506 research outputs found
On the criticality of inferred models
Advanced inference techniques allow one to reconstruct the pattern of
interaction from high dimensional data sets. We focus here on the statistical
properties of inferred models and argue that inference procedures are likely to
yield models which are close to a phase transition. On one side, we show that
the reparameterization invariant metrics in the space of probability
distributions of these models (the Fisher Information) is directly related to
the model's susceptibility. As a result, distinguishable models tend to
accumulate close to critical points, where the susceptibility diverges in
infinite systems. On the other, this region is the one where the estimate of
inferred parameters is most stable. In order to illustrate these points, we
discuss inference of interacting point processes with application to financial
data and show that sensible choices of observation time-scales naturally yield
models which are close to criticality.Comment: 6 pages, 2 figures, version to appear in JSTA
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Secondary organic aerosol formation from in-use motor vehicle emissions using a potential aerosol mass reactor.
Secondary organic aerosol (SOA) formation from in-use vehicle emissions was investigated using a potential aerosol mass (PAM) flow reactor deployed in a highway tunnel in Pittsburgh, Pennsylvania. Experiments consisted of passing exhaust-dominated tunnel air through a PAM reactor over integrated hydroxyl radical (OH) exposures ranging from ⌠0.3 to 9.3 days of equivalent atmospheric oxidation. Experiments were performed during heavy traffic periods when the fleet was at least 80% light-duty gasoline vehicles on a fuel-consumption basis. The peak SOA production occurred after 2-3 days of equivalent atmospheric oxidation. Additional OH exposure decreased the SOA production presumably due to a shift from functionalization to fragmentation dominated reaction mechanisms. Photo-oxidation also produced substantial ammonium nitrate, often exceeding the mass of SOA. Analysis with an SOA model highlight that unspeciated organics (i.e., unresolved complex mixture) are a very important class of precursors and that multigenerational processing of both gases and particles is important at longer time scales. The chemical evolution of the organic aerosol inside the PAM reactor appears to be similar to that observed in the atmosphere. The mass spectrum of the unoxidized primary organic aerosol closely resembles ambient hydrocarbon-like organic aerosol (HOA). After aging the exhaust equivalent to a few hours of atmospheric oxidation, the organic aerosol most closely resembles semivolatile oxygenated organic aerosol (SV-OOA) and then low-volatility organic aerosol (LV-OOA) at higher OH exposures. Scaling the data suggests that mobile sources contribute ⌠2.9 ± 1.6 Tg SOA yr(-1) in the United States, which is a factor of 6 greater than all mobile source particulate matter emissions reported by the National Emissions Inventory. This highlights the important contribution of SOA formation from vehicle exhaust to ambient particulate matter concentrations in urban areas
Intrinsic limitations of inverse inference in the pairwise Ising spin glass
We analyze the limits inherent to the inverse reconstruction of a pairwise
Ising spin glass based on susceptibility propagation. We establish the
conditions under which the susceptibility propagation algorithm is able to
reconstruct the characteristics of the network given first- and second-order
local observables, evaluate eventual errors due to various types of noise in
the originally observed data, and discuss the scaling of the problem with the
number of degrees of freedom
The Effect of Nonstationarity on Models Inferred from Neural Data
Neurons subject to a common non-stationary input may exhibit a correlated
firing behavior. Correlations in the statistics of neural spike trains also
arise as the effect of interaction between neurons. Here we show that these two
situations can be distinguished, with machine learning techniques, provided the
data are rich enough. In order to do this, we study the problem of inferring a
kinetic Ising model, stationary or nonstationary, from the available data. We
apply the inference procedure to two data sets: one from salamander retinal
ganglion cells and the other from a realistic computational cortical network
model. We show that many aspects of the concerted activity of the salamander
retinal neurons can be traced simply to the external input. A model of
non-interacting neurons subject to a non-stationary external field outperforms
a model with stationary input with couplings between neurons, even accounting
for the differences in the number of model parameters. When couplings are added
to the non-stationary model, for the retinal data, little is gained: the
inferred couplings are generally not significant. Likewise, the distribution of
the sizes of sets of neurons that spike simultaneously and the frequency of
spike patterns as function of their rank (Zipf plots) are well-explained by an
independent-neuron model with time-dependent external input, and adding
connections to such a model does not offer significant improvement. For the
