We report, for the first time, the long-awaited detection of diffuse gamma rays with energies between 100 TeV and 1 PeV in the Galactic disk. Particularly, all gamma rays above 398 TeV are observed ...apart from known TeV gamma-ray sources and compatible with expectations from the hadronic emission scenario in which gamma rays originate from the decay of π^{0}'s produced through the interaction of protons with the interstellar medium in the Galaxy. This is strong evidence that cosmic rays are accelerated beyond PeV energies in our Galaxy and spread over the Galactic disk.
This paper describes a novel approach for incremental learning of human motion pattern primitives through online observation of human motion. The observed time series data stream is first ...stochastically segmented into potential motion primitive segments, based on the assumption that data belonging to the same motion primitive will have the same underlying distribution. The motion segments are then abstracted into a stochastic model representation and automatically clustered and organized. As new motion patterns are observed, they are incrementally grouped together into a tree structure, based on their relative distance in the model space. The tree leaves, which represent the most specialized learned motion primitives, are then passed back to the segmentation algorithm so that as the number of known motion primitives increases, the accuracy of the segmentation can also be improved. The combined algorithm is tested on a sequence of continuous human motion data that are obtained through motion capture, and demonstrates the performance of the proposed approach.
Abstract
Gamma rays from HESS J1849−000, a middle-aged TeV pulsar wind nebula (PWN), are observed by the Tibet air shower array and the muon detector array. The detection significance of gamma rays ...reaches 4.0
σ
and 4.4
σ
levels above 25 TeV and 100 TeV, respectively, in units of the Gaussian standard deviation
σ
. The energy spectrum measured between 40 TeV <
E
< 320 TeV for the first time is described with a simple power-law function of
dN
/
dE
=
(
2.86
±
1.44
)
×
10
−
16
(
E
/
40
TeV
)
−
2.24
±
0.41
TeV
−
1
cm
−
2
s
−
1
. The gamma-ray energy spectrum from the sub-TeV (
E
< 1 TeV) to sub-PeV (100 TeV <
E
< 1 PeV) ranges, including the results of previous studies, can be modeled with the leptonic scenario, i.e., inverse Compton scattering by high-energy electrons accelerated by the PWN of PSR J1849−0001. On the other hand, the gamma-ray energy spectrum can also be modeled with the hadronic scenario in which gamma rays are generated from the decay of neutral pions produced by collisions between accelerated cosmic-ray protons and the ambient molecular cloud found in the gamma-ray-emitting region. The cutoff energy of cosmic-ray protons
E
p,cut
is estimated as
log
10
(
E
p
,
cut
/
TeV
)
=
3.73
−
0.66
+
2.98
, suggesting that protons are accelerated up to the PeV energy range. Our study thus proposes that HESS J1849−000 should be further investigated as a new candidate as a Galactic PeV cosmic-ray accelerator, or “PeVatron.”
Abstract
HESS J1843–033 is a very high energy gamma-ray source whose origin remains unidentified. This work presents, for the first time, the energy spectrum of gamma rays beyond 100 TeV from the ...HESS J1843–033 region using the data recorded by the Tibet air shower array and its underground muon detector array. A gamma-ray source with an extension of 0.°34 ± 0.°12 is successfully detected above 25 TeV at (
α
,
δ
) = (281.°09 ± 0.°10, −3.°76 ± 0.°09) near HESS J1843–033 with a statistical significance of 6.2
σ
, and the source is named TASG J1844–038. The position of TASG J1844–038 is consistent with those of HESS J1843–033, eHWC J1842–035, and LHAASO J1843–0338. The measured gamma-ray energy spectrum in 25 TeV <
E
< 130 TeV is described with
dN
/
dE
=
(
9.70
±
1.89
)
×
10
−
16
(
E
/40 TeV)
−3.26±0.30
TeV
−1
cm
−2
s
−1
, and the spectral fit to the combined spectra of HESS J1843–033, LHAASO J1843–0338, and TASG J1844–038 implies the existence of a cutoff at 49.5 ± 9.0 TeV. Associations of TASG J1844–038 with SNR G28.6–0.1 and PSR J1844–0346 are also discussed in detail for the first time.
The ALPACA experiment is a new international project between Bolivia and Japan. It is going to consist of an 83,000 m2 surface air-shower array and a 5,400 m2 underground water Cherenkov muon ...detector array, and the experimental site is at Mt. Chacaltaya plateau at an altitude of 4,740 m. Its main target is to observe 100 TeV gamma rays and explore high-energy gamma-ray sources in the southern sky. This is because such high-energy gamma rays hold the key to identify the origin of cosmic rays at the knee region of the energy spectrum. So far many high-energy gamma-ray sources have been found in the southern sky. They are emitting gamma rays of several tens of TeV, so some of them could be PeVatrons which accelerate cosmic rays to PeV energy region in the Galaxy. By observing them in higher energy region, we will obtain new knowledge of cosmic-ray acceleration to the knee region, and discover new gamma-ray sources. As the prototype experiment of ALPACA, the ALPAQUITA experiment is now under construction. In a MC simulation, we found that ALPAQUITA has the ability of detecting bright gamma-ray sources in the southern hemisphere such as Vela X within 1 year.
This paper describes an imitative learning of driving time series data for intellectual cognition toward future automobiles. The driving pattern primitives consisting of states of the environment, ...vehicle and driver are symbolized by hidden Markov models (HMMs), which can be used for both recognition and generation of the driving patterns. The relationship among the HMMs can be represented by locating the HMMs in a multidimensional space. The contribution of each variable to the HMM space can be analyzed such that important variables can be selected out of the driving data in order to reduce the size of the HMMs. Moreover, this paper presents a hierarchical model with the HMMs abstracting the primitive driving patterns in the lower layer, and another HMMs abstracting the longterm contextual driving patterns which are representation in the HMM space. Tests with a driving simulator and a actual vehicle demonstrate not only the validity of symbolization of driving pattern primitives, recognition and generation, but also availability of key feature selection. The extended hierarchical model is also proved to have a potential to predict the driving data appropriately.
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