---
title: Les Houches Tune (LH Tune) for Hadronization
url: https://www.emergentmind.com/topics/les-houches-tune-lh-tune
type: topic
---

# Les Houches Tune (LH Tune) for Hadronization

The **Les Houches Tune**, or **LH Tune**, is a general-purpose tune for **Herwig 7** in which the generator’s default **cluster hadronization model** is replaced by the **Lund string hadronization model** from **Pythia 8**, accessed through **TheP8I**, while keeping **Herwig 7.3’s Angular Ordered Parton Shower (AOPS)** as the perturbative baseline. Its defining purpose is to enable a controlled comparison of hadronization models inside a common event-generator framework, so that **Herwig 7 + AOPS + cluster hadronization** can be compared directly with **Herwig 7 + AOPS + Lund string hadronization** without simultaneously changing the shower algorithm [2509.02348]. The tune was finished during the **Les Houches PhysTeV workshop**, which is the origin of the name, and it is intended for both **lepton and hadron collider physics**; the paper states that it **will be included in the Herwig 7.4 release** [2509.02348].

## 1. Definition and historical placement

In the 2025 study **“Herwig 7 with the Lund String Model: Tuning and Comparative Hadronization Studies”**, the LH Tune is introduced as a new tune for a hybrid setup: **Herwig 7** provides the hard-process and shower environment, while **Pythia 8** provides the **Lund string hadronization model** and the **QCD-based colour reconnection (CR)** model through **TheP8I** [2509.02348]. The tune is explicitly presented as a tool for comparative hadronization studies rather than as a purely phenomenological replacement for existing defaults.

A central point of clarification is that the phrase **“Les Houches Tune”** is not, in the accessible Les Houches 2015 and 2017 Standard Model Working Group reports, the name of an explicit benchmark tune. In the visible material of the 2015 report, there is **no explicit “Les Houches Tune”, “LH Tune”, “benchmark tune”, or “recommended tune”**, although the report identifies **“new developments in Monte Carlo event generators”** and a chapter titled **“MC uncertainties and output formats”** as relevant themes [1605.04692]. Likewise, the visible material of the 2017 report does **not** provide a self-contained tune card called **“Les Houches Tune”**, but it does discuss the rationale for common generator setups by emphasizing parton-shower comparisons, tune/retune issues, and the correlation of **PDF choices** with **underlying-event modeling via multiparton interactions (MPI)** [1803.07977]. This establishes that the modern LH Tune is a specific 2025 deliverable rather than a long-standing tune label from the earlier workshop reports.

The tune also belongs to a longer lineage of systematic Monte Carlo tuning. The 2009 **Professor** paper does not mention Les Houches, but it introduced a reproducible **Professor + Rivet** framework and produced **recommended base tunes for LHC experiments** in **Pythia 6**, thereby contributing to the methodological background from which later community-style reference tunes emerged [0907.2973].

## 2. Generator architecture and physics rationale

The LH Tune is defined by a deliberate division of responsibilities between **Herwig 7** and **Pythia 8**. The perturbative environment is fixed to Herwig’s **Angular Ordered Parton Shower**, and only the non-perturbative hadronization and CR sector is swapped. This design is the basis for the paper’s claim that hadronization-model systematics can be isolated more cleanly than in a standard Herwig-versus-Pythia comparison, where both shower and hadronization differ simultaneously [2509.02348].

| Subsystem | Provider | Role in the LH Tune |
|---|---|---|
| LO matrix elements, AOPS, MPI/UE, PDFs, event generation infrastructure | Herwig 7 / ThePEG | Perturbative and hadron-collision baseline |
| Lund string hadronization | Pythia 8 via TheP8I | Non-perturbative string fragmentation |
| QCD-based colour reconnection and associated beam remnants | Pythia 8 via TheP8I | CR sector used with the string model |

In this setup, **Herwig 7** supplies **LO matrix elements**, **AOPS** for both **FSR** and **ISR**, the hadron-collision framework including the **MPI / Underlying Event model**, **CT14LO** PDFs via **LHAPDF**, and the overall event-generation infrastructure through **ThePEG** [2509.02348]. Through **TheP8I**, **Pythia 8** contributes the **Lund string hadronization model**, the **QCD-based colour reconnection model**, and the associated beam-remnant treatment required by that CR model [2509.02348].

