Showing papers by "Vienna University of Technology published in 2021"

Quantum simulation of 2D antiferromagnets with hundreds of Rydberg atoms.

Abstract: Quantum simulation using synthetic systems is a promising route to solve outstanding quantum many-body problems in regimes where other approaches, including numerical ones, fail1. Many platforms are being developed towards this goal, in particular based on trapped ions2–4, superconducting circuits5–7, neutral atoms8–11 or molecules12,13. All of these platforms face two key challenges: scaling up the ensemble size while retaining high-quality control over the parameters, and validating the outputs for these large systems. Here we use programmable arrays of individual atoms trapped in optical tweezers, with interactions controlled by laser excitation to Rydberg states11, to implement an iconic many-body problem—the antiferromagnetic two-dimensional transverse-field Ising model. We push this platform to a regime with up to 196 atoms manipulated with high fidelity and probe the antiferromagnetic order by dynamically tuning the parameters of the Hamiltonian. We illustrate the versatility of our platform by exploring various system sizes on two qualitatively different geometries—square and triangular arrays. We obtain good agreement with numerical calculations up to a computationally feasible size (approximately 100 particles). This work demonstrates that our platform can be readily used to address open questions in many-body physics. Programmable quantum simulation of two-dimensional antiferromagnets is achieved with up to 196 neutral atoms, and the capability of the platform is demonstrated on square and triangular arrays.

Handbook of Model Checking

Abstract: Model checking is a computer-assisted method for the analysis of dynamical systems that can be modeled by state-transition systems. Drawing from research traditions in mathematical logic, programming languages, hardware design, and theoretical computer science, model checking is now widely used for the verification of hardware and software in industry. The editors and authors of this handbook are among the world's leading researchers in this domain, and the 32 contributed chapters present a thorough view of the origin, theory, and application of model checking. In particular, the editors classify the advances in this domain and the chapters of the handbook in terms of two recurrent themes that have driven much of the research agenda: the algorithmic challenge, that is, designing model-checking algorithms that scale to real-life problems; and the modeling challenge, that is, extending the formalism beyond Kripke structures and temporal logic. The book will be valuable for researchers and graduate students engaged with the development of formal methods and verification tools.

Efficiently Teaching an Effective Dense Retriever with Balanced Topic Aware Sampling

Abstract: A vital step towards the widespread adoption of neural retrieval models is their resource efficiency throughout the training, indexing and query workflows. The neural IR community made great advancements in training effective dual-encoder dense retrieval (DR) models recently. A dense text retrieval model uses a single vector representation per query and passage to score a match, which enables low-latency first-stage retrieval with a nearest neighbor search. Increasingly common, training approaches require enormous compute power, as they either conduct negative passage sampling out of a continuously updating refreshing index or require very large batch sizes. Instead of relying on more compute capability, we introduce an efficient topic-aware query and balanced margin sampling technique, called TAS-Balanced. We cluster queries once before training and sample queries out of a cluster per batch. We train our lightweight 6-layer DR model with a novel dual-teacher supervision that combines pairwise and in-batch negative teachers. Our method is trainable on a single consumer-grade GPU in under 48 hours. We show that our TAS-Balanced training method achieves state-of-the-art low-latency (64ms per query) results on two TREC Deep Learning Track query sets. Evaluated on NDCG@10, we outperform BM25 by 44%, a plainly trained DR by 19%, docT5query by 11%, and the previous best DR model by 5%. Additionally, TAS-Balanced produces the first dense retriever that outperforms every other method on recall at any cutoff on TREC-DL and allows more resource intensive re-ranking models to operate on fewer passages to improve results further.

