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

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

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

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

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

Nuclear Broadening Effects on Hard Prompt Photons at Relativistic Energies

We calculate prompt photon production in high-energy nuclear collisions. We focus on the broadening of the intrinsic transverse momenta of the partons in the initial state from nuclear effects, and their influence on the prompt photon p_t distribution. Comparing to WA98 data from Pb+Pb collisions at SPS energy we find evidence for the presence of nuclear broadening at high p_t in this hard process. Below p_t=2.7 GeV the photon distribution is due to small momentum transfer processes. At RHIC energy, the effect of intrinsic transverse momentum on the spectrum of prompt photons is less prominent. The region p_t=3-4 GeV would be the most promising for studying the nuclear broadening effects at that energy. Below p_t=2-3 GeV the contribution from large momentum transfers flattens out, and we expect that region to be dominated by soft contributions.Comment: 19 pages, 3 figures, minor changes, a few references adde

Prompt photons at RHIC

We calculate the inclusive cross section for prompt photon production in heavy-ion collisions at RHIC energies ($\sqrt{s}=130$ GeV and $\sqrt{s}=200$ GeV) in the central rapidity region including next-to-leading order, $O(\alpha_{em}\alpha_s^2)$, radiative corrections, initial state nuclear shadowing and parton energy loss effects. We show that there is a significant suppression of the nuclear cross section, up to $\sim 30$ at $\sqrt{s}=200$ GeV, due to shadowing and medium induced parton energy loss effects. We find that the next-to-leading order contributions are large and have a strong $p_t$ dependence.Comment: 9 pages, 5 figures, expanded discussion of the K facto

Triticale: cultivo e aproveitamento.

bitstream/item/126691/1/ID-6914.pdf2. imp

Probabilistic Verification at Runtime for Self-Adaptive Systems

An effective design of effective and efficient self-adaptive systems may rely on several existing approaches. Software models and model checking techniques at run time represent one of them since they support automatic reasoning about such changes, detect harmful configurations, and potentially enable appropriate (self-)reactions. However, traditional model checking techniques and tools may not be applied as they are at run time, since they hardly meet the constraints imposed by on-the-fly analysis, in terms of execution time and memory occupation. For this reason, efficient run-time model checking represents a crucial research challenge. This paper precisely addresses this issue and focuses on probabilistic run-time model checking in which reliability models are given in terms of Discrete Time Markov Chains which are verified at run-time against a set of requirements expressed as logical formulae. In particular, the paper discusses the use of probabilistic model checking at run-time for self-adaptive systems by surveying and comparing the existing approaches divided in two categories: state-elimination algorithms and algebra-based algorithms. The discussion is supported by a realistic example and by empirical experiments

Effects of Parton Intrinsic Transverse Momentum on Photon Production in Hard-Scattering Processes

We calculate the photon production cross section arising from the hard scattering of partons in nucleon-nucleon collisions by taking into account the intrinsic parton transverse momentum distribution and the next-to-leading-order contributions. As first pointed out by Owens, the inclusion of the intrinsic transverse momentum distribution of partons leads to an enhancement of photon production cross section in the region of photon transverse momenta of a few GeV/c for nucleon-nucleon collisions at a center-of-mass energy of a few tens of GeV. The enhancement increases as $\sqrt{s}$ decreases. Such an enhancement is an important consideration in the region of photon momenta under investigation in high-energy heavy-ion collisions.Comment: 10 pages, 9 figures, in LaTex, revised to include ananlytic evaluation of the hard-scattering integra