@article{9199, abstract = {We associate a certain tensor product lattice to any primitive integer lattice and ask about its typical shape. These lattices are related to the tangent bundle of Grassmannians and their study is motivated by Peyre's programme on "freeness" for rational points of bounded height on Fano varieties.}, author = {Browning, Timothy D and Horesh, Tal and Wilsch, Florian Alexander}, issn = {1944-7833}, journal = {Algebra & Number Theory}, number = {10}, pages = {2385--2407}, publisher = {Mathematical Sciences Publishers}, title = {{Equidistribution and freeness on Grassmannians}}, doi = {10.2140/ant.2022.16.2385}, volume = {16}, year = {2022}, } @article{22531, abstract = {To make sound decisions in the face of climate change, government agencies, policymakers and private stakeholders require suitable climate information on local to regional scales. In Switzerland, the development of climate change scenarios is strongly linked to the climate adaptation strategy of the Confederation. The current climate scenarios for Switzerland CH2018 - released in form of six user-oriented products - were the result of an intensive collaboration between academia and administration under the umbrella of the National Centre for Climate Services (NCCS), accounting for user needs and stakeholder dialogues from the beginning. A rigorous scientific concept ensured consistency throughout the various analysis steps of the EURO-CORDEX projections and a common procedure on how to extract robust results and deal with associated uncertainties. The main results show that Switzerland’s climate will face dry summers, heavy precipitation, more hot days and snow-scarce winters. Approximately half of these changes could be alleviated by mid-century through strong global mitigation efforts. A comprehensive communication concept ensured that the results were rolled out and distilled in specific user-oriented communication measures to increase their uptake and to make them actionable. A narrative approach with four fictitious persons was used to communicate the key messages to the general public. Three years after the release, the climate scenarios have proven to be an indispensable information basis for users in climate adaptation and for downstream applications. Potential for extensions and updates has been identified since then and will shape the concept and planning of the next scenario generation in Switzerland.}, author = {Fischer, A.M. and Strassmann, K.M. and Croci-Maspoli, M. and Hama, A.M. and Knutti, R. and Kotlarski, S. and Schär, C. and Schnadt Poberaj, C. and Ban, N. and Bavay, M. and Beyerle, U. and Bresch, D.N. and Brönnimann, S. and Burlando, P. and Casanueva, A. and Fatichi, Simone and Feigenwinter, I. and Fischer, E.M. and Hirschi, M. and Liniger, M.A. and Marty, C. and Medhaug, I. and Peleg, N. and Pickl, M. and Raible, C.C. and Rajczak, J. and Rössler, O. and Scherrer, S.C. and Schwierz, C. and Seneviratne, S.I. and Skelton, M. and Sørland, S.L. and Spirig, C. and Tschurr, F. and Zeder, J. and Zubler, E.M.}, issn = {2405-8807}, journal = {Climate Services}, keywords = {Climate scenario, Climate services, Switzerland, EURO-CORDEX, User-oriented communication, National projections}, publisher = {Elsevier}, title = {{Climate Scenarios for Switzerland CH2018 – Approach and Implications}}, doi = {10.1016/j.cliser.2022.100288}, volume = {26}, year = {2022}, } @article{22519, abstract = {Glacier health across High Mountain Asia (HMA) is highly heterogeneous and strongly governed by regional climate, which is variably influenced by monsoon dynamics and the westerlies. We explore four decades of glacier energy and mass balance at three climatically distinct sites across HMA by utilising a detailed land surface model driven by bias-corrected Weather Research and Forecasting meteorological forcing. All three glaciers have experienced long-term mass losses (ranging from −0.04 ± 0.09 to −0.59 ± 0.20 m w.e. a−1) consistent with widespread warming across the region. However, complex and contrasting responses of glacier energy and mass balance to the patterns of the Indian Summer Monsoon were evident, largely driven by the role snowfall timing, amount and phase. A later monsoon onset generates less total snowfall to the glacier in the southeastern Tibetan Plateau during May–June, augmenting net shortwave radiation and affecting annual mass balance (−0.5 m w.e. on average compared to early onset years). Conversely, timing of the monsoon’s arrival has limited impact for the Nepalese Himalaya which is more strongly governed by the temperature and snowfall amount during the core monsoon season. In the arid central Tibetan Plateau, a later monsoon arrival results in a 40 mm (58%) increase of May–June snowfall on average compared to early onset years, likely driven by the greater interaction of westerly storm events. Meanwhile, a late monsoon cessation at this site sees an average 200 mm (192%) increase in late summer precipitation due to monsoonal storms. A trend towards weaker intensity monsoon conditions in recent decades, combined with long-term warming patterns, has produced predominantly negative glacier mass balances for all sites (up to 1 m w.e. more mass loss in the Nepalese Himalaya compared to strong monsoon intensity years) but sub-regional variability in monsoon timing can additionally complicate this response.