	Quark-versus-gluon discriminator score.
Composite Jet Pairs	`m4j`	GeV	Invariant mass of the four-jet system.
	Candidate masses `m_H1`, `m_H2`	GeV	Invariant mass of the two candidate reconstructed Higgs bosons chosen by minimizing pairing asymmetry.
Global Shape Observables	`nJet`, `nSelJets`	Integer	Total reconstructed jet multiplicity and high-purity selected jets.
	`ptt`	GeV	Scalar transverse thrust momentum.
Blinding & Partitions	`SR`	Boolean	True if the event falls in the Signal Region disk.
	`SB`	Boolean	True if the event falls in the Sideband ring.
	`threeTag`, `fourTag`	Boolean	True for 3-tag and 4-tag event selections, respectively.
	`passHLT`	Boolean	Trigger selection flag (High-Level Trigger passing state).
Event Weights	`weight`	Float	Monte Carlo generator and cross-section weight.
	`pseudoTagWeight`	Float	Weight accounting for 3-tag to 4-tag combinatoric sampling.
	`FvT`	Float	Baseline Four-vs-Three-tag neural network reweighting factor.

6. Quickstart / Usage Examples

Loading Direct Parquet Partitions with Pandas or Polars

import pandas as pd

BASE_URL = "https://huggingface.co/datasets/alefisico/LHC_HH4b_mixeddata/resolve/main"

# Read sample partition directly in under a second
df_signal = pd.read_parquet(f"{BASE_URL}/GluGluToHHTo4B_cHHH1/part_UL17_0.parquet")
df_3b = pd.read_parquet(f"{BASE_URL}/data/3b/part_UL16_postVFP_F.parquet")

# For mixed data, load Replica 0 as the target pseudo-data
df_mixed_rep0 = pd.read_parquet(f"{BASE_URL}/mixeddata_all/4b/part_UL16_postVFP_F_0.parquet")

Loading via Hugging Face `datasets`

from datasets import load_dataset

# Stream a configuration
ds_stream = load_dataset("alefisico/LHC_HH4b_mixeddata", "mixeddata_4b", split="train", streaming=True)
sample_rows = list(ds_stream.take(100))

# Or load specific partition files directly
ds_file = load_dataset(
    "alefisico/LHC_HH4b_mixeddata", 
    data_files="mixeddata_all/4b/part_UL16_postVFP_F_0.parquet", 
    split="train"
)

7. Citation and Acknowledgements

This dataset is distributed under the Creative Commons CC0 1.0 Universal Public Domain Dedication.

When using this dataset in research or benchmarking, please cite the official CERN Open Data record:

@misc{cms_opendata_hh4b_mixeddata,
  author       = {{CMS Collaboration}},
  title        = {{HH4b reconstructed, mixed and simulated data in Parquet format for multijet background modelling}},
  year         = 2026,
  publisher    = {CERN Open Data Portal},
  doi          = {10.7483/OPENDATA.CMS.WWHU.D4ON},
  url          = {https://opendata.cern.ch/record/cms-93965}
}

For the machine learning reweighting framework and hemisphere mixing methodology, please refer to:

CMS Collaboration, Search for nonresonant Higgs boson pair production in the four b jet final state in proton-proton collisions at (\sqrt{s} = 13\text{ TeV}), Phys. Rev. Lett. 129, 081802 (2022).
CMS Collaboration, Search for the standard model Higgs boson produced in association with a W or Z boson and decaying into a pair of b quarks, Eur. Phys. J. C 81, 178 (2021).

8. Maintainers & Community

Maintainer: Alejandro Gómez Espinosa (CERN / Carnegie Mellon University)
Feedback & Questions: Please open an issue or thread in the Community tab of this repository!