IA Scholar Query: Conceptual Representations for Planar Sections of Parametric Surfaces.
https://scholar.archive.org/
Internet Archive Scholar query results feedeninfo@archive.orgThu, 01 Dec 2022 00:00:00 GMTfatcat-scholarhttps://scholar.archive.org/help1440Vision- and touch-dependent brain correlates of body-related mental processing
https://scholar.archive.org/work/amsfm3bygfaxjaknd745qugj6q
In humans, the nature of sensory input influences body-related mental processing. For instance, behavioral differences (e.g., response time) can be found between mental spatial transformations (e.g., mental rotation) of viewed and touched body parts. It can thus be hypothesized that distinct brain activation patterns are associated with such sensorydependent body-related mental processing. However, direct evidence that the neural correlates of body-related mental processing can be modulated by the nature of the sensory stimuli is still missing. We thus analyzed event-related functional magnetic resonance imaging (fMRI) data from thirty-one healthy participants performing mental rotation of visually-(images) and haptically-presented (plastic) hands. We also dissociated the neural activity related to rotation or task-related performance using models that either regressed out or included the variance associated with response time. Haptically-mediated mental rotation recruited mostly the sensorimotor brain network. Visually-mediated mental rotation led to parieto-occipital activations. In addition, faster mental rotation was associated with sensorimotor activity, while slower mental rotation was associated with parieto-occipital activations. The fMRI results indicated that changing the type of sensory inputs modulates the neural correlates of body-related mental processing. These findings suggest that distinct sensorimotor brain dynamics can be exploited to execute similar tasks depending on the available sensory input. The present study can contribute to a better evaluation of body-related mental processing in experimental and clinical settings.Gustavo S.P. Pamplona, Martina Hardmeier, Sofian Younes, Isabelle Goy, Eleonora Fornari, Silvio Iontawork_amsfm3bygfaxjaknd745qugj6qThu, 01 Dec 2022 00:00:00 GMTUsing models of baseline gameplay to design for physical rehabilitation
https://scholar.archive.org/work/k6xupsktzfgmvjpqgl6npascsq
Modified digital games manage to drive motivation in repetitive exercises needed for motor rehabilitation, however designing modifications that satisfy both rehabilitation and engagement goals is challenging. We present a method wherein a statistical model of baseline gameplay identifies design configurations that emulate behaviours compatible with unmodified play. We illustrate this approach through a case study involving upper limb rehabilitation with a custom controller for a Pac-Man game. A participatory design workshop with occupational therapists defined two interaction parameters for gameplay and rehabilitation adjustments. The parameters' effect on the interaction was measured experimentally with 12 participants. We show that a low-latency model, using both user input behaviour and internal game state, identifies values for interaction parameters that reproduce baseline gameplay under degraded control. We discuss how this method can be applied to systematically balance gamification problems involving trade-offs between physical requirements and subjectively engaging experiences.Antoine Loriette, Baptiste Caramiaux, Sebastian Stein, John H. Williamsonwork_k6xupsktzfgmvjpqgl6npascsqMon, 21 Nov 2022 00:00:00 GMTRobotic manipulators for in situ inspections of jet engines
https://scholar.archive.org/work/akn6hclqbnggrcnwxuhvh2oiby
Jet engines need to be inspected periodically and, in some instances, repaired. Currently, some of these maintenance operations require the engine to be removed from the wing and dismantled, which has a significant associated cost. The capability of performing some of these inspections and repairs while the engine is on-wing could lead to important cost savings. However, existing technology for on-wing operations is limited, and does not suffice to satisfy some of the needs. In this work, the problem of performing on-wing operations such as inspection and repair is analysed, and after an extensive literature review, a novel robotic system for the on-wing insertion and deployment of probes or other tools is proposed. The system consists of a fine-positioner, which is a miniature and dexterous robotic manipulator; a