4,641 research outputs found
Probabilistic abstract interpretation: From trace semantics to DTMC’s and linear regression
In order to perform probabilistic program analysis we need to consider probabilistic languages or languages with a probabilistic semantics, as well as a corresponding framework for the analysis which is able to accommodate probabilistic properties and properties of probabilistic computations. To this purpose we investigate the relationship between three different types of probabilistic semantics for a core imperative language, namely Kozen’s Fixpoint Semantics, our Linear Operator Semantics and probabilistic versions of Maximal Trace Semantics. We also discuss the relationship between Probabilistic Abstract Interpretation (PAI) and statistical or linear regression analysis. While classical Abstract Interpretation, based on Galois connection, allows only for worst-case analyses, the use of the Moore-Penrose pseudo inverse in PAI opens the possibility of exploiting statistical and noisy observations in order to analyse and identify various system properties
Quantifying Timing Leaks and Cost Optimisation
We develop a new notion of security against timing attacks where the attacker
is able to simultaneously observe the execution time of a program and the
probability of the values of low variables. We then show how to measure the
security of a program with respect to this notion via a computable estimate of
the timing leakage and use this estimate for cost optimisation.Comment: 16 pages, 2 figures, 4 tables. A shorter version is included in the
proceedings of ICICS'08 - 10th International Conference on Information and
Communications Security, 20-22 October, 2008 Birmingham, U
A Numerical Study of Partially Twisted Boundary Conditions
We investigate the use of partially twisted boundary conditions in a lattice
simulation with two degenerate flavours of improved Wilson sea quarks. The use
of twisted boundary conditions on a cubic volume (L^3) gives access to
components of hadronic momenta other than integer multiples of 2*pi/L. Partial
twisting avoids the need for new gluon configurations for every choice of
momentum, while, as recently demonstrated, keeping the finite-volume errors
exponentially small for the physical quantities investigated in this letter. In
this study we focus on the spectrum of pseudo scalar and vector mesons, on
their leptonic decay constants and on Z_P, the matrix element of the pseudo
scalar density between the pseudo scalar meson and the vacuum. The results
confirm the momentum shift imposed by these boundary conditions and in addition
demonstrate that they do not introduce any appreciable noise. We therefore
advocate the use of partially twisted boundary conditions in applications where
good momentum resolution is necessary.Comment: 10 pages, 3 figure
Estimating the Maximum Information Leakage
none2noopenAldini, Alessandro; DI PIERRO, A.Aldini, Alessandro; DI PIERRO, A
On dynamical probabilities, or: how to learn to shoot straight
© IFIP International Federation for Information Processing 2016.In order to support, for example, a quantitative analysis of various algorithms, protocols etc. probabilistic features have been introduced into a number of programming languages and calculi. It is by now quite standard to define the formal semantics of (various) probabilistic languages, for example, in terms of Discrete Time Markov Chains (DTMCs). In most cases however the probabilities involved are represented by constants, i.e. one deals with static probabilities. In this paper we investigate a semantical framework which allows for changing, i.e. dynamic probabilities which is still based on time-homogenous DTMCs, i.e. the transition matrix representing the semantics of a program does not change over time
An Algorithmic Approach to Quantum Field Theory
The lattice formulation provides a way to regularize, define and compute the
Path Integral in a Quantum Field Theory. In this paper we review the
theoretical foundations and the most basic algorithms required to implement a
typical lattice computation, including the Metropolis, the Gibbs sampling, the
Minimal Residual, and the Stabilized Biconjugate inverters. The main emphasis
is on gauge theories with fermions such as QCD. We also provide examples of
typical results from lattice QCD computations for quantities of
phenomenological interest.Comment: 44 pages, to be published in IJMP
Hamming distance kernelisation via topological quantum computation
We present a novel approach to computing Hamming distance and its kernelisation within Topological Quantum Computation. This approach is based on an encoding of two binary strings into a topological Hilbert space, whose inner product yields a natural Hamming distance kernel on the two strings. Kernelisation forges a link with the field of Machine Learning, particularly in relation to binary classifiers such as the Support Vector Machine (SVM). This makes our approach of potential interest to the quantum machine learning community
The second moment of the pion's distribution amplitude
We present preliminary results for the second moment of the pion's
distribution amplitude. The lattice formulation and the phenomenological
implications are briefly reviewed, with special emphasis on some subtleties
that arise when the Lorentz group is replaced by the hypercubic group. Having
analysed more than half of the available configurations, the result obtained is
\xi^2_L = 0.06 \pm 0.02.Comment: Lattice 99 (matrix elements), 3 page
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