The theoretical basis of the hadronization model is described in the paper through the linear confinement potential
$$
V(r)=\kappa r,
$$
with \(\kappa\) the string tension, and through the Lund/Bowler fragmentation form
$$
f(z)\propto \frac{1}{z^{1+r_Q b m_Q^2}}(1-z)^a e^{-b m_T^2/z},
\qquad m_T^2=m^2+p_T^2,
$$
where \(a\) and \(b\) are the Lund longitudinal-fragmentation parameters, \(\sigma\) controls the Gaussian transverse-momentum kicks at string breaking, and the heavy-quark Bowler modification is governed through **rFactC** and **rFactB** [2509.02348].

The **Angular Ordered Parton Shower** serves two roles. It is, first, the perturbative backbone of the generator setup, and, second, the fixed reference point against which hadronization can be varied. This allows two complementary comparisons: **Herwig string vs Herwig cluster**, which isolates hadronization-model differences at fixed shower, and **Herwig string vs Pythia string**, which exposes shower/framework differences at fixed hadronization model [2509.02348].

## 3. Tuning workflow and methodology

The LH Tune is obtained through a **four-stage tuning strategy** implemented with **Rivet** for observable evaluation and **Professor** for interpolation-based optimization [2509.02348]. The stages are:

1. **String fragmentation + FSR parameters** tuned to LEP data.  
2. **String flavour parameters** tuned to identified-particle multiplicity and flavour observables at LEP.  
3. **ISR \(\alpha_s\)** and primordial \(k_T\) tuned to LHC Drell–Yan \(Z\)-boson data.  
4. **MPI + colour reconnection parameters** tuned to **Minimum Bias** and **Underlying Event** data from hadron collisions [2509.02348].

This decomposition follows the assumption, also used in earlier Pythia tuning practice, that fragmentation and flavour sectors can be approximately decoupled enough to be tuned in stages without unacceptable correlations [2509.02348]. That factorized logic closely matches the methodology described in the Professor framework paper, which advocated systematic tuning through per-bin response parameterization rather than manual or brute-force optimization [0907.2973].

The objective function is the standard weighted Professor goodness-of-fit,
$$
\chi^2(\boldsymbol{p})=
\sum_{\mathcal O} w_{\mathcal O}
\sum_{b\in\mathcal O}
\frac{\left(f^{(b)}(\boldsymbol p)-\mathcal R_b\right)^2}{\Delta_b^2},
$$
where \(w_{\mathcal O}\) is the observable weight, \(f^{(b)}(\boldsymbol p)\) is the Professor response in bin \(b\), \(\mathcal R_b\) is the reference value, and \(\Delta_b\) is the total uncertainty [2509.02348]. The use of weighted observables is consistent with the Professor methodology, which formalized a weighted \(\chi^2\) over observable bins and emphasized that weighting is subjective but unavoidable in practical tune construction [0907.2973].

The first LEP stage tunes **7 string-fragmentation parameters** and **2 final-state shower parameters** using \(e^+e^-\) data at \(\sqrt{s}=91.2\) GeV. The observables include **event shapes**, **momentum spectra**, **mean charged multiplicities**, and **flavour-specific mean charged multiplicities**, with input from **DELPHI 1996** and **OPAL 1998**. The sampling setup is a **9-dimensional hypercube**, **575 sampled parameter points**, **1 million events per run**, and **40 different interpolations**, each built from **400 generator runs chosen randomly from the full set**. A **sequential parameter-fixing procedure** is then applied to parameters whose optimized values are stable across interpolations [2509.02348].