gross-positioner, which is a device to insert the fine-positioner to the engine region of interest; an end-effector, such as a probe; a deployment mechanism, which is a passive device to ensure correct contact between probe and component; and a feedback system that provides information about the robot state for control. The research and development work conducted to address the main challenges to create this robotic system is presented in this thesis. The work is focussed on the fine-positioner, as it is the most relevant and complex part of the system. After a literature review of relevant work, and as part of the exploration of potential robot concepts for the system, the kinematic capabilities of concentric tube robots (CTRs) are first investigated. The complete set of stable trajectories that can be traced in follow-the-leader motion is discovered. A case study involving simulations and an experiment is then presented to showcase and verify the work. The research findings indicate that CTRs are not suitable for the fine-positioner. However, they show that CTRs with non-annular cross section can be used for the gross-positioner. In addition, the new trajectories discovered show promise in minimally i [...]Arnau Garriga Casanovas, Ferdinando Rodriguez Y Baena, Engineering And Physical Sciences Research Council, Rolls-Royce Group Plc.work_akn6hclqbnggrcnwxuhvh2oibyFri, 18 Nov 2022 00:00:00 GMTWater structure, dynamics and reactivity on a TiO2-nanoparticle surface: new insights from ab initio molecular dynamics
https://scholar.archive.org/work/zisiv4alunehneyjrr6baxsxsu
An ab initio molecular dynamics simulation of a TiO2 nanoparticle fully immersed in water demonstrates the role of surface defects in water dissociation and elucidates water structure and dynamics at the surface.Fredrik Grote, Alexander P. Lyubartsevwork_zisiv4alunehneyjrr6baxsxsuThu, 17 Nov 2022 00:00:00 GMTPhase separation of competing memories along the human hippocampal theta rhythm
https://scholar.archive.org/work/crlyalacq5dzbalxbvpxmvmaam
Competition between overlapping memories is considered one of the major causes of forgetting, and it is still unknown how the human brain resolves such mnemonic conflict. In the present magnetoencephalography (MEG) study, we empirically tested a computational model that leverages an oscillating inhibition algorithm to minimise overlap between memories. We used a proactive interference task, where a reminder word could be associated with either a single image (non-competitive condition) or two competing images, and participants were asked to always recall the most recently learned word–image association. Time-resolved pattern classifiers were trained to detect the reactivated content of target and competitor memories from MEG sensor patterns, and the timing of these neural reactivations was analysed relative to the phase of the dominant hippocampal 3 Hz theta oscillation. In line with our pre-registered hypotheses, target and competitor reactivations locked to different phases of the hippocampal theta rhythm after several repeated recalls. Participants who behaviourally experienced lower levels of interference also showed larger phase separation between the two overlapping memories. The findings provide evidence that the temporal segregation of memories, orchestrated by slow oscillations, plays a functional role in resolving mnemonic competition by separating and prioritising relevant memories under conditions of high interference.Casper Kerrén, Sander van Bree, Benjamin J Griffiths, Maria Wimberwork_crlyalacq5dzbalxbvpxmvmaamThu, 17 Nov 2022 00:00:00 GMTCharacterizing 4-string contact interaction using machine learning
https://scholar.archive.org/work/qwyyhmqkdvccxka2jvruonat4u
The geometry of 4-string contact interaction of closed string field theory is characterized using machine learning. We obtain Strebel quadratic differentials on 4-punctured spheres as a neural network by performing unsupervised learning with a custom-built loss function. This allows us to solve for local coordinates and compute their associated mapping radii numerically. We also train a neural network distinguishing vertex from Feynman region. As a check, 4-tachyon contact term in the tachyon potential is computed and a good agreement with the results in the literature is observed. We argue that our algorithm is manifestly independent of number of punctures and scaling it to characterize the geometry of n-string contact interaction is feasible.Harold Erbin, Atakan Hilmi Fıratwork_qwyyhmqkdvccxka2jvruonat4uWed, 16 Nov 2022 00:00:00 GMTDesign and training of deep reinforcement learning agents
