@article{9162, abstract = {Active navigation relies on effectively extracting information from the surrounding environment, and often features the tracking of gradients of a relevant signal—such as the concentration of molecules. Microfluidic networks of closed pathways pose the challenge of determining the shortest exit pathway, which involves the proper local decision-making at each bifurcating junction. Here, we focus on the basic decision faced at a T-junction by a microscopic particle, which orients among possible paths via its sensing of a diffusible substance's concentration. We study experimentally the navigation of colloidal particles following concentration gradients by diffusiophoresis. We treat the situation as a mean first passage time (MFPT) problem that unveils the important role of a separatrix in the concentration field to determine the statistics of path taking. Further, we use numerical experiments to study different strategies, including biomimetic ones such as run and tumble or Markovian chemotactic migration. The discontinuity in the MFPT at the junction makes it remarkably difficult for microscopic agents to follow the shortest path, irrespective of adopted navigation strategy. In contrast, increasing the size of the sensing agents improves the efficiency of short-path taking by harvesting information on a larger scale. It inspires the development of a run-and-whirl dynamics that takes advantage of the mathematical properties of harmonic functions to emulate particles beyond their own size.}, author = {Gandhi, Tanvi and Mac Huang, Jinzi and Aubret, Antoine and Li, Yaocheng and Ramananarivo, Sophie and Vergassola, Massimo and Palacci, Jérémie A}, issn = {2469-990X}, journal = {Physical Review Fluids}, number = {10}, publisher = {American Physical Society}, title = {{Decision-making at a T-junction by gradient-sensing microscopic agents}}, doi = {10.1103/physrevfluids.5.104202}, volume = {5}, year = {2020}, } @article{9164, author = {Speck, Thomas and Tailleur, Julien and Palacci, Jérémie A}, issn = {1367-2630}, journal = {New Journal of Physics}, keywords = {General Physics and Astronomy}, number = {6}, publisher = {IOP Publishing}, title = {{Focus on active colloids and nanoparticles}}, doi = {10.1088/1367-2630/ab90d9}, volume = {22}, year = {2020}, } @article{9194, abstract = {Quantum transduction, the process of converting quantum signals from one form of energy to another, is an important area of quantum science and technology. The present perspective article reviews quantum transduction between microwave and optical photons, an area that has recently seen a lot of activity and progress because of its relevance for connecting superconducting quantum processors over long distances, among other applications. Our review covers the leading approaches to achieving such transduction, with an emphasis on those based on atomic ensembles, opto-electro-mechanics, and electro-optics. We briefly discuss relevant metrics from the point of view of different applications, as well as challenges for the future.}, author = {Lauk, Nikolai and Sinclair, Neil and Barzanjeh, Shabir and Covey, Jacob P and Saffman, Mark and Spiropulu, Maria and Simon, Christoph}, issn = {2058-9565}, journal = {Quantum Science and Technology}, number = {2}, publisher = {IOP Publishing}, title = {{Perspectives on quantum transduction}}, doi = {10.1088/2058-9565/ab788a}, volume = {5}, year = {2020}, } @article{9195, abstract = {Quantum information technology based on solid state qubits has created much interest in converting quantum states from the microwave to the optical domain. Optical photons, unlike microwave photons, can be transmitted by fiber, making them suitable for long distance quantum communication. Moreover, the optical domain offers access to a large set of very well‐developed quantum optical tools, such as highly efficient single‐photon detectors and long‐lived quantum memories. For a high fidelity microwave to optical transducer, efficient conversion at single photon level and low added noise is needed. Currently, the most promising approaches to build such systems are based on second‐order nonlinear phenomena such as optomechanical and electro‐optic interactions. Alternative approaches, although not yet as efficient, include magneto‐optical coupling and schemes based on isolated quantum systems like atoms, ions, or quantum dots. Herein, the necessary theoretical foundations for the most important microwave‐to‐optical conversion experiments are provided, their implementations are described, and the current limitations and future prospects are discussed.