Hasil untuk "q-bio.OT"

K. Koshelev, S. Lepeshov, Mingkai Liu et al.

We reveal that metasurfaces created by seemingly different lattices of (dielectric or metallic) meta-atoms with broken in-plane symmetry can support sharp high-Q resonances arising from a distortion of symmetry-protected bound states in the continuum. We develop a rigorous theory of such asymmetric periodic structures and demonstrate a link between the bound states in the continuum and Fano resonances. Our results suggest the way for smart engineering of resonances in metasurfaces for many applications in nanophotonics and metaoptics.

Lei Zhang, X. Q. Chen, Shuo Liu et al.

The recently proposed digital coding metasurfaces make it possible to control electromagnetic (EM) waves in real time, and allow the implementation of many different functionalities in a programmable way. However, current configurations are only space-encoded, and do not exploit the temporal dimension. Here, we propose a general theory of space-time modulated digital coding metasurfaces to obtain simultaneous manipulations of EM waves in both space and frequency domains, i.e., to control the propagation direction and harmonic power distribution simultaneously. As proof-of-principle application examples, we consider harmonic beam steering, beam shaping, and scattering-signature control. For validation, we realize a prototype controlled by a field-programmable gate array, which implements the harmonic beam steering via an optimized space-time coding sequence. Numerical and experimental results, in good agreement, demonstrate good performance of the proposed approach, with potential applications to diverse fields such as wireless communications, cognitive radars, adaptive beamforming, holographic imaging. Current digital coding metasurfaces are only space-encoded. Here, the authors propose space-time modulated digital coding metasurfaces to obtain simultaneous manipulations of electromagnetic waves and present harmonic beam steering, beam shaping, and scattering-signature control as application examples.

A. Kodigala, T. Lepetit, Q. Gu et al.

H. V. Hasselt, A. Guez, David Silver

The popular Q-learning algorithm is known to overestimate action values under certain conditions. It was not previously known whether, in practice, such overestimations are common, whether they harm performance, and whether they can generally be prevented. In this paper, we answer all these questions affirmatively. In particular, we first show that the recent DQN algorithm, which combines Q-learning with a deep neural network, suffers from substantial overestimations in some games in the Atari 2600 domain. We then show that the idea behind the Double Q-learning algorithm, which was introduced in a tabular setting, can be generalized to work with large-scale function approximation. We propose a specific adaptation to the DQN algorithm and show that the resulting algorithm not only reduces the observed overestimations, as hypothesized, but that this also leads to much better performance on several games.

Matthew J. Hausknecht, P. Stone

Deep Reinforcement Learning has yielded proficient controllers for complex tasks. However, these controllers have limited memory and rely on being able to perceive the complete game screen at each decision point. To address these shortcomings, this article investigates the effects of adding recurrency to a Deep Q-Network (DQN) by replacing the first post-convolutional fully-connected layer with a recurrent LSTM. The resulting \textit{Deep Recurrent Q-Network} (DRQN), although capable of seeing only a single frame at each timestep, successfully integrates information through time and replicates DQN's performance on standard Atari games and partially observed equivalents featuring flickering game screens. Additionally, when trained with partial observations and evaluated with incrementally more complete observations, DRQN's performance scales as a function of observability. Conversely, when trained with full observations and evaluated with partial observations, DRQN's performance degrades less than DQN's. Thus, given the same length of history, recurrency is a viable alternative to stacking a history of frames in the DQN's input layer and while recurrency confers no systematic advantage when learning to play the game, the recurrent net can better adapt at evaluation time if the quality of observations changes.

V. Khachatryan, A. Sirunyan, A. Tumasyan et al.

New sets of parameters ("tunes") for the underlying-event (UE) modeling of the PYTHIA8, PYTHIA6 and HERWIG++ Monte Carlo event generators are constructed using different parton distribution functions. Combined fits to CMS UE proton-proton (pp) data at sqrt(s) = 7 TeV and to UE proton-antiproton (p p-bar) data from the CDF experiment at lower sqrt(s), are used to study the UE models and constrain their parameters, providing thereby improved predictions for proton-proton collisions at 13 TeV. In addition, it is investigated whether the values of the parameters obtained from fits to UE observables are consistent with the values determined from fitting observables sensitive to double-parton scattering processes. Finally, comparisons of the UE tunes to"minimum bias"(MB) events, multijet, and Drell-Yan (q q-bar to Z / gamma* to lepton-antilepton + jets) observables at 7 and 8 TeV are presented, as well as predictions for MB and UE observables at 13 TeV.

R. Peters, Lucian A. Taylor

Khachatryan, A. Sirunyan, A. Tumasyan et al.