https://scholar.archive.org/work/v4bnexxtdbgkvdgyu4jub7gulm
Deep reinforcement learning is a field of research at the intersection of reinforcement learning and deep learning. On one side, the problem that researchers address is the one of reinforcement learning: to act efficiently. A large number of algorithms were developed decades ago in this field to update value functions and policies, explore, and plan. On the other side, deep learning methods provide powerful function approximators to address the problem of representing functions such as policies, value functions, and models. The combination of ideas from these two fields offers exciting new perspectives. However, building successful deep reinforcement learning experiments is particularly difficult due to the large number of elements that must be combined and adjusted appropriately. This thesis proposes a broad overview of the organization of these elements around three main axes: agent design, environment design, and infrastructure design. Arguably, the success of deep reinforcement learning research is due to the tremendous amount of effort that went into each of them, both from a scientific and engineering perspective, and their diffusion via open source repositories. For each of these three axes, a dedicated part of the thesis describes a number of related works that were carried out during the doctoral research. The first part, devoted to the design of agents, presents two works. The first one addresses the problem of applying discrete action methods to large multidimensional action spaces. A general method called action branching is proposed, and its effectiveness is demonstrated with a novel agent, named BDQ, applied to discretized continuous action spaces. The second work deals with the problem of maximizing the utility of a single transition when learning to achieve a large number of goals. In particular, it focuses on learning to reach spatial locations in games and proposes a new method called Q-map to do so efficiently. An exploration mechanism based on this method is then used to demonstrate the effect [...]Fabio Pardo, Petar Kormushev, Andrew Davison, Dyson Technology Limited (Firm)work_v4bnexxtdbgkvdgyu4jub7gulmTue, 15 Nov 2022 00:00:00 GMTPhysics-regularized neural network of the ideal-MHD solution operator in Wendelstein 7-X configurations
https://scholar.archive.org/work/ke5tphot7feunf2syjjsf5p6ry
The stellarator is a promising concept to produce energy from nuclear fusion by magnetically confining a high-pressure plasma. Magnetohydrodynamics (MHD) describes how plasma pressure, current density and magnetic field interact. In a stellarator, the confining field is three-dimensional, and the computational cost of solving the 3D MHD equations currently limits stellarator comprehension, exploration and optimization. Although data-driven approaches have been proposed to provide fast 3D MHD equilibria, the accuracy with which equilibrium properties are reconstructed is unknown. In this work, we describe an artificial neural network (NN) that quickly approximates the ideal-MHD solution operator in Wendelstein 7-X (W7-X) configurations. This model fulfils equilibrium symmetries by construction. The MHD force residual regularizes the solution of the NN to satisfy the ideal-MHD equations. The model predicts the equilibrium solution with high accuracy, and it faithfully reconstructs global equilibrium quantities and proxy functions used in stellarator optimization. The regularization term enforces that the NN reduces the ideal-MHD force residual, and solutions that are better than ground truth equilibria can be obtained at inference time. We also optimize W7-X magnetic configurations, where competitive configurations can be found in terms of fast particle confinement. This work demonstrates with which accuracy NN models can approximate the 3D ideal-MHD solution operator and reconstruct equilibrium properties of interest, and it suggests how they might be used to optimize stellarator magnetic configurations.Andrea Merlo, Daniel Böckenhoff, Jonathan Schilling, Samuel Aaron Lazerson, Thomas Sunn Pedersen, the W7-X teamwork_ke5tphot7feunf2syjjsf5p6ryTue, 15 Nov 2022 00:00:00 GMTBiGONLight: a new package for computing optical observables in Numerical Relativity
https://scholar.archive.org/work/kygd44jstnhitenm4qlpwvpgwa