}, author = {Shaw, T E and Miles, E S and Chen, D and Jouberton, A and Kneib, M and Fugger, S and Ou, T and Lai, H-W and Fujita, K and Yang, W and Fatichi, Simone and Pellicciotti, F}, issn = {1748-9326}, journal = {Environmental Research Letters}, keywords = {Glacier, Long-term mass balance, Monsoon, Snowfall}, number = {10}, publisher = {IOP Publishing}, title = {{Multi-decadal monsoon characteristics and glacier response in High Mountain Asia}}, doi = {10.1088/1748-9326/ac9008}, volume = {17}, year = {2022}, } @article{22502, abstract = {The Indian and East Asian summer monsoons shape the melt and accumulation patterns of glaciers in High Mountain Asia in complex ways due to the interaction of persistent cloud cover, large temperature ranges, high atmospheric water content and high precipitation rates. Glacier energy- and mass-balance modelling using in situ measurements offers insights into the ways in which surface processes are shaped by climatic regimes. In this study, we use a full energy- and mass-balance model and seven on-glacier automatic weather station datasets from different parts of the Central and Eastern Himalaya to investigate how monsoon conditions influence the glacier surface energy and mass balance. In particular, we look at how debris-covered and debris-free glaciers respond differently to monsoonal conditions. The radiation budget primarily controls the melt of clean-ice glaciers, but turbulent fluxes play an important role in modulating the melt energy on debris-covered glaciers. The sensible heat flux decreases during core monsoon, but the latent heat flux cools the surface due to evaporation of liquid water. This interplay of radiative and turbulent fluxes causes debris-covered glacier melt rates to stay almost constant through the different phases of the monsoon. Ice melt under thin debris, on the other hand, is amplified by both the dark surface and the turbulent fluxes, which intensify melt during monsoon through surface heating and condensation. Pre-monsoon snow cover can considerably delay melt onset and have a strong impact on the seasonal mass balance. Intermittent monsoon snow cover lowers the melt rates at high elevation. This work is fundamental to the understanding of the present and future Himalayan cryosphere and water budget, while informing and motivating further glacier- and catchment-scale research using process-based models.The radiation budget primarily controls the melt of clean-ice glaciers, but turbulent fluxes play an important role in modulating the melt energy on debris-covered glaciers. The sensible heat flux decreases during core monsoon, but the latent heat flux cools the surface due to evaporation of liquid water. This interplay of radiative and turbulent fluxes causes debris-covered glacier melt rates to stay almost constant through the different phases of the monsoon. Ice melt under thin debris, on the other hand, is amplified by both the dark surface and the turbulent fluxes, which intensify melt during monsoon through surface heating and condensation. Pre-monsoon snow cover can considerably delay melt onset and have a strong impact on the seasonal mass balance. Intermittent monsoon snow cover lowers the melt rates at high elevation. This work is fundamental to the understanding of the present and future Himalayan cryosphere and water budget, while informing and motivating further glacier- and catchment-scale research using process-based models.}, author = {Fugger, Stefan and Fyffe, Catriona L. and Fatichi, Simone and Miles, Evan and McCarthy, Michael and Shaw, Thomas E. and Ding, Baohong and Yang, Wei and Wagnon, Patrick and Immerzeel, Walter and Liu, Qiao and Pellicciotti, Francesca}, issn = {1994-0424}, journal = {The Cryosphere}, number = {5}, pages = {1631--1652}, publisher = {Copernicus Publications}, title = {{Understanding monsoon controls on the energy and mass balance of glaciers in the Central and Eastern Himalaya}}, doi = {10.5194/tc-16-1631-2022}, volume = {16}, year = {2022}, } @article{22537, abstract = {Urban heat islands (UHIs) are a widely studied phenomenon, while research on urban-rural differences in humidity, the so called urban dry or moisture islands (UDIs, UMIs), is less common and a large-scale quantification of the seasonal and diurnal patterns of the UDI is still lacking. However, quantification of the UDI/UMI effect is essential to understand the impacts of humidity on