3,614 research outputs found
Partonic Energy Loss and the Drell-Yan Process
We examine the current status of the extraction of the rate of partonic
energy loss in nuclei from A dependent data. The advantages and difficulties of
using the Drell-Yan process to measure the energy loss of a parton traversing a
cold nuclear medium are discussed. The prospects of using relatively low energy
proton beams for a definitive measurement of partonic energy loss are
presented.Comment: 12 pages, 2 figure
Maximizing the Conditional Expected Reward for Reaching the Goal
The paper addresses the problem of computing maximal conditional expected
accumulated rewards until reaching a target state (briefly called maximal
conditional expectations) in finite-state Markov decision processes where the
condition is given as a reachability constraint. Conditional expectations of
this type can, e.g., stand for the maximal expected termination time of
probabilistic programs with non-determinism, under the condition that the
program eventually terminates, or for the worst-case expected penalty to be
paid, assuming that at least three deadlines are missed. The main results of
the paper are (i) a polynomial-time algorithm to check the finiteness of
maximal conditional expectations, (ii) PSPACE-completeness for the threshold
problem in acyclic Markov decision processes where the task is to check whether
the maximal conditional expectation exceeds a given threshold, (iii) a
pseudo-polynomial-time algorithm for the threshold problem in the general
(cyclic) case, and (iv) an exponential-time algorithm for computing the maximal
conditional expectation and an optimal scheduler.Comment: 103 pages, extended version with appendices of a paper accepted at
TACAS 201
Limit Synchronization in Markov Decision Processes
Markov decision processes (MDP) are finite-state systems with both strategic
and probabilistic choices. After fixing a strategy, an MDP produces a sequence
of probability distributions over states. The sequence is eventually
synchronizing if the probability mass accumulates in a single state, possibly
in the limit. Precisely, for 0 <= p <= 1 the sequence is p-synchronizing if a
probability distribution in the sequence assigns probability at least p to some
state, and we distinguish three synchronization modes: (i) sure winning if
there exists a strategy that produces a 1-synchronizing sequence; (ii)
almost-sure winning if there exists a strategy that produces a sequence that
is, for all epsilon > 0, a (1-epsilon)-synchronizing sequence; (iii) limit-sure
winning if for all epsilon > 0, there exists a strategy that produces a
(1-epsilon)-synchronizing sequence.
We consider the problem of deciding whether an MDP is sure, almost-sure,
limit-sure winning, and we establish the decidability and optimal complexity
for all modes, as well as the memory requirements for winning strategies. Our
main contributions are as follows: (a) for each winning modes we present
characterizations that give a PSPACE complexity for the decision problems, and
we establish matching PSPACE lower bounds; (b) we show that for sure winning
strategies, exponential memory is sufficient and may be necessary, and that in
general infinite memory is necessary for almost-sure winning, and unbounded
memory is necessary for limit-sure winning; (c) along with our results, we
establish new complexity results for alternating finite automata over a
one-letter alphabet
Jet correlation measurement in heavy-ion collisions: from RHIC to LHC
We attempt to deduce simple options of `jet quenching' phenomena in heavy-ion
collisions at \snn=5.5 \tev at the LHC from the present knowledge of
leading-hadron suppression at RHIC energies. In light of the nuclear
modification factor for leading particles we introduce the nuclear modification
factor for jets, \RAA^{jet}, and for the longitudinal momenta of particles
along the jet axis, \RAA^{p_{\rm L}}.Comment: 9 pages, 7 figures, proceedings, MIT workshop on fluctuations and
correlations in relativistic nuclear collision
Quantitative multi-objective verification for probabilistic systems
We present a verification framework for analysing multiple quantitative objectives of systems that exhibit both nondeterministic and stochastic behaviour. These systems are modelled as probabilistic automata, enriched with cost or reward structures that capture, for example, energy usage or performance metrics. Quantitative properties of these models are expressed in a specification language that incorporates probabilistic safety and liveness properties, expected total cost or reward, and supports multiple objectives of these types. We propose and implement an efficient verification framework for such properties and then present two distinct applications of it: firstly, controller synthesis subject to multiple quantitative objectives; and, secondly, quantitative compositional verification. The practical applicability of both approaches is illustrated with experimental results from several large case studies
On finitely ambiguous B\"uchi automata
Unambiguous B\"uchi automata, i.e. B\"uchi automata allowing only one
accepting run per word, are a useful restriction of B\"uchi automata that is