Transistors based on two-dimensional materials for future integrated circuits

Abstract: Field-effect transistors based on two-dimensional (2D) materials have the potential to be used in very large-scale integration (VLSI) technology, but whether they can be used at the front end of line or at the back end of line through monolithic or heterogeneous integration remains to be determined. To achieve this, multiple challenges must be overcome, including reducing the contact resistance, developing stable and controllable doping schemes, advancing mobility engineering and improving high-κ dielectric integration. The large-area growth of uniform 2D layers is also required to ensure low defect density, low device-to-device variation and clean interfaces. Here we review the development of 2D field-effect transistors for use in future VLSI technologies. We consider the key performance indicators for aggressively scaled 2D transistors and discuss how these should be extracted and reported. We also highlight potential applications of 2D transistors in conventional micro/nanoelectronics, neuromorphic computing, advanced sensing, data storage and future interconnect technologies. This Review examines the development of field-effect transistors based on two-dimensional materials and considers the challenges that need to be addressed for the devices to be incorporated into very large-scale integration (VLSI) technology.

Polarons in materials

Abstract: Polarons are quasiparticles that easily form in polarizable materials due to the coupling of excess electrons or holes with ionic vibrations. These quasiparticles manifest themselves in many different ways and have a profound impact on materials properties and functionalities. Polarons have been the testing ground for the development of numerous theories, and their manifestations have been studied by many different experimental probes. This Review provides a map of the enormous amount of data and knowledge accumulated on polaron effects in materials, ranging from early studies and standard treatments to emerging experimental techniques and novel theoretical and computational approaches. Polarons — quasiparticles arising from the interaction of electrons with lattice vibrations — strongly influence materials properties. This Review provides a map of the theoretical models and experimental techniques used to study polarons in materials, presenting paradigmatic examples of different types of polarons and polaron-driven phenomena.

Evaluation of 18 satellite- and model-based soil moisture products using in situ measurements from 826 sensors

Abstract: . Information about the spatiotemporal variability of soil moisture is critical for many purposes, including monitoring of hydrologic extremes, irrigation scheduling, and prediction of agricultural yields. We evaluated the temporal dynamics of 18 state-of-the-art (quasi-)global near-surface soil moisture products, including six based on satellite retrievals, six based on models without satellite data assimilation (referred to hereafter as open-loop models), and six based on models that assimilate satellite soil moisture or brightness temperature data. Seven of the products are introduced for the first time in this study: one multi-sensor merged satellite product called MeMo and six estimates from the HBV model with three precipitation inputs (ERA5, IMERG, and MSWEP) and with and without assimilation of SMAPL3E satellite retrievals, respectively. As reference, we used in situ soil moisture measurements between 2015 and 2019 at 5-cm depth from 826 sensors, located primarily in the USA and Europe. The 3-hourly Pearson correlation (R) was chosen as the primary performance metric. The median R ± interquartile range across all sites and products in each category was 0.66 ± 0.30 for the satellite products, 0.69 ± 0.25 for the open-loop models, and 0.72 ± 0.22 for the models with satellite data assimilation. The best-to-worst performance ranking of the four single-sensor satellite products was SMAPL3E, SMOS, AMSR2, and ASCAT, with the L-band-based SMAPL3E (median R of 0.72) outperforming the others at 50 % of the sites. Among the two multi-sensor satellite products (MeMo and ESA-CCI), MeMo performed better on average (median R of 0.72 versus 0.67), mainly due to the inclusion of SMAPL3E. The best-to-worst performance ranking of the six open-loop models was HBV-MSWEP, HBV-ERA5, ERA5-Land, HBV-IMERG, VIC-PGF, and GLDAS-Noah. This ranking largely reflects the quality of the precipitation forcing. HBV-MSWEP (median R of 0.78) performed best not just among the open-loop models but among all products. The calibration of HBV improved the median R by +0.12 on average compared to random parameters, highlighting the importance of model calibration. The best-to-worst performance ranking of the six models with satellite data assimilation was HBV-MSWEP+SMAPL3E, HBV-ERA5+SMAPL3E, GLEAM, SMAPL4, HBV-IMERG+SMAPL3E, and ERA5. The assimilation of SMAPL3E retrievals into HBV-IMERG improved the median R by +0.06, suggesting that data assimilation yields significant benefits at the global scale.

