Finite-Size Effects on Nucleation in a First-Order Phase Transition

We discuss finite-size effects on homogeneous nucleation in first-order phase transitions. We study their implications for cosmological phase transitions and to the hadronization of a quark-gluon plasma generated in high-energy heavy ion collisions. Very general arguments allow us to show that the finite size of the early universe has virtually no relevance in the process of nucleation and in the growth of cosmological bubbles during the primordial quark-hadron and the electroweak phase transitions. In the case of high-energy heavy ion collisions, finite-size effects play an important role in the late-stage growth of hadronic bubbles.Comment: 6 pages, no figures, 1 reference adde

Exact Solutions of the Caldeira-Leggett Master Equation: A Factorization Theorem For Decoherence

Exact solutions of the Caldeira-Leggett Master equation for the reduced density matrix for a free particle and for a harmonic oscillator system coupled to a heat bath of oscillators are obtained for arbitrary initial conditions. The solutions prove that the Fourier transform of the density matrix at time t with respect to (x + x')/2, where x and x' are the initial and final coordinates, factorizes exactly into a part depending linearly on the initial density matrix and a part independent of it. The theorem yields the exact initial state dependence of the density operator at time t and its eventual diagonalization in the energy basis.Comment: 8 pages, late

Multiparticle production in the Glasma at NLO and plasma instabilities

We discuss the relation between multi-particle production in the Glasma at next-to-leading order and the physics of plasma instabilities.Comment: 4 pages, talk at Quark Matter 200

Basin of attraction for turbulent thermalization and the range of validity of classical-statistical simulations

Different thermalization scenarios for systems with large fields have been proposed in the literature based on classical-statistical lattice simulations approximating the underlying quantum dynamics. We investigate the range of validity of these simulations for condensate driven as well as fluctuation dominated initial conditions for the example of a single component scalar field theory. We show that they lead to the same phenomenon of turbulent thermalization for the whole range of (weak) couplings where the classical-statistical approach is valid. In the turbulent regime we establish the existence of a dual cascade characterized by universal scaling exponents and scaling functions. This complements previous investigations where only the direct energy cascade has been studied for the single component theory. A proposed alternative thermalization scenario for stronger couplings is shown to be beyond the range of validity of classical-statistical simulations.Comment: 11 pages, 10 figures; version published in JHEP (minor revisions

From RHIC to EIC: Nuclear Structure Functions

We study the nuclear structure function $F_2^A$ and its logarithmic derivative in the high energy limit (small $x$ region) using the Color Glass Condensate formalism. In this limit the structure function $F_2$ depends on the quark anti-quark dipole-target scattering cross section $N_F (x_{bj}, r_t, b_t)$. The same dipole cross section appears in single hadron and hadron-photon production cross sections in the forward rapidity region in deuteron (proton)-nucleus collisions at high energy, i.e. at RHIC and LHC. We use a parameterization of the dipole cross section, which has successfully been used to describe the deuteron-gold data at RHIC, to compute the nuclear structure function $F_2^A$ and its log $Q^2$ derivative (which is related to gluon distribution function in the double log limit). We provide a quantitative estimate of the nuclear shadowing of $F_2^A$ and the gluon distribution function in the kinematic region relevant to a future Electron-Ion Collider.Comment: 13 pages, 6 figure

Need of Improved Non-Destructive Technique for the Surface Condition Monitoring of High Speed Steel (HSS) Work Rolls

Over the last few years, the use of work rolls for hot rolling of flat steel has changed from clear chill rolls to indefinite chill, then came high chrome steel and now High Speed tool Steel (HSS). The hardness of HSS roll reaches 80/85 ShC, hence it becomes very much crack-sensitive and the developed crack is usually oriented parallel to the roll axis and propagates in a non-radial direction. In the next phase, a fatigue “cat’s tongue” like fracture band propagates progressively in a circumferential direction running more or less parallel to the barrel surface. The direction of propagation is opposite to that of the direction of roll rotation. Crack propagation develops within the working surface of the roll, gradually increasing in depth and width followed by a large surface spall of the overlying barrel surface. Hence it is highly recommended to eliminate all kinds of surface cracks, whenever these rolls are reground, otherwise these `cats – tongue’ band type spalls may lead to abnormal failure. This paper presents the necessity of development of improved non-destructive technique for the crack detection of HSS rolls and also highlights the recent attempts at Tata Steel in collaboration with CSIR-National Metallurgical Laboratory, Jamshedpur to develop surface wave based ultrasonic technique to detect fine cracks on the barrel surface of HSS rolls to optimise the grinding procedure for having crack free roll surface

The Effect of Normalization on Intrusion Detection Classifiers (Na�ve Bayes and J48)

Intrusion Detection has become an inevitable area for commercial applications and academic research. Network traffic is typically very high volume and consists of both qualitative and quantitative data with different range of values. Raw data needs to be pre-processed before fed into any learning model and the most used technique is normalization [1]. Attribute normalization eliminates the dominance of attributes with extreme values by scaling it within the range. However, many intrusion detection methods do not normalize attributes before training and detection [2]. Network traffic data contains features that are qualitative or quantitative nature and has to be treated differently [3]. This work studies the effect of normalization on Naive Bayes and J48 Decision tree classifier with the corrected KDDCUP99 and Kyoto 2006+ dataset. A comprehensive approach for normalization for network traffic attributes has been proposed