The second LEP stage tunes **11 flavour parameters** in an **11-dimensional hypercube** using **950 sampled points**, **1 million events per run**, and **40 interpolations**, each built from **500 runs**. The data include the **\(b\)-quark fragmentation function from DELPHI**, \(\pi^+\) and \(\pi^0\) multiplicities from a **PDG compilation**, numerous identified-hadron multiplicity ratios with respect to \(\pi^\pm\), and reduced-weight **OPAL flavour-tagged charged multiplicities** [2509.02348].

The hadron-collision ISR stage tunes **\(\alpha_{\mathrm S}^{\mathrm{ISR}}\)** and primordial \(k_T\) to **7 TeV Drell–Yan \(Z\)-boson production**, using **ATLAS 2012 \(\phi_\eta^*\)**, **ATLAS 2014 \(Z\) \(p_T\)**, and **CMS 2012 \(Z\) \(p_T\)** data. Following a previous Herwig strategy, the paper uses **muon-channel \(Z\) \(p_T\)** distributions and **electron-channel angular observables** to reduce correlations [2509.02348].

The final hadron-collision stage tunes **MPI + CR** against MB and UE data at **0.9 TeV**, **1.8 TeV**, **7 TeV**, and **13 TeV**. The original sample contains **1000 generator runs**, but only **265 valid runs** are retained for interpolation because the multi-energy setup reduces the number of usable runs [2509.02348]. The stage also studies the energy evolution of the MPI cutoff through
$$
p_{\perp}^{\min}(s)=p_{\perp,0}^{\min}\left(\frac{b+\sqrt{s}}{E_0}\right)^c,
$$
with reference energy fixed to \(E_0=7\) TeV [2509.02348].

## 4. Parameter content of the LH Tune

The LH Tune specifies a complete parameter set across fragmentation, flavour, ISR, MPI, and colour reconnection [2509.02348].

**Final-state shower and string-fragmentation sector**: the tuned values are \(\alpha_{\mathrm S}^{\mathrm{FSR}}=0.126\), \(p_{\perp}^{\min}=1.03\) GeV, \(a=0.75\), \(b=0.90\) GeV\(^{-2}\), \(\sigma=0.31\) GeV, **aExtraSQuark** \(=0.18\), **aExtraDiquark** \(=0.05\), **rFactC** \(=0.68\), and **rFactB** \(=1.27\) [2509.02348].

**String flavour sector**: the tuned flavour parameters are **probStoUD** \(=0.19\), **probQQtoQ** \(=0.08\), **probSQtoQQ** \(=0.99\), **probQQ1toQQ0** \(=0.02\), **etaSup** \(=0.51\), **etaPrimeSup** \(=0.18\), **popcornRate** \(=0.73\), **mesonUDvector** \(=0.33\), **mesonSvector** \(=0.68\), **mesonCvector** \(=1.07\), and **mesonBvector** \(=1.85\) [2509.02348]. The paper describes these parameters as controlling, respectively, strangeness suppression, diquark suppression, strange-diquark suppression, spin-1 diquark suppression, \(\eta\) and \(\eta'\) suppression, baryon–meson–antibaryon popcorn production, and vector-to-pseudoscalar ratios in the light, strange, charm, and bottom sectors [2509.02348].

**Hadron-collision ISR sector**: the tuned values are \(\alpha_{\mathrm S}^{\mathrm{ISR}}=0.124\) and primordial \(k_T=1.304\) GeV [2509.02348].

**MPI and colour-reconnection sector**: in the energy-extrapolated LH Tune, the parameters are **Power \(c\)** \(=0.23\), \(p_{\perp,0}^{\min}=3.13\) GeV, **Offset \(b\)** \(=530.5\) GeV, \(\mu^2=1.14\) GeV\(^{-2}\), **ladderMult** \(=0.57\), **ladderbFactor** \(=0.97\), \(R_{\mathrm{diff}}=0.21\), **m0** \(=2.87\) GeV, and **junctionCorrection** \(=4.55\) [2509.02348].