Unraveling CO adsorption on model single-atom catalysts

Abstract: Understanding how the local environment of a "single-atom" catalyst affects stability and reactivity remains a challenge We present an in-depth study of copper1, silver1, gold1, nickel1, palladium1, platinum1, rhodium1, and iridium1 species on Fe3O4(001), a model support in which all metals occupy the same twofold-coordinated adsorption site upon deposition at room temperature Surface science techniques revealed that CO adsorption strength at single metal sites differs from the respective metal surfaces and supported clusters Charge transfer into the support modifies the d-states of the metal atom and the strength of the metal-CO bond These effects could strengthen the bond (as for Ag1-CO) or weaken it (as for Ni1-CO), but CO-induced structural distortions reduce adsorption energies from those expected on the basis of electronic structure alone The extent of the relaxations depends on the local geometry and could be predicted by analogy to coordination chemistry

Real-time optimal quantum control of mechanical motion at room temperature

Abstract: The ability to accurately control the dynamics of physical systems by measurement and feedback is a pillar of modern engineering1. Today, the increasing demand for applied quantum technologies requires adaptation of this level of control to individual quantum systems2,3. Achieving this in an optimal way is a challenging task that relies on both quantum-limited measurements and specifically tailored algorithms for state estimation and feedback4. Successful implementations thus far include experiments on the level of optical and atomic systems5–7. Here we demonstrate real-time optimal control of the quantum trajectory8 of an optically trapped nanoparticle. We combine confocal position sensing close to the Heisenberg limit with optimal state estimation via Kalman filtering to track the particle motion in phase space in real time with a position uncertainty of 1.3 times the zero-point fluctuation. Optimal feedback allows us to stabilize the quantum harmonic oscillator to a mean occupation of 0.56 ± 0.02 quanta, realizing quantum ground-state cooling from room temperature. Our work establishes quantum Kalman filtering as a method to achieve quantum control of mechanical motion, with potential implications for sensing on all scales. In combination with levitation, this paves the way to full-scale control over the wavepacket dynamics of solid-state macroscopic quantum objects in linear and nonlinear systems. Optimal quantum control of an optically trapped nanoparticle in its ground state is demonstrated at room temperature, using Kalman filtering to track its quantum trajectory in real time.

The performance limits of hexagonal boron nitride as an insulator for scaled CMOS devices based on two-dimensional materials

Abstract: Complementary metal–oxide–semiconductor (CMOS) logic circuits at their ultimate scaling limits place extreme demands on the properties of all materials involved. The requirements for semiconductors are well explored and could possibly be satisfied by a number of layered two-dimensional (2D) materials, such as transition metal dichalcogenides or black phosphorus. The requirements for gate insulators are arguably even more challenging. At present, hexagonal boron nitride (hBN) is the most common 2D insulator and is widely considered to be the most promising gate insulator in 2D material-based transistors. Here we assess the material parameters and performance limits of hBN. We compare experimental and theoretical tunnel currents through ultrathin layers (equivalent oxide thickness of less than 1 nm) of hBN and other 2D gate insulators, including the ideal case of defect-free hBN. Though its properties make hBN a candidate for many applications in 2D nanoelectronics, excessive leakage currents lead us to conclude that hBN is unlikely to be suitable for use as a gate insulator in ultrascaled CMOS devices. This Perspective assesses the performance limits of hexagonal boron nitride when used as a gate insulator in complementary metal–oxide–semiconductor (CMOS) devices based on two-dimensional materials, concluding that due to excessive leakage currents, the material is unlikely to be suitable for use in ultrascaled CMOS devices.

Electron and photon reconstruction and identification with the CMS experiment at the CERN LHC

Abstract: The performance is presented of the reconstruction and identification algorithms for electrons and photons with the CMS experiment at the LHC. The reported results are based on proton-proton collision data collected at a center-of-mass energy of 13 TeV and recorded in 2016-2018, corresponding to an integrated luminosity of 136 fb$^{-1}$. Results obtained from lead-lead collision data collected at $\sqrt{s_\mathrm{NN}}=$ 5.02 TeV are also presented. Innovative techniques are used to reconstruct the electron and photon signals in the detector and to optimize the energy resolution. Events with electrons and photons in the final state are used to measure the energy resolution and energy scale uncertainty in the recorded events. The measured energy resolution for electrons produced in Z boson decays in proton-proton collision data ranges from 2 to 5%, depending on electron pseudorapidity and energy loss through bremsstrahlung in the detector material. The energy scale in the same range of energies is measured with an uncertainty smaller than 0.1 (0.3)% in the barrel (endcap) region in proton-proton collisions and better than 1 (3)% in the barrel (endcap) region in heavy ion collisions. The timing resolution for electrons from Z boson decays with the full 2016-2018 proton-proton collision data set is measured to be 200 ps.

