| 1. |
- Schael, S., et al.
(author)
-
Electroweak measurements in electron positron collisions at W-boson-pair energies at LEP
- 2013
-
In: Physics Reports. - : Elsevier BV. - 0370-1573 .- 1873-6270. ; 532:4, s. 119-244
-
Research review (peer-reviewed)abstract
- Electroweak measurements performed with data taken at the electron positron collider LEP at CERN from 1995 to 2000 are reported. The combined data set considered in this report corresponds to a total luminosity of about 3 fb(-1) collected by the four LEP experiments ALEPH, DELPHI, 13 and OPAL, at centre-of-mass energies ranging from 130 GeV to 209 GeV. Combining the published results of the four LEP experiments, the measurements include total and differential cross-sections in photon-pair, fermion-pair and four-fermion production, the latter resulting from both double-resonant WW and ZZ production as well as singly resonant production. Total and differential cross-sections are measured precisely, providing a stringent test of the Standard Model at centre-of-mass energies never explored before in electron positron collisions. Final-state interaction effects in four-fermion production, such as those arising from colour reconnection and Bose Einstein correlations between the two W decay systems arising in WW production, are searched for and upper limits on the strength of possible effects are obtained. The data are used to determine fundamental properties of the W boson and the electroweak theory. Among others, the mass and width of the W boson, m(w) and Gamma(w), the branching fraction of W decays to hadrons, B(W -> had), and the trilinear gauge-boson self-couplings g(1)(Z), K-gamma and lambda(gamma), are determined to be: m(w) = 80.376 +/- 0.033 GeV Gamma(w) = 2.195 +/- 0.083 GeV B(W -> had) = 67.41 +/- 0.27% g(1)(Z) = 0.984(-0.020)(+0.018) K-gamma - 0.982 +/- 0.042 lambda(gamma) = 0.022 +/- 0.019. (C) 2013 Elsevier B.V. All rights reserved.
|
|
| 2. |
- Baumann, Dominik, Ph.D. 1991-, et al.
(author)
-
A computationally lightweight safe learning algorithm
- 2023
-
In: 2023 62nd IEEE Conference on Decision and Control, (CDC). - : Institute of Electrical and Electronics Engineers (IEEE). - 9798350301243 - 9798350301250 ; , s. 1022-1027
-
Conference paper (peer-reviewed)abstract
- Safety is an essential asset when learning control policies for physical systems, as violating safety constraints during training can lead to expensive hardware damage. In response to this need, the field of safe learning has emerged with algorithms that can provide probabilistic safety guarantees without knowledge of the underlying system dynamics. Those algorithms often rely on Gaussian process inference. Unfortunately, Gaussian process inference scales cubically with the number of data points, limiting applicability to high-dimensional and embedded systems. In this paper, we propose a safe learning algorithm that provides probabilistic safety guarantees but leverages the Nadaraya-Watson estimator instead of Gaussian processes. For the Nadaraya-Watson estimator, we can reach logarithmic scaling with the number of data points. We provide theoretical guarantees for the estimates, embed them into a safe learning algorithm, and show numerical experiments on a simulated seven-degrees-of-freedom robot manipulator.
|
|
| 3. |
|
|
| 4. |
- Baumann, Dominik, Ph.D. 1991-, et al.
(author)
-
Safe Reinforcement Learning in Uncertain Contexts
- 2024
-
In: IEEE Transactions on robotics. - : IEEE. - 1552-3098 .- 1941-0468. ; 40, s. 1828-1841
-
Journal article (peer-reviewed)abstract
- When deploying machine learning algorithms in the real world, guaranteeing safety is an essential asset. Existing safe learning approaches typically consider continuous variables, i.e., regression tasks. However, in practice, robotic systems are also subject to discrete, external environmental changes, e.g., having to carry objects of certain weights or operating on frozen, wet, or dry surfaces. Such influences can be modeled as discrete context variables. In the existing literature, such contexts are, if considered, mostly assumed to be known. In this work, we drop this assumption and show how we can perform safe learning when we cannot directly measure the context variables. To achieve this, we derive frequentist guarantees for multiclass classification, allowing us to estimate the current context from measurements. Furthermore, we propose an approach for identifying contexts through experiments. We discuss under which conditions we can retain theoretical guarantees and demonstrate the applicability of our algorithm on a Furuta pendulum with camera measurements of different weights that serve as contexts.
|
|
| 5. |
- Clement, E., et al.