well-suited for probabilistic model-checking. In this paper we propose a more
permissive variant, namely finitely ambiguous B\"uchi automata, a
generalisation where each word has at most accepting runs, for some fixed
. We adapt existing notions and results concerning finite and bounded
ambiguity of finite automata to the setting of -languages and present a
translation from arbitrary nondeterministic B\"uchi automata with states to
finitely ambiguous automata with at most states and at most accepting
runs per word
DFTCalc: a tool for efficient fault tree analysis
Effective risk management is a key to ensure that our nuclear power plants, medical equipment, and power grids are dependable; and it is often required by law. Fault Tree Analysis (FTA) is a widely used methodology here, computing important dependability measures like system reliability. This paper presents DFTCalc, a powerful tool for FTA, providing (1) efficient fault tree modelling via compact representations; (2) effective analysis, allowing a wide range of dependability properties to be analysed (3) efficient analysis, via state-of-the-art stochastic techniques; and (4) a flexible and extensible framework, where gates can easily be changed or added. Technically, DFTCalc is realised via stochastic model checking, an innovative technique offering a wide plethora of powerful analysis techniques, including aggressive compression techniques to keep the underlying state space small
Quantitative Analysis of DoS Attacks and Client Puzzles in IoT Systems
Denial of Service (DoS) attacks constitute a major security threat to today's
Internet. This challenge is especially pertinent to the Internet of Things
(IoT) as devices have less computing power, memory and security mechanisms to
mitigate DoS attacks. This paper presents a model that mimics the unique
characteristics of a network of IoT devices, including components of the system
implementing `Crypto Puzzles' - a DoS mitigation technique. We created an
imitation of a DoS attack on the system, and conducted a quantitative analysis
to simulate the impact such an attack may potentially exert upon the system,
assessing the trade off between security and throughput in the IoT system. We
model this through stochastic model checking in PRISM and provide evidence that
supports this as a valuable method to compare the efficiency of different
implementations of IoT systems, exemplified by a case study
Flow Faster: Efficient Decision Algorithms for Probabilistic Simulations
Strong and weak simulation relations have been proposed for Markov chains,
while strong simulation and strong probabilistic simulation relations have been
proposed for probabilistic automata. However, decision algorithms for strong
and weak simulation over Markov chains, and for strong simulation over
probabilistic automata are not efficient, which makes it as yet unclear whether
they can be used as effectively as their non-probabilistic counterparts. This
paper presents drastically improved algorithms to decide whether some
(discrete- or continuous-time) Markov chain strongly or weakly simulates
another, or whether a probabilistic automaton strongly simulates another. The
key innovation is the use of parametric maximum flow techniques to amortize
computations. We also present a novel algorithm for deciding strong
probabilistic simulation preorders on probabilistic automata, which has
polynomial complexity via a reduction to an LP problem. When extending the
algorithms for probabilistic automata to their continuous-time counterpart, we
retain the same complexity for both strong and strong probabilistic
simulations.Comment: LMC
Zero-Reachability in Probabilistic Multi-Counter Automata
We study the qualitative and quantitative zero-reachability problem in
probabilistic multi-counter systems. We identify the undecidable variants of
the problems, and then we concentrate on the remaining two cases. In the first
case, when we are interested in the probability of all runs that visit zero in
some counter, we show that the qualitative zero-reachability is decidable in
time which is polynomial in the size of a given pMC and doubly exponential in
the number of counters. Further, we show that the probability of all
zero-reaching runs can be effectively approximated up to an arbitrarily small
given error epsilon > 0 in time which is polynomial in log(epsilon),
exponential in the size of a given pMC, and doubly exponential in the number of
counters. In the second case, we are interested in the probability of all runs
that visit zero in some counter different from the last counter. Here we show
that the qualitative zero-reachability is decidable and SquareRootSum-hard, and
the probability of all zero-reaching runs can be effectively approximated up to
an arbitrarily small given error epsilon > 0 (these result applies to pMC
satisfying a suitable technical condition that can be verified in polynomial
time). The proof techniques invented in the second case allow to construct
counterexamples for some classical results about ergodicity in stochastic Petri
nets.Comment: 20 page
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