Serverless Edge Computing: Vision and Challenges

Abstract: Born from a need for a pure “pay-per-use” model and highly scalable platform, the “Serverless” paradigm emerged and has the potential to become a dominant way of building cloud applications Although it was originally designed for cloud environments, Serverless is finding its position in the Edge Computing landscape, aiming to bring computational resources closer to the data source That is, Serverless is crossing cloud borders to assess its merits in Edge computing, whose principal partner will be the Internet of Things (IoT) applications This move sounds promising as Serverless brings particular benefits such as eliminating always-on services causing high electricity usage, for instance However, the community is still hesitant to uptake Serverless Edge Computing because of the cloud-driven design of current Serverless platforms, and distinctive characteristics of edge landscape and IoT applications In this paper, we evaluate both sides to shed light on the Serverless new territory Our in-depth analysis promotes a broad vision for bringing Serverless to the Edge Computing It also issues major challenges for Serverless to be met before entering Edge computing

The International Soil Moisture Network: Serving Earth system science for over a decade

Abstract: . In 2009, the International Soil Moisture Network (ISMN) was initiated as a community effort, funded by the European Space Agency, to serve as a centralised data hosting facility for globally available in situ soil moisture measurements ( Dorigo et al. , 2011 b , a ) . The ISMN brings together in situ soil moisture measurements collected and freely shared by a multitude of organisations, harmonises them in terms of units and sampling rates, applies advanced quality control, and stores them in a database. Users can freely retrieve the data from this database through an online web portal ( https://ismn.earth/en/ , last access: 28 October 2021). Meanwhile, the ISMN has evolved into the primary in situ soil moisture reference database worldwide, as evidenced by more than 3000 active users and over 1000 scientific publications referencing the data sets provided by the network. As of July 2021, the ISMN now contains the data of 71 networks and 2842 stations located all over the globe, with a time period spanning from 1952 to the present. The number of networks and stations covered by the ISMN is still growing, and approximately 70 % of the data sets contained in the database continue to be updated on a regular or irregular basis. The main scope of this paper is to inform readers about the evolution of the ISMN over the past decade, including a description of network and data set updates and quality control procedures. A comprehensive review of the existing literature making use of ISMN data is also provided in order to identify current limitations in functionality and data usage and to shape priorities for the next decade of operations of this unique community-based data repository.

International Consensus Based Review and Recommendations for Minimum Reporting Standards in Research on Transcutaneous Vagus Nerve Stimulation (Version 2020).

Abstract: Given its non-invasive nature, there is increasing interest in the use of transcutaneous vagus nerve stimulation (tVNS) across basic, translational and clinical research. Contemporaneously, tVNS can be achieved by stimulating either the auricular branch or the cervical bundle of the vagus nerve, referred to as transcutaneous auricular vagus nerve stimulation(VNS) and transcutaneous cervical VNS, respectively. In order to advance the field in a systematic manner, studies using these technologies need to adequately report sufficient methodological detail to enable comparison of results between studies, replication of studies, as well as enhancing study participant safety. We systematically reviewed the existing tVNS literature to evaluate current reporting practices. Based on this review, and consensus among participating authors, we propose a set of minimal reporting items to guide future tVNS studies. The suggested items address specific technical aspects of the device and stimulation parameters. We also cover general recommendations including inclusion and exclusion criteria for participants, outcome parameters and the detailed reporting of side effects. Furthermore, we review strategies used to identify the optimal stimulation parameters for a given research setting and summarize ongoing developments in animal research with potential implications for the application of tVNS in humans. Finally, we discuss the potential of tVNS in future research as well as the associated challenges across several disciplines in research and clinical practice.

