Differentiable Algorithm Networks for Composable Robot Learning

This paper introduces the Differentiable Algorithm Network (DAN), a composable architecture for robot learning systems. A DAN is composed of neural network modules, each encoding a differentiable robot algorithm and an associated model; and it is trained end-to-end from data. DAN combines the strengths of model-driven modular system design and data-driven end-to-end learning. The algorithms and models act as structural assumptions to reduce the data requirements for learning; end-to-end learning allows the modules to adapt to one another and compensate for imperfect models and algorithms, in order to achieve the best overall system performance. We illustrate the DAN methodology through a case study on a simulated robot system, which learns to navigate in complex 3-D environments with only local visual observations and an image of a partially correct 2-D floor map.Comment: RSS 2019 camera ready. Video is available at https://youtu.be/4jcYlTSJF4

Independent Eigenstates of Angular Momentum in a Quantum N-body System

The global rotational degrees of freedom in the Schr\"{o}dinger equation for an $N$-body system are completely separated from the internal ones. After removing the motion of center of mass, we find a complete set of $(2\ell+1)$ independent base functions with the angular momentum $\ell$. These are homogeneous polynomials in the components of the coordinate vectors and the solutions of the Laplace equation, where the Euler angles do not appear explicitly. Any function with given angular momentum and given parity in the system can be expanded with respect to the base functions, where the coefficients are the functions of the internal variables. With the right choice of the base functions and the internal variables, we explicitly establish the equations for those functions. Only (3N-6) internal variables are involved both in the functions and in the equations. The permutation symmetry of the wave functions for identical particles is discussed.Comment: 24 pages, no figure, one Table, RevTex, Will be published in Phys. Rev. A 64, 0421xx (Oct. 2001

Supersymmetric QCD: Exact Results and Strong Coupling

We revisit two longstanding puzzles in supersymmetric gauge theories. The first concerns the question of the holomorphy of the coupling, and related to this the possible definition of an exact (NSVZ) beta function. The second concerns instantons in pure gluodynamics, which appear to give sensible, exact results for certain correlation functions, which nonetheless differ from those obtained using systematic weak coupling expansions. For the first question, we extend an earlier proposal of Arkani-Hamed and Murayama, showing that if their regulated action is written suitably, the holomorphy of the couplings is manifest, and it is easy to determine the renormalization scheme for which the NSVZ formula holds. This scheme, however, is seen to be one of an infinite class of schemes, each leading to an exact beta function; the NSVZ scheme, while simple, is not selected by any compelling physical consideration. For the second question, we explain why the instanton computation in the pure supersymmetric gauge theory is not reliable, even at short distances. The semiclassical expansion about the instanton is purely formal; if infrared divergences appear, they spoil arguments based on holomorphy. We demonstrate that infrared divergences do not occur in the perturbation expansion about the instanton, but explain that there is no reason to think this captures all contributions from the sector with unit topological charge. That one expects additional contributions is illustrated by dilute gas corrections. These are infrared divergent, and so difficult to define, but if non-zero give order one, holomorphic, corrections to the leading result. Exploiting an earlier analysis of Davies et al, we demonstrate that in the theory compactified on a circle of radius beta, due to infrared effects, finite contributions indeed arise which are not visible in the formal limit that beta goes to infinity.Comment: 28 pages, two references added, one typo correcte

Self-Consistent Electron-Nucleus Cusp Correction for Molecular Orbitals

We describe a method for imposing the correct electron-nucleus (e-n) cusp in molecular orbitals expanded as a linear combination of (cuspless) Gaussian basis functions. Enforcing the e-n cusp in trial wave functions is an important asset in quantum Monte Carlo calculations as it significantly reduces the variance of the local energy during the Monte Carlo sampling. In the method presented here, the Gaussian basis set is augmented with a small number of Slater basis functions. Note that, unlike other e-n cusp correction schemes, the presence of the Slater function is not limited to the vicinity of the nuclei. Both the coefficients of these cuspless Gaussian and cusp-correcting Slater basis functions may be self-consistently optimized by diagonalization of an orbital-dependent effective Fock operator. Illustrative examples are reported for atoms (\ce{H}, \ce{He} and \ce{Ne}) as well as for a small molecular system (\ce{BeH2}). For the simple case of the \ce{He} atom, we observe that, with respect to the cuspless version, the variance is reduced by one order of magnitude by applying our cusp-corrected scheme.Comment: 23 pages, 5 figure

Combining Feature Selection and Integration—A Neural Model for MT Motion Selectivity

