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The longitudinal and transverse spin transfers to Λ (Λ¯¯¯¯) hyperons in polarized proton-proton collisions are expected to be sensitive to the helicity and transversity distributions, respectively, of (anti-)strange quarks in the proton, and to the corresponding polarized fragmentation functions. We report improved measurements of the longitudinal spin transfer coefficient, DLL, and the transverse spin transfer coefficient, DTT, to Λ and Λ¯¯¯¯ in polarized proton-proton collisions at s√ = 200 GeV by the STAR experiment at RHIC. The data set includes longitudinally polarized proton-proton collisions with an integrated luminosity of 52 pb−1, and transversely polarized proton-proton collisions with a similar integrated luminosity. Both data sets have about twice the statistics of previous results and cover a kinematic range of |ηΛ(Λ¯¯¯¯)| < 1.2 and transverse momentum pT,Λ(Λ¯¯¯¯) up to 8 GeV/c. We also report the first measurements of the hyperon spin transfer coefficients DLL and DTT as a function of the fractional jet momentum z carried by the hyperon, which can provide more direct constraints on the polarized fragmentation functions.
We report a new measurement of transverse single-spin asymmetries for dijet production in collisions of polarized protons at s√ = 200 GeV. Possible correlations between the proton spin and the transverse momenta of its partons, mutually orthogonal, with each perpendicular to the proton momentum direction, are probed at high Q2 ≈160 GeV2. The associated Sivers observable ⟨kT⟩, the average parton transverse momentum, is extracted using simple kinematics. Nonzero Sivers effects are observed for the first time in proton-proton collisions, but only when the jets are sorted by their net charge, which enhances the u- or d-quark contributions to separate data samples. This also enables a determination of the individual partonic contributions to the observed asymmetries.
Jet-hadron correlations with respect to the event plane in √sNN = 200 GeV Au+Au collisions in STAR
(2023)
Angular distributions of charged particles relative to jet axes are studied in sNN−−−√ = 200 GeV Au+Au collisions as a function of the jet orientation with respect to the event plane.This differential study tests the expected path-length dependence of energy loss experienced by a hard-scattered parton as it traverses the hot and dense medium formed in heavy-ion collisions.A second-order event plane is used in the analysis as an experimental estimate of the reaction plane formed by the collision impact parameter and the beam direction. Charged-particle jets with 15<pT,jet< 20 and 20<pT,jet< 40 GeV/c were reconstructed with the anti-kT algorithm with radius parameter setting of \(R=0.4\) in the 20-50\% centrality bin to maximize the initial-state eccentricity of the interaction region. The reaction plane fit method is implemented to remove the flow-modulated background with better precision than prior methods. Yields and widths of jet-associated charged-hadron distributions are extracted in three angular bins between the jet axis and the event plane. The event-plane (EP) dependence is further quantified by ratios of the associated yields in different EP bins. No dependence on orientation of the jet axis with respect to the event plane is seen within the uncertainties in the kinematic regime studied. This finding is consistent with a similar experimental observation by ALICE in sNN−−−√ = 2.76 TeV Pb-Pb collision data.
We report the first measurements of cumulants, up to 4th order, of deuteron number distributions and proton-deuteron correlations in Au+Au collisions recorded by the STAR experiment in phase-I of Beam Energy Scan (BES-I) program at the Relativistic Heavy Ion Collider (RHIC). Deuteron cumulants, their ratios, and proton-deuteron mixed cumulants are presented for different collision centralities covering a range of center of mass energy per nucleon pair sNN−−−√ = 7.7 to 200 GeV. It is found that the cumulant ratios at lower collision energies favor a canonical ensemble over a grand canonical ensemble in thermal models. An anti-correlation between proton and deuteron multiplicity is observed across all collision energies and centralities, consistent with the expectation from global baryon number conservation. The UrQMD model coupled with a phase-space coalescence mechanism qualitatively reproduces the collision-energy dependence of cumulant ratios and proton-deuteron correlations.
