We report the development of a detection optics for the integration of Raman scattering and scanning probe microscopy at low temperature based on a parabolic mirror. In our set-up, half of the paraboloid mirror covers a solid angle of π corresponding to a numerical aperture of N.A. ≈ 0.85. The optical system can be used for far- and near-field spectroscopy. In the far field, the polarizations can be maintained to within 80%–90%. In combination with a scanning microscope (AFM/STM), tunneling or near-field experiments are possible with less than 10% loss of aperture. Our set-up provides ideal conditions for the future development of tip-enhanced Raman spectroscopy at low temperature.
Resolving the microscopic pairing mechanism and its experimental identification in unconventional superconductors is among the most vexing problems of contemporary condensed matter physics. We show that Raman spectroscopy provides an avenue for this quest by probing the structure of the pairing interaction at play in an unconventional superconductor. As we study the spectra of the prototypical Fe-based superconductor ${\rm Ba_{1-x}K_xFe_2As_2}$ for $0.22\le x \le 0.70$ in all symmetry channels, Raman spectroscopy allows us to distill the leading $s$-wave state. In addition, the spectra collected in the $B_{1g}$ symmetry channel reveal the existence of two collective modes which are indicative of the presence of two competing, yet sub-dominant, pairing tendencies of $d_{x^2-y^2}$ symmetry type. A comprehensive functional Renormalization Group (fRG) and random-phase approximation (RPA) study on this compound confirms the presence of the two sub-leading channels, and consistently matches the experimental doping dependence of the related modes. The synopsis of experimental evidence and theoretical modelling supports a spin-fluctuation mediated superconducting pairing mechanism.
Resolving the microscopic pairing mechanism and its experimental identification in unconventional superconductors is among the most vexing problems of contemporary condensed matter physics. We show that Raman spectroscopy provides an avenue for this quest by probing the structure of the pairing interaction at play in an unconventional superconductor. As we study the spectra of the prototypical Fe-based superconductor ${\rm Ba_{1-x}K_xFe_2As_2}$ for $0.22\le x \le 0.70$ in all symmetry channels, Raman spectroscopy allows us to distill the leading $s$-wave state. In addition, the spectra collected in the $B_{1g}$ symmetry channel reveal the existence of two collective modes which are indicative of the presence of two competing, yet sub-dominant, pairing tendencies of $d_{x^2-y^2}$ symmetry type. A comprehensive functional Renormalization Group (fRG) and random-phase approximation (RPA) study on this compound confirms the presence of the two sub-leading channels, and consistently matches the experimental doping dependence of the related modes. The synopsis of experimental evidence and theoretical modelling supports a spin-fluctuation mediated superconducting pairing mechanism.
We establish a relation between the Raman response function in the $B_{1g}$ channel and the electronic contribution to the nematic susceptibility within the spin-driven approach to electron nematicity of the iron based superconductors. The spin-driven nematic phase, characterized by the broken $C_4$ symmetry, but unbroken $O(3$) spin-rotational symmetry, is generated by the presence of magnetic fluctuations associated with the striped phase. It occurs as a separate phase between $T_N$ and $T_s$ in systems where the structural and magnetic phase transitions are separated. Detecting the presence of nematic degrees of freedom in iron-based superconductors is a difficult task, since it involves measuring higher order spin correlation functions. We show that the nematic degrees of freedom manifest themselves in the experimentally measurable Raman response function. We calculate the Raman response function in tetragonal phase in the large $N$ limit by considering Aslamazov-Larkin type of diagrams that contain a series of inserted fermionic boxes that resemble the nematic coupling constant of the theory. These diagrams effectively account for collisions between spin fluctuations. By summing an infinite number of such higher order diagrams, we demonstrate that the electronic Raman response function shows a clear maximum at the structural phase transition in the $B_{1g}$ channel. Hence, the Raman response function can be used to probe nematic degrees of freedom.