outdoor thermal comfort, building energy consumption, and urban ecology in cities worldwide. Here, we use a set of globally distributed air temperature and humidity measurements (1089 stations) to quantify diurnal and seasonal patterns of UHI and UDI resulting from rapid urbanization over many regions of the world. The terms ‘absolute UDI’ and ‘relative UDI’ are defined, which quantify urban–rural differences in actual and relative humidity metrics, respectively. Results show that absolute UDI is largest during daytime with the peak humidity decrease in urban areas occurring during late afternoon hours. In contrast, relative UDI is largest during night and the peak urban relative humidity (RH) decrease and vapor pressure deficit (VPD) increase occurs in the late evening hours with values of around −10% to −11% for RH and 2.9–3.6 hPa for VPD between 20–00 local time during summer. Relative and absolute UDIs are largest during the warm season, except for daytime RH UDI, which does not show any seasonal pattern. In agreement with literature, canopy air UHI is shown to be a nighttime phenomenon, which is larger during summer than winter. Relative UDI is predominantly caused by changes in actual humidity during day and UHI during nighttime.}, author = {Meili, Naika and Paschalis, Athanasios and Manoli, Gabriele and Fatichi, Simone}, issn = {1748-9326}, journal = {Environmental Research Letters}, keywords = {Urban dry island, Urban moisture island, Urban heat island, Urban climate, Urbanization effects, Humidity}, number = {5}, publisher = {IOP Publishing}, title = {{Diurnal and seasonal patterns of global urban dry islands}}, doi = {10.1088/1748-9326/ac68f8}, volume = {17}, year = {2022}, } @article{22555, abstract = {The current Chilean megadrought has led to acute water shortages in central Chile since 2010.Glaciers have provided vital fresh water to the region's rivers, but the quantity, timing and sustainability ofthat provision remain unclear. Here we combine in-situ, remote sensing and climate reanalysis data to showthat from 2010 to 2018 during the megadrought, unsustainable imbalance ablation of glaciers (ablation notbalanced by new snowfall) strongly buffered the late-summer discharge of the Maipo River, a primary sourceof water to Santiago. If there had been no glaciers, water availability would have been reduced from Decemberthrough May, with a 31 ± 19% decrease during March. Our results indicate that while the annual contributionsof imbalance ablation to river discharge during the megadrought have been small compared to those fromprecipitation and sustainable balance ablation, they have nevertheless been a substantial input to a hydrologicalsystem that was already experiencing high water stress. The water-equivalent volume of imbalance ablationgenerated in the Maipo Basin between 2010 and 2018 was 740 × 10 6 m 3 (19 ± 12 mm yr −1), approximately 3.4times the capacity of the basin's El Yeso Reservoir. This is equivalent to 14% of Santiago's potable water use inthat time, while total glacier ablation was equivalent to 59%. We show that glacier retreat will exacerbate riverdischarge deficits and further jeopardize water availability in central Chile if precipitation deficits endure, andconjecture that these effects will be amplified by climatic warming.}, author = {McCarthy, Michael and Meier, Fabienne and Fatichi, Simone and Stocker, Benjamin D. and Shaw, Thomas E. and Miles, Evan and Dussaillant, Inés and Pellicciotti, Francesca}, issn = {2328-4277}, journal = {Earth's Future}, number = {10}, publisher = {American Geophysical Union}, title = {{Glacier contributions to river discharge during the current chilean megadrought}}, doi = {10.1029/2022ef002852}, volume = {10}, year = {2022}, } @article{22564, abstract = {It is well known that cities increase air and surface temperatures compared to their rural surroundings, the so-called urban heat island (UHI) effect. However, the associated changes in atmospheric humidity (also known as urban dry island, UDI) and convection triggering remain largely unexplored and it is still unclear how urban modifications of the surface energy budget Influence the diurnal evolution of temperature and humidity in the Atmospheric Boundary Layer (ABL) and ultimately control the initiation of convective clouds. Here we quantify the impact of different urban settings and free atmospheric conditions on UHI, UDI, and convection triggers by means of a zero-order model of the ABL. Specifically, we derive an approximate solution for urban-rural changes in surface energy fluxes and ABL potential temperature and humidity and we investigate the crossing between the ABL height and the lifting condensation level (LCL) which is a proxy for the triggering of convective clouds. We show that urban areas are generally warmer and drier, thus causing an increase in both ABL and LCL heights. However, the response of the ABL-LCL crossing to surface conditions is non-linear and there exists a range of free atmosphere conditions for which changes in imperviousness can impact convective clouds.