Microsoft (Netherlands)

Large Language Models (LLMs), utilised through a number of software tools, are now widely used by students to support their learning and complete their assignments. Evaluating the intellectual abilities of learners has always been an important compone

The extended tight binding (xTB) family of methods opened many new possibilities in the field of computational chemistry. Within just 5 years, the GFN2-xTB parametrization for all elements up to Z = 86 enabled more than a thousand applications, which were previously not feasible with other electronic structure methods. The xTB methods provide a robust and efficient way to apply quantum mechanics-based approaches for obtaining molecular geometries, computing free energy corrections or describing noncovalent interactions and found applicability for many more targets. A crucial contribution to the success of the xTB methods is the availability within many simulation packages and frameworks, supported by the open source development of its program library and packages. We present a comprehensive summary of the applications and capabilities of xTB methods in different fields of chemistry. Moreover, we consider the main software packages for xTB calculations, covering their current ecosystem, novel features, and usage by the scientific community.

We numerically study the strong-interaction limit of the exchange-correlation functional for neutral atoms and Bohr atoms as the number of electrons increases. Using a compact representation, we analyze the second-order gradient expansion, comparing it with the one for exchange (weak interaction limit). The two gradient expansions, at strong and weak interaction, turn out to be very similar in magnitude but with opposite signs. We find that the point-charge plus continuum model is surprisingly accurate for the gradient expansion coefficient at strong coupling, while generalized gradient approximations, such as Perdew-Burke-Ernzerhof (PBE) and PBEsol, severely underestimate it. We then use our results to analyze the Lieb-Oxford bound from the point of view of slowly varying densities, clarifying some aspects on the bound at a fixed number of electrons.

Coarse-grained (CG) molecular dynamics enables the study of biological processes at temporal and spatial scales that would be intractable at an atomistic resolution. However, accurately learning a CG force field remains a challenge. In this work, we leverage connections between score-based generative models, force fields, and molecular dynamics to learn a CG force field without requiring any force inputs during training. Specifically, we train a diffusion generative model on protein structures from molecular dynamics simulations, and we show that its score function approximates a force field that can directly be used to simulate CG molecular dynamics. While having a vastly simplified training setup compared to previous work, we demonstrate that our approach leads to improved performance across several protein simulations for systems up to 56 amino acids, reproducing the CG equilibrium distribution and preserving the dynamics of all-atom simulations such as protein folding events.

The realization of hybrid superconductor–semiconductor quantum devices, in particular a topological qubit, calls for advanced techniques to readily and reproducibly engineer induced superconductivity in semiconductor nanowires. Here, we introduce an on-chip fabrication paradigm based on shadow walls that offers substantial advances in device quality and reproducibility. It allows for the implementation of hybrid quantum devices and ultimately topological qubits while eliminating fabrication steps such as lithography and etching. This is critical to preserve the integrity and homogeneity of the fragile hybrid interfaces. The approach simplifies the reproducible fabrication of devices with a hard induced superconducting gap and ballistic normal-/superconductor junctions. Large gate-tunable supercurrents and high-order multiple Andreev reflections manifest the exceptional coherence of the resulting nanowire Josephson junctions. Our approach enables the realization of 3-terminal devices, where zero-bias conductance peaks emerge in a magnetic field concurrently at both boundaries of the one-dimensional hybrids.

Strong spin–orbit semiconductor nanowires coupled to a superconductor are predicted to host Majorana zero modes. Exchange (braiding) operations of Majorana modes form the logical gates of a topological quantum computer and require a network of nanowires. Here, we utilize an in-plane selective area growth technique for InSb–Al semiconductor–superconductor nanowire networks. Transport channels, free from extended defects, in InSb nanowire networks are realized on insulating, but heavily mismatched InP (111)B substrates by full relaxation of the lattice mismatch at the nanowire/substrate interface and nucleation of a complete network from a single nucleation site by optimizing the surface diffusion length of the adatoms. Essential quantum transport phenomena for topological quantum computing are demonstrated in these structures including phase-coherence lengths exceeding several micrometers with Aharonov–Bohm oscillations up to five harmonics and a hard superconducting gap accompanied by 2e-periodic Coulomb oscillations with an Al-based Cooper pair island integrated in the nanowire network.

We study superconducting quantum interference in InSb flake Josephson junctions. An even-odd effect in the amplitude and periodicity of the superconducting quantum interference pattern is found. Interestingly, the occurrence of this pattern coincides with enhanced conduction at both edges of the flake, as is deduced from measuring a superconducting quantum interference device (SQUID) pattern at reduced gate voltages. We identify the specific crystal facet of the edge with enhanced conduction, and confirm this by measuring multiple devices. Furthermore, we argue the even-odd effect is due to crossed Andreev reflection, a process where a Cooper pair splits up over the two edges and recombines at the opposite contact. An entirely h/e periodic SQUID pattern, as well as the observation of both even-odd and odd-even effects, corroborates this conclusion. Crossed Andreev reflection could be harnessed for creating a topological state of matter or performing experiments on the nonlocal spin entanglement of spatially separated Cooper pairs.

When managing a software project, communication is one of the most, if not the most, important aspects of software development. In this chapter you’ll learn the excellent features that Visual Studio Team Services offers you for managing your project.

In this chapter the authors present a revision of the information overload concept elaborated by Eppler and Mengis (2004). The main elements of our approach are literature synopsis and analysis, qualitative semi-structured interviews, and discussion. Their review of the information overload concept is multidisciplinary as we identify similarities and differences among the various management perspectives and refine it with the empirical findings. They hope that by doing so, we can identify synergies between the theoretical conceptualization (Epper and Mengis, 2004), and real-life settings. They present results in a highly compressed, visualized format that allows for a more concise representation of the subject domain, easy comparisons, and hopefully – reduction of information overload. The empirical study was done at the Microsoft B.V. (The Netherlands) where Information workers became the most important type of workers within an organization.

As a consequence of the importance of technology platforms, it is almost impossible for firms to engage the competitive battle on their own. We therefore see patterns of competition emerge that do not match the economic models of perfect competition or even of oligopolistic or monopolistic competition. Rather, competition takes place between a few large coalitions, or networks, of firms around a common technological platform. Such networks, consisting of multiple firms performing different roles, are not unlike biological ecosystems. For such networks, therefore, the term business ecosystem is increasingly used (Den Hartigh & Van Asseldonk, 2004; Iansiti & Levien, 2002, 2004a, 2004b; Moore, 1993, 1996; Witte, 2004). The term business ecosystem was coined by James Moore in his 1993 Harvard Business Review article Predators and Prey. Moore (1996, p. 15) defines a business ecosystem as “The term circumscribes the microeconomics of intense coevolution coalescing around innovative ideas. Business ecosystems span a variety of industries. The companies within them coevolve capabilities around the innovation and cooperatively and competitively to support new products, satisfy customer needs, and incorporate the next round of innovation.” There is a strong analogy between business ecosystems and biological ecosystems, as implied by the “ecosystems” terminology.