One of the most important goals in the field of autonomous driving development is to make the experience for the passenger as pleasant and comfortable as possible. In addition to traditional influence factors on passenger comfort, new aspects arise due to the transfer of control from the human to the vehicle. Some of these are apparent safety, motion sickness, user preferences regarding driving style and information needs. Ideally, the vehicle and the passenger should form a team, whereby the vehicle should be able to detect and predict situations of discomfort in real time and take measures accordingly. This requires not only the continuous monitoring of the passengers state but also the implementation of adequate mathematical models. To investigate how this teaming of human and automated agents can be shaped in the most effective way is a key topic of the Collaborative Research Center “Hybrid Societies (https://hybrid-societies.org/). In this framework, driving simulator data from the previous project “KomfoPilot” (https://bit.ly/komfopilot) is re-analyzed using new mathematical models. The participants in the study completed several automated drives and reported continuously situations of discomfort using a handset control. Sensor data was collected simultaneously using eye tracking glasses, a smart band, seat pressure sensors and video cameras for motion and face tracking. While pupil diameter, heart rate, interblink intervals, skin conductance and head movement have already been identified as potential single indicators of discomfort, it is now necessary to integrate these and other findings of the project into a functional multivariate model. In this paper, we investigate how such a model can be shaped to offer high prediction accuracy and viable practical implementation. The first important question – which arises from the heterogeneity of the participants – is whether to work with training data on an individual or aggregated level. We compare both possibilities by applying techniques from the field of stochastic approximation for clustering of the chosen training set and subsequent classification of the test data. In the case of an individual model for each participant, we furthermore divide the participants into subgroups and analyze whether there is a connection between the physiological reactions of a passenger and his/her demographic characteristics and driving experience. Finally, we discuss the potential of our method as a reliable prediction model as well as implications for future driving simulator studies and related research.
The valence states of transition metals were studied by measuring the x-ray absorption spectra at both $\mathrm{Mn}\phantom{\rule{0.2em}{0ex}}{L}_{2,3}$ and $\mathrm{Co}\phantom{\rule{0.2em}{0ex}}{L}_{2,3}$ edges of partially $B$-site-disordered perovskite $\mathrm{Eu}{\mathrm{Mn}}_{0.5}{\mathrm{Co}}_{0.5}{\mathrm{O}}_{3}$. By comparison with analogous spectra in various Co- and Mn-based compounds, the divalent state of the Co ions and the tetravalent state of the Mn ions were established analogous to ${\mathrm{Mn}}^{4+}∕{\mathrm{Co}}^{2+}$ charge ordering found by Dass and Goodenough [Phys. Rev. B 67, 014401 (2003)] in $\mathrm{La}{\mathrm{Mn}}_{0.5}{\mathrm{Co}}_{0.5}{\mathrm{O}}_{3}$. The specific heat and magnetic susceptibility data indicate the formation of the magnetically ordered state at ${T}_{C}\ensuremath{\sim}120\phantom{\rule{0.3em}{0ex}}\mathrm{K}$. The first-order metamagnetic transitions seen in $\mathrm{Eu}{\mathrm{Mn}}_{0.5}{\mathrm{Co}}_{0.5}{\mathrm{O}}_{3}$ at $T<{T}_{C}$ suggest the existence of antiferromagnetic and/or paramagnetic clusters embedded into the ferromagnetic matrix.
We show that electronic Raman scattering affords a window into the essential properties of the pairing potential $V_{\vk,\vk^{\prime}}$ of iron-based superconductors. In ${\rm Ba_{0.6}K_{0.4}Fe_2As_2}$ we observe band dependent energy gaps along with excitonic Bardasis-Schrieffer modes characterizing, respectively, the dominant and subdominant pairing channel. The $d_{x^2-y^2}$ symmetry of all excitons allows us to identify the subdominant channel to originate from the interaction between the electron bands. Consequently, the dominant channel driving superconductivity results from the interaction between the electron and hole bands and has the full lattice symmetry. The results in ${\rm Rb_{0.8}Fe_{1.6}Se_2}$ along with earlier ones in ${\rm Ba(Fe_{0.939}Co_{0.061})_2As_2}$ highlight the influence of the Fermi surface topology on the pairing interactions.
High-speed laser scanning systems have been known from laser marking applications for several years. The beam deflection is done by small galvo-driven scanning mirrors, which were capable of transmitting several hundred watts of laser power. Innovative developments have resulted in scanning systems capable of transmitting several thousand watts of CO2 and Nd:YAG laser power. In conjunction with new processing optics and intelligent sensor systems, this technology opens up new perspectives in high precision, high-speed laser welding of complex shaped and small parts.The paper will introduce a welding application in which an integrated optical sensor provides exact positioning of the laser beam prior to welding. The tilting motion of the mirrors guides the laser beam rapidly and precisely on a well-defined path on the part contour with both the welding head and the part fixed. Another example will describe a hardening application. Here the scanning head is utilized to optimize the shape, size and intensity distribution of the laser spot on a tool surface. A pyrometer based process control is used to monitor the surface temperature and change the process parameters accordingly.