Causes, impacts and patterns of disastrous river floods

Abstract: Disastrous floods have caused millions of fatalities in the twentieth century, tens of billions of dollars of direct economic loss each year and serious disruption to global trade. In this Review, we provide a synthesis of the atmospheric, land surface and socio-economic processes that produce river floods with disastrous consequences. Disastrous floods have often been caused by processes fundamentally different from those of non-disastrous floods, such as unusual but recurring atmospheric circulation patterns or failures of flood defences, which lead to high levels of damage because they are unexpected both by citizens and by flood managers. Past trends in economic flood impacts show widespread increases, mostly driven by economic and population growth. However, the number of fatalities and people affected has decreased since the mid-1990s because of risk reduction measures, such as improved risk awareness and structural flood defences. Disastrous flooding is projected to increase in many regions, particularly in Asia and Africa, owing to climate and socio-economic changes, although substantial uncertainties remain. Assessing the risk of disastrous river floods requires a deeper understanding of their distinct causes. Transdisciplinary research is needed to understand the potential for surprise in flood risk systems better and to operationalize risk management concepts that account for limited knowledge and unexpected developments. River floods have direct and indirect consequences for society, and can cause fatalities, displacement and economic loss. This Review examines the physical and socioeconomic causes and impacts of disastrous river flooding, and past and projected trends in their occurrence.

Optimal Application Deployment in Resource Constrained Distributed Edges

Abstract: The dramatically increasing of mobile applications make it convenient for users to complete complex tasks on their mobile devices. However, the latency brought by unstable wireless networks and the computation failures caused by constrained resources limit the development of mobile computing. A popular approach to solve this problem is to establish a mobile service provisioning system based on a mobile edge computing (MEC) paradigm. In the MEC paradigm, plenty of machines are placed at the edge of the network so that the performance of applications can be optimized by using the involved microservice instances deployed on them. In this paper, we explore the deployment problem of microserivce-based applications in the MEC environment and propose an approach to help to optimize the cost of application deployment with the constraints of resources and the requirement of performance. We conduct a series of experiments to evaluate the performance of our approach. The result shows that our approach can improve the average response time of mobile services.

Ti-based MOFs: New insights on the impact of ligand composition and hole scavengers on stability, charge separation and photocatalytic hydrogen evolution

Abstract: We synthesized a series of isostructural MIL-125-Ti with various terephthalic: amino-terephthalic acid ratios and evaluated their photostability and performance for photocatalytic hydrogen evolution in aqueous solutions with different hole scavengers. We demonstrate that the commonly used triethanolamine corroded the MOFs under photocatalytic conditions, in contrast to methanol. The combination of MIL-125-Ti and methanol outperformed the photocatalytic activity of NH2-MIL-125-Ti by 45 times under broad UV irradiation. Photoluminescence spectroscopy under simulated photocatalytic conditions and in solid-state as well as time-resolved emission studies reveal that the holes residing in the metal-oxo cluster can be effectively scavenged by methanol, leading to high HER activity, while the holes residing in the NH2-groups in the ligand favour charge recombination and are thus detrimental to the photocatalytic performance. The mixed-ligand MOFs follow a dual-excitation pathway, introducing new states and transitions. These results are expected to advance our understanding of MOF-based photocatalysis.

