Combining superconducting qubits with mesoscopic devices that carry topological states of matter may lead to compact and improved qubit devices with properties useful for fault-tolerant quantum computation. Recently, a charge qubit device based on a topological superconductor circuit has been introduced where signatures of Majorana fermions could be detected spectroscopically in the transmon regime. This device stores quantum information in coherent superpositions of fermion parity states originating from the Majorana fermions, generating a highly isolated qubit whose coherence time could be greatly enhanced. We extended the conventional semi-classical method and obtained analytical derivations for strong transmon-photon coupling. The analytical challenge is rendered tractable via a formalism based on the WKB method that allows to extract the energy eigenstates of the qubit and its dipole matrix elements. Using this formalism, we study the effect of the Majorana fermions on the quantum electrodynamics of the device embedded within an optical cavity and develop protocols to initialise, control and measure the parity states. We show that, remarkably, the parity eigenvalue can be detected via dispersive shifts of the optical cavity in the strong coupling regime and its state can be coherently manipulated via a second order sideband transition

Hybrid ferromagnetic/superconducting systems are well known for hosting intriguing phenomena such as emergent triplet superconductivity at their interfaces and the appearance of in-gap, spin polarized Yu-Shiba-Rusinov (YSR) states bound to magnetic impurities on a superconducting surface. In this work we demonstrate that similar phenomena can be induced on a surface of a conventional superconductor by chemisorbing non-magnetic chiral molecules.Conductance spectra measured on NbSe2 flakes over which chiral alpha helix polyalanine molecules were adsorbed, exhibit, in some cases, in-gap states nearly symmetrically positioned around zero bias that shift with magnetic field, akin to YSR states, as corroborated by theoretical simulations. Other samples show evidence for a collective phenomenon of hybridized YSR-like states giving rise to unconventional, possibly triplet superconductivity, manifested in the conductance spectra by the appearance of a zero bias conductance that diminishes, but does not split, with magnetic field. The transition between these two scenarios appears to be governed by the density of adsorbed molecules.

We investigate the low-energy theory of a one-dimensional finite capacitance topological Josephson junction. Charge fluctuations across the junction couple to resonant microwave fields and can be used to probe microscopic excitations such as Majorana and Andreev bound states. This marriage between localized microscopic degrees of freedom and macroscopic dynamics of the superconducting phase, leads to unique spectroscopic patterns which allow us to reveal the presence of Majorana fermions among the low-lying excitations.

Correct risk estimation of policyholders is of great significance to auto insurance companies. While the current tools used in this field have been proven in practice to be quite efficient and beneficial, we argue that there is still a lot of room for development and improvement in the auto insurance risk estimation process. To this end, we develop a framework based on a combination of a neural network together with a dimensionality reduction technique t-SNE (t-distributed stochastic neighbour embedding). This enables us to visually represent the complex structure of the risk as a two-dimensional surface, while still preserving the properties of the local region in the features space. The obtained results, which are based on real insurance data, reveal a clear contrast between the high and the low risk policy holders, and indeed improve upon the actual risk estimation performed by the insurer. Due to the visual accessibility of the portfolio in this approach, we argue that this framework could be advantageous to the auto insurer, both as a main risk prediction tool and as an additional validation stage in other approaches.

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