Mon·May 18, 2020Monday·May 18, 2020

1. 01*

   Recent results on cold-QCD from RHIC

   Qing-hua Xu (for the STAR Collaboration)🇨🇳

   Polarized proton-proton collisions at the Relativistic Heavy Ion Collider (RHIC) provide unique opportunities to study the spin structure of the nucleon. We will highlight recent results on the nucleon spin structure from the STAR and PHENIX experiments at RHIC: (1) A sizable gluon polarization in the proton is measured with longitudinal double spin asymmetries of jet and hadron production; (2) Longitudinal single spin asymmetries in W boson production improve constraints on the sea quark polarization. The new spin asymmetry results for W boson confirmed the SU(2) flavor asymmetry of the light sea quark polarization in the proton; (3) Transverse spin effects in hadronic systems offer new implications on parton distribution functions in the collinear and transverse momentum dependent frameworks. We will also discuss near term plans for the STAR forward detector upgrade and prospects for proton-proton and proton-ion collisions in the years beyond 2021 at STAR.

   nucl-exhep-exEPJ Web Conf.(2020)·0 citations
2. 02*

   Bayesian Inference of the Symmetry Energy of Super-Dense Neutron-Rich Matter from Future Radius Measurements of Massive Neutron Stars

   Wen-Jie Xie🇨🇳 · Bao-An Li🇺🇸

   Using an explicitly isospin-dependent parametric Equation of State (EOS) for the core of neutron stars (NSs) within the Bayesian statistical approach, we infer the EOS parameters of super-dense neutron-rich nuclear matter from three sets of imagined mass-radius correlation data representing typical predictions by various nuclear many-body theories, i.e, the radius stays the same, decreases or increases with increasing NS mass within $\pm 15\%$ between 1.4 M${}_{\odot }$ and 2.0 M${}_{\odot }$. The corresponding average density increases quickly, slowly or slightly decreases as the NS mass increases from 1.4 M${}_{\odot }$ to 2.0 M${}_{\odot }$. Using the posterior probability distribution functions (PDFs) of EOS parameters inferred from GW170817 and NICER radius data for canonical NSs as references, we investigate how future radius measurements of massive NS will improve our knowledge about the EOS of super-dense neutron-rich nuclear matter, especially its symmetry energy term, compared to what people have already learned from analyzing the GW170817 and NICER data. While the EOS of symmetric nuclear matter (SNM) inferred from the three data sets are approximately the same, the corresponding high-density symmetry energies at densities above about $2{\rho }_0$ are very different, indicating that the radii of massive NSs carry reliable information about the high-density behavior of nuclear symmetry energy with little influence from the remaining uncertainties of the SNM EOS.

   ↳ astro-ph.HEnucl-exnucl-thApJ(2020)·96 citations
3. 03*

   Helicity at Small $x$: Oscillations Generated by Bringing Back the Quarks

   Yuri V. Kovchegov🇺🇸 · Yossathorn Tawabutr🇺🇸

   We construct a numerical solution of the recently-derived large-$N_c\&N_f$ small-$x$ helicity evolution equations with the aim to establish the small-$x$ asymptotics of the quark helicity distribution beyond the large-$N_c$ limit explored previously in the same framework. (Here $N_c$ and $N_f$ are the numbers of quark colors and flavors.) While the large-$N_c$ helicity evolution involves gluons only, the large-$N_c\&N_f$ evolution includes contributions from quarks as well. We find that adding quarks to the evolution makes quark helicity distribution oscillate as a function of $x$. Our numerical results in the large-$N_c\&N_f$ limit lead to the $x$-dependence of the flavor-singlet quark helicity distribution which is well-approximated by \begin{align} \Delta \Sigma (x, Q^2)\bigg|_{\mbox{large-}N_c \& N_f} \sim \left( \frac{1}{x} \right)^{\alpha_h^q} \, \cos \left[ \omega_q \, \ln \left( \frac{1}{x} \right) + \varphi_q \right]. \end{align} The power ${\alpha }_h^q$ exhibits a weak $N_f$-dependence, and, for all $N_f$ values considered, remains very close to ${\alpha }_h^q(N_f=0)=(4/\sqrt{3})\sqrt{{\alpha }_s{N}_c/(2\pi )}$ obtained earlier in the large-$N_c$ limit. The novel oscillation frequency ${\omega }_q$ and phase shift ${\phi }_q$ depend more strongly on the number of flavors $N_f$ (with ${\omega }_q=0$ in the pure-glue large-$N_c$ limit). The typical period of oscillations for $\Delta \Sigma$ is rather long, spanning many units of rapidity. We speculate whether the oscillations we find are related to the sign variation with $x$ seen in the strange quark helicity distribution extracted from the data.

   ↳ hep-phhep-exnucl-exnucl-thJHEP(2020)·58 citations
4. 04*

   Tagging boosted hadronic objects with dynamical grooming

   Yacine Mehtar-Tani🇺🇸 · Alba Soto-Ontoso🇺🇸 · Konrad Tywoniuk🇳🇴

   We evaluate the phenomenological applicability of the dynamical grooming technique, introduced in [1], to boosted W and top tagging at LHC conditions. An extension of our method intended for multi-prong decays with an internal mass scale, such as the top quark decay, is presented. First, we tackle the reconstruction of the mass distribution of W and top jets quantifying the smearing due to pileup. When compared to state-of-the-art grooming algorithms like SoftDrop and its recursive version, dynamical grooming shows an enhanced resilience to background fluctuations. In addition, we asses the discriminating power of dynamical grooming to distinguish W (top) jets from QCD ones by performing a two-step analysis: introduce a cut on the groomed mass around the W (top) mass peak followed by a restriction on the N-subjettinnes ratio ${\tau }_{21}$ (${\tau }_{32}$). For W jets, the out-of-the-box version of dynamical grooming, free of ad-hoc parameters, results into a comparable performance to SoftDrop. Regarding the top tagger efficiency, 3-prong dynamical grooming, in spite of its simplicity, presents better performance than SoftDrop and similar results to Recursive SoftDrop.

   ↳ hep-phhep-exnucl-exnucl-thPRD(2020)·15 citations

* Reconstructed cohort: no mailing for this day survives in the archive. Papers are grouped by their submission times and arXiv's announcement cut-off, assuming announcement without delay; positions follow identifier order. Validated at ~91% exact-day agreement against the archived era.