The investigation of relativistic effects in the most general way requires a unified treatment of light propagation in cosmology. This goal can be achieved with the new interpretation of the geodesic deviation equation in terms of the bilocal geodesic operators (BGO). The BGO formalism extends the standard formulation, providing a unified framework to describe all possible optical phenomena due to the interaction between light and spacetime curvature. In my dissertation, I present BiGONLight, a Mathematica package that applies the BGO formalism to study light propagation in numerical relativity. The package encodes the 3+1 bilocal geodesic operators framework as a collection of Mathematica functions. The inputs are the spacetime metric plus the kinematics of the observer and the source in the form of the 3+1 quantities, which may come directly from a numerical simulation or can be provided by the user as analytical components. These data are then used for ray tracing and computing the BGOs in a completely general way, i.e. without relying on symmetries or specific coordinate choices. The primary purpose of the package is the computation of optical observables in arbitrary spacetimes. The uniform theoretical framework of the BGO formalism allows for the extraction of multiple observables within a single computation, while the Wolfram language provides a flexible computational framework that makes the package highly adaptable to perform both numerical and analytical studies of light propagation.Michele Grassowork_kygd44jstnhitenm4qlpwvpgwaTue, 15 Nov 2022 00:00:00 GMTDagstuhl Reports, Volume 12, Issue 3, March 2022, Complete Issue
https://scholar.archive.org/work/atzdjkohs5hsdlk3uxxlt2ydry
Dagstuhl Reports, Volume 12, Issue 3, March 2022, Complete Issuework_atzdjkohs5hsdlk3uxxlt2ydryMon, 14 Nov 2022 00:00:00 GMTMicrodrone-Based Indoor Mapping with Graph SLAM
https://scholar.archive.org/work/7pysoh76ejg6rbhbrlasjpcr3i
Unmanned aerial vehicles offer a safe and fast approach to the production of three-dimensional spatial data on the surrounding space. In this article, we present a low-cost SLAM-based drone for creating exploration maps of building interiors. The focus is on emergency response mapping in inaccessible or potentially dangerous places. For this purpose, we used a quadcopter microdrone equipped with six laser rangefinders (1D scanners) and an optical sensor for mapping and positioning. The employed SLAM is designed to map indoor spaces with planar structures through graph optimization. It performs loop-closure detection and correction to recognize previously visited places, and to correct the accumulated drift over time. The proposed methodology was validated for several indoor environments. We investigated the performance of our drone against a multilayer LiDAR-carrying macrodrone, a vision-aided navigation helmet, and ground truth obtained with a terrestrial laser scanner. The experimental results indicate that our SLAM system is capable of creating quality exploration maps of small indoor spaces, and handling the loop-closure problem. The accumulated drift without loop closure was on average 1.1% (0.35 m) over a 31-m-long acquisition trajectory. Moreover, the comparison results demonstrated that our flying microdrone provided a comparable performance to the multilayer LiDAR-based macrodrone, given the low deviation between the point clouds built by both drones. Approximately 85 % of the cloud-to-cloud distances were less than 10 cm.Samer Karam, Francesco Nex, Bhanu Teja Chidura, Norman Kerlework_7pysoh76ejg6rbhbrlasjpcr3iMon, 14 Nov 2022 00:00:00 GMTHigh-Q magnetic levitation and control of superconducting microspheres at millikelvin temperatures
https://scholar.archive.org/work/dzmxf4h4nbg5hgpazhs6wglpfm
We report the levitation of a superconducting lead-tin sphere with 100 micrometer diameter (corresponding to a mass of 5.6 micrograms) in a static magnetic trap formed by two coils in an anti-Helmholtz configuration, with adjustable resonance frequencies up to 240 hertz. The center-of-mass motion of the sphere is monitored magnetically using a dc-SQUID as well as optically and exhibits quality factors of up to 2.6e7. We also demonstrate 3D magnetic feedback control of the sphere's motion. By implementing a cryogenic vibration isolation system we can attenuate environmental vibrations at 200 hertz by approximately seven orders of magnitude. The combination of low temperature (15 millikelvin), large mass and high quality factor as well as adjustable resonance frequencies provides a promising platform for testing quantum physics in previously unexplored regimes with high mass and long coherence times.Joachim Hofer, Gerard Higgins, Hans Huebl, Oliver F. Kieler, Reinhold Kleiner, Dieter Koelle, Philip Schmidt, Joshua A. Slater, Michael Trupke, Kevin Uhl, Thomas Weimann, Witlef Wieczorek, Friedrich Wulschner, Markus Aspelmeyerwork_dzmxf4h4nbg5hgpazhs6wglpfmFri, 11 Nov 2022 00:00:00 GMTImplicit modeling of patient-specific aortic dissections with elliptic fourier descriptors
