2,516 research outputs found
Measurement of the mass difference and the binding energy of the hypertriton and antihypertriton
According to the CPT theorem, which states that the combined operation of
charge conjugation, parity transformation and time reversal must be conserved,
particles and their antiparticles should have the same mass and lifetime but
opposite charge and magnetic moment. Here, we test CPT symmetry in a nucleus
containing a strange quark, more specifically in the hypertriton. This
hypernucleus is the lightest one yet discovered and consists of a proton, a
neutron, and a hyperon. With data recorded by the STAR
detector{\cite{TPC,HFT,TOF}} at the Relativistic Heavy Ion Collider, we measure
the hyperon binding energy for the hypertriton, and
find that it differs from the widely used value{\cite{B_1973}} and from
predictions{\cite{2019_weak, 1995_weak, 2002_weak, 2014_weak}}, where the
hypertriton is treated as a weakly bound system. Our results place stringent
constraints on the hyperon-nucleon interaction{\cite{Hammer2002,
STAR-antiH3L}}, and have implications for understanding neutron star interiors,
where strange matter may be present{\cite{Chatterjee2016}}. A precise
comparison of the masses of the hypertriton and the antihypertriton allows us
to test CPT symmetry in a nucleus with strangeness for the first time, and we
observe no deviation from the expected exact symmetry
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.Comment: 27 pages, 11 figures, AI4EIC workshop, tutorials and hackatho
3D Multi-system Bayesian Calibration with Energy Conservation to Study Rapidity-dependent Dynamics of Nuclear Collisions
Considerable information about the early-stage dynamics of heavy-ion
collisions is encoded in the rapidity dependence of measurements. To leverage
the large amount of experimental data, we perform a systematic analysis using
three-dimensional hydrodynamic simulations of multiple collision systems --
large and small, symmetric and asymmetric. Specifically, we perform fully 3D
multi-stage hydrodynamic simulations initialized by a parameterized model for
rapidity-dependent energy deposition, which we calibrate on the hadron
multiplicity and anisotropic flow coefficients. We utilize Bayesian inference
to constrain properties of the early- and late- time dynamics of the system,
and highlight the impact of enforcing global energy conservation in our 3D
model
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