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N. Sato

Publications and source records attributed to N. Sato.

At least 37 records · Page 2Linked to original sources

Number density interpretation of dihadron fragmentation functions

We present a new quantum field-theoretic definition of fully unintegrated dihadron fragmentation functions (DiFFs) as well as a generalized version for $n$-hadron fragmentation functions. We demonstrate that this definition allows certain sum rules to be satisfied, making it consistent with a number density interpretation. Moreover, we show how our corresponding so-called extended DiFFs that enter existing phenomenological studies are number densities and also derive their evolution equations. Within this new framework, DiFFs extracted from experimental measurements will have a clear physical meaning.

hep-ph↗

Gluon helicity from global analysis of experimental data and lattice QCD Ioffe time distributions

We perform a new global analysis of spin-dependent parton distribution functions with the inclusion of Ioffe time pseudo-distributions computed in lattice QCD (LQCD), which are directly sensitive to the gluon helicity distribution, $Δg$. These lattice data have an analogous relationship to parton distributions as do experimental cross sections, and can be readily included in global analyses. We focus in particular on the constraining capability of current LQCD data on the sign of $Δg$ at intermediate parton momentum fractions $x$, which was recently brought into question by analysis of data in the absence of parton positivity constraints. We find that present LQCD data cannot discriminate between positive and negative $Δg$ solutions, although significant changes in the solutions for both the gluon and quark sectors are observed.

hep-ph↗

Tomography of pions and protons via transverse momentum dependent distributions

We perform the first simultaneous extraction of parton collinear and transverse degrees of freedom from low-energy fixed-target Drell-Yan data in order to compare the transverse momentum dependent (TMD) parton distribution functions (PDFs) of the pion and proton. We demonstrate that the transverse separation of the quark field encoded in TMDs of the pion is more than $4 σ$ smaller than that of the proton. Additionally, we find the transverse separation of the quark field decreases as its longitudinal momentum fraction decreases. In studying the nuclear modification of TMDs, we find clear evidence for a transverse EMC effect. We comment on possible explanations for these intriguing behaviors, which call for a deeper examination of tomography in a variety of strongly interacting quark-gluon systems.

hep-ph↗

Polarized Antimatter in the Proton from Global QCD Analysis

We present the first simultaneous global QCD analysis of spin-dependent parton distribution functions alongside their spin-averaged counterparts and pion, kaon, and unidentified hadron fragmentation functions. This analysis includes all data relevant for constraining the polarized light quark sea asymmetry $Δ\bar{u} - Δ\bar{d}$, in particular the latest polarized $W$-lepton production data from the STAR collaboration at RHIC and semi-inclusive deep inelastic scattering data from COMPASS, allowing the most robust extraction available with minimal theoretical assumptions. We also extract a self-consistent set of antiquark polarization ratios $Δ\bar{u}/\bar{u}$ and $Δ\bar{d}/\bar{d}$ and determine the signs of the truncated contributions to the proton spin from the light antiquarks.

hep-ph↗

Accelerating Markov Chain Monte Carlo sampling with diffusion models

Global fits of physics models require efficient methods for exploring high-dimensional and/or multimodal posterior functions. We introduce a novel method for accelerating Markov Chain Monte Carlo (MCMC) sampling by pairing a Metropolis-Hastings algorithm with a diffusion model that can draw global samples with the aim of approximating the posterior. We briefly review diffusion models in the context of image synthesis before providing a streamlined diffusion model tailored towards low-dimensional data arrays. We then present our adapted Metropolis-Hastings algorithm which combines local proposals with global proposals taken from a diffusion model that is regularly trained on the samples produced during the MCMC run. Our approach leads to a significant reduction in the number of likelihood evaluations required to obtain an accurate representation of the Bayesian posterior across several analytic functions, as well as for a physical example based on a global analysis of parton distribution functions. Our method is extensible to other MCMC techniques, and we briefly compare our method to similar approaches based on normalizing flows. A code implementation can be found at https://github.com/NickHunt-Smith/MCMC-diffusion.

hep-ph↗

Global QCD Analysis and Dark Photons

We perform a global QCD analysis of high energy scattering data within the JAM Monte Carlo framework, including a coupling to a dark photon that augments the standard model electroweak coupling via kinetic mixing with the hypercharge $B$ boson. Including the most recent measurement of the anomalous magnetic moment of the muon as a constraint, we find a significant reduction in the combined $χ^2$, favoring the inclusion of a dark photon, with a statistical significance in excess of 8$σ$. With respect to the experimental data, the improvements in the theoretical predictions are spread across a wide range of $x$ and $Q^2$, with the largest improvement corresponding to neutral current data from HERA, while the best fit yields a value of $g-2$ which significantly reduces the disagreement with the latest experimental determination. The best fit yields a dark photon mass in the range 4.2--6.2 GeV and a mixing parameter of order 0.1.