Improved jet energy scale corrections, based on a data sample corresponding to an integrated luminosity of 19.7 inverse-femtobarns collected by the CMS experiment in proton-proton collisions at a center-of-mass energy of 8 TeV, are presented. The corrections as a function of pseudorapidity eta and transverse momentum pT are extracted from data and simulated events combining several channels and methods. They account successively for the effects of pileup, uniformity of the detector response, and residual data-simulation jet energy scale differences. Further corrections, depending on the jet flavor and distance parameter (jet size) R, are also presented. The jet energy resolution is measured in data and simulated events and is studied as a function of pileup, jet size, and jet flavor. Typical jet energy resolutions at the central rapidities are 15-20% at 30 GeV, about 10% at 100 GeV, and 5% at 1 TeV. The studies exploit events with dijet topology, as well as photon+jet, Z+jet and multijet events. Several new techniques are used to account for the various sources of jet energy scale corrections, and a full set of uncertainties, and their correlations, are provided. The final uncertainties on the jet energy scale are below 3% across the phase space considered by most analyses (pT>30 GeV and abs(eta)30 GeV is reached, when excluding the jet flavor uncertainties, which are provided separately for different jet flavors. A new benchmark for jet energy scale determination at hadron colliders is achieved with 0.32% uncertainty for jets with pT of the order of 165-330 GeV, and abs(eta)<0.8.

Peide Liu, Peng Wang

The q‐rung orthopair fuzzy sets (q‐ROFs) are an important way to express uncertain information, and they are superior to the intuitionistic fuzzy sets and the Pythagorean fuzzy sets. Their eminent characteristic is that the sum of the qth power of the membership degree and the qth power of the degrees of non‐membership is equal to or less than 1, so the space of uncertain information they can describe is broader. Under these environments, we propose the q‐rung orthopair fuzzy weighted averaging operator and the q‐rung orthopair fuzzy weighted geometric operator to deal with the decision information, and their some properties are well proved. Further, based on these operators, we presented two new methods to deal with the multi‐attribute decision making problems under the fuzzy environment. Finally, we used some practical examples to illustrate the validity and superiority of the proposed method by comparing with other existing methods.

Can Huang, Chen Zhang, S. Xiao et al.

Ultrafast vortex microlasers For applications in ultrafast communication, all-optical switches will require low energy consumption, high speed, a strong modulation ratio, a small footprint, and on-chip integration. Although the small footprint and on-chip integration are accessible, the trade-off between low energy consumption and high speed has been challenging. Huang et al. exploited the idea of bound states in the continuum, effectively a high–quality (Q) cavity without the physical cavity, to design vortex lasers with highly directional output and single-mode operation. With the trade-off between low energy consumption and high speed now broken, it should be possible to realize ultrafast optical switching that meets all the requirements of modern classic and quantum information. Science, this issue p. 1018 Ultrafast vortex lasers with highly directional output and single-mode operation have been realized. The development of classical and quantum information–processing technology calls for on-chip integrated sources of structured light. Although integrated vortex microlasers have been previously demonstrated, they remain static and possess relatively high lasing thresholds, making them unsuitable for high-speed optical communication and computing. We introduce perovskite-based vortex microlasers and demonstrate their application to ultrafast all-optical switching at room temperature. By exploiting both mode symmetry and far-field properties, we reveal that the vortex beam lasing can be switched to linearly polarized beam lasing, or vice versa, with switching times of 1 to 1.5 picoseconds and energy consumption that is orders of magnitude lower than in previously demonstrated all-optical switching. Our results provide an approach that breaks the long-standing trade-off between low energy consumption and high-speed nanophotonics, introducing vortex microlasers that are switchable at terahertz frequencies.

Mian Zhang, Cheng Wang, Rebecca Cheng et al.

We demonstrate an ultralow loss monolithic integrated lithium niobate photonic platform consisting of dry-etched subwavelength waveguides with extracted propagation losses as low as 2.7 dB/m and microring resonators with quality factors up to 107.

Jicheng Jin, Xuefan Yin, Liangfu Ni et al.

Because of their ability to confine light, optical resonators1–3 are of great importance to science and technology, but their performance is often limited by out-of-plane-scattering losses caused by inevitable fabrication imperfections4,5. Here we theoretically propose and experimentally demonstrate a class of guided resonances in photonic crystal slabs, in which out-of-plane-scattering losses are strongly suppressed by their topological nature. These resonances arise when multiple bound states in the continuum—each carrying a topological charge6—merge in momentum space and enhance the quality factors Q of all nearby resonances in the same band. Using such resonances in the telecommunication regime, we experimentally achieve quality factors as high as 4.9 × 105—12 times higher than those obtained with standard designs—and this enhancement remains robust for all of our samples. Our work paves the way for future explorations of topological photonics in systems with open boundary conditions and for their application to the improvement of optoelectronic devices in photonic integrated circuits. Bound states in the continuum are merged in momentum space by varying the periodicity of the photonic crystal lattice, giving high-quality-factor guided resonances that are robust to out-of-plane scattering.