Background: The computation of pattern motion in visual area MT based on motion input from area V1 has been investigated in many experiments and models attempting to replicate the main mechanisms. Two different core conceptual approaches were developed to explain the findings. In integrationist models the key mechanism to achieve pattern selectivity is the nonlinear integration of V1 motion activity. In contrast, selectionist models focus on the motion computation at positions with 2D features. Methodology/Principal Findings: Recent experiments revealed that neither of the two concepts alone is sufficient to explain all experimental data and that most of the existing models cannot account for the complex behaviour found. MT pattern selectivity changes over time for stimuli like type II plaids from vector average to the direction computed with an intersection of constraint rule or by feature tracking. Also, the spatial arrangement of the stimulus within the receptive field of a MT cell plays a crucial role. We propose a recurrent neural model showing how feature integration and selection can be combined into one common architecture to explain these findings. The key features of the model are the computation of 1D and 2D motion in model area V1 subpopulations that are integrated in model MT cells using feedforward and feedback processing. Our results are also in line with findings concerning the solution of the aperture problem. Conclusions/Significance: We propose a new neural model for MT pattern computation and motion disambiguation that i

Cation-swapped homogeneous nanoparticles in perovskite oxides for high power density

Exsolution has been intensively studied in the fields of energy conversion and storage as a method for the preparation of catalytically active and durable metal nanoparticles. Under typical conditions, however, only a limited number of nanoparticles can be exsolved from the host oxides. Herein, we report the preparation of catalytic nanoparticles by selective exsolution through topotactic ion exchange, where deposited Fe guest cations can be exchanged with Co host cations in PrBaMn1.7Co0.3O5+delta. Interestingly, this phenomenon spontaneously yields the host PrBaMn1.7Fe0.3O5+delta, liberating all the Co cations from the host owing to the favorable incorporation energy of Fe into the lattice of the parent host (Delta E-incorporation = -0.41 eV) and the cation exchange energy (Delta E-exchange = -0.34 eV). Remarkably, the increase in the number of exsolved nanoparticles leads to their improved catalytic activity as a solid oxide fuel cell electrode and in the dry reforming of methane

Extended Driving Impairs Nocturnal Driving Performances

Though fatigue and sleepiness at the wheel are well-known risk factors for traffic accidents, many drivers combine extended driving and sleep deprivation. Fatigue-related accidents occur mainly at night but there is no experimental data available to determine if the duration of prior driving affects driving performance at night. Participants drove in 3 nocturnal driving sessions (3–5am, 1–5am and 9pm–5am) on open highway. Fourteen young healthy men (mean age [±SD] = 23.4 [±1.7] years) participated Inappropriate line crossings (ILC) in the last hour of driving of each session, sleep variables, self-perceived fatigue and sleepiness were measured. Compared to the short (3–5am) driving session, the incidence rate ratio of inappropriate line crossings increased by 2.6 (95% CI, 1.1 to 6.0; P<.05) for the intermediate (1–5am) driving session and by 4.0 (CI, 1.7 to 9.4; P<.001) for the long (9pm–5am) driving session. Compared to the reference session (9–10pm), the incidence rate ratio of inappropriate line crossings were 6.0 (95% CI, 2.3 to 15.5; P<.001), 15.4 (CI, 4.6 to 51.5; P<.001) and 24.3 (CI, 7.4 to 79.5; P<.001), respectively, for the three different durations of driving. Self-rated fatigue and sleepiness scores were both positively correlated to driving impairment in the intermediate and long duration sessions (P<.05) and increased significantly during the nocturnal driving sessions compared to the reference session (P<.01). At night, extended driving impairs driving performances and therefore should be limited

Tau and spectraplakins promote synapse formation and maintenance through Jun kinase and neuronal trafficking

© Voelzmann et al.The mechanisms regulating synapse numbers during development and ageing are essential for normal brain function and closely linked to brain disorders including dementias. Using Drosophila, we demonstrate roles of the microtubule-associated protein Tau in regulating synapse numbers, thus unravelling an important cellular requirement of normal Tau. In this context, we find that Tau displays a strong functional overlap with microtubule-binding spectraplakins, establishing new links between two different neurodegenerative factors. Tau and the spectraplakin Short Stop act upstream of a three-step regulatory cascade ensuring adequate delivery of synaptic proteins. This cascade involves microtubule stability as the initial trigger, JNK signalling as the central mediator, and kinesin-3 mediated axonal transport as the key effector. This cascade acts during development (synapse formation) and ageing (synapse maintenance) alike. Therefore, our findings suggest novel explanations for intellectual disability in Tau deficient individuals, as well as early synapse loss in dementias including Alzheimer’s disease