}, author = {Lambert, Nicholas J. and Rueda Sanchez, Alfredo R and Sedlmeir, Florian and Schwefel, Harald G. L.}, issn = {2511-9044}, journal = {Advanced Quantum Technologies}, number = {1}, publisher = {Wiley}, title = {{Coherent conversion between microwave and optical photons - An overview of physical implementations}}, doi = {10.1002/qute.201900077}, volume = {3}, year = {2020}, } @article{9196, abstract = {In order to provide a local description of a regular function in a small neighbourhood of a point x, it is sufficient by Taylor’s theorem to know the value of the function as well as all of its derivatives up to the required order at the point x itself. In other words, one could say that a regular function is locally modelled by the set of polynomials. The theory of regularity structures due to Hairer generalizes this observation and provides an abstract setup, which in the application to singular SPDE extends the set of polynomials by functionals constructed from, e.g., white noise. In this context, the notion of Taylor polynomials is lifted to the notion of so-called modelled distributions. The celebrated reconstruction theorem, which in turn was inspired by Gubinelli’s \textit {sewing lemma}, is of paramount importance for the theory. It enables one to reconstruct a modelled distribution as a true distribution on Rd which is locally approximated by this extended set of models or “monomials”. In the original work of Hairer, the error is measured by means of Hölder norms. This was then generalized to the whole scale of Besov spaces by Hairer and Labbé. It is the aim of this work to adapt the analytic part of the theory of regularity structures to the scale of Triebel–Lizorkin spaces.}, author = {Hensel, Sebastian and Rosati, Tommaso}, issn = {1730-6337}, journal = {Studia Mathematica}, keywords = {General Mathematics}, number = {3}, pages = {251--297}, publisher = {Instytut Matematyczny}, title = {{Modelled distributions of Triebel–Lizorkin type}}, doi = {10.4064/sm180411-11-2}, volume = {252}, year = {2020}, } @article{9197, abstract = {In this paper we introduce and study all-pay bidding games, a class of two player, zero-sum games on graphs. The game proceeds as follows. We place a token on some vertex in the graph and assign budgets to the two players. Each turn, each player submits a sealed legal bid (non-negative and below their remaining budget), which is deducted from their budget and the highest bidder moves the token onto an adjacent vertex. The game ends once a sink is reached, and Player 1 pays Player 2 the outcome that is associated with the sink. The players attempt to maximize their expected outcome. Our games model settings where effort (of no inherent value) needs to be invested in an ongoing and stateful manner. On the negative side, we show that even in simple games on DAGs, optimal strategies may require a distribution over bids with infinite support. A central quantity in bidding games is the ratio of the players budgets. On the positive side, we show a simple FPTAS for DAGs, that, for each budget ratio, outputs an approximation for the optimal strategy for that ratio. We also implement it, show that it performs well, and suggests interesting properties of these games. Then, given an outcome c, we show an algorithm for finding the necessary and sufficient initial ratio for guaranteeing outcome c with probability 1 and a strategy ensuring such. Finally, while the general case has not previously been studied, solving the specific game in which Player 1 wins iff he wins the first two auctions, has been long stated as an open question, which we solve.}, author = {Avni, Guy and Ibsen-Jensen, Rasmus and Tkadlec, Josef}, isbn = {9781577358350}, issn = {2374-3468}, journal = {Proceedings of the AAAI Conference on Artificial Intelligence}, location = {New York, NY, United States}, number = {02}, pages = {1798--1805}, publisher = {Association for the Advancement of Artificial Intelligence}, title = {{All-pay bidding games on graphs}}, doi = {10.1609/aaai.v34i02.5546}, volume = {34}, year = {2020}, } @inproceedings{9198, abstract = {The optimization of multilayer neural networks typically leads to a solution with zero training error, yet the landscape can exhibit spurious local minima and the minima can be disconnected. In this paper, we shed light on this phenomenon: we show that the combination of stochastic gradient descent (SGD) and over-parameterization makes the landscape of multilayer neural networks approximately connected and thus more