hep-ph↗

Artificial Intelligence for the Electron Ion Collider (AI4EIC)

The Electron-Ion Collider (EIC), a state-of-the-art facility for studying the strong force, is expected to begin commissioning its first experiments in 2028. This is an opportune time for artificial intelligence (AI) to be included from the start at this facility and in all phases that lead up to the experiments. The second annual workshop organized by the AI4EIC working group, which recently took place, centered on exploring all current and prospective application areas of AI for the EIC. This workshop is not only beneficial for the EIC, but also provides valuable insights for the newly established ePIC collaboration at EIC. This paper summarizes the different activities and R&D projects covered across the sessions of the workshop and provides an overview of the goals, approaches and strategies regarding AI/ML in the EIC community, as well as cutting-edge techniques currently studied in other experiments.

physics.acc-ph↗

Toward a generative modeling analysis of CLAS exclusive $2π$ photoproduction

AI-supported algorithms, particularly generative models, have been successfully used in a variety of different contexts. In this work, we demonstrate for the first time that generative adversarial networks (GANs) can be used in high-energy experimental physics to unfold detector effects from multi-particle final states, while preserving correlations between kinematic variables in multidimensional phase space. We perform a full closure test on two-pion photoproduction pseudodata generated with a realistic model in the kinematics of the Jefferson Lab CLAS g11 experiment. The overlap of different reaction mechanisms leading to the same final state associated with the CLAS detector's nontrivial effects represents an ideal test case for AI-supported analysis. Uncertainty quantification performed via bootstrap provides an estimate of the systematic uncertainty associated with the procedure. The test demonstrates that GANs can reproduce highly correlated multidifferential cross sections even in the presence of detector-induced distortions in the training datasets, and provides a solid basis for applying the framework to real experimental data.

hep-ph↗

Snowmass 2021 White Paper: Electron Ion Collider for High Energy Physics

Electron Ion Collider (EIC) is a particle accelerator facility planned for construction at Brookhaven National Laboratory on Long Island, New York by the United States Department of Energy. EIC will provide capabilities of colliding beams of polarized electrons with polarized beams of proton and light ions. EIC will be one of the largest and most sophisticated new accelerator facilities worldwide, and the only new large-scale accelerator facility planned for construction in the United States in the next few decades. The versatility, resolving power and intensity of EIC will present many new opportunities to address some of the crucial and fundamental open scientific questions in particle physics. This document provides an overview of the science case of EIC from the perspective of the high energy physics community.

hep-ph↗

On the determination of uncertainties in parton densities

We review various methods used to estimate uncertainties in quantum correlation functions, such as parton distribution functions (PDFs). Using a toy model of a PDF, we compare the uncertainty estimates yielded by the traditional Hessian and data resampling methods, as well as from explicitly Bayesian analyses using nested sampling or hybrid Markov chain Monte Carlo techniques. We investigate how uncertainty bands derived from neural network approaches depend on details of the network training, and how they compare to the uncertainties obtained from more traditional methods with a specific underlying parametrization. Our results show that utilizing a neural network on a simplified example of PDF data has the potential to inflate uncertainties, in part due to the cross validation procedure that is generally used to avoid overfitting data.

hep-ph↗

Complementarity of experimental and lattice QCD data on pion parton distributions

We extract pion parton distribution functions (PDFs) in a Monte Carlo global QCD analysis of experimental data together with reduced Ioffe time pseudo-distributions and matrix elements of current-current correlators generated from lattice QCD. By including both experimental and lattice QCD data, our analysis rigorously quantifies both the uncertainties of the pion PDFs and systematic effects intrinsic to the lattice QCD observables. The reduced Ioffe time pseudo-distributions significantly decrease the uncertainties on the PDFs, while the current-current correlators are limited by the systematic effects associated with the lattice. Consistent with recent phenomenological determinations, the behavior of the valence quark distribution of the pion at large momentum fraction is found to be $\sim (1-x)^{ β_{\rm eff}}$ with $β_{\rm eff} \approx 1.0-1.2$.

hep-ph↗

Combining nonperturbative transverse momentum dependence with TMD evolution

Central to understanding the nonpertubative, intrinsic partonic nature of hadron structure are the concepts of transverse momentum dependent (TMD) parton distribution and fragmentation functions. A TMD factorization approach to the phenomenology of semi-inclusive processes that includes evolution, higher orders, and matching to larger transverse momentum, is ultimately necessary for reliably connecting with phenomenologically extracted nonperturbative structures, especially when widely different scales are involved. In this paper, we will address some of the difficulties that arise when phenomenological techniques that were originally designed for very high energy applications are extended to studies of hadron structures, and we will solidify the connection between standard high energy TMD implementations and the more intuitive, parton model based approaches to phenomenology that emphasize nonperturbative hadron structure. In the process, we will elaborate on differences between forward and backward TMD evolution, which in the context of this paper we call "bottom-up" and "top-down" approaches, and we will explain the advantages of a bottom-up strategy. We will also emphasize and clarify the role of the integral relations that connect TMD and collinear correlation functions. We will show explicitly how they constrain the nonperturbative "$g$-functions" of standard Collins-Soper-Sterman (CSS) implementations of TMD factorization. This paper is especially targeted toward phenomenologists and model builders who are interested in merging specific nonperturbative models and calculations (including lattice QCD) with TMD factorization at large $Q$. Our main result is a recipe for incorporating nonperturbative models into TMD factorization, and for constraining their parameters in a way that matches to perturbative QCD and evolution.

