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An investigation of photoelectron angular distributions and circular dichroism of chiral molecules
(2021)
The present work demonstrates the capability of several type of molecular frame photoelectron angular distributions (MFPADs) and their linked chiroptical phenomenon the photoelectron circular dichroism (PECD) to map in great detail the molecular geometry of polyatomic chiral molecules as a function of photoelectron energy. To investigate the influence of the molecular potential on the MFPADs, two chiral molecules were selected, namely 2-(methyl)oxirane (C3H6O, MOx, m = 58,08 uma) and 2-(trifluoromethyl)oxirane (C3H3F3O, TFMOx, m = 112,03 uma). The two molecules differs in one substitutional group and share an oxirane group where the O(1s) electron was directly photoionized with the use of synchrotron radiation in the soft X-ray regime. The direct photoionization of the K-shell electron is well localized in the molecule and it induces the ejection of two or more electrons; the excited system separates into several charged (and eventually neutral) fragments which undergo Coulomb explosion due to their charges. The electrons and the fragments were detected using the COLd Target Recoil Ion Momentum Spectroscopy (COLTRIMS) and the momentum vectors calculated for each fragment belonging from a single ionization. The former method gives the possibility to post-orient molecules in space, giving access to the molecular frame, thus the MFPAD and its related PECD for multiple light propagation direction.
Stereochemistry (from the Greek στερεο- stereo- meaning solid) refers to chemistry in three dimensions. Since most molecules show a three-dimensional structure (3D), stereochemistry pervades all fields of chemistry and biology, and it is an essential point of view for the understanding of chemical structure, molecular dynamics and molecular reactions. The understanding of the chemistry of life is tightly bounded with major discoveries in stereochemistry, which triggered tremendous technical advancements, making it a flourishing field of research since its revolutionary introduction in late 18th century. In chemistry, chirality is a brunch of stereochemistry which focuses on objects with the peculiar geometrical property of not being superimposable to their mirror-images. The word chirality is derived from the Greek χειρ for “hand”, and the first use of this term in chemistry is usually attributed to Lord Kelvin who called during a lecture at the Oxford University Junior Scientific Club in 1893 “any geometrical figure, or group of points, “chiral”, and say that it has chirality if its image in a plane mirror, ideally realized, cannot be brought to coincide with itself.”. Although the latter is usually considered as the birth of the word chirality, the concept underlying it was already present in several fields of science (above all mathematics), already proving the already multidisciplinary relevance of chirality across many field of science and beyond. Nature shows great examples of chiral symmetry on all scales. Empirically, it is possible to observe it at macroscopic scale (e.g. distribution of rotations of galaxies), down to the microscopic scale (e.g. structure of some plankton species), but it is at the molecular level where the number gets remarkable: most of the pharmaceutical drugs, food fragrances, pheromones, enzymes, amino acids and DNA molecules, in fact, are chiral. Moreover, the concept of chirality goes far beyond the mere spatial symmetry of objects being crucially entangled with the fundamental properties of physical forces in nature. The symmetry breaking, namely the different physical behaviour of a two chiral systems upon the same stimuli, is considered to be one of the best explanation for the long standing questions of homochirality in biological life, and ultimately to the chemical origin of life on Earth as we know it. Our organism shows high enantio-selectivity towards specific compounds ranging from drugs, to fragrances. Over 800 odour molecules commonly used in food and fragrance industries have been identified as chiral and their enantiomeric forms are perceived to have very different smells, as the well-know example of D- and L- limonene. Similarly, responses to pharmaceuticals drugs can be enantiomer specific, and in fact about 60 % the drugs currently on the market are chiral compounds, and nearly 90 % of them are sold as racemates. The same degree of enantio-selectivity is observed in the communications systems of plants and insects. Plants produce lipophilic liquids with high vapour pressure called plant volatiles (PVs) which are synthesized via different enzymes called tarpene synthases that are usually chiral. Chiral molecules and chiral effects have a strong impact on all the fields of science with exciting developments ranging from stereo-selective synthesis based on heterogeneous enantioselective catalysis, to optoelctronics, to photochemical asymmetric synthesis, and chiral surface science, just to cite a few.
Chiral molecules come in two forms called enantiomers. Their almost identical chemical and physical properties continue to pose technical challenges concerning the resolution of racemic mixtures, the determination of the enantiomeric excess, and the direct determination of the absolute configuration of an enantiomer. ...