favorable to optimization. More specifically, we prove that SGD solutions are connected via a piecewise linear path, and the increase in loss along this path vanishes as the number of neurons grows large. This result is a consequence of the fact that the parameters found by SGD are increasingly dropout stable as the network becomes wider. We show that, if we remove part of the neurons (and suitably rescale the remaining ones), the change in loss is independent of the total number of neurons, and it depends only on how many neurons are left. Our results exhibit a mild dependence on the input dimension: they are dimension-free for two-layer networks and depend linearly on the dimension for multilayer networks. We validate our theoretical findings with numerical experiments for different architectures and classification tasks.}, author = {Shevchenko, Alexander and Mondelli, Marco}, booktitle = {Proceedings of the 37th International Conference on Machine Learning}, pages = {8773--8784}, publisher = {ML Research Press}, title = {{Landscape connectivity and dropout stability of SGD solutions for over-parameterized neural networks}}, volume = {119}, year = {2020}, } @inproceedings{9202, abstract = {We propose a novel hybridization method for stability analysis that over-approximates nonlinear dynamical systems by switched systems with linear inclusion dynamics. We observe that existing hybridization techniques for safety analysis that over-approximate nonlinear dynamical systems by switched affine inclusion dynamics and provide fixed approximation error, do not suffice for stability analysis. Hence, we propose a hybridization method that provides a state-dependent error which converges to zero as the state tends to the equilibrium point. The crux of our hybridization computation is an elegant recursive algorithm that uses partial derivatives of a given function to obtain upper and lower bound matrices for the over-approximating linear inclusion. We illustrate our method on some examples to demonstrate the application of the theory for stability analysis. In particular, our method is able to establish stability of a nonlinear system which does not admit a polynomial Lyapunov function.}, author = {Garcia Soto, Miriam and Prabhakar, Pavithra}, booktitle = {2020 IEEE Real-Time Systems Symposium}, issn = {2576-3172}, location = {Houston, TX, USA }, pages = {244--256}, publisher = {IEEE}, title = {{Hybridization for stability verification of nonlinear switched systems}}, doi = {10.1109/RTSS49844.2020.00031}, year = {2020}, } @article{9208, abstract = {Bending-active structures are able to efficiently produce complex curved shapes from flat panels. The desired deformation of the panels derives from the proper selection of their elastic properties. Optimized panels, called FlexMaps, are designed such that, once they are bent and assembled, the resulting static equilibrium configuration matches a desired input 3D shape. The FlexMaps elastic properties are controlled by locally varying spiraling geometric mesostructures, which are optimized in size and shape to match specific bending requests, namely the global curvature of the target shape. The design pipeline starts from a quad mesh representing the input 3D shape, which defines the edge size and the total amount of spirals: every quad will embed one spiral. Then, an optimization algorithm tunes the geometry of the spirals by using a simplified pre-computed rod model. This rod model is derived from a non-linear regression algorithm which approximates the non-linear behavior of solid FEM spiral models subject to hundreds of load combinations. This innovative pipeline has been applied to the project of a lightweight plywood pavilion named FlexMaps Pavilion, which is a single-layer piecewise twisted arch that fits a bounding box of 3.90x3.96x3.25 meters. This case study serves to test the applicability of this methodology at the architectural scale. The structure is validated via FE analyses and the fabrication of the full scale prototype.