https://scholar.archive.org/work/k2si4cuokres5g4a5g65zi7vyy
Aortic dissection is a life-threatening vascular disease characterized by abrupt formation of a new flow channel (false lumen) within the aortic wall. Survivors of the acute phase remain at high risk for late complications, such as aneurysm formation, rupture, and death. Morphologic features of aortic dissection determine not only treatment strategies in the acute phase (surgical vs. endovascular vs. medical), but also modulate the hemodynamics in the false lumen, ultimately responsible for late complications. Accurate description of the true and false lumen, any communications across the dissection membrane separating the two lumina, and blood supply from each lumen to aortic branch vessels is critical for risk prediction. Patient-specific surface representations are also a prerequisite for hemodynamic simulations, but currently require time-consuming manual segmentation of CT data. We present an aortic dissection cross-sectional model that captures the varying aortic anatomy, allowing for reliable measurements and creation of high-quality surface representations. In contrast to the traditional spline-based cross-sectional model, we employ elliptic Fourier descriptors, which allows users to control the accuracy of the cross-sectional contour of a flow channel. We demonstrate (i) how our approach can solve the requirements for generating surface and wall representations of the flow channels, (ii) how any number of communications between flow channels can be specified in a consistent manner, and (iii) how well branches connected to the respective flow channels are handled. Finally, we discuss how our approach is a step forward to an automated generation of surface models for aortic dissections from raw 3D imaging segmentation masks.Gabriel Mistelbauer, Christian Rössl, K. Bäumler, Bernhard Preim, D. Fleischmann, Universitäts- Und Landesbibliothek Sachsen-Anhalt, Martin-Luther Universitätwork_k2si4cuokres5g4a5g65zi7vyyFri, 11 Nov 2022 00:00:00 GMTPermutons, meanders, and SLE-decorated Liouville quantum gravity
https://scholar.archive.org/work/7andxu444rgxtbhqaxx7mum24u
We study a class of random permutons which can be constructed from a pair of space-filling Schramm-Loewner evolution (SLE) curves on a Liouville quantum gravity (LQG) surface. This class includes the skew Brownian permutons introduced by Borga (2021), which describe the scaling limit of various types of random pattern-avoiding permutations. Another interesting permuton in our class is the meandric permuton, which corresponds to two independent SLE_8 curves on a γ-LQG surface with γ = √(1/3( 17 - √(145))). Building on work by Di Francesco, Golinelli, and Guitter (2000), we conjecture that the meandric permuton describes the scaling limit of uniform meandric permutations, i.e., the permutations induced by a simple loop in the plane which crosses a line a specified number of times. We show that for any sequence of random permutations which converges to one of the above random permutons, the length of the longest increasing subsequence is sublinear. This proves that the length of the longest increasing subsequence is sublinear for Baxter, strong-Baxter, and semi-Baxter permutations and leads to the conjecture that the same is true for meandric permutations. We also prove that the closed support of each of the random permutons in our class has Hausdorff dimension one. Finally, we prove a re-rooting invariance property for the meandric permuton and write down a formula for its expected pattern densities in terms of LQG correlation functions (which are known explicitly) and the probability that an SLE_8 hits a given set of points in numerical order (which is not known explicitly). We conclude with a list of open problems.Jacopo Borga, Ewain Gwynne, Xin Sunwork_7andxu444rgxtbhqaxx7mum24uFri, 11 Nov 2022 00:00:00 GMTSnowmass Theory Frontier Report
https://scholar.archive.org/work/4c7uvvpwl5ajfjddlrc5awneaa