Relying on the existing estimates for the production cross sections of mini black holes in models with large extra dimensions, we review strategies for identifying those objects at collider experiments. We further consider a possible stable final state of such black holes and discuss their characteristic signatures. Keywords: Black holes
In this thesis the first fully integrated Boltzmann+hydrodynamics approach to relativistic heavy ion reactions has been developed. After a short introduction that motivates the study of heavy ion reactions as the tool to get insights about the QCD phase diagram, the most important theoretical approaches to describe the system are reviewed. To model the dynamical evolution of the collective system assuming local thermal equilibrium ideal hydrodynamics seems to be a good tool. Nowadays, the development of either viscous hydrodynamic codes or hybrid approaches is favoured. For the microscopic description of the hadronic as well as the partonic stage of the evolution transport approaches have beeen successfully applied, since they generate the full phse-space dynamics of all the particles. The hadron-string transport approach that this work is based on is the Ultra-relativistic Quantum Molecular Dynamics (UrQMD) approach. It constitutes an effective solution of the relativistic Boltzmann equation and is restricted to binary collisions of the propagated hadrons. Therefore, the Boltzmann equation and the basic assumptions of this model are introduced. Furthermore, predictions for the charged particle multiplicities at LHC energies are made. The next step is the development of a new framework to calculate the baryon number density in a transport approach. Time evolutions of the net baryon number and the quark density have been calculated at AGS, SPS and RHIC energies and the new approach leads to reasonable results over the whole energy range. Studies of phase diagram trajectories using hydrodynamics are performed as a first move into the direction of the development of the hybrid approach. The hybrid approach that has been developed as the main part of this thesis is based on the UrQMD transport approach with an intermediate hydrodynamical evolution for the hot and dense stage of the collision. The initial energy and baryon number density distributions are not smooth and not symmetric in any direction and the initial velocity profiles are non-trivial since they are generated by the non-equilibrium transport approach. The fulll (3+1) dimensional ideal relativistic one fluid dynamics evolution is solved using the SHASTA algorithm. For the present work, three different equations of state have been used, namely a hadron gas equation of state without a QGP phase transition, a chiral EoS and a bag model EoS including a strong first order phase transition. For the freeze-out transition from hydrodynamics to the cascade calculation two different set-ups are employed. Either an in the computational frame isochronous freeze-out or an gradual freeze-out that mimics an iso-eigentime criterion. The particle vectors are generated by Monte Carlo methods according to the Cooper-Frye formula and UrQMD takes care of the final decoupling procedure of the particles. The parameter dependences of the model are investigated and the time evolution of different quantities is explored. The final pion and proton multiplicities are lower in the hybrid model calculation due to the isentropic hydrodynamic expansion while the yields for strange particles are enhanced due to the local equilibrium in the hydrodynamic evolution. The elliptic flow values at SPS energies are shown to be in line with an ideal hydrodynamic evolution if a proper initial state is used and the final freeze-out proceeds gradually. The hybrid model calculation is able to reproduce the experimentally measured integrated as well as transverse momentum dependent $v_2$ values for charged particles. The multiplicity and mean transverse mass excitation function is calculated for pions, protons and kaons in the energy range from $E_{\rm lab}=2-160A~$GeV. It is observed that the different freeze-out procedures have almost as much influence on the mean transverse mass excitation function as the equation of state. The experimentally observed step-like behaviour of the mean transverse mass excitation function is only reproduced, if a first order phase transition with a large latent heat is applied or the EoS is effectively softened due to non-equilibrium effects in the hadronic transport calculation. The HBT correlation of the negatively charged pion source created in central Pb+Pb collisions at SPS energies are investigated with the hybrid model. It has been found that the latent heat influences the emission of particles visibly and hence the HBT radii of the pion source. The final hadronic interactions after the hydrodynamic freeze-out are very important for the HBT correlation since a large amount of collisions and decays still takes place during this period.
This thesis presents the implementation of the online reconstruction, calibration and monitoring of the data of the Transition Radiation Detector of ALICE. This reconstruction is performed on the High Level Trigger, the third level of the ALICE trigger system, and enables online calibration and monitoring of the incoming data. Additionally, the HLT can steer the data storage, such that only physical interesting events are saved. The online reconstruction, as well as the calibration, makes use of the existing offline algorithms. Therefore, interfaces between the HLT and these offline algorithms were implemented. For being able to reach the speed of 2000 Hz in proton-proton collisions, and 200 Hz in leadlead collisions, the algorithms had to be accelerated. Bottlenecks were tracked down using dedicated tools, and respective code was either reimplemented or it is being skipped during the online reconstruction. The quality of the output data was monitored throughout the implementation, to assure that it is not being cut too much.