}, author = {Laccone, Francesco and Malomo, Luigi and Perez Rodriguez, Jesus and Pietroni, Nico and Ponchio, Federico and Bickel, Bernd and Cignoni, Paolo}, issn = {25233971}, journal = {SN Applied Sciences}, number = {9}, publisher = {Springer Nature}, title = {{A bending-active twisted-arch plywood structure: Computational design and fabrication of the FlexMaps Pavilion}}, doi = {10.1007/s42452-020-03305-w}, volume = {2}, year = {2020}, } @inproceedings{9221, abstract = {Recent works have shown that gradient descent can find a global minimum for over-parameterized neural networks where the widths of all the hidden layers scale polynomially with N (N being the number of training samples). In this paper, we prove that, for deep networks, a single layer of width N following the input layer suffices to ensure a similar guarantee. In particular, all the remaining layers are allowed to have constant widths, and form a pyramidal topology. We show an application of our result to the widely used LeCun’s initialization and obtain an over-parameterization requirement for the single wide layer of order N2. }, author = {Nguyen, Quynh and Mondelli, Marco}, booktitle = {34th Conference on Neural Information Processing Systems}, location = {Vancouver, Canada}, pages = {11961–11972}, publisher = {Curran Associates}, title = {{Global convergence of deep networks with one wide layer followed by pyramidal topology}}, volume = {33}, year = {2020}, } @misc{9222, author = {Katsaros, Georgios}, publisher = {Institute of Science and Technology Austria}, title = {{Transport data for: Site‐controlled uniform Ge/Si Hut wires with electrically tunable spin–orbit coupling}}, doi = {10.15479/AT:ISTA:9222}, year = {2020}, } @article{9249, abstract = {Rhombic dodecahedron is a space filling polyhedron which represents the close packing of spheres in 3D space and the Voronoi structures of the face centered cubic (FCC) lattice. In this paper, we describe a new coordinate system where every 3-integer coordinates grid point corresponds to a rhombic dodecahedron centroid. In order to illustrate the interest of the new coordinate system, we propose the characterization of 3D digital plane with its topological features, such as the interrelation between the thickness of the digital plane and the separability constraint we aim to obtain. We also present the characterization of 3D digital lines and study it as the intersection of multiple digital planes. Characterization of 3D digital sphere with relevant topological features is proposed as well along with the 48-symmetry appearing in the new coordinate system.}, author = {Biswas, Ranita and Largeteau-Skapin, Gaëlle and Zrour, Rita and Andres, Eric}, issn = {2353-3390}, journal = {Mathematical Morphology - Theory and Applications}, number = {1}, pages = {143--158}, publisher = {De Gruyter}, title = {{Digital objects in rhombic dodecahedron grid}}, doi = {10.1515/mathm-2020-0106}, volume = {4}, year = {2020}, } @inproceedings{9299, abstract = {We call a multigraph non-homotopic if it can be drawn in the plane in such a way that no two edges connecting the same pair of vertices can be continuously transformed into each other without passing through a vertex, and no loop can be shrunk to its end-vertex in the same way. It is easy to see that a non-homotopic multigraph on n>1 vertices can have arbitrarily many edges. We prove that the number of crossings between the edges of a non-homotopic multigraph with n vertices and m>4n edges is larger than cm2n for some constant c>0 , and that this bound is tight up to a polylogarithmic factor. We also show that the lower bound is not asymptotically sharp as n is fixed and m⟶∞ .}, author = {Pach, János and Tardos, Gábor and Tóth, Géza}, booktitle = {28th International Symposium on Graph Drawing and Network Visualization}, isbn = {9783030687656}, issn = {1611-3349}, location = {Virtual, Online}, pages = {359--371}, publisher = {Springer Nature}, title = {{Crossings between non-homotopic edges}}, doi = {10.1007/978-3-030-68766-3_28}, volume = {12590}, year = {2020}, } @article{9308, author = {Avvakumov, Sergey and Wagner, Uli and Mabillard, Isaac and Skopenkov, A. B.}, issn = {0036-0279}, journal = {Russian Mathematical Surveys}, number = {6}, pages = {1156--1158}, publisher = {IOP Publishing}, title = {{Eliminating higher-multiplicity intersections, III. Codimension 2}}, doi = {10.1070/RM9943}, volume = {75}, year = {2020}, } @misc{9326, abstract = {The mitochondrial respiratory chain, formed by five protein complexes, utilizes energy from catabolic processes to synthesize ATP. Complex I, the first and the largest protein complex of the chain, harvests electrons from NADH to reduce quinone, while pumping protons across the mitochondrial membrane. Detailed knowledge of the working principle of such coupled charge-transfer processes remains, however, fragmentary due to bottlenecks in understanding redox-driven conformational transitions and their interplay with the hydrated proton pathways. Complex I from Thermus thermophilus encases 16 subunits with nine iron–sulfur clusters, reduced by electrons from