253 research outputs found
Reconstruction of Causal Networks by Set Covering
We present a method for the reconstruction of networks, based on the order of
nodes visited by a stochastic branching process. Our algorithm reconstructs a
network of minimal size that ensures consistency with the data. Crucially, we
show that global consistency with the data can be achieved through purely local
considerations, inferring the neighbourhood of each node in turn. The
optimisation problem solved for each individual node can be reduced to a Set
Covering Problem, which is known to be NP-hard but can be approximated well in
practice. We then extend our approach to account for noisy data, based on the
Minimum Description Length principle. We demonstrate our algorithms on
synthetic data, generated by an SIR-like epidemiological model.Comment: Under consideration for the ECML PKDD 2010 conferenc
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Generating Bounds for the Ground State Energy of the Infinite Quantum Lens Potential
Moment based methods have produced efficient multiscale quantization
algorithms for solving singular perturbation/strong coupling problems. One of
these, the Eigenvalue Moment Method (EMM), developed by Handy et al (Phys. Rev.
Lett.{\bf 55}, 931 (1985); ibid, {\bf 60}, 253 (1988b)), generates converging
lower and upper bounds to a specific discrete state energy, once the signature
property of the associated wavefunction is known. This method is particularly
effective for multidimensional, bosonic ground state problems, since the
corresponding wavefunction must be of uniform signature, and can be taken to be
positive. Despite this, the vast majority of problems studied have been on
unbounded domains. The important problem of an electron in an infinite quantum
lens potential defines a challenging extension of EMM to systems defined on a
compact domain. We investigate this here, and introduce novel modifications to
the conventional EMM formalism that facilitate its adaptability to the required
boundary conditions.Comment: Submitted to J. Phys.
Generating Converging Bounds to the (Complex) Discrete States of the Hamiltonian
The Eigenvalue Moment Method (EMM), Handy (2001), Handy and Wang (2001)) is
applied to the Hamiltonian, enabling
the algebraic/numerical generation of converging bounds to the complex energies
of the states, as argued (through asymptotic methods) by Delabaere and
Trinh (J. Phys. A: Math. Gen. {\bf 33} 8771 (2000)).Comment: Submitted to J. Phys.
Generating Converging Eigenenergy Bounds for the Discrete States of the -ix^3 Non-Hermitian Potential
Recent investigations by Bender and Boettcher (Phys. Rev. Lett 80, 5243
(1998)) and Mezincescu (J. Phys. A. 33, 4911 (2000)) have argued that the
discrete spectrum of the non-hermitian potential should be real.
We give further evidence for this through a novel formulation which transforms
the general one dimensional Schrodinger equation (with complex potential) into
a fourth order linear differential equation for . This permits the
application of the Eigenvalue Moment Method, developed by Handy, Bessis, and
coworkers (Phys. Rev. Lett. 55, 931 (1985);60, 253 (1988a,b)), yielding rapidly
converging lower and upper bounds to the low lying discrete state energies. We
adapt this formalism to the pure imaginary cubic potential, generating tight
bounds for the first five discrete state energy levels.Comment: Work to appear in J. Phys. A: Math & Ge
Extension of a Spectral Bounding Method to Complex Rotated Hamiltonians, with Application to
We show that a recently developed method for generating bounds for the
discrete energy states of the non-hermitian potential (Handy 2001) is
applicable to complex rotated versions of the Hamiltonian. This has important
implications for extension of the method in the analysis of resonant states,
Regge poles, and general bound states in the complex plane (Bender and
Boettcher (1998)).Comment: Submitted to J. Phys.
Overcoming controllability problems in distributed testing from an input output transition system
This is the Pre-print version of the Article. The official published version can be accessed from the link below - Copyright @ 2012 Springer VerlagThis paper concerns the testing of a system with physically distributed interfaces, called ports, at which it interacts with its environment. We place a tester at each port and the tester at port p observes events at p only. This can lead to controllability problems, where the observations made by the tester at a port p are not sufficient for it to be able to know when to send an input. It is known that there are test objectives, such as executing a particular transition, that cannot be achieved if we restrict attention to test cases that have no controllability problems. This has led to interest in schemes where the testers at the individual ports send coordination messages to one another through an external communications network in order to overcome controllability problems. However, such approaches have largely been studied in the context of testing from a deterministic finite state machine. This paper investigates the use of coordination messages to overcome controllability problems when testing from an input output transition system and gives an algorithm for introducing sufficient messages. It also proves that the problem of minimising the number of coordination messages used is NP-hard
Necessary and sufficient conditions of solution uniqueness in minimization
This paper shows that the solutions to various convex minimization
problems are \emph{unique} if and only if a common set of conditions are
satisfied. This result applies broadly to the basis pursuit model, basis
pursuit denoising model, Lasso model, as well as other models that
either minimize or impose the constraint , where
is a strictly convex function. For these models, this paper proves that,
given a solution and defining I=\supp(x^*) and s=\sign(x^*_I),
is the unique solution if and only if has full column rank and there
exists such that and for . This
condition is previously known to be sufficient for the basis pursuit model to
have a unique solution supported on . Indeed, it is also necessary, and
applies to a variety of other models. The paper also discusses ways to
recognize unique solutions and verify the uniqueness conditions numerically.Comment: 6 pages; revised version; submitte
MaxPre : An Extended MaxSAT Preprocessor
We describe MaxPre, an open-source preprocessor for (weighted partial) maximum satisfiability (MaxSAT). MaxPre implements both SAT-based and MaxSAT-specific preprocessing techniques, and offers solution reconstruction, cardinality constraint encoding, and an API for tight integration into SAT-based MaxSAT solvers.Peer reviewe
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