106 research outputs found
Global linear stability analysis of kinetic Trapped Ion Mode (TIM) turbulence in tokamak plasma using spectral method
Trapped ion modes (TIM) which belong to the family of ion temperature
gradient (ITG) modes, is one of the important ingredients in heat turbulent
transport at the ion scale in tokamak plasmas. It is essential to properly
estimate their linear growth rate to understand their influence on ion-scale
turbulent transport. A global linear analysis of a reduced gyro-bounce kinetic
model for trapped particle modes is performed, and a spectral method is
proposed to solve the dispersion relation. Importantly, the radial profile of
the particle drift velocity is taken into account in the linear analysis by
considering the exact magnetic flux {\psi} dependency of the equilibrium
Hamiltonian H_{eq}({\psi}) in the quasi-neutrality equation and equilibrium
gyro-bounce averaged distribution function F_{eq} . Using this spectral method,
linear growth-rates of TIM instability in presence of different temperature
profiles and precession frequencies of trapped ions, with an approximated
constant Hamiltonian and the exact {\psi} dependent equilibrium Hamiltonian,
are investigated. The growth-rate depends on the logarithmic gradient of
temperature \kappa_{T} , density \kappa_{n} and equilibrium Hamiltonian
\kappa_{\Lambda} . With the exact {\psi} dependent Hamiltonian, the growth
rates and potential profiles are modified significantly, compared to the cases
with approximated constant Hamiltonian. All the results from the global linear
analysis agree with a semi-Lagrangian based linear Vlasov solver with a good
accuracy. This spectral method is very fast and requires very less computation
resources compared to a linear version of Vlasov-solver based on a
semi-Lagrangian scheme
What controls the isotopic composition of Greenland surface snow?
International audienceWater stable isotopes in Greenland ice core data provide key paleoclimatic information, and have been compared with precipitation isotopic composition simulated by isotopically enabled atmospheric models. However, post-depositional processes linked with snow metamorphism remain poorly documented. For this purpose, monitoring of the isotopic composition (d18O, dD) of near-surface water vapor, precipitation and samples of the top (0.5 cm) snow surface has been conducted during two summers (2011-2012) at NEEM, NW Greenland. The samples also include a subset of 17O-excess measurements over 4 days, and the measurements span the 2012 Greenland heat wave. Our observations are consistent with calculations assuming isotopic equilibrium between surface snow and water vapor. We observe a strong correlation between near-surface vapor d18O and air temperature (0.85 ± 0.11‰ °C-1 (R = 0.76) for 2012). The correlation with air temperature is not observed in precipitation data or surface snow data. Deuterium excess (d-excess) is strongly anti-correlated with d18O with a stronger slope for vapor than for precipitation and snow surface data. During nine 1-5-day periods between precipitation events, our data demonstrate parallel changes of d18O and d-excess in surface snow and near-surface vapor. The changes in d18O of the vapor are similar or larger than those of the snow d18O. It is estimated using the CROCUS snow model that 6 to 20% of the surface snow mass is exchanged with the atmosphere. In our data, the sign of surface snow isotopic changes is not related to the sign or magnitude of sublimation or deposition. Comparisons with atmospheric models show that day-to-day variations in near-surface vapor isotopic composition are driven by synoptic variations and changes in air mass trajectories and distillation histories. We suggest that, in between precipitation events, changes in the surface snow isotopic composition are driven by these changes in near-surface vapor isotopic composition. This is consistent with an estimated 60% mass turnover of surface snow per day driven by snow recrystallization processes under NEEM summer surface snow temperature gradients. Our findings have implications for ice core data interpretation and model-data comparisons, and call for further process studies. © Author(s) 2014
High spatial resolution imaging of methane and other trace gases with the airborne Hyperspectral Thermal Emission Spectrometer (HyTES)
Currently large uncertainties exist associated with the
attribution and quantification of fugitive emissions of criteria pollutants
and greenhouse gases such as methane across large regions and key economic
sectors. In this study, data from the airborne Hyperspectral Thermal
Emission Spectrometer (HyTES) have been used to develop robust and reliable