NADH. Here, employing the latest crystal structure of T. thermophilus complex I, we have used microsecond-scale molecular dynamics simulations to study the chemo-mechanical coupling between redox changes of the iron–sulfur clusters and conformational transitions across complex I. First, we identify the redox switches within complex I, which allosterically couple the dynamics of the quinone binding pocket to the site of NADH reduction. Second, our free-energy calculations reveal that the affinity of the quinone, specifically menaquinone, for the binding-site is higher than that of its reduced, menaquinol forma design essential for menaquinol release. Remarkably, the barriers to diffusive menaquinone dynamics are lesser than that of the more ubiquitous ubiquinone, and the naphthoquinone headgroup of the former furnishes stronger binding interactions with the pocket, favoring menaquinone for charge transport in T. thermophilus. Our computations are consistent with experimentally validated mutations and hierarchize the key residues into three functional classes, identifying new mutation targets. Third, long-range hydrogen-bond networks connecting the quinone-binding site to the transmembrane subunits are found to be responsible for proton pumping. Put together, the simulations reveal the molecular design principles linking redox reactions to quinone turnover to proton translocation in complex I.}, author = {Gupta, Chitrak and Khaniya, Umesh and Chan, Chun and Dehez, Francois and Shekhar, Mrinal and Gunner, M. R. and Sazanov, Leonid A and Chipot, Christophe and Singharoy, Abhishek}, publisher = {American Chemical Society}, title = {{Charge transfer and chemo-mechanical coupling in respiratory complex I}}, doi = {10.1021/jacs.9b13450.s002}, year = {2020}, } @article{6918, abstract = {We consider the classic problem of Network Reliability. A network is given together with a source vertex, one or more target vertices, and probabilities assigned to each of the edges. Each edge of the network is operable with its associated probability and the problem is to determine the probability of having at least one source-to-target path that is entirely composed of operable edges. This problem is known to be NP-hard. We provide a novel scalable algorithm to solve the Network Reliability problem when the treewidth of the underlying network is small. We also show our algorithm’s applicability for real-world transit networks that have small treewidth, including the metro networks of major cities, such as London and Tokyo. Our algorithm leverages tree decompositions to shrink the original graph into much smaller graphs, for which reliability can be efficiently and exactly computed using a brute force method. To the best of our knowledge, this is the first exact algorithm for Network Reliability that can scale to handle real-world instances of the problem.}, author = {Goharshady, Amir Kafshdar and Mohammadi, Fatemeh}, issn = {09518320}, journal = {Reliability Engineering and System Safety}, publisher = {Elsevier}, title = {{An efficient algorithm for computing network reliability in small treewidth}}, doi = {10.1016/j.ress.2019.106665}, volume = {193}, year = {2020}, } @article{6944, abstract = {We study the problem of automatically detecting if a given multi-class classifier operates outside of its specifications (out-of-specs), i.e. on input data from a different distribution than what it was trained for. This is an important problem to solve on the road towards creating reliable computer vision systems for real-world applications, because the quality of a classifier’s predictions cannot be guaranteed if it operates out-of-specs. Previously proposed methods for out-of-specs detection make decisions on the level of single inputs. This, however, is insufficient to achieve low false positive rate and high false negative rates at the same time. In this work, we describe a new procedure named KS(conf), based on statistical reasoning. Its main component is a classical Kolmogorov–Smirnov test that is applied to the set of predicted confidence values for batches of samples. Working with batches instead of single samples allows increasing the true positive rate without negatively affecting the false positive rate, thereby overcoming a crucial limitation of single sample tests. We show by extensive experiments using a variety of convolutional network architectures and datasets that KS(conf) reliably detects out-of-specs situations even under conditions where other tests fail. It furthermore has a number of properties that make it an excellent candidate for practical deployment: it is easy to implement, adds almost no overhead to the system, works with any classifier that outputs confidence scores, and requires no a priori knowledge about how the data distribution could change.