Jet-hadron correlations with respect to the event plane in √sNN = 200 GeV Au+Au collisions in STAR
(2023)
Angular distributions of charged particles relative to jet axes are studied in sNN−−−√ = 200 GeV Au+Au collisions as a function of the jet orientation with respect to the event plane. This differential study tests the expected path-length dependence of energy loss experienced by a hard-scattered parton as it traverses the hot and dense medium formed in heavy-ion collisions. A second-order event plane is used in the analysis as an experimental estimate of the reaction plane formed by the collision impact parameter and the beam direction. Charged-particle jets with 15<pT,jet< 20 and 20<pT,jet< 40 GeV/c were reconstructed with the anti-kT algorithm with radius parameter setting of \(R=0.4\) in the 20-50\% centrality bin to maximize the initial-state eccentricity of the interaction region. The reaction plane fit method is implemented to remove the flow-modulated background with better precision than prior methods. Yields and widths of jet-associated charged-hadron distributions are extracted in three angular bins between the jet axis and the event plane. The event-plane (EP) dependence is further quantified by ratios of the associated yields in different EP bins. No dependence on orientation of the jet axis with respect to the event plane is seen within the uncertainties in the kinematic regime studied. This finding is consistent with a similar experimental observation by ALICE in sNN−−−√ = 2.76 TeV Pb+Pb collision data.
Gravitational waves from a core g-mode in supernovae as probes of the high-density equation of state
(2023)
Using relativistic supernova simulations of massive progenitor stars with a quark-hadron equation of state (EoS) and a purely hadronic EoS, we identify a distinctive feature in the gravitational-wave signal that originates from a buoyancy-driven mode (g-mode) below the proto-neutron star convection zone. The mode frequency lies in the range 200≲f≲800Hz and decreases with time. As the mode lives in the core of the proto-neutron star, its frequency and power are highly sensitive to the EoS, in particular the sound speed around twice saturation density.
Gravitational waves from a core g-mode in supernovae as probes of the high-density equation of state
(2023)
Using relativistic supernova simulations of massive progenitor stars with a quark-hadron equation of state (EoS) and a purely hadronic EoS, we identify a distinctive feature in the gravitational-wave signal that originates from a buoyancy-driven mode (g-mode) below the proto-neutron star convection zone. The mode frequency lies in the range 200≲f≲800Hz and decreases with time. As the mode lives in the core of the proto-neutron star, its frequency and power are highly sensitive to the EoS, in particular the sound speed around twice saturation density.
We investigate the early time dynamics of heavy ion collisions studying the time evolution of the energy-momentum tensor as well as energy-momentum correlations within a uniformly thermalizing holographic QGP. From these quantities, we suggest a far-from equilibrium definition of shear viscosity, which is a crucial property of QCD matter as it significantly determines the generation of elliptic flow already at early times. During an exemplary initial heating phase of the holographic QGP the shear viscosity of entropy density ratio decreases down to 60%, followed by an overshoot to 110% of the near-equilibrium value, η/s=1/(4π). Implications for the QCD QGP are discussed. Subsequently, we consider a holographic QGP which is Bjorken-expanding. Its energy-momentum tensor components have a known hydrodynamic attractor to which all time evolutions collapse independent of the initial conditions. Based on this, we propose a definition for a far from equilibrium speed of sound, and analytically compute its hydrodynamic attractor. Subjecting this Bjorken-expanding plasma to an external magnetic field and an axial chemical potential, we study the chiral magnetic effect far from equilibrium.
The cosmological implications of the Covariant Canonical Gauge Theory of Gravity (CCGG) are investigated. CCGG is a Palatini theory derived from first principles using the canonical transformation formalism in the covariant Hamiltonian formulation. The Einstein-Hilbert theory is thereby extended by a quadratic Riemann-Cartan term in the Lagrangian. Moreover, the requirement of covariant conservation of the stress-energy tensor leads to necessary presence of torsion. In the Friedman universe that promotes the cosmological constant to a time-dependent function, and gives rise to a geometrical correction with the EOS of dark radiation. The resulting cosmology, compatible with the ΛCDM parameter set, encompasses bounce and bang scenarios with graceful exits into the late dark energy era. Testing those scenarios against low-z observations shows that CCGG is a viable theory.
We investigate the thermodynamic geometry of the quark-meson model at finite temperature, T, and quark number chemical potential, μ. We extend previous works by the inclusion of fluctuations exploiting the functional renormalization group approach. We use recent developments to recast the flow equation into the form of an advection-diffusion equation. We adopt the local potential approximation for the effective average action. We focus on the thermodynamic curvature, R, in the (μ,T) plane, in proximity of the chiral crossover, up to the critical point of the phase diagram. We find that the inclusion of fluctuations results in a smoother behavior of R near the chiral crossover. Moreover, for small μ, R remains negative, signaling the fact that bosonic fluctuations reduce the capability of the system to completely overcome the fermionic statistical repulsion of the quarks. We investigate in more detail the small μ region by analyzing a system in which we artificially lower the pion mass, thus approaching the chiral limit in which the crossover is actually a second order phase transition. On the other hand, as μ is increased and the critical point is approached, we find that R is enhanced and a sign change occurs, in agreement with mean field studies. Hence, we completely support the picture that R is sensitive to a crossover and a phase transition, and provides information about the effective behavior of the system at the phase transition.