(author)
-
Conceptual design of the AGATA 1 π array at GANIL
- 2017
-
In: Nuclear Instruments and Methods in Physics Research Section A. - : Elsevier BV. - 0168-9002 .- 1872-9576. ; 855, s. 1-12
-
Journal article (peer-reviewed)abstract
- The Advanced GAmma Tracking Array (AGATA) has been installed at the GANIL facility, Caen-France. This setup exploits the stable and radioactive heavy-ions beams delivered by the cyclotron accelerator complex of GANIL. Additionally, it benefits from a large palette of ancillary detectors and spectrometers to address in-beam γ-ray spectroscopy of exotic nuclei. The set-up has been designed to couple AGATA with a magnetic spectrometer, charged-particle and neutron detectors, scintillators for the detection of high-energy γ rays and other devices such as a plunger to measure nuclear lifetimes. In this paper, the design and the mechanical characteristics of the set-up are described. Based on simulations, expected performances of the AGATA l π array are presented.
|
|
| 6. |
|
|
| 7. |
- Gräfe, Alexander, et al.
(author)
-
Towards remote fault detection by analyzing communication priorities
- 2022
-
In: 2022 IEEE 61st Conference on Decision and Control (CDC). - : Institute of Electrical and Electronics Engineers (IEEE). - 9781665467612 - 9781665467605 - 9781665467629 ; , s. 1758-1763
-
Conference paper (peer-reviewed)abstract
- The ability to detect faults is an important safety feature for event-based multi-agent systems. In most existing algorithms, each agent tries to detect faults by checking its own behavior. But what if one agent becomes unable to recognize misbehavior, for example due to failure in its onboard fault detection? To improve resilience and avoid propagation of individual errors to the multi-agent system, agents should check each other remotely for malfunction or misbehavior. In this paper, we build upon a recently proposed predictive triggering architecture that involves communication priorities shared throughout the network to manage limited bandwidth. We propose a fault detection method that uses these priorities to detect errors in other agents. The resulting algorithms is not only able to detect faults, but can also run on a low-power microcontroller in real-time, as we demonstrate in hardware experiments.
|
|
| 8. |
- Hulme, Oliver, et al.
(author)
-
Reply to "The Limitations of Growth-Optimal Approaches to Decision Making Under Uncertainty"
- 2023
-
In: Econ Journal Watch. - : Institute of Spontaneous Order Economics. - 1933-527X. ; 20:2, s. 335-348
-
Journal article (other academic/artistic)abstract
- In an article appearing concurrently with the present one, Matthew Ford and John Kay put forward their understanding of a decision theory which emerges in ergodicity economics. Their understanding leads them to believe that ergodicity economics evades the core problem of decisions under uncertainty and operates solely in a regime where there is no measurable uncertainty. If this were the case, then the authors' critical stance would be justified and, as the authors point out, the decision theory would yield only trivial results, identical to a flavor of expected-utility theory. Here we clarify that the critique is based on a theoretical misunderstanding, and that uncertainty-quantified in any reasonable way-is large in the regime where the model operates. Our resolution explains the success of recent laboratory experiments, where ergodicity economics makes predictions different from expected-utility theory, contrary to the claim of equivalence by Ford and Kay. Also, a state of the world is identified where ergodicity economics outperforms expected-utility theory empirically.
|
|
| 9. |
- Li, Y., et al.