}, author = {Sun, Rémy and Lampert, Christoph}, issn = {1573-1405}, journal = {International Journal of Computer Vision}, number = {4}, pages = {970--995}, publisher = {Springer Nature}, title = {{KS(conf): A light-weight test if a multiclass classifier operates outside of its specifications}}, doi = {10.1007/s11263-019-01232-x}, volume = {128}, year = {2020}, } @article{6952, abstract = {We present a unified framework tackling two problems: class-specific 3D reconstruction from a single image, and generation of new 3D shape samples. These tasks have received considerable attention recently; however, most existing approaches rely on 3D supervision, annotation of 2D images with keypoints or poses, and/or training with multiple views of each object instance. Our framework is very general: it can be trained in similar settings to existing approaches, while also supporting weaker supervision. Importantly, it can be trained purely from 2D images, without pose annotations, and with only a single view per instance. We employ meshes as an output representation, instead of voxels used in most prior work. This allows us to reason over lighting parameters and exploit shading information during training, which previous 2D-supervised methods cannot. Thus, our method can learn to generate and reconstruct concave object classes. We evaluate our approach in various settings, showing that: (i) it learns to disentangle shape from pose and lighting; (ii) using shading in the loss improves performance compared to just silhouettes; (iii) when using a standard single white light, our model outperforms state-of-the-art 2D-supervised methods, both with and without pose supervision, thanks to exploiting shading cues; (iv) performance improves further when using multiple coloured lights, even approaching that of state-of-the-art 3D-supervised methods; (v) shapes produced by our model capture smooth surfaces and fine details better than voxel-based approaches; and (vi) our approach supports concave classes such as bathtubs and sofas, which methods based on silhouettes cannot learn.}, author = {Henderson, Paul M and Ferrari, Vittorio}, issn = {1573-1405}, journal = {International Journal of Computer Vision}, pages = {835--854}, publisher = {Springer Nature}, title = {{Learning single-image 3D reconstruction by generative modelling of shape, pose and shading}}, doi = {10.1007/s11263-019-01219-8}, volume = {128}, year = {2020}, } @article{6976, abstract = {Origami is rapidly transforming the design of robots1,2, deployable structures3,4,5,6 and metamaterials7,8,9,10,11,12,13,14. However, as foldability requires a large number of complex compatibility conditions that are difficult to satisfy, the design of crease patterns is limited to heuristics and computer optimization. Here we introduce a systematic strategy that enables intuitive and effective design of complex crease patterns that are guaranteed to fold. First, we exploit symmetries to construct 140 distinct foldable motifs, and represent these as jigsaw puzzle pieces. We then show that when these pieces are fitted together they encode foldable crease patterns. This maps origami design to solving combinatorial problems, which allows us to systematically create, count and classify a vast number of crease patterns. We show that all of these crease patterns are pluripotent—capable of folding into multiple shapes—and solve exactly for the number of possible shapes for each pattern. Finally, we employ our framework to rationally design a crease pattern that folds into two independently defined target shapes, and fabricate such pluripotent origami. Our results provide physicists, mathematicians and engineers with a powerful new design strategy.}, author = {Dieleman, Peter and Vasmel, Niek and Waitukaitis, Scott R and van Hecke, Martin}, issn = {1745-2481}, journal = {Nature Physics}, number = {1}, pages = {63–68}, publisher = {Springer Nature}, title = {{Jigsaw puzzle design of pluripotent origami}}, doi = {10.1038/s41567-019-0677-3}, volume = {16}, year = {2020}, } @article{6997, author = {Zhang, Yuzhou and Friml, Jiří}, issn = {1469-8137}, journal = {New Phytologist}, number = {3}, pages = {1049--1052}, publisher = {Wiley}, title = {{Auxin guides roots to avoid obstacles during gravitropic growth}}, doi = {10.1111/nph.16203}, volume = {225}, year = {2020}, }