In honor of John Bissett: authoritative guidelines on molecular identification of Trichoderma

Abstract: Modern taxonomy has developed towards the establishment of global authoritative lists of species that assume the standardized principles of species recognition, at least in a given taxonomic group. However, in fungi, species delimitation is frequently subjective because it depends on the choice of a species concept and the criteria selected by a taxonomist. Contrary to it, identification of fungal species is expected to be accurate and precise because it should predict the properties that are required for applications or that are relevant in pathology. The industrial and plant-beneficial fungi from the genus Trichoderma (Hypocreales) offer a suitable model to address this collision between species delimitation and species identification. A few decades ago, Trichoderma diversity was limited to a few dozen species. The introduction of molecular evolutionary methods resulted in the exponential expansion of Trichoderma taxonomy, with up to 50 new species recognized per year. Here, we have reviewed the genus-wide taxonomy of Trichoderma and compiled a complete inventory of all Trichoderma species and DNA barcoding material deposited in public databases (the inventory is available at the website of the International Subcommission on Taxonomy of Trichoderma www.trichoderma.info ). Among the 375 species with valid names as of July 2020, 361 (96%) have been cultivated in vitro and DNA barcoded. Thus, we have developed a protocol for molecular identification of Trichoderma that requires analysis of the three DNA barcodes (ITS, tef1, and rpb2), and it is supported by online tools that are available on www.trichokey.info . We then used all the whole-genome sequenced (WGS) Trichoderma strains that are available in public databases to provide versatile practical examples of molecular identification, reveal shortcomings, and discuss possible ambiguities. Based on the Trichoderma example, this study shows why the identification of a fungal species is an intricate and laborious task that requires a background in mycology, molecular biological skills, training in molecular evolutionary analysis, and knowledge of taxonomic literature. We provide an in-depth discussion of species concepts that are applied in Trichoderma taxonomy, and conclude that these fungi are particularly suitable for the implementation of a polyphasic approach that was first introduced in Trichoderma taxonomy by John Bissett (1948–2020), whose work inspired the current study. We also propose a regulatory and unifying role of international commissions on the taxonomy of particular fungal groups. An important outcome of this work is the demonstration of an urgent need for cooperation between Trichoderma researchers to get prepared to the efficient use of the upcoming wave of Trichoderma genomic data.

Evidence for Higgs boson decay to a pair of muons

Abstract: Evidence for Higgs boson decay to a pair of muons is presented. This result combines searches in four exclusive categories targeting the production of the Higgs boson via gluon fusion, via vector boson fusion, in association with a vector boson, and in association with a top quark-antiquark pair. The analysis is performed using proton-proton collision data at $ \sqrt{s} $ = 13 TeV, corresponding to an integrated luminosity of 137 fb$^{−1}$, recorded by the CMS experiment at the CERN LHC. An excess of events over the back- ground expectation is observed in data with a significance of 3.0 standard deviations, where the expectation for the standard model (SM) Higgs boson with mass of 125.38 GeV is 2.5. The combination of this result with that from data recorded at $ \sqrt{s} $ = 7 and 8 TeV, corresponding to integrated luminosities of 5.1 and 19.7 fb$^{−1}$, respectively, increases both the expected and observed significances by 1%. The measured signal strength, relative to the SM prediction, is $ {1.19}_{-0.39}^{+0.40}{\left(\mathrm{stat}\right)}_{-0.14}^{+0.15}\left(\mathrm{syst}\right) $. This result constitutes the first evidence for the decay of the Higgs boson to second generation fermions and is the most precise measurement of the Higgs boson coupling to muons reported to date.[graphic not available: see fulltext]

Quantum phases driven by strong correlations

Abstract: It has long been thought that strongly correlated systems are adiabatically connected to their non-interacting counterpart. Recent developments have highlighted the fallacy of this traditional notion in a variety of settings. In this Review, we use a class of strongly correlated electron systems to illustrate the type of quantum phases and fluctuations that are created by strong correlations. Examples include quantum critical states that violate the Fermi liquid paradigm, unconventional superconductivity that goes beyond the Bardeen–Cooper–Schrieffer framework, and topological semimetals induced by the Kondo interaction. We assess the prospects for designing other exotic phases of matter by using alternative degrees of freedom or alternative interactions, and discuss the potential of these correlated states for quantum technology. Strong correlations may produce states of matter that do not have non-interacting counterparts, with new types of quantum criticality, superconductivity, and topological phases being recent highlights. This Review describes the physics underlying these correlated states and points to their potential for quantum applications.