The CR model is Pythia8’s **QCD-based colour reconnection scheme** with the **new beam remnant model**, including **junction strings**, but the implementation is intentionally simplified. Several optional features are disabled, including **double-junction remnants**, **time causality to string decays**, and **special heavy-quark parity treatment**, so that CR is effectively controlled mainly by **m0** and **junctionCorrection** [2509.02348]. In the paper’s terminology, **m0** is a lower bound on the mass of the colour-reconnected system, while **junctionCorrection** rescales this threshold for junction strings and therefore governs how readily junctions form [2509.02348].

For practical use, the paper states that the tune **will be included in the Herwig 7.4 release** and **can also be used with Herwig 7.3**, provided a patch is applied to the **herwig-bootstrap** installation script. The relevant TheP8I modifications expose Pythia8 CR controls such as **CRreconnect**, **CRmode**, **BRremnantMode**, **CRm0**, and **CRjunctionCorrection** [2509.02348].

## 5. Phenomenology and validation

The paper’s overall conclusion is that the LH Tune gives a **good and competitive description across a broad range of observables** in both lepton and hadron collisions, while remaining most valuable as a controlled platform for hadronization comparisons [2509.02348].

For **LEP observables**, the tune describes **fragmentation and flavour observables accurately**. On many event shapes and momentum spectra it lies **between the Herwig cluster tune and the Pythia Monash string tune**, and in hadronization-sensitive regions it often follows Pythia’s string tune closely, which the paper attributes naturally to the shared string model and similar tuning philosophy [2509.02348]. Where observables are more sensitive to the shower, the differences with Pythia grow, showing the effect of **AOPS** relative to Pythia’s **\(p_T\)-ordered shower** [2509.02348].

The paper records several more specific LEP-level observations. \(\pi^+\) and \(\pi^0\) multiplicities are modeled well by the Herwig string tunes; meson multiplicities are generally reasonable for all tunes; all tunes produce too many \(D^+\) mesons; and baryon multiplicities are harder to model, with \(\Lambda\) relatively well described [2509.02348]. Some event shapes are within approximately \(10\%\) over much of the distribution, but tails of thrust, thrust minor, aplanarity, and the \(D\)-parameter remain difficult, largely because of missing higher perturbative orders [2509.02348]. The tune also **generalises reasonably well to observables not included in the fit**, which the authors interpret as evidence against severe overtuning [2509.02348].

For the **Drell–Yan ISR tuning stage**, the LH Tune describes small and intermediate \(\phi^*\) and \(p_T^Z\) very well, but at large \(p_T^Z\) it undershoots the data. The paper identifies the reason as the use of **LO matrix elements without higher-order corrections** [2509.02348].

For **Underlying Event** measurements at **0.9, 1.8, 7, and 13 TeV**, the tune is generally **within the envelope** formed by the Herwig cluster and Pythia string tunes [2509.02348]. It often follows the Herwig cluster tune in shape, but with **slightly better data agreement**, except close to the leading-particle direction, where it moves toward the Pythia result [2509.02348]. In high-multiplicity regions, especially for UE observables sensitive to colour reconnection and hadronization, the LH Tune can improve on the cluster tune [2509.02348]. For validation observables not used in the fit, **trans-max** and **trans-min** are reasonably described, while **trans-diff** is overestimated by all tunes by roughly **10–20%**, with the Herwig cluster tune slightly better [2509.02348].

