Soft-hard framework with exact four-momentum conservation for small systems
Bibliographic record
Abstract
A new framework, called , for the combined study of both hard and soft transverse momentum sectors in high-energy proton-proton ( <a:math xmlns:a="http://www.w3.org/1998/Math/MathML"> <a:mrow> <a:mi>p</a:mi> <a:mtext>−</a:mtext> <a:mi>p</a:mi> </a:mrow> </a:math> ) and proton-nucleus ( <b:math xmlns:b="http://www.w3.org/1998/Math/MathML"> <b:mrow> <b:mi>p</b:mi> <b:mtext>−</b:mtext> <b:mi>A</b:mi> </b:mrow> </b:math> ) collisions is set up. A dynamical initial state is set up using the model with transverse locations of hotspots within each incoming nucleon. A hard scattering that emanates from two colliding hotspots is carried out using the Pythia generator. Initial state radiation from the incoming hard partons is carried out in a new module called , which includes the longitudinal location of initial splits. The energy-momentum of both the initial hard partons and their associated beam remnants is removed from the hot spots, depleting the energy-momentum available for the formation of the bulk medium. Outgoing showers are simulated using the generator, and results are presented for both cases, allowing for and not allowing for energy loss. First comparisons between this hard-soft model and single inclusive hadron and jet data from <c:math xmlns:c="http://www.w3.org/1998/Math/MathML"> <c:mrow> <c:mi>p</c:mi> <c:mtext>−</c:mtext> <c:mi>p</c:mi> </c:mrow> </c:math> and minimum bias <d:math xmlns:d="http://www.w3.org/1998/Math/MathML"> <d:mrow> <d:mi>p</d:mi> <d:mtext>−</d:mtext> <d:mtext>Pb</d:mtext> </d:mrow> </d:math> collisions are presented. Single hadron spectra in <e:math xmlns:e="http://www.w3.org/1998/Math/MathML"> <e:mrow> <e:mi>p</e:mi> <e:mtext>−</e:mtext> <e:mi>p</e:mi> </e:mrow> </e:math> are used to carry out a limited (in number of parameters) Bayesian calibration of the model. Fair comparisons with data are indicative of the utility of this new framework. Theoretical studies of the correlation between jet <f:math xmlns:f="http://www.w3.org/1998/Math/MathML"> <f:msub> <f:mi>p</f:mi> <f:mi>T</f:mi> </f:msub> </f:math> and event activity at mid and forward rapidity are carried out.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".