}, author = {Chiu, Clinton T.F. and Wang, Kai and Paschalis, Athanasios and Erfani, Tohid and Peleg, Nadav and Fatichi, Simone and Theeuwes, Natalie and Manoli, Gabriele}, issn = {2212-0955}, journal = {Urban Climate}, keywords = {Urban heat island, Urban dry island, Boundary layer, Convective clouds, Analytical model}, publisher = {Elsevier}, title = {{An analytical approximation of urban heat and dry islands and their impact on convection triggering}}, doi = {10.1016/j.uclim.2022.101346}, volume = {46}, year = {2022}, } @article{10827, abstract = {Titanium dioxide has been extensively studied in the rutile or anatase phase, while its high-pressure phases are less well-understood, despite that many are thought to have interesting optical, mechanical, and electrochemical properties. First-principles methods, such as density functional theory (DFT), are often used to compute the enthalpies of TiO2 phases at 0 K, but they are expensive and, thus, impractical for long time scale and large system-size simulations at finite temperatures. On the other hand, cheap empirical potentials fail to capture the relative stabilities of various polymorphs. To model the thermodynamic behaviors of ambient and high-pressure phases of TiO2, we design an empirical model as a baseline and then train a machine learning potential based on the difference between the DFT data and the empirical model. This so-called Δ-learning potential contains long-range electrostatic interactions and predicts the 0 K enthalpies of stable TiO2 phases that are in good agreement with DFT. We construct a pressure–temperature phase diagram of TiO2 in the range 0 < P < 70 GPa and 100 < T < 1500 K. We then simulate dynamic phase transition processes by compressing anatase at different temperatures. At 300 K, we predominantly observe an anatase-to-baddeleyite transformation at about 20 GPa via a martensitic two-step mechanism with a highly ordered and collective atomic motion. At 2000 K, anatase can transform into cotunnite around 45–55 GPa in a thermally activated and probabilistic manner, accompanied by diffusive movement of oxygen atoms. The pressures computed for these transitions show good agreement with experiments. Our results shed light on how to synthesize and stabilize high-pressure TiO2 phases, and our method is generally applicable to other functional materials with multiple polymorphs.}, author = {Lee, Jacob G. and Pickard, Chris J. and Cheng, Bingqing}, issn = {1089-7690}, journal = {The Journal of chemical physics}, number = {7}, publisher = {AIP Publishing}, title = {{High-pressure phase behaviors of titanium dioxide revealed by a Δ-learning potential}}, doi = {10.1063/5.0079844}, volume = {156}, year = {2022}, } @article{12128, abstract = {We introduce a machine-learning (ML) framework for high-throughput benchmarking of diverse representations of chemical systems against datasets of materials and molecules. The guiding principle underlying the benchmarking approach is to evaluate raw descriptor performance by limiting model complexity to simple regression schemes while enforcing best ML practices, allowing for unbiased hyperparameter optimization, and assessing learning progress through learning curves along series of synchronized train-test splits. The resulting models are intended as baselines that can inform future method development, in addition to indicating how easily a given dataset can be learnt. Through a comparative analysis of the training outcome across a diverse set of physicochemical, topological and geometric representations, we glean insight into the relative merits of these representations as well as their interrelatedness.}, author = {Poelking, Carl and Faber, Felix A and Cheng, Bingqing}, issn = {2632-2153}, journal = {Machine Learning: Science and Technology}, keywords = {Artificial Intelligence, Human-Computer Interaction, Software}, number = {4}, publisher = {IOP Publishing}, title = {{BenchML: An extensible pipelining framework for benchmarking representations of materials and molecules at scale}}, doi = {10.1088/2632-2153/ac4d11}, volume = {3}, year = {2022}, } @article{12249, abstract = {The chemical potential of a component in a solution is defined as the free energy change as the amount of that component changes. Computing this fundamental thermodynamic property from atomistic simulations is notoriously difficult because of the convergence issues involved in free energy methods and finite size effects. This Communication presents the so-called S0 method, which can be used to obtain chemical potentials from static structure factors computed from equilibrium molecular dynamics simulations under the isothermal–isobaric ensemble. This new method is demonstrated on the