23,290 research outputs found
Bose-Einstein Correlations in e+e- -> W+W- at a Linear Collider
We show that the most popular method to simulate Bose-Einstein (BE)
interference effects predicts negligible correlations between identical pions
originating from the hadronic decay of different W's produced in e+e- -> W+W-
-> 4 jets at typical linear collider energies.Comment: 5 pages, 2 eps figures, Proccedings of the Workshop "Physics Studies
for a Future Linear Collider", QCD Working Group, 2000, DESY 123
Justifications in Constraint Handling Rules for Logical Retraction in Dynamic Algorithms
We present a straightforward source-to-source transformation that introduces
justifications for user-defined constraints into the CHR programming language.
Then a scheme of two rules suffices to allow for logical retraction (deletion,
removal) of constraints during computation. Without the need to recompute from
scratch, these rules remove not only the constraint but also undo all
consequences of the rule applications that involved the constraint. We prove a
confluence result concerning the rule scheme and show its correctness. When
algorithms are written in CHR, constraints represent both data and operations.
CHR is already incremental by nature, i.e. constraints can be added at runtime.
Logical retraction adds decrementality. Hence any algorithm written in CHR with
justifications will become fully dynamic. Operations can be undone and data can
be removed at any point in the computation without compromising the correctness
of the result. We present two classical examples of dynamic algorithms, written
in our prototype implementation of CHR with justifications that is available
online: maintaining the minimum of a changing set of numbers and shortest paths
in a graph whose edges change.Comment: Pre-proceedings paper presented at the 27th International Symposium
on Logic-Based Program Synthesis and Transformation (LOPSTR 2017), Namur,
Belgium, 10-12 October 2017 (arXiv:1708.07854
Quantum Weakly Nondeterministic Communication Complexity
We study the weakest model of quantum nondeterminism in which a classical
proof has to be checked with probability one by a quantum protocol. We show the
first separation between classical nondeterministic communication complexity
and this model of quantum nondeterministic communication complexity for a total
function. This separation is quadratic.Comment: 12 pages. v3: minor correction
Maps of zeroes of the grand canonical partition function in a statistical model of high energy collisions
Theorems on zeroes of the truncated generating function in the complex plane
are reviewed. When examined in the framework of a statistical model of high
energy collisions based on the negative binomial (Pascal) multiplicity
distribution, these results lead to maps of zeroes of the grand canonical
partition function which allow to interpret in a novel way different classes of
events in pp collisions at LHC c.m. energies.Comment: 17 pages, figures (ps included); added references, some figures
enlarged. To appear in J. Phys.
Lattice Boltzmann models for non-ideal fluids with arrested phase-separation
The effects of mid-range repulsion in Lattice Boltzmann models on the
coalescence/breakup behaviour of single-component, non-ideal fluids are
investigated. It is found that mid-range repulsive interactions allow the
formation of spray-like, multi-droplet configurations, with droplet size
directly related to the strength of the repulsive interaction. The simulations
show that just a tiny ten-percent of mid-range repulsive pseudo-energy can
boost the surface/volume ratio of the phase- separated fluid by nearly two
orders of magnitude. Drawing upon a formal analogy with magnetic Ising systems,
a pseudo-potential energy is defined, which is found to behave like a
quasi-conserved quantity for most of the time-evolution. This offers a useful
quantitative indicator of the stability of the various configurations, thus
helping the task of their interpretation and classification. The present
approach appears to be a promising tool for the computational modelling of
complex flow phenomena, such as atomization, spray formation and
micro-emulsions, break-up phenomena and possibly glassy-like systems as well.Comment: 12 pages, 9 figure
Exponential Separation of Quantum and Classical Online Space Complexity
Although quantum algorithms realizing an exponential time speed-up over the
best known classical algorithms exist, no quantum algorithm is known performing
computation using less space resources than classical algorithms. In this
paper, we study, for the first time explicitly, space-bounded quantum
algorithms for computational problems where the input is given not as a whole,
but bit by bit. We show that there exist such problems that a quantum computer
can solve using exponentially less work space than a classical computer. More
precisely, we introduce a very natural and simple model of a space-bounded
quantum online machine and prove an exponential separation of classical and
quantum online space complexity, in the bounded-error setting and for a total
language. The language we consider is inspired by a communication problem (the
set intersection function) that Buhrman, Cleve and Wigderson used to show an
almost quadratic separation of quantum and classical bounded-error
communication complexity. We prove that, in the framework of online space
complexity, the separation becomes exponential.Comment: 13 pages. v3: minor change
Optimal quantum sample complexity of learning algorithms
In learning theory, the VC dimension of a concept class C is the most common way to measure its “richness.” A fundamental result says that the number of examples needed to learn an unknown target concept c∈C under an unknown distribution D, is tightly determined by the VC dimension d of the concept class C. Specifically, in the PAC model
Θ(dϵ+log(1/δ)ϵ)
examples are necessary and sufficient for a learner to output, with probability 1−δ, a hypothesis h that is ϵ-close to the target concept c (measured under D). In the related agnostic model, where the samples need not come from a c∈C, we know that
Θ(dϵ2+log(1/δ)ϵ2)
examples are necessary and sufficient to output an hypothesis h∈C whose error is at most ϵ worse than the error of the best concept in C. Here we analyze quantum sample complexity, where each example is a coherent quantum state. This model was introduced by Bshouty and Jackson (1999), who showed that quantum examples are more powerful than classical examples in some fixed-distribution settings. However, Atıcı and Servedio (2005), improved by Zhang (2010), showed that in the PAC setting (where the learner has to succeed for every distribution), quantum examples cannot be much more powerful: the required number of quantum examples is
Ω(d1−ηϵ+d+log(1/δ)ϵ) for arbitrarily small constant η>0.
Our main result is that quantum and classical sample complexity are in fact equal up to constant factors in both the PAC and agnostic models. We give two proof approaches. The first is a fairly simple information-theoretic argument that yields the above two classical bounds and yields the same bounds for quantum sample complexity up to a log(d/ϵ) factor. We then give a second approach that avoids the log-factor loss, based on analyzing the behavior of the “Pretty Good Measurement” on the quantum state-identification problems that correspond to learning. This shows classical and quantum sample complexity are equal up to constant factors for every concept class C
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