Frankfurt Institute for Advanced Studies

About: Frankfurt Institute for Advanced Studies is a facility organization based out in Frankfurt am Main, Germany. It is known for research contribution in the topics: Baryon & Quark–gluon plasma. The organization has 798 authors who have published 2733 publications receiving 82799 citations. The organization is also known as: FIAS.

Surprisingly large uncertainties in temperature extraction from thermal fits to hadron yield data at LHC

Abstract: The conventional hadron-resonance gas (HRG) model with the Particle Data Group (PDG) hadron input, full chemical equilibrium, and the hadron type dependent eigenvolume interactions is employed to fit the hadron mid-rapidity yield data of ALICE Collaboration for the most central Pb+Pb collisions. For the case of point-like hadrons the well-known fit result $T = 154 \pm 2$ MeV is reproduced. However, the situation changes if hadrons have different eigenvolumes. In the case when all mesons are point-like while all baryons have an effective hard-core radius of 0.3 fm the $\chi^2$ temperature dependence of the $\chi^2$ has a broad minimum in the temperature range of $155-210$ MeV, with fit quality comparable to the $T \sim 155$ MeV minimum in the point-particle case. Very similar result is obtained when only baryon-baryon eigenvolume interactions are considered, with eigenvolume parameter taken from previous fit to ground state of nuclear matter. Finally, when we apply the eigenvolume corrections with mass-proportional eigenvolume $v_i \sim m_i$, fixed to particular proton hard-core radius $r_p$, we observe a second minimum in the temperature dependence of the $\chi^2$, located at the significantly higher temperatures. For instance, at $r_p = 0.5$ fm the fit quality is better than in the point-particle HRG case in a very wide temperature range of $170-320$ MeV, which gives an uncertainty in the temperature determination from the fit to the data of 150 MeV. These results show that thermal fits to the heavy-ion hadron yield data are very sensitive to the modeling of the short-range repulsion eigenvolume between hadrons, and that chemical freeze-out temperature can be extracted from the LHC hadron yield data only with sizable uncertainty.

EEG-triggered TMS reveals stronger brain state-dependent modulation of motor evoked potentials at weaker stimulation intensities

Abstract: Background: Corticospinal excitability depends on the current brain state. The recent development of real-time EEG-triggered transcranial magnetic stimulation (EEG-TMS) allows studying this relationship in a causal fashion. Specifically, it has been shown that corticospinal excitability is higher during the scalp surface negative EEG peak compared to the positive peak of μ-oscillations in sensorimotor cortex, as indexed by larger motor evoked potentials (MEPs) for fixed stimulation intensity. Objective: We further characterize the effect of μ-rhythm phase on the MEP input-output (IO) curve by measuring the degree of excitability modulation across a range of stimulation intensities. We furthermore seek to optimize stimulation parameters to enable discrimination of functionally relevant EEG-defined brain states. Methods: A real-time EEG-TMS system was used to trigger MEPs during instantaneous brain-states corresponding to μ-rhythm surface positive and negative peaks with five different stimulation intensities covering an individually calibrated MEP IO curve in 15 healthy participants. Results: MEP amplitude is modulated by μ-phase across a wide range of stimulation intensities, with larger MEPs at the surface negative peak. The largest relative MEP-modulation was observed for weak intensities, the largest absolute MEP-modulation for intermediate intensities. These results indicate a leftward shift of the MEP IO curve during the μ-rhythm negative peak. Conclusion: The choice of stimulation intensity influences the observed degree of corticospinal excitability modulation by μ-phase. Lower stimulation intensities enable more efficient differentiation of EEG μ-phase-defined brain states.

Seeing [u] aids vocal learning: Babbling and imitation of vowels using a 3D vocal tract model, reinforcement learning, and reservoir computing

Abstract: We present a model of imitative vocal learning consisting of two stages. First, the infant is exposed to the ambient language and forms auditory knowledge of the speech items to be acquired. Second, the infant attempts to imitate these speech items and thereby learns to control the articulators for speech production. We model these processes using a recurrent neural network and a realistic vocal tract model. We show that vowel production can be successfully learnt by imitation. Moreover, we find that acquisition of [u] is impaired if visual information is discarded during imitation. This might give sighted infants an advantage over blind infants during vocal learning, which is in agreement with experimental evidence.

Molecular dynamics study of the stability of a carbon nanotube atop a catalytic nanoparticle

Abstract: The stability of a single-walled carbon nanotube placed on top of a catalytic nickel nanoparticle is investigated by means of molecular dynamics simulations. As a case study, we consider the (12,0) nanotube consisting of 720 carbon atoms and the icosahedral Ni309 cluster. An explicit set of constant-temperature simulations is performed in order to cover a broad temperature range from 400 to 1200 K, at which a successful growth of carbon nanotubes has been achieved experimentally by means of chemical vapor deposition. The stability of the system depending on parameters of the involved interatomic interactions is analyzed. It is demonstrated that different scenarios of the nanotube dynamics atop the nanoparticle are possible depending on the parameters of the Ni-C potential. When the interaction is weak the nanotube is stable and resembles its highly symmetric structure, while an increase of the interaction energy leads to the abrupt collapse of the nanotube in the initial stage of simulation. In order to validate the parameters of the Ni-C interaction utilized in the simulations, DFT calculations of the potential energy surface for carbon-nickel compounds are performed. The calculated dissociation energy of the Ni-C bond is in good agreement with the values, which correspond to the case of a stable and not deformed nanotube simulated within the MD approach.