systems of binary Lennard-Jones particles, urea–water mixtures, a NaCl aqueous solution, and a high-pressure carbon–hydrogen mixture. }, author = {Cheng, Bingqing}, issn = {1089-7690}, journal = {The Journal of Chemical Physics}, keywords = {Physical and Theoretical Chemistry, General Physics and Astronomy}, number = {12}, publisher = {AIP Publishing}, title = {{Computing chemical potentials of solutions from structure factors}}, doi = {10.1063/5.0107059}, volume = {157}, year = {2022}, } @article{11937, abstract = {Most experimentally known high-pressure ice phases have a body-centred cubic (bcc) oxygen lattice. Our large-scale molecular-dynamics simulations with a machine-learning potential indicate that, amongst these bcc ice phases, ices VII, VII′ and X are the same thermodynamic phase under different conditions, whereas superionic ice VII″ has a first-order phase boundary with ice VII′. Moreover, at about 300 GPa, the transformation between ice X and the Pbcm phase has a sharp structural change but no apparent activation barrier, whilst at higher pressures the barrier gradually increases. Our study thus clarifies the phase behaviour of the high-pressure ices and reveals peculiar solid–solid transition mechanisms not known in other systems.}, author = {Reinhardt, Aleks and Bethkenhagen, Mandy and Coppari, Federica and Millot, Marius and Hamel, Sebastien and Cheng, Bingqing}, issn = {2041-1723}, journal = {Nature Communications}, publisher = {Springer Nature}, title = {{Thermodynamics of high-pressure ice phases explored with atomistic simulations}}, doi = {10.1038/s41467-022-32374-1}, volume = {13}, year = {2022}, } @article{9695, abstract = {Real-world data typically contain a large number of features that are often heterogeneous in nature, relevance, and also units of measure. When assessing the similarity between data points, one can build various distance measures using subsets of these features. Using the fewest features but still retaining sufficient information about the system is crucial in many statistical learning approaches, particularly when data are sparse. We introduce a statistical test that can assess the relative information retained when using two different distance measures, and determine if they are equivalent, independent, or if one is more informative than the other. This in turn allows finding the most informative distance measure out of a pool of candidates. The approach is applied to find the most relevant policy variables for controlling the Covid-19 epidemic and to find compact yet informative representations of atomic structures, but its potential applications are wide ranging in many branches of science.}, author = {Glielmo, Aldo and Zeni, Claudio and Cheng, Bingqing and Csanyi, Gabor and Laio, Alessandro}, issn = {2752-6542}, journal = {PNAS Nexus}, number = {2}, publisher = {Oxford University Press}, title = {{Ranking the information content of distance measures}}, doi = {10.1093/pnasnexus/pgac039}, volume = {1}, year = {2022}, } @article{11700, abstract = {This paper contains two contributions in the study of optimal transport on metric graphs. Firstly, we prove a Benamou–Brenier formula for the Wasserstein distance, which establishes the equivalence of static and dynamical optimal transport. Secondly, in the spirit of Jordan–Kinderlehrer–Otto, we show that McKean–Vlasov equations can be formulated as gradient flow of the free energy in the Wasserstein space of probability measures. The proofs of these results are based on careful regularisation arguments to circumvent some of the difficulties arising in metric graphs, namely, branching of geodesics and the failure of semi-convexity of entropy functionals in the Wasserstein space.}, author = {Erbar, Matthias and Forkert, Dominik L and Maas, Jan and Mugnolo, Delio}, issn = {1556-181X}, journal = {Networks and Heterogeneous Media}, number = {5}, pages = {687--717}, publisher = {AIMS}, title = {{Gradient flow formulation of diffusion equations in the Wasserstein space over a metric graph}}, doi = {10.3934/nhm.2022023}, volume = {17}, year = {2022}, } @inproceedings{12299, abstract = {Transfer learning is a classic paradigm by which models pretrained on large “upstream” datasets are adapted to yield good results on “downstream” specialized datasets. Generally, more accurate models on the “upstream” dataset tend to provide better transfer accuracy “downstream”. In this work, we perform an in-depth investigation of this phenomenon in the context of convolutional neural networks (CNNs) trained on the ImageNet dataset, which have been pruned-that is, compressed by sparsifiying their connections. We consider transfer using unstructured pruned models obtained by applying several state-of-the-art pruning methods, including magnitude-based, second-order, regrowth, lottery-ticket, and regularization approaches, in the context of twelve standard transfer tasks. In a nutshell, our study shows that sparse models can match or even outperform the transfer performance of dense models, even at high sparsities, and, while doing so, can lead to significant inference and even training speedups. At the same time, we observe and analyze significant differences in the behaviour of different pruning methods. The code is available at: https://github.com/IST-DASLab/sparse-imagenet-transfer.