techniques for the detection and wide-area mapping of emission plumes of
methane and other atmospheric trace gas species over challenging and diverse
environmental conditions with high spatial resolution that permits direct
attribution to sources. HyTES is a pushbroom imaging spectrometer with high
spectral resolution (256 bands from 7.5 to 12 µm), wide swath (1–2 km),
and high spatial resolution (∼ 2 m at 1 km altitude) that
incorporates new thermal infrared (TIR) remote sensing technologies. In this
study we introduce a hybrid clutter matched filter (CMF) and plume dilation
algorithm applied to HyTES observations to efficiently detect and
characterize the spatial structures of individual plumes of CH4,
H2S, NH3, NO2, and SO2 emitters. The sensitivity and
field of regard of HyTES allows rapid and frequent airborne surveys of large
areas including facilities not readily accessible from the surface. The
HyTES CMF algorithm produces plume intensity images of methane and other
gases from strong emission sources. The combination of high spatial
resolution and multi-species imaging capability provides source attribution
in complex environments. The CMF-based detection of strong emission sources
over large areas is a fast and powerful tool needed to focus on more
computationally intensive retrieval algorithms to quantify emissions with
error estimates, and is useful for expediting mitigation efforts and
addressing critical science questions
Using continuous measurements of near-surface atmospheric water vapour isotopes to document snow-air interactions
Water stable isotope data from Greenland ice cores provide key paleoclimatic information. However, postdepositional processes linked with snow metamorphism remain poorly documented. For this purpose, a monitoring of the isotopic composition δ18O and δD at several height levels (up to 13 meter) of near-surface water vapor, precipitation and snow in the first 0.5 cm from the surface has been conducted during three summers (2010-2012) at NEEM, NW Greenland. We observe a clear diurnal cycle in both the value and gradient of the isotopic composition of the water vapor above the snow surface. The diurnal amplitude in δD is found to be ~15‰. The diurnal isotopic composition follows the absolute humidity cycle. This indicates a large flux of vapor from the snow surface to the atmosphere during the daily warming and reverse flux during the daily cooling. The isotopic measurements of the flux of water vapor above the snow give new insights into the post depositional processes of the isotopic composition of the snow. During nine 1-5 days periods between precipitation events, our data demonstrate parallel changes of δ18O and d-excess in surface snow and near-surface vapor. The changes in δ18O of the vapor are similar or larger than those of the snow δ18O. It is estimated using the CROCUS snow model that 6 to 20% of the surface snow mass is exchanged with the atmosphere. In our data, the sign of surface snow isotopic changes is not related to the sign or magnitude of sublimation or deposition. Comparisons with atmospheric models show that day-to-day variations in near-surface vapor isotopic composition are driven by synoptic variations and changes in air mass trajectories and distillation histories. We suggest that, in-between precipitation events, changes in the surface snow isotopic composition are driven by these changes in near-surface vapor isotopic composition. This is consistent with an estimated 60% mass turnover of surface snow per day driven by snow recrystallization processes associated with temperature gradients near the snow surface. Our findings have implications for ice core data interpretation and model-data comparisons, and call for further process studies
Rerandomizable Signatures under Standard Assumption
The Camenisch-Lysyanskaya rerandomizable signature (CL-RRS) scheme is an important tool in the construction of privacy preserving protocols. One of the limitations of CL-RRS is that the signature size is linear in the number of messages to be signed. In 2016, Pointcheval-Sanders introduced a variant of rerandomizable signature (PS-RRS) scheme which removes the above limitation. However, the security of PS-RRS scheme was proved under an interactive assumption. In 2018, Pointcheval-Sanders improved this to give a reduction under a parameterized assumption.
In 2012, Gerbush et al.\ introduced the dual-form signature technique to remove the dependency on interactive/parameterized assumption. They applied this technique on the CL-RRS scheme (for single message) and proved its unforgeability under static assumptions instead of the interactive assumption used in the original work but in the symmetric composite-order pairing setting.
