2,458 research outputs found
Enhancing Reuse of Constraint Solutions to Improve Symbolic Execution
Constraint solution reuse is an effective approach to save the time of
constraint solving in symbolic execution. Most of the existing reuse approaches
are based on syntactic or semantic equivalence of constraints; e.g. the Green
framework is able to reuse constraints which have different representations but
are semantically equivalent, through canonizing constraints into syntactically
equivalent normal forms. However, syntactic/semantic equivalence is not a
necessary condition for reuse--some constraints are not syntactically or
semantically equivalent, but their solutions still have potential for reuse.
Existing approaches are unable to recognize and reuse such constraints.
In this paper, we present GreenTrie, an extension to the Green framework,
which supports constraint reuse based on the logical implication relations
among constraints. GreenTrie provides a component, called L-Trie, which stores
constraints and solutions into tries, indexed by an implication partial order
graph of constraints. L-Trie is able to carry out logical reduction and logical
subset and superset querying for given constraints, to check for reuse of
previously solved constraints. We report the results of an experimental
assessment of GreenTrie against the original Green framework, which shows that
our extension achieves better reuse of constraint solving result and saves
significant symbolic execution time.Comment: this paper has been submitted to conference ISSTA 201
COFFE: a code for the full-sky relativistic galaxy correlation function
We present a public version of the code COFFE (COrrelation Function Full-sky
Estimator) available at https://github.com/JCGoran/coffe. The code computes the
galaxy two-point correlation function and its multipoles in linear perturbation
theory, including all relativistic and wide angle corrections. COFFE also
calculates the covariance matrix for two physically relevant estimators of the
correlation function multipoles. We illustrate the usefulness of our code by a
simple but relevant example: a forecast of the detectability of the lensing
signal in the multipoles of the two-point function. In particular, we show that
lensing should be detectable in the multipoles of the two-point function, with
a signal-to-noise larger than 10, in future surveys like Euclid or the SKA.Comment: Code available at https://github.com/JCGoran/coff
Effects of baryons on weak lensing peak statistics
Upcoming weak-lensing surveys have the potential to become leading
cosmological probes provided all systematic effects are under control.
Recently, the ejection of gas due to feedback energy from active galactic
nuclei (AGN) has been identified as major source of uncertainty, challenging
the success of future weak-lensing probes in terms of cosmology. In this paper
we investigate the effects of baryons on the number of weak-lensing peaks in
the convergence field. Our analysis is based on full-sky convergence maps
constructed via light-cones from -body simulations, and we rely on the
baryonic correction model of Schneider et al. (2019) to model the baryonic
effects on the density field. As a result we find that the baryonic effects
strongly depend on the Gaussian smoothing applied to the convergence map. For a
DES-like survey setup, a smoothing of arcmin is sufficient
to keep the baryon signal below the expected statistical error. Smaller
smoothing scales lead to a significant suppression of high peaks (with
signal-to-noise above 2), while lower peaks are not affected. The situation is
more severe for a Euclid-like setup, where a smoothing of
arcmin is required to keep the baryonic suppression signal below the
statistical error. Smaller smoothing scales require a full modelling of
baryonic effects since both low and high peaks are strongly affected by
baryonic feedback.Comment: 22 pages, 11 figures, JCAP accepte
Proceedings of the second "international Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST'14)
The implicit objective of the biennial "international - Traveling Workshop on
Interactions between Sparse models and Technology" (iTWIST) is to foster
collaboration between international scientific teams by disseminating ideas
through both specific oral/poster presentations and free discussions. For its
second edition, the iTWIST workshop took place in the medieval and picturesque
town of Namur in Belgium, from Wednesday August 27th till Friday August 29th,
2014. The workshop was conveniently located in "The Arsenal" building within
walking distance of both hotels and town center. iTWIST'14 has gathered about
70 international participants and has featured 9 invited talks, 10 oral
presentations, and 14 posters on the following themes, all related to the
theory, application and generalization of the "sparsity paradigm":
Sparsity-driven data sensing and processing; Union of low dimensional
subspaces; Beyond linear and convex inverse problem; Matrix/manifold/graph
sensing/processing; Blind inverse problems and dictionary learning; Sparsity
and computational neuroscience; Information theory, geometry and randomness;
Complexity/accuracy tradeoffs in numerical methods; Sparsity? What's next?;
Sparse machine learning and inference.Comment: 69 pages, 24 extended abstracts, iTWIST'14 website:
http://sites.google.com/site/itwist1
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