This report summarizes the recent progress and promising future directions in theoretical high-energy physics (HEP) identified within the Theory Frontier of the 2021 Snowmass Process.N. Craig, C. Csáki, A. X. El-Khadra, Z. Bern, R. Boughezal, S. Catterall, Z. Davoudi, A. de Gouvêa, P. Draper, P. J. Fox, D. Green, D. Harlow, R. Harnik, V. Hubeny, T. Izubuchi, S. Kachru, G. Kribs, H. Murayama, Z. Ligeti, J. Maldacena, F. Maltoni, I. Mocioiu, E. T. Neil, S. Pastore, D. Poland, L. Rastelli, I. Rothstein, J. Ruderman, B. Safdi, J. Shelton, L. Strigari, S. Su, J. Thaler, J. Trnka, K. Babu, Steven Gottlieb, A. Petrov, L. Reina, F. Tanedo, D. Walker, L.-T. Wangwork_4c7uvvpwl5ajfjddlrc5awneaaThu, 10 Nov 2022 00:00:00 GMTReconstruct from BEV: A 3D Lane Detection Approach based on Geometry Structure Prior
https://scholar.archive.org/work/rreghr6xuvetng3lniapy7t6vi
In this paper, we propose an advanced approach in targeting the problem of monocular 3D lane detection by leveraging geometry structure underneath the process of 2D to 3D lane reconstruction. Inspired by previous methods, we first analyze the geometry heuristic between the 3D lane and its 2D representation on the ground and propose to impose explicit supervision based on the structure prior, which makes it achievable to build inter-lane and intra-lane relationships to facilitate the reconstruction of 3D lanes from local to global. Second, to reduce the structure loss in 2D lane representation, we directly extract BEV lane information from front view images, which tremendously eases the confusion of distant lane features in previous methods. Furthermore, we propose a novel task-specific data augmentation method by synthesizing new training data for both segmentation and reconstruction tasks in our pipeline, to counter the imbalanced data distribution of camera pose and ground slope to improve generalization on unseen data. Our work marks the first attempt to employ the geometry prior information into DNN-based 3D lane detection and makes it achievable for detecting lanes in an extra-long distance, doubling the original detection range. The proposed method can be smoothly adopted by other frameworks without extra costs. Experimental results show that our work outperforms state-of-the-art approaches by 3.8% F-Score on Apollo 3D synthetic dataset at real-time speed of 82 FPS without introducing extra parameters.Chenguang Li, Jia Shi, Ya Wang, Guangliang Chengwork_rreghr6xuvetng3lniapy7t6viWed, 09 Nov 2022 00:00:00 GMTPotential of metal–organic frameworks for adsorptive separation of industrially and environmentally relevant liquid mixtures
https://scholar.archive.org/work/arhf7q27rbfjflbxd7rdilh3t4
Metal-organic frameworks (MOFs) or porous coordination polymers (PCPs) are defined as crystalline, open,coordination network architectures with potential voids. They have drawn momentous attention across several crossroads of material chemistry since their discovery, owing to an exciting plethora of application-oriented footprints left by this class of crystalline, supramolecular and open coordination architectures. The unmatched aspect of tunable coordination nanospace arising from the countless choice of pre-functionalized organic struts pertaining to varying lengths alongside multivariate coordination geometries/oxidation states of the metal nodes, bestows a distinct chemical tailorability facet to this class of porous materials. Amidst the two-decade long attention dedicated to the adsorption-governed purification of gases, the MOF literature has substantially expanded its horizon into the manifestation of industrially relevant liquid mixtures' adsorptive separation-driven purification. Such chemical separation phenomena categorically encompasses high importance to the manufacturing and processing industry sectors, apart from the fundamental scientific pursuit of discovering novel physicochemical principles. Aimed at the energy-economic preparation of pure industrial feedstocks and their consequent usage as end products, structure-property correlations pursued in the alleys of coordination chemistry has led to major advancements in a number of critical separation frontiers, inclusive of biofuels (alcohol/water), diverse hydrocarbon mixtures, and chiral species. This comprehensive review summarizes the topical developments accrued in the field of MOF-based liquid mixtures' adsorptive separation phenomena, structure-selectivity relationships as well as the associated plausible mechanisms substantiating such behavior.Soumya Mukherjee, Aamod V. Desai, Sujit K. Ghoshwork_arhf7q27rbfjflbxd7rdilh3t4Mon, 07 Nov 2022 00:00:00 GMTIsing model and s-embeddings of planar graphs