In this work, we realize a fully rerandomizable signature scheme in the prime order setting without random oracle based on the SXDH assumption. The signature structure is derived from Ghadafi\u27s structure-preserving signature. We first apply the dual-form signature technique to obtain a composite-order variant, called \texttt{RRSc}. A signature in \texttt{RRSc} consists of only two group elements and is thus independent of the message block length. The security of the proposed scheme is based on subgroup hiding assumptions. Then we use the dual pairing vector space framework to obtain a prime-order
variant called \texttt{RRS} and prove its security under the SXDH assumption
Adaptively Simulation-Secure Attribute-Hiding Predicate Encryption
This paper demonstrates how to achieve simulation-based strong attribute hiding against adaptive adversaries
for predicate encryption (PE) schemes supporting expressive predicate families under standard
computational assumptions in bilinear groups. Our main result is a simulation-based adaptively strongly
partially-hiding PE (PHPE) scheme for predicates computing arithmetic branching programs (ABP) on
public attributes, followed by an inner-product predicate on private attributes. This simultaneously generalizes
attribute-based encryption (ABE) for boolean formulas and ABP’s as well as strongly attribute-hiding
PE schemes for inner products. The proposed scheme is proven secure for any a priori bounded
number of ciphertexts and an unbounded (polynomial) number of decryption keys, which is the best possible
in the simulation-based adaptive security framework. This directly implies that our construction
also achieves indistinguishability-based strongly partially-hiding security against adversaries requesting an
unbounded (polynomial) number of ciphertexts and decryption keys. The security of the proposed scheme
is derived under (asymmetric version of) the well-studied decisional linear (DLIN) assumption. Our work
resolves an open problem posed by Wee in TCC 2017, where his result was limited to the semi-adaptive
setting. Moreover, our result advances the current state of the art in both the fields of simulation-based
and indistinguishability-based strongly attribute-hiding PE schemes. Our main technical contribution lies
in extending the strong attribute hiding methodology of Okamoto and Takashima [EUROCRYPT 2012,
ASIACRYPT 2012] to the framework of simulation-based security and beyond inner products
Asymptotic complexities of discrete logarithm algorithms in pairing-relevant finite fields
International audienceWe study the discrete logarithm problem at the boundary case between small and medium characteristic finite fields, which is precisely the area where finite fields used in pairing-based cryptosystems live. In order to evaluate the security of pairing-based protocols, we thoroughly analyze the complexity of all the algorithms that coexist at this boundary case: the Quasi-Polynomial algorithms, the Number Field Sieve and its many variants, and the Function Field Sieve. We adapt the latter to the particular case where the extension degree is composite, and show how to lower the complexity by working in a shifted function field. All this study finally allows us to give precise values for the characteristic asymptotically achieving the highest security level for pairings. Surprisingly enough, there exist special characteristics that are as secure as general ones
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A first chronology for the North Greenland Eemian Ice Drilling (NEEM) ice core
A stratigraphy-based chronology for the North Greenland Eemian Ice Drilling (NEEM) ice core has been derived by transferring the annual layer counted Greenland Ice Core Chronology 2005 (GICC05) and its model extension (GICC05modelext) from the NGRIP core to the NEEM core using 787 match points of mainly volcanic origin identified in the electrical conductivity measurement (ECM) and dielectrical profiling (DEP) records. Tephra horizons found in both the NEEM and NGRIP ice cores are used to test the matching based on ECM and DEP and provide five additional horizons used for the timescale transfer. A thinning function reflecting the accumulated strain along the core has been determined using a Dansgaard–Johnsen flow model and an isotope-dependent accumulation rate parameterization. Flow parameters are determined from Monte Carlo analysis constrained by the observed depth-age horizons. In order to construct a chronology for the gas phase, the ice age–gas age difference (Δage) has been reconstructed using a coupled firn densification-heat diffusion model. Temperature and accumulation inputs to the Δage model, initially derived from the water isotope proxies, have been adjusted to optimize the fit to timing constraints from δ¹⁵N of nitrogen and high-resolution methane data during the abrupt onset of Greenland interstadials. The ice and gas chronologies and the corresponding thinning function represent the first chronology for the NEEM core, named GICC05modelext-NEEM-1. Based on both the flow and firn modelling results, the accumulation history for the NEEM site has been reconstructed. Together, the timescale and accumulation reconstruction provide the necessary basis for further analysis of the records from NEEM.This is the publisher’s final pdf. The published article is copyrighted by the author(s) and published by Copernicus Publications on behalf of the European Geosciences Union. The published article can be found at: http://www.clim-past.net/volumes_and_issues.html
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