n this paper we study invasion probabilities and invasion times of cooperative parasites spreading in spatially structured host populations. The spatial structure of the host population is given by a random geometric graph on [0,1]n, n∈N, with a Poisson(N)-distributed number of vertices and in which vertices are connected over an edge when they have a distance of at most rN∈Θ(Nβ−1n) for some 0<β<1 and N→∞. At a host infection many parasites are generated and parasites move along edges to neighbouring hosts. We assume that parasites have to cooperate to infect hosts, in the sense that at least two parasites need to attack a host simultaneously. We find lower and upper bounds on the invasion probability of the parasites in terms of survival probabilities of branching processes with cooperation. Furthermore, we characterize the asymptotic invasion time.
An important ingredient of the proofs is a comparison with infection dynamics of cooperative parasites in host populations structured according to a complete graph, i.e. in well-mixed host populations. For these infection processes we can show that invasion probabilities are asymptotically equal to survival probabilities of branching processes with cooperation.
Furthermore, we build in the proofs on techniques developed in [BP22], where an analogous invasion process has been studied for host populations structured according to a configuration model.
We substantiate our results with simulations.
We compute the critical exponents of the O(N) model within the Functional Renormalization Group (FRG) approach. We use recent advances which are based on the observation that the FRG flow equation can be put into the form of an advection-diffusion equation. This allows to employ well-tested hydrodynamical algorithms for its solution. In this study we work in the local potential approximation (LPA) for the effective average action and put special emphasis on estimating the various sources of errors. Our results complement previous results for the critical exponents obtained within the FRG approach in LPA. Despite the limitations imposed by restricting the discussion to the LPA, the results compare favorably with those obtained via other methods.
We compute the critical exponents of the O(N) model within the Functional Renormalization Group (FRG) approach. We use recent advances which are based on the observation that the FRG flow equation can be put into the form of an advection-diffusion equation. This allows to employ well-tested hydrodynamical algorithms for its solution. In this study we work in the local potential approximation (LPA) for the effective average action and put special emphasis on estimating the various sources of errors. Our results complement previous results for the critical exponents obtained within the FRG approach in LPA. Despite the limitations imposed by restricting the discussion to the LPA, the results compare favorably with those obtained via other methods.
We analyze the experimental data on nuclei and hypernuclei yields recently obtained by the STAR collaboration. The hybrid dynamical and statistical approaches which have been developed previously are able to describe the experimental data reasonably. We discuss the intriguing difference between the yields of normal nuclei and hypernuclei which may be related to the properties of hypermatter at subnuclear densities. Most importantly new (hyper-)nuclei could be detected via particle correlations, and such measurements are relevant to pin down the production mechanism.
We analyze the experimental data on nuclei and hypernuclei yields recently obtained by the STAR collaboration. The hybrid dynamical and statistical approaches which have been developed previously are able to describe the experimental data reasonably. We discuss the intriguing difference between the yields of normal nuclei and hypernuclei which may be related to the properties of hypermatter at subnuclear densities. Most importantly new (hyper-)nuclei could be detected via particle correlations, and such measurements are relevant to pin down the production mechanism.
The European bison was saved from the brink of extinction due to considerable conservation efforts since the early 20th century. The current global population of > 9,500 individuals is the result of successful ex situ breeding based on a stock of only 12 founders, resulting in an extremely low level of genetic variability. Due to the low allelic diversity, traditional molecular tools, such as microsatellites, fail to provide sufficient resolution for accurate genetic assessments in European bison, let alone from non-invasive samples. Here, we present a SNP panel for accurate high-resolution genotyping of European bison, which is suitable for a wide variety of sample types. The panel accommodates 96 markers allowing for individual and parental assignment, sex determination, breeding line discrimination, and cross-species detection. Two applications were shown to be utilisable in further Bos species with potential conservation significance. The new SNP panel will allow to tackle crucial tasks in European bison conservation, including the genetic monitoring of reintroduced populations, and a molecular assessment of pedigree data documented in the world’s first studbook of a threatened species.