We estimate the production rate of photons by the quark-gluon plasma in lattice QCD. We propose a new correlation function which provides better control over the systematic uncertainty in estimating the photon production rate at photon momenta in the range πT/2 to 2πT. The relevant Euclidean vector current correlation functions are computed with Nf = 2 Wilson clover fermions in the chirally-symmetric phase. In order to estimate the photon rate, an ill-posed problem for the vector-channel spectral function must be regularized. We use both a direct model for the spectral function and a modelindependent estimate from the Backus-Gilbert method to give an estimate for the photon rate.
A primordial state of matter consisting of free quarks and gluons that existed in the early universe a few microseconds after the Big Bang is also expected to form in high-energy heavy-ion collisions. Determining the equation of state (EoS) of such a primordial matter is the ultimate goal of high-energy heavy-ion experiments. Here we use supervised learning with a deep convolutional neural network to identify the EoS employed in the relativistic hydrodynamic simulations of heavy ion collisions. High-level correlations of particle spectra in transverse momentum and azimuthal angle learned by the network act as an effective EoS-meter in deciphering the nature of the phase transition in quantum chromodynamics. Such EoS-meter is model-independent and insensitive to other simulation inputs including the initial conditions for hydrodynamic simulations.
A novel method for identifying the nature of QCD transitions in heavy-ion collision experiments is introduced. PointNet based Deep Learning (DL) models are developed to classify the equation of state (EoS) that drives the hydrodynamic evolution of the system created in Au-Au collisions at 10 AGeV. The DL models were trained and evaluated in different hypothetical experimental situations. A decreased performance is observed when more realistic experimental effects (acceptance cuts and decreased resolutions) are taken into account. It is shown that the performance can be improved by combining multiple events to make predictions. The PointNet based models trained on the reconstructed tracks of charged particles from the CBM detector simulation discriminate a crossover transition from a first order phase transition with an accuracy of up to 99.8%. The models were subjected to several tests to evaluate the dependence of its performance on the centrality of the collisions and physical parameters of fluid dynamic simulations. The models are shown to work in a broad range of centralities (b=0–7 fm). However, the performance is found to improve for central collisions (b=0–3 fm). There is a drop in the performance when the model parameters lead to reduced duration of the fluid dynamic evolution or when less fraction of the medium undergoes the transition. These effects are due to the limitations of the underlying physics and the DL models are shown to be superior in its discrimination performance in comparison to conventional mean observables.
An empirical study of the per capita yield of science Nobel prizes : is the US era coming to an end?
(2018)
We point out that the Nobel prize production of the USA, the UK, Germany and France has been in numbers that are large enough to allow for a reliable analysis of the long-term historical developments. Nobel prizes are often split, such that up to three awardees receive a corresponding fractional prize. The historical trends for the fractional number of Nobelists per population are surprisingly robust, indicating in particular that the maximum Nobel productivity peaked in the 1970s for the USA and around 1900 for both France and Germany. The yearly success rates of these three countries are to date of the order of 0.2–0.3 physics, chemistry and medicine laureates per 100 million inhabitants, with the US value being a factor of 2.4 down from the maximum attained in the 1970s. The UK in contrast managed to retain during most of the last century a rate of 0.9–1.0 science Nobel prizes per year and per 100 million inhabitants. For the USA, one finds that the entire history of science Noble prizes is described on a per capita basis to an astonishing accuracy by a single large productivity boost decaying at a continuously accelerating rate since its peak in 1972.
The new heavy ion superconducting continuous wave HElmholtz LInear ACcelerator (HELIAC) is under construction at GSI. A normal conducting injector, comprising an ECR ion source, an RFQ and a DTL, is recently in development. The new Interdigital H-mode DTL, presented in this paper, accelerates the heavy ion beam from 300 to 1400 keV/u, applying an Alternating Phase Focusing (APF) beam dynamics scheme. This APF section, consisting of two separately controlled tanks, has to provide for stable routine operation with assistance of dedicated beam diagnostics devices in the Intertank section. The installed quadrupole lenses and beam steerers installed there ensure full transmission in a wide range of input beam parameters.
Since the last 20 years, modern heuristic algorithms and machine learning have been increasingly used for several purposes in accelerator technology and physics. Since computing power has become less and less of a limiting factor, these tools have become part of the physicist community's standard toolkit [1][2] [3] [4] [5]. This paper describes the construction of an algorithm that can be used to generate an optimised lattice design for transfer lines under the consideration of restrictions that usually limit design options in reality. The developed algorithm has been applied to the existing SIS18 to HADES transfer line in GSI.