Xudong Zhang, Yilin Liu, Jiecai Han et al.

Ultracompact sources of circularly polarized light are important for classical and quantum optical information processing. Conventional approaches for generating chiral emission are restricted to excitation power ranges and fail to provide high-quality radiation with perfect polarization conversion. We used the physics of chiral quasi-bound states in the continuum to demonstrate the efficient and controllable emission of circularly polarized light from resonant metasurfaces. Exploiting intrinsic chirality and giant field enhancement, we revealed how to simultaneously modify and control spectra, radiation patterns, and spin angular momentum of photoluminescence and lasing without any spin injection. The superior characteristics of chiral emission and lasing promise multiple applications in nanophotonics and quantum optics. Description Another twist for metasurfaces Metasurfaces are specially designed arrays of dielectric components that transform the function of bulk optical components into thin films. Exploiting the physics of bulk states in the continuum for the highly efficient trapping of light, Zhang et al. demonstrate metasurfaces that operate as a source of chiral light (see the Perspective by Forbes). Using a dielectric metasurface doped with light-emitting molecules, they were able to produce chiral photoluminescence and lasing. This approach will be useful for the development of integrated optical devices. —ISO Cobalt carbonyl catalysts prove stable at lower gas pressure than previously thought.

W. Jin, Qifan Yang, L. Chang et al.

Driven by narrow-linewidth bench-top lasers, coherent optical systems spanning optical communications, metrology and sensing provide unrivalled performance. To transfer these capabilities from the laboratory to the real world, a key missing ingredient is a mass-produced integrated laser with superior coherence. Here, we bridge conventional semiconductor lasers and coherent optical systems using CMOS-foundry-fabricated microresonators with a high Q factor of over 260 million and finesse over 42,000. A five-orders-of-magnitude noise reduction in the pump laser is demonstrated, enabling a frequency noise of 0.2 Hz2 Hz−1 to be achieved in an electrically pumped integrated laser, with a corresponding short-term linewidth of 1.2 Hz. Moreover, the same configuration is shown to relieve the dispersion requirements for microcomb generation that have handicapped certain nonlinear platforms. The simultaneous realization of this high Q factor, highly coherent lasers and frequency combs using foundry-based technologies paves the way for volume manufacturing of a wide range of coherent optical systems. Using CMOS-ready ultra-high-Q microresonators, a highly coherent electrically pumped integrated laser with frequency noise of 0.2 Hz2 Hz−1, corresponding to a short-term linewidth of 1.2 Hz, is demonstrated. The device configuration is also found to relieve the dispersion requirements for microcomb generation that have limited certain nonlinear platforms.

A. Sirunyan, A. Tumasyan, W. Adam et al.

New sets of CMS underlying-event parameters (“tunes”) are presented for the pythia8 event generator. These tunes use the NNPDF3.1 parton distribution functions (PDFs) at leading (LO), next-to-leading (NLO), or next-to-next-to-leading (NNLO) orders in perturbative quantum chromodynamics, and the strong coupling evolution at LO or NLO. Measurements of charged-particle multiplicity and transverse momentum densities at various hadron collision energies are fit simultaneously to determine the parameters of the tunes. Comparisons of the predictions of the new tunes are provided for observables sensitive to the event shapes at LEP, global underlying event, soft multiparton interactions, and double-parton scattering contributions. In addition, comparisons are made for observables measured in various specific processes, such as multijet, Drell–Yan, and top quark-antiquark pair production including jet substructure observables. The simulation of the underlying event provided by the new tunes is interfaced to a higher-order matrix-element calculation. For the first time, predictions from pythia8 obtained with tunes based on NLO or NNLO PDFs are shown to reliably describe minimum-bias and underlying-event data with a similar level of agreement to predictions from tunes using LO PDF sets.

Beakcheol Jang, Myeonghwi Kim, Gaspard Harerimana et al.