The family of cubic noncentrosymmetric 3-4-3 compounds has become a fertile ground for the discovery of novel correlated metallic and insulating phases. Here, we report the synthesis of a new heavy fermion compound, Ce3Bi4Ni3. It is an isoelectronic analog of the prototypical Kondo insulator Ce3Bi4Pt3 and of the recently discovered Weyl-Kondo semimetal Ce3Bi4Pd3. In contrast to the volume-preserving Pt-Pd substitution, structural and chemical analyses reveal a positive chemical pressure effect in Ce3Bi4Ni3 relative to its heavier counterparts. Based on the results of electrical resistivity, Hall effect, magnetic susceptibility, and specific heat measurements, we identify an energy gap of 65-70 meV, about 8 times larger than that in Ce3Bi4Pt3 and about 45 times larger than that of the Kondo-insulating background hosting the Weyl nodes in Ce3Bi4Pd3. We show that this gap as well as other physical properties do not evolve monotonically with increasing atomic number, i.e., in the sequence Ce3Bi4Ni3-Ce3Bi4Pd3-Ce3Bi4Pt3, but instead with increasing partial electronic density of states of the d orbitals at the Fermi energy. To understand under which condition topological states form in these materials is a topic for future studies.
Investigators in the cognitive neurosciences have turned to Big Data to address persistent replication and reliability issues by increasing sample sizes, statistical power, and representativeness of data. While there is tremendous potential to advance science through open data sharing, these efforts unveil a host of new questions about how to integrate data arising from distinct sources and instruments. We focus on the most frequently assessed area of cognition - memory testing - and demonstrate a process for reliable data harmonization across three common measures. We aggregated raw data from 53 studies from around the world which measured at least one of three distinct verbal learning tasks, totaling N = 10,505 healthy and brain-injured individuals. A mega analysis was conducted using empirical bayes harmonization to isolate and remove site effects, followed by linear models which adjusted for common covariates. After corrections, a continuous item response theory (IRT) model estimated each individual subject’s latent verbal learning ability while accounting for item difficulties. Harmonization significantly reduced inter-site variance by 37% while preserving covariate effects. The effects of age, sex, and education on scores were found to be highly consistent across memory tests. IRT methods for equating scores across AVLTs agreed with held-out data of dually-administered tests, and these tools are made available for free online. This work demonstrates that large-scale data sharing and harmonization initiatives can offer opportunities to address reproducibility and integration challenges across the behavioral sciences.
The Calderón problem with finitely many unknowns is equivalent to convex semidefinite optimization
(2023)
We consider the inverse boundary value problem of determining a coefficient function in an elliptic partial differential equation from knowledge of the associated Neumann-Dirichlet-operator. The unknown coefficient function is assumed to be piecewise constant with respect to a given pixel partition, and upper and lower bounds are assumed to be known a-priori.
We will show that this Calderón problem with finitely many unknowns can be equivalently formulated as a minimization problem for a linear cost functional with a convex non-linear semidefinite constraint. We also prove error estimates for noisy data, and extend the result to the practically relevant case of finitely many measurements, where the coefficient is to be reconstructed from a finite-dimensional Galerkin projection of the Neumann-Dirichlet-operator.
Our result is based on previous works on Loewner monotonicity and convexity of the Neumann-Dirichlet-operator, and the technique of localized potentials. It connects the emerging fields of inverse coefficient problems and semidefinite optimization.
Bacterial biosynthetic assembly lines, such as non-ribosomal peptide synthetases (NRPS) and polyketide synthases, are often subject of synthetic biology – because they produce a variety of natural products invaluable for modern pharmacotherapy. Acquiring the ability to engineer these biosynthetic assembly lines allows the production of artificial non-ribosomal peptides (NRP), polyketides, and hybrids thereof with new or improved properties. However, traditional bioengineering approaches have suffered for decades from their very limited applicability and, unlike combinatorial chemistry, are stigmatized as inefficient because they cannot be linked to the high-throughput screening platforms of the pharmaceutical industry. Although combinatorial chemistry can generate new molecules cheaper, faster, and in greater numbers than traditional natural product discovery and bioengineering approaches, it does not meet current medical needs because it covers only a limited biologically relevant chemical space. Hence, methods for high-throughput generation of new natural product-like compound libraries could provide a new avenue towards the identification of new lead compounds. To this end, prior to this work, we introduced an artificial synthetic NRPS type, referred to as type S NRPS, to provide a first-of-its-kind bicombinatorial approach to parallelized high-throughput NRP library generation. However, a bottleneck of these first two generations of type S NRPS was a significant drop in production yields. To address this issue, we applied an iterative optimization process that enabled titer increases of up to 55-fold compared to the non-optimized equivalents, restoring them to wild-type levels and beyond.