For **Minimum Bias** observables, the spread between tunes is larger than for UE, with differences up to **30–40%** in some regions; the paper notes that this is expected because MB is more sensitive to soft physics and is not anchored by a hard trigger [2509.02348]. At low \(N_{\rm ch}\), the LH Tune often follows the Herwig cluster tune, plausibly reflecting the same diffractive model; at high \(N_{\rm ch}\), it tends to follow the Pythia string tune and often performs better than the cluster tune, plausibly reflecting different CR behavior [2509.02348]. Charged-particle pseudorapidity remains problematic; in some **100 MeV-track selections** the LH Tune is furthest from the data among the compared tunes, although the inter-tune spread is only about **10%** [2509.02348].

A major caveat concerns **identified-particle spectra at the LHC**. The paper states that **none of the tunes describe identified-particle spectra at the LHC well**; for \(p\), \(\pi\), \(K\), \(\Xi\), \(\Lambda\), \(\Sigma\), \(\phi\), and related observables, discrepancies between models can reach **up to 50%** [2509.02348]. The authors therefore conclude that tuning flavour parameters alone is unlikely to remove all tensions and that genuine model improvements are needed [2509.02348].

The tune was **not explicitly tuned to diffraction-sensitive observables**, but it nonetheless gives a reasonable description of forward rapidity gaps. Agreement with Herwig cluster is within about **20%**; the non-diffractive small-gap region is better modeled by Pythia, the diffractive large-gap region is better modeled by Herwig cluster, and the Herwig string setup tends to underestimate the diffraction-dominated region [2509.02348].

## 6. Significance, limitations, and relation to broader tuning practice

The principal significance of the LH Tune is methodological. The paper argues not that one model wins universally, but that the tune creates a more meaningful basis for assessing **non-perturbative uncertainties** by permitting controlled **string-versus-cluster** comparisons at fixed shower [2509.02348]. This yields four broader lessons explicitly highlighted in the study: **hadronization model dependence matters**; **shower and hadronization are intertwined**; **universality is only partial**; and the LH Tune is valuable as a **systematic tool** in addition to being a phenomenological tune [2509.02348].

This positioning aligns with earlier Les Houches discussions of Monte Carlo systematics. The visible 2017 report emphasizes that a sensible description of data sensitive to non-perturbative effects may require **retuning the event generator when varying renormalization scales**, and it stresses the correlation between **PDF choices** and **underlying-event modeling via multiparton interactions** [1803.07977]. That point is conceptually important for interpreting the LH Tune: tune parameters, shower choices, PDF choices, and non-perturbative modeling are not independent knobs in any physically faithful uncertainty assessment. A plausible implication is that the LH Tune is best understood not as an isolated parameter card but as a coherent generator configuration.

The tune also sits naturally in the tradition of systematic community tuning formalized by **Professor + Rivet**. The 2009 Professor paper described the now-standard practice of sampling a parameter hypercube, building **bin-by-bin polynomial response functions**, and minimizing a weighted global goodness-of-fit to construct recommended LHC baseline tunes [0907.2973]. The LH Tune adopts the same infrastructure and the same broad philosophy of staged, data-driven calibration, but applies it to a hybrid **Herwig + Pythia8-string** setup whose scientific purpose is comparative hadronization studies rather than only production of a new default [2509.02348].

The paper’s limitations are stated directly. Large-\(p_T\) Drell–Yan tails are not expected to be perfect because the setup uses **LO matrix elements** without higher-order corrections; some event-shape tails are perturbatively limited rather than hadronization limited; diffraction was not directly tuned; identified-flavour spectra remain poorly described by all available tunes; and the implemented CR model is a **simplified subset** of Pythia’s full QCD-based CR model [2509.02348]. The authors therefore recommend the LH Tune as a useful basis for comparative uncertainty studies and suggest future directions such as repeating the analysis with **Herwig’s dipole shower**, providing **systematic variations/eigentunes**, and incorporating additional LHC hadronization-sensitive observables in future tuning campaigns [2509.02348].

Source: https://www.emergentmind.com/topics/les-houches-tune-lh-tune