Zhang<i>et al.</i>Reply:

Zhang, J.; Levy, Peter M.; Zhang, S.; Antropov, Vladimir

doi:10.1103/physrevlett.96.019708

Cited by 226 publications

(377 citation statements)

References 4 publications

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“…Its linear field dependence suggests that the splitting might be spin related. Comparison with a Zeeman splitting using a free-electron g-factor g = 2 [24], dashed line in the inset of Fig. 4, yields a reasonable agreement.…”

Section: High-field Properties At the Charge Neutrality Pointsupporting

confidence: 56%

“…In this level, electrons and holes of opposite chirality reside simultaneously in two possible spin states resulting in a four-fold degenerate level. In experiments performed on highmobility SLG (made from Kish-graphite) a lifting of this chiral degeneracy was observed by the appearance of a ν = ±1 state [24,25]. Most other experiments [16,17,[26][27][28] did not find such state, which points to a larger disorder preventing spontaneous symmetry breaking [29].…”

Section: High-field Properties At the Charge Neutrality Pointmentioning

confidence: 95%

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High-Field Electronic Properties of Graphene

et al. 2010

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We have measured the energy gaps in single-layer and bilayer graphene by means of temperature dependent transport experiments in high magnetic fields up to 33 T. They follow the expected Landau level splitting when a finite level width is taken into account. The quantum Hall effect, hitherto only observed up to 30 K, remains visible up to 200 K in bilayers and even up to room temperature in singlelayer graphene. Our experiments in single-layer graphene show that the lowest Landau level, shared equally between electrons and holes at zero energy, becomes extremely narrow in high magnetic fields. It is this narrowing, together with the large Landau level splitting in graphene that leads to an extremely robust localization and makes the quantum Hall effect visible up to room temperature. In high magnetic fields (B > 20 T) we observe a strongly increasing resistance with decreasing temperature. These results are explained with field dependent splitting of the lowest Landau level of the order of a few Kelvin, as extracted from activated transport measurements.

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Section: High-field Properties At the Charge Neutrality Pointsupporting

confidence: 56%

Section: High-field Properties At the Charge Neutrality Pointmentioning

confidence: 95%

High-Field Electronic Properties of Graphene

et al. 2010

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“…Almost identical results were obtained by the CDF experiment, with a mixing significance of 3.8σ , from an integrated luminosity of about 1.5 fb −1 and a signal yield of (12.7 ± 0.3) × 10 3 events [7]. The Belle experiment, using 400 fb −1 of data with a signal yield of 4024 ± 88 events, was able to exclude the no-mixing hypothesis at only the 2.1σ level [8]. The results from the different experiments for the CP-conserving mixing analyses are reported in Table 1.…”

Section: Wrong-sign Decaysmentioning

confidence: 99%

Charm Mixing and CPV from the B Factories

Neri¹

2010

Proceedings of 12th International Conference on B-Physics at Hadron Machines — PoS(BEAUTY 2009)

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We report on recent results from B factories regarding charm mixing measurements and searches for CP violation in D 0 meson decays. Charm mixing is established with a significance exceeding 10 standard deviations when combining all the available measurements, while CP violation in D 0 decays is constrained below the percent level in decay modes such asThe results are based on 530 fb −1 and 950 fb −1 of BABAR and Belle data respectively, accumulated at a center-of-mass energy near 10.6 GeV, overall containing about 1.9 × 10 9 e + e − → cc events. Data have been collected with the BABAR detector at the PEP-II asymmetric-energy B Factory at SLAC, and with the Belle detector at the KEKB asymmetricenergy B Factory at KEK.

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“…Zhang and Small (2006), 4 Yang (2008) 5 and 6 use linear correlation coefficient as the criterion to connect the nodes. Shimada et al (2008), 7 Xu et al (2008), 8 Liu and Zhou (2009), 9 and Donner et al (2010) 10 construct the networks based on Recurrence Plot and k-nearest neighbor.…”

Section: Introductionmentioning

confidence: 99%

“…A node in the generated network graph can refer to an original data point or a small original data series. Zhang and Small (2006) 4 define a single node which represents a cycle according to the local minimum (or maximum). In this paper, we define a node as a point in the reconstructed phase space of different dimension, i.e., a series segment of different length.…”

Section: Introductionmentioning

confidence: 99%

A comparison of two methods for modeling large-scale data from time series as complex networks

2011

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In this paper, we compare two methods of mapping time series data to complex networks based on correlation coefficient and distance, respectively. These methods make use of two different physical aspects of large-scale data. We find that the method based on correlation coefficient cannot distinguish the randomness of a chaotic series from a purely random series, and it cannot express the certainty of chaos. The method based on distance can express the certainty of a chaotic series and can distinguish a chaotic series from a random series easily. Therefore, the distance method can be helpful in analyzing chaotic systems and random systems. We have also discussed the effectiveness of the distance method with noisy data

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Zhanget al.Reply:

Cited by 226 publications

References 4 publications

High-Field Electronic Properties of Graphene

High-Field Electronic Properties of Graphene

Charm Mixing and CPV from the B Factories

A comparison of two methods for modeling large-scale data from time series as complex networks

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