2,228 research outputs found
Combination of measurements and the BLUE method
The most accurate method to combine measurement from different experiments is
to build a combined likelihood function and use it to perform the desired
inference. This is not always possible for various reasons, hence approximate
methods are often convenient. Among those, the best linear unbiased estimator
(BLUE) is the most popular, allowing to take into account individual
uncertainties and their correlations. The method is unbiased by construction if
the true uncertainties and their correlations are known, but it may exhibit a
bias if uncertainty estimates are used in place of the true ones, in particular
if those estimated uncertainties depend on measured values. In those cases, an
iterative application of the BLUE method may reduce the bias of the combined
measurement.Comment: 10 pages, 4 figures, proceedings of the XIIth Quark Confinement and
Hadron Spectrum conference, 28/8-2/9 2016, Tessaloniki, Greec
Evaluation of the Beam Background Contribution to the pp Minimum Bias Sample Used for First Physics
The note describes the beam background conditions during first physics data taking with ALICE and the strategy for the evaluation of the LHC beam background contribution to the minimum bias event sample used for first physics
Simulation and Track Reconstruction Techniques for the J-PARC muon g-2 experiment
The Muon g-2/EDM proposed experiment at J-PARC is a promising and innovative attempt at the field of Precision Physics. The sensitivity goal of 0.1 ppm will test the limits of our current understanding, and may probe for Beyond the Standard Model observations. This paper seeks out to investigate the computational techniques required by the experiment. The GEANT4 [1] framework was used to simulate the detector setup, according to the experiment’s Conceptual Design Report (CDR) [2]. This allowed to observe the event hierarchy in different energies, generate signal hit data, and construct an event-selection algorithm. ROOT and GDML enabled us to use the geometry and parsed output data in a platform-independent way. Using techniques pertaining to Machine Learning and Image Feature extraction, such as the Canny Edge detection and the Hough Transform, we were able to construct a generic representation of ‘track families’ from each event category. Finally, the modular GENFIT2 [3] framework was used to implement the Kalman Filter [4] along with an Deterministic Annealing Filter (DAF) [5] and the Runge-Kutta stepper to reconstruct tracks from a few digitized, smeared singular event data
Conservation of information and the foundations of quantum mechanics
We review a recent approach to the foundations of quantum mechanics inspired
by quantum information theory. The approach is based on a general framework,
which allows one to address a large class of physical theories which share
basic information-theoretic features. We first illustrate two very primitive
features, expressed by the axioms of causality and purity-preservation, which
are satisfied by both classical and quantum theory. We then discuss the axiom
of purification, which expresses a strong version of the Conservation of
Information and captures the core of a vast number of protocols in quantum
information. Purification is a highly non-classical feature and leads directly
to the emergence of entanglement at the purely conceptual level, without any
reference to the superposition principle. Supplemented by a few additional
requirements, satisfied by classical and quantum theory, it provides a complete
axiomatic characterization of quantum theory for finite dimensional systems.Comment: 11 pages, contribution to the Proceedings of the 3rd International
Conference on New Frontiers in Physics, July 28-August 6 2014, Orthodox
Academy of Crete, Kolymbari, Cret
Avenues of cognition of nongravitational local gauge field theories
This controbution is devoted to present basic fearures of a unifying local gauge field theory, prevailing up to a mass scale of approximately 10 16 GeV , allowing the neglect of gravitational curvature effects – indicated by the attribute : ’nongravitational’ in the title above
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