Zero waste approach towards a sustainable waste management

Abstract: On 30 June 2020, young scholars presented & discussed their work in a virtual forum, as a special session organized by The 15th International Conference on Waste Management and Technology (June 28–30), 2020 Beijing China. The forum convened researchers and attendees approaching innovative aspects of waste management from a variety of perspectives and disciplines. While their presentations spanned topics as broad as the stakeholder coordination and as specific technological approach for rapid carbonization of agricultural waste, several conceptual threads could be traced across them.

Search for resonant and nonresonant new phenomena in high-mass dilepton final states at √s = 13 TeV

Abstract: A search is presented for physics beyond the standard model (SM) using electron or muon pairs with high invariant mass. A data set of proton-proton collisions collected by the CMS experiment at the LHC at s = 13 TeV from 2016 to 2018 corresponding to a total integrated luminosity of up to 140 fb−1 is analyzed. No significant deviation is observed with respect to the SM background expectations. Upper limits are presented on the ratio of the product of the production cross section and the branching fraction to dileptons of a new narrow resonance to that of the Z boson. These provide the most stringent lower limits to date on the masses for various spin-1 particles, spin-2 gravitons in the Randall-Sundrum model, as well as spin-1 mediators between the SM and dark matter particles. Lower limits on the ultraviolet cutoff parameter are set both for four-fermion contact interactions and for the Arkani-Hamed, Dimopoulos, and Dvali model with large extra dimensions. Lepton flavor universality is tested at the TeV scale for the first time by comparing the dimuon and dielectron mass spectra. No significant deviation from the SM expectation of unity is observed.

Giant spontaneous Hall effect in a nonmagnetic Weyl-Kondo semimetal.

Abstract: Nontrivial topology in condensed-matter systems enriches quantum states of matter to go beyond either the classification into metals and insulators in terms of conventional band theory or that of symmetry-broken phases by Landau's order parameter framework. So far, focus has been on weakly interacting systems, and little is known about the limit of strong electron correlations. Heavy fermion systems are a highly versatile platform to explore this regime. Here we report the discovery of a giant spontaneous Hall effect in the Kondo semimetal [Formula: see text] that is noncentrosymmetric but preserves time-reversal symmetry. We attribute this finding to Weyl nodes-singularities of the Berry curvature-that emerge in the immediate vicinity of the Fermi level due to the Kondo interaction. We stress that this phenomenon is distinct from the previously detected anomalous Hall effect in materials with broken time-reversal symmetry; instead, it manifests an extreme topological response that requires a beyond-perturbation-theory description of the previously proposed nonlinear Hall effect. The large magnitude of the effect in even tiny electric and zero magnetic fields as well as its robust bulk nature may aid the exploitation in topological quantum devices.

Phonon renormalization in reconstructed MoS2 moiré superlattices.

Abstract: In moire crystals formed by stacking van der Waals materials, surprisingly diverse correlated electronic phases and optical properties can be realized by a subtle change in the twist angle. Here, we discover that phonon spectra are also renormalized in MoS2 twisted bilayers, adding an insight to moire physics. Over a range of small twist angles, the phonon spectra evolve rapidly owing to ultra-strong coupling between different phonon modes and atomic reconstructions of the moire pattern. We develop a low-energy continuum model for phonons that overcomes the outstanding challenge of calculating the properties of large moire supercells and successfully captures the essential experimental observations. Remarkably, simple optical spectroscopy experiments can provide information on strain and lattice distortions in moire crystals with nanometre-size supercells. The model promotes a comprehensive and unified understanding of the structural, optical and electronic properties of moire superlattices.

Fungal taxonomy and sequence-based nomenclature.

Abstract: The identification and proper naming of microfungi, in particular plant, animal and human pathogens, remains challenging. Molecular identification is becoming the default approach for many fungal groups, and environmental metabarcoding is contributing an increasing amount of sequence data documenting fungal diversity on a global scale. This includes lineages represented only by sequence data. At present, these taxa cannot be formally described under the current nomenclature rules. By considering approaches used in bacterial taxonomy, we propose solutions for the nomenclature of taxa known only from sequences to facilitate consistent reporting and communication in the literature and public sequence repositories.