https://scholar.archive.org/work/er7k7muv4jexzjh2m57o5ov53q
We discuss the notion of s-embeddings 𝒮=𝒮_𝒳 of planar graphs carrying a nearest-neighbor Ising model. The construction of 𝒮_𝒳 is based upon a choice of a global complex-valued solution 𝒳 of the propagation equation for Kadanoff-Ceva fermions. Each choice of 𝒳 provides an interpretation of all other fermionic observables as s-holomorphic functions on 𝒮_𝒳. We set up a general framework for the analysis of such functions on s-embeddings 𝒮^δ with δ→ 0. Throughout this analysis, a key role is played by the functions 𝒬^δ associated with 𝒮^δ, the so-called origami maps in the bipartite dimer model terminology. In particular, we give an interpretation of the mean curvature of the limit of discrete surfaces (𝒮^δ;𝒬^δ) viewed in the Minkowski space ℝ^2,1 as the mass in the Dirac equation describing the continuous limit of the model. We then focus on the simplest situation when 𝒮^δ have uniformly bounded lengths/angles and 𝒬^δ=O(δ); as a particular case this includes all critical Ising models on doubly periodic graphs via their canonical s-embeddings. In this setup we prove RSW-type crossing estimates for the random cluster representation of the model and the convergence of basic fermionic observables. The proof relies upon a new strategy as compared to the already existing literature, it also provides a quantitative estimate on the speed of convergence.Dmitry Chelkakwork_er7k7muv4jexzjh2m57o5ov53qMon, 07 Nov 2022 00:00:00 GMTDimer model and holomorphic functions on t-embeddings of planar graphs
https://scholar.archive.org/work/x4m42h6fufdnrop35qdrlpngty
We introduce the framework of discrete holomorphic functions on t-embeddings of weighted bipartite planar graphs; t-embeddings also appeared under the name Coulomb gauges in a recent paper arXiv:1810.05616. We argue that this framework is particularly relevant for the analysis of scaling limits of the height fluctuations in the corresponding dimer models. In particular, it unifies both Kenyon's interpretation of dimer observables as derivatives of harmonic functions on T-graphs and the notion of s-holomorphic functions originated in Smirnov's work on the critical Ising model. We develop an a priori regularity theory for such functions and provide a meta-theorem on convergence of the height fluctuations to the Gaussian Free Field. We also discuss how several more standard discretizations of complex analysis fit this general framework.Dmitry Chelkak, Benoît Laslier, Marianna Russkikhwork_x4m42h6fufdnrop35qdrlpngtyMon, 07 Nov 2022 00:00:00 GMTAn Uncertainty Weighted Non-Cooperative Target Pose Estimation Algorithm, Based on Intersecting Vectors
https://scholar.archive.org/work/quybn4afubg5diuroxscmkey4m
Aiming at the relative pose estimation of non-cooperative targets in space traffic management tasks, a two-step pose estimation method, based on spatially intersecting straight lines, is proposed, which mainly includes three aspects: (1) Use binocular vision to reconstruct the straight space line, and based on the direction vector of the straight line and the intersection of the straight line, solve the pose of the measured target in the measurement coordinate system, and obtain the initial value of the pose estimation. (2) Analyze the uncertainty of the spatial straight-line imaging, construct the uncertainty description matrix of the line, and filter the line features, accordingly. (3) Analyze the problems existing in the current linear distance measurement, construct the spatial linear back-projection error in the parametric coordinate space, and use the linear imaging uncertainty to weigh the projection error term to establish the optimization objective function of the pose estimation. Finally, the nonlinear optimization algorithm is used to iteratively solve the above optimization problem, to obtain high-precision pose estimation results. The experimental results show that the two-step pose estimation algorithm, proposed in this paper, can effectively achieve a high-precision and robust pose estimation for non-cooperative spatial targets. When the measurement distance is 10 m, the position accuracy can reach 10 mm, and the attitude measurement accuracy can reach 1°, which meets the pose estimation accuracy requirements of space traffic management.Yunhui Li, Yunhang Yan, Xianchao Xiu, Zhonghua Miaowork_quybn4afubg5diuroxscmkey4mThu, 03 Nov 2022 00:00:00 GMT