cortical model data, robust couplings, well correlated with the real
connections, can be inferred using the non-stationary model. Adding connections
to this model slightly improves the agreement with the data for the probability
of synchronous spikes but hardly affects the Zipf plot.Comment: version in press in J Stat Mec
Production of Secondary Organic Aerosol During Aging of Biomass Burning Smoke From Fresh Fuels and Its Relationship to VOC Precursors
After smoke from burning biomass is emitted into the atmosphere, chemical and physical processes change the composition and amount of organic aerosol present in the aged, diluted plume. During the fourth Fire Lab at Missoula Experiment, we performed smog-chamber experiments to investigate formation of secondary organic aerosol (SOA) and multiphase oxidation of primary organic aerosol (POA). We simulated atmospheric aging of diluted smoke from a variety of biomass fuels while measuring particle composition using high-resolution aerosol mass spectrometry. We quantified SOA formation using a tracer ion for low-volatility POA as a reference standard (akin to a naturally occurring internal standard). These smoke aging experiments revealed variable organic aerosol (OA) enhancements, even for smoke from similar fuels and aging mechanisms. This variable OA enhancement correlated well with measured differences in the amounts of emitted volatile organic compounds (VOCs) that could subsequently be oxidized to form SOA. For some aging experiments, we were able to predict the SOA production to within a factor of 2 using a fuel-specific VOC emission inventory that was scaled by burn-specific toluene measurements. For fires of coniferous fuels that were dominated by needle burning, volatile biogenic compounds were the dominant precursor class. For wiregrass fires, furans were the dominant SOA precursors. We used a POA tracer ion to calculate the amount of mass lost due to gas-phase oxidation and subsequent volatilization of semivolatile POA. Less than 5% of the POA mass was lost via multiphase oxidation-driven evaporation during up to 2 hr of equivalent atmospheric oxidation
A Very High Speed True Random Number Generator with Entropy Assessment
International audienceThe proposed true random number generator (TRNG) exploits the jitter of events propagating in a self-timed ring (STR) to generate random bit sequences at a very high bit rate. It takes advantage of a special feature of STRs that allows the time elapsed between successive events to be set as short as needed, even in the order of picoseconds. If the time interval between the events is set in concordance with the clock jitter magnitude, a simple entropy extraction scheme can be applied to generate random numbers. The proposed STR-based TRNG (STRNG) follows AIS31 recommendations: by using the proposed stochastic model, designers can compute a lower entropy bound as a function of the STR characteristics (number of stages, oscillation period and jitter magnitude). Using the resulting entropy assessment, they can then set the compression rate in the arithmetic post-processing block to reach the required security level determined by the entropy per output bit. Implementation of the generator in two FPGA families confirmed its feasibility in digital technologies and also confirmed it can provide high quality random bit sequences that pass the statistical tests required by AIS31 at rates as high as 200 Mbit/s
Production of Secondary Organic Aerosol During Aging of Biomass Burning Smoke From Fresh Fuels and Its Relationship to VOC Precursors
After smoke from burning biomass is emitted into the atmosphere, chemical and physical processes change the composition and amount of organic aerosol present in the aged, diluted plume. During the fourth Fire Lab at Missoula Experiment, we performed smogâchamber experiments to investigate formation of secondary organic aerosol (SOA) and multiphase oxidation of primary organic aerosol (POA). We simulated atmospheric aging of diluted smoke from a variety of biomass fuels while measuring particle composition using highâresolution aerosol mass spectrometry. We quantified SOA formation using a tracer ion for lowâvolatility POA as a reference standard (akin to a naturally occurring internal standard). These smoke aging experiments revealed variable organic aerosol (OA) enhancements, even for smoke from similar fuels and aging mechanisms. This variable OA enhancement correlated well with measured differences in the amounts of emitted volatile organic compounds (VOCs) that could subsequently be oxidized to form SOA. For some aging experiments, we were able to predict the SOA production to within a factor of 2 using a fuelâspecific VOC emission inventory that was scaled by burnâspecific toluene measurements. For fires of coniferous fuels that were dominated by needle burning, volatile biogenic compounds were the dominant precursor class. For wiregrass fires, furans were the dominant SOA precursors. We used a POA tracer ion to calculate the amount of mass lost due to gasâphase oxidation and subsequent volatilization of semivolatile POA. Less than 5% of the POA mass was lost via multiphase oxidationâdriven evaporation during up to 2 hr of equivalent atmospheric oxidation
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