(author)
-
Complex structural dynamics of nanocatalysts revealed in Operando conditions by correlated imaging and spectroscopy probes
- 2015
-
In: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 6
-
Journal article (peer-reviewed)abstract
- Understanding how heterogeneous catalysts change size, shape and structure during chemical reactions is limited by the paucity of methods for studying catalytic ensembles in working state, that is, in operando conditions. Here by a correlated use of synchrotron X-ray absorption spectroscopy and scanning transmission electron microscopy in operando conditions, we quantitatively describe the complex structural dynamics of supported Pt catalysts exhibited during an exemplary catalytic reaction-ethylene hydrogenation. This work exploits a microfabricated catalytic reactor compatible with both probes. The results demonstrate dynamic transformations of the ensemble of Pt clusters that spans a broad size range throughout changing reaction conditions. This method is generalizable to quantitative operando studies of complex systems using a wide variety of X-ray and electron-based experimental probes.
|
|
| 10. |
- Mazza, T., et al.
(author)
-
Mapping Resonance Structures in Transient Core-Ionized Atoms
- 2020
-
In: Physical Review X. - 2160-3308. ; 10:4
-
Journal article (peer-reviewed)abstract
- The nature of transient electronic states created by photoabsorption critically determines the dynamics of the subsequently evolving system. Here, we investigate K-shell photoionized atomic neon by absorbing a second photon within the Auger-decay lifetime of 2.4 fs using the European XFEL, a unique high-repetition-rate, wavelength-tunable x-ray free-electron laser. By high-resolution electron spectroscopy, we map out the transient Rydberg resonances unraveling the details of the subsequent decay of the hollow atom. So far, ultra-short-lived electronic transients, which are often inaccessible by experiments, were mainly inferred from theory but are now addressed by nonlinear x-ray absorption. The successful characterization of these resonances with femtosecond lifetimes provides the basis for a novel class of site-specific, nonlinear, and time-resolved studies with strong impact for a wide range of topics in physics and chemistry.
|
|
| 11. |
|
|
| 12. |
- Sukhija, Bhavya, et al.
(author)
-
GOSAFEOPT : Scalable safe exploration for global optimization of dynamical systems
- 2023
-
In: Artificial Intelligence. - : Elsevier BV. - 0004-3702 .- 1872-7921. ; 320
-
Journal article (peer-reviewed)abstract
- Learning optimal control policies directly on physical systems is challenging. Even a single failure can lead to costly hardware damage. Most existing model-free learning methods that guarantee safety, i.e., no failures, during exploration are limited to local optima. This work proposes GOSAFEOPT as the first provably safe and optimal algorithm that can safely discover globally optimal policies for systems with high-dimensional state space. We demonstrate the superiority of GOSAFEOPT over competing model-free safe learning methods in simulation and hardware experiments on a robot arm.(c) 2023 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons .org /licenses /by /4 .0/).
|
|
| 13. |
- Weichwald, Sebastian, et al.
(author)
-
Learning by Doing : Controlling a Dynamical System using Causality, Control, and Reinforcement Learning
- 2022
-
In: Proceedings of the NeurIPS 2021 Competitions and Demonstrations Track. - : PMLR. ; 176, s. 246-258
-
Conference paper (peer-reviewed)abstract
- Questions in causality, control, and reinforcement learning go beyond the classical machine learning task of prediction under i.i.d. observations. Instead, these fields consider the problem of learning how to actively perturb a system to achieve a certain effect on a response variable. Arguably, they have complementary views on the problem: In control, one usually aims to first identify the system by excitation strategies to then apply model-based design techniques to control the system. In (non-model-based) reinforcement learning, one directly optimizes a reward. In causality, one focus is on identifiability of causal structure. We believe that combining the different views might create synergies and this competition is meant as a first step toward such synergies. The participants had access to observational and (offline) interventional data generated by dynamical systems. Track CHEM considers an open-loop problem in which a single impulse at the beginning of the dynamics can be set, while Track ROBO considers a closed-loop problem in which control variables can be set at each time step. The goal in both tracks is to infer controls that drive the system to a desired state. Code is open-sourced ( https://github.com/LearningByDoingCompetition/learningbydoing-comp ) to reproduce the winning solutions of the competition and to facilitate trying out new methods on the competition tasks.
|
|
| 14. |
|
|