Q-learning is arguably one of the most applied representative reinforcement learning approaches and one of the off-policy strategies. Since the emergence of Q-learning, many studies have described its uses in reinforcement learning and artificial intelligence problems. However, there is an information gap as to how these powerful algorithms can be leveraged and incorporated into general artificial intelligence workflow. Early Q-learning algorithms were unsatisfactory in several aspects and covered a narrow range of applications. It has also been observed that sometimes, this rather powerful algorithm learns unrealistically and overestimates the action values hence abating the overall performance. Recently with the general advances of machine learning, more variants of Q-learning like Deep Q-learning which combines basic Q learning with deep neural networks have been discovered and applied extensively. In this paper, we thoroughly explain how Q-learning evolved by unraveling the mathematical complexities behind it as well its flow from reinforcement learning family of algorithms. Improved variants are fully described, and we categorize Q-learning algorithms into single-agent and multi-agent approaches. Finally, we thoroughly investigate up-to-date research trends and key applications that leverage Q-learning algorithms.

Gaon An, Seungyong Moon, Jang-Hyun Kim et al.

Offline reinforcement learning (offline RL), which aims to find an optimal policy from a previously collected static dataset, bears algorithmic difficulties due to function approximation errors from out-of-distribution (OOD) data points. To this end, offline RL algorithms adopt either a constraint or a penalty term that explicitly guides the policy to stay close to the given dataset. However, prior methods typically require accurate estimation of the behavior policy or sampling from OOD data points, which themselves can be a non-trivial problem. Moreover, these methods under-utilize the generalization ability of deep neural networks and often fall into suboptimal solutions too close to the given dataset. In this work, we propose an uncertainty-based offline RL method that takes into account the confidence of the Q-value prediction and does not require any estimation or sampling of the data distribution. We show that the clipped Q-learning, a technique widely used in online RL, can be leveraged to successfully penalize OOD data points with high prediction uncertainties. Surprisingly, we find that it is possible to substantially outperform existing offline RL methods on various tasks by simply increasing the number of Q-networks along with the clipped Q-learning. Based on this observation, we propose an ensemble-diversified actor-critic algorithm that reduces the number of required ensemble networks down to a tenth compared to the naive ensemble while achieving state-of-the-art performance on most of the D4RL benchmarks considered.

Xinyue Chen, Che Wang, Zijian Zhou et al.

Using a high Update-To-Data (UTD) ratio, model-based methods have recently achieved much higher sample efficiency than previous model-free methods for continuous-action DRL benchmarks. In this paper, we introduce a simple model-free algorithm, Randomized Ensembled Double Q-Learning (REDQ), and show that its performance is just as good as, if not better than, a state-of-the-art model-based algorithm for the MuJoCo benchmark. Moreover, REDQ can achieve this performance using fewer parameters than the model-based method, and with less wall-clock run time. REDQ has three carefully integrated ingredients which allow it to achieve its high performance: (i) a UTD ratio>>1; (ii) an ensemble of Q functions; (iii) in-target minimization across a random subset of Q functions from the ensemble. Through carefully designed experiments, we provide a detailed analysis of REDQ and related model-free algorithms. To our knowledge, REDQ is the first successful model-free DRL algorithm for continuous-action spaces using a UTD ratio>>1.

Lujun Huang, Rong Jin, Chaobiao Zhou et al.

High quality(Q) factor optical resonators are indispensable for many photonic devices. While very large Q-factors can be obtained theoretically in guided-mode settings, free-space implementations suffer from various limitations on the narrowest linewidth in real experiments. Here, we propose a simple strategy to enable ultrahigh-Q guided-mode resonances by introducing a patterned perturbation layer on top of a multilayer-waveguide system. We demonstrate that the associated Q-factors are inversely proportional to the perturbation squared while the resonant wavelength can be tuned through material or structural parameters. We experimentally demonstrate such high-Q resonances at telecom wavelengths by patterning a low-index layer on top of a 220 nm silicon on insulator substrate. The measurements show Q-factors up to 2.39 × 105, comparable to the largest Q-factor obtained by topological engineering, while the resonant wavelength is tuned by varying the lattice constant of the top perturbation layer. Our results hold great promise for exciting applications like sensors and filters.

M. Achasov, X. Ai, R. Aliberti et al.

The super τ-charm facility (STCF) is an electron–positron collider proposed by the Chinese particle physics community. It is designed to operate in a center-of-mass energy range from 2 to 7 GeV with a peak luminosity of 0.5 × 1035 cm−2·s−1 or higher. The STCF will produce a data sample about a factor of 100 larger than that of the present τ-charm factory — the BEPCII, providing a unique platform for exploring the asymmetry of matter-antimatter (charge-parity violation), in-depth studies of the internal structure of hadrons and the nature of non-perturbative strong interactions, as well as searching for exotic hadrons and physics beyond the Standard Model. The STCF project in China is under development with an extensive R&D program. This document presents the physics opportunities at the STCF, describes conceptual designs of the STCF detector system, and discusses future plans for detector R&D and physics case studies.