}, author = {Iofinova, Eugenia B and Peste, Elena-Alexandra and Kurtz, Mark and Alistarh, Dan-Adrian}, booktitle = {2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition}, issn = {2575-7075}, location = {New Orleans, LA, United States}, pages = {12256--12266}, publisher = {IEEE}, title = {{How well do sparse ImageNet models transfer?}}, doi = {10.1109/cvpr52688.2022.01195}, year = {2022}, } @inproceedings{12161, abstract = {We introduce LIMES, a new method for learning with non-stationary streaming data, inspired by the recent success of meta-learning. The main idea is not to attempt to learn a single classifier that would have to work well across all occurring data distributions, nor many separate classifiers, but to exploit a hybrid strategy: we learn a single set of model parameters from which a specific classifier for any specific data distribution is derived via classifier adaptation. Assuming a multiclass classification setting with class-prior shift, the adaptation step can be performed analytically with only the classifier’s bias terms being affected. Another contribution of our work is an extrapolation step that predicts suitable adaptation parameters for future time steps based on the previous data. In combination, we obtain a lightweight procedure for learning from streaming data with varying class distribution that adds no trainable parameters and almost no memory or computational overhead compared to training a single model. Experiments on a set of exemplary tasks using Twitter data show that LIMES achieves higher accuracy than alternative approaches, especially with respect to the relevant real-world metric of lowest within-day accuracy.}, author = {Tomaszewska, Paulina and Lampert, Christoph}, booktitle = {26th International Conference on Pattern Recognition}, issn = {2831-7475}, location = {Montreal, Canada}, pages = {2128--2134}, publisher = {IEEE}, title = {{Lightweight conditional model extrapolation for streaming data under class-prior shift}}, doi = {10.1109/icpr56361.2022.9956195}, volume = {2022}, year = {2022}, } @unpublished{11366, abstract = {Adversarial training (i.e., training on adversarially perturbed input data) is a well-studied method for making neural networks robust to potential adversarial attacks during inference. However, the improved robustness does not come for free but rather is accompanied by a decrease in overall model accuracy and performance. Recent work has shown that, in practical robot learning applications, the effects of adversarial training do not pose a fair trade-off but inflict a net loss when measured in holistic robot performance. This work revisits the robustness-accuracy trade-off in robot learning by systematically analyzing if recent advances in robust training methods and theory in conjunction with adversarial robot learning can make adversarial training suitable for real-world robot applications. We evaluate a wide variety of robot learning tasks ranging from autonomous driving in a high-fidelity environment amenable to sim-to-real deployment, to mobile robot gesture recognition. Our results demonstrate that, while these techniques make incremental improvements on the trade-off on a relative scale, the negative side-effects caused by adversarial training still outweigh the improvements by an order of magnitude. We conclude that more substantial advances in robust learning methods are necessary before they can benefit robot learning tasks in practice.}, author = {Lechner, Mathias and Amini, Alexander and Rus, Daniela and Henzinger, Thomas A}, booktitle = {arXiv}, title = {{Revisiting the adversarial robustness-accuracy tradeoff in robot learning}}, doi = {10.48550/arXiv.2204.07373}, year = {2022}, } @inproceedings{12300, abstract = {Distributed Key Generation (DKG) is a technique to bootstrap threshold cryptosystems without a trusted third party and is a building block to decentralized protocols such as randomness beacons, threshold signatures, and general multiparty computation. Until recently, DKG protocols have assumed the synchronous model and thus are vulnerable when their underlying network assumptions do not hold. The recent advancements in asynchronous DKG protocols are insufficient as they either have poor efficiency or limited functionality, resulting in a lack of concrete implementations. In this paper, we present a simple and concretely efficient asynchronous DKG (ADKG) protocol. In a network of n nodes, our ADKG protocol can tolerate up to t