hep-ph↗

Machine learning-based event generator for electron-proton scattering

We present a new machine learning-based Monte Carlo event generator using generative adversarial networks (GANs) that can be trained with calibrated detector simulations to construct a vertex-level event generator free of theoretical assumptions about femtometer scale physics. Our framework includes a GAN-based detector folding as a fast-surrogate model that mimics detector simulators. The framework is tested and validated on simulated inclusive deep-inelastic scattering data along with existing parametrizations for detector simulation, with uncertainty quantification based on a statistical bootstrapping technique. Our results provide for the first time a realistic proof-of-concept to mitigate theory bias in inferring vertex-level event distributions needed to reconstruct physical observables.

hep-ph↗

New tool for kinematic regime estimation in semi-inclusive deep-inelastic scattering

We introduce a new phenomenological tool based on momentum region indicators to guide the analysis and interpretation of semi-inclusive deep-inelastic scattering measurements. The new tool, referred to as "affinity", is devised to help visualize and quantify the proximity of any experimental kinematic bin to a particular hadron production region, such as that associated with transverse momentum dependent factorization. We apply the affinity estimator to existing HERMES and COMPASS data and expected data from Jefferson Lab and the future Electron-Ion Collider. We also provide an interactive notebook based on Machine Learning for fast evaluation of affinity.

hep-ph↗

How well do we know the gluon polarization in the proton?

We perform the first simultaneous global QCD analysis of spin-averaged and spin-dependent parton distribution functions (PDFs), including single jet production data from unpolarized and polarized hadron collisions. We critically assess the impact of SU(3) flavor symmetry and PDF positivity assumptions on the quark and gluon helicity PDFs, and find strong bias from these, particularly on the gluon polarization. The simultaneous analysis allows for the first time extraction of individual helicity-aligned and antialigned PDFs with a consistent treatment of uncertainties.

hep-ph↗

Isovector EMC effect from global QCD analysis with MARATHON data

We report the results of a Monte Carlo global QCD analysis of unpolarized parton distribution functions (PDFs), including for the first time constraints from ratios of $^3$He to $^3$H structure functions recently obtained by the MARATHON experiment at Jefferson Lab. Our simultaneous analysis of nucleon PDFs and nuclear effects in $A=2$ and $A=3$ nuclei reveals the first indication for an isovector nuclear EMC effect in light nuclei. We find that while the MARATHON data yield relatively weak constraints on the $F_2^n/F_2^p$ neutron to proton structure function ratio and on the $d/u$ PDF ratio, they suggest an enhanced nuclear effect on the $d$-quark PDF in the bound proton, questioning the assumptions commonly made in nuclear PDF analyses.

hep-ph↗

Towards the three-dimensional parton structure of the pion: Integrating transverse momentum data into global QCD analysis

We perform a new Monte Carlo QCD analysis of pion parton distribution functions, including, for the first time, transverse momentum dependent pion-nucleus Drell-Yan cross sections together with $p_{\rm T}$-integrated Drell-Yan and leading neutron electroproduction data from HERA. We assess the sensitivity of the Monte Carlo fits to kinematic cuts, factorization scale, and parametrization choice, and we discuss the impact of the various datasets on the pion's quark and gluon distributions. This study provides the necessary step towards the simultaneous analysis of collinear and transverse momentum dependent pion distributions and the determination of the pion's three-dimensional structure.

hep-ph↗

Global QCD Analysis of Pion Parton Distributions with Threshold Resummation

We perform the first global QCD analysis of pion valence, sea quark, and gluon distributions within a Bayesian Monte Carlo framework with threshold resummation on Drell-Yan cross sections at next-to-leading log accuracy. Exploring various treatments of resummation, we find that the large-$x$ asymptotics of the valence quark distribution $\sim (1-x)^{β_v}$ can differ significantly, with $β_v$ ranging from $\approx 1$ to $> 2.5$ at the input scale. Regardless of the specific implementation, however, the resummation induced redistribution of the momentum between valence quarks and gluons boosts the total momentum carried by gluons to $\approx 40\%$, increasing the gluon contribution to the pion mass to $\approx 40$ MeV.

hep-ph↗