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A model where chiral boson is coupled to a background dilaton field is considered to study the s-wave scattering of fermion by a background dilaton black hole. It is found that the scattering process of chiral fermion does not violate unitarity and information remains preserved. Faddevian anomaly plays a crucial role on the information scenario.

We discuss some of the issues relating to information loss and black hole thermodynamics in the light of recent work on local black hole horizons. Understood in terms of pure states evolving into mixed states, the possibility of information loss in black holes is closely related to the global causal structure of space–time, as is the existence of event horizons. However, black holes need not be defined by event horizons, and in fact we argue that in order to have a fully unitary evolution for black holes, they should be defined in terms of something else, such as a trapping horizon. The Misner–Sharp mass in spherical symmetry shows very simply how trapping horizons can give rise to black hole thermodynamics, Hawking radiation and singularities. We show how the Misner–Sharp mass can also be used to give insights into the process of collapse and evaporation of locally defined black holes.

Sequential pattern mining has become one of the most important topics in data mining. It has broad applications such as analyzing customer purchase data, Web access patterns, network traffic data, DNA sequencing, and so on. Previous studies have concentrated on reducing redundant patterns among the sequential patterns, and on finding meaningful patterns from huge datasets. In sequential pattern mining, closed sequential pattern mining and weighted sequential pattern mining are the two main approaches to perform mining tasks. This is because closed sequential pattern mining finds representative sequential patterns which show exactly the same knowledge as the complete set of frequent sequential patterns, and weight-based sequential pattern mining discovers important sequential patterns by considering the importance of each sequential pattern. In this paper, we study the problem of mining robust closed weighted sequential patterns by integrating two paradigms from large sequence databases. We first show that the joining order between the weight constraints and the closure property in sequential pattern mining leads to different sets of results. From our analysis of joining orders, we suggest robust closed weighted sequential pattern mining without information loss, and present how to discover representative important sequential patterns without information loss. Through performance tests, we show that our approach gives high performance in terms of efficiency, effectiveness, memory usage, and scalability.

It has been claimed recently that the black hole information-loss paradox has been resolved: the evolution of quantum states in the presence of a black hole is unitary and information preserving. We point out that, contrary to some claims in literature, information-preserving black holes still violate the baryon number and any other quantum number which follows from an effective (and thus approximate) or anomalous symmetry.

Taking the self-gravitational interaction and unfixed background space–time into account, we discuss the tunneling radiation of the Dilaton–Maxwell black hole by the Hamilton–Jacobi method. The result shows that the tunneling rate is related not only to the change of Bekenstein–Hawking entropy, but also to a subtle integral about the black hole mass, which does not satisfy the unitary theory and is different from Parikh and Wilczek's result. This implies that information loss in black hole evaporation is possible.

We consider the emission of Hawking radiation by black holes as a consequence of a tunneling process. By requiring energy conservation in the derivation of the emission rate we get a well-known deviation from an exact thermal spectrum. A model that takes into account the implications of energy conservation, as well as the back-scattered radiation, is then constructed in order to describe the evolution of black holes as they evaporate. The evaporation process in this model is compared with the results in the standard "thermal" approximation. This allows us to point out the relevance that energy conservation might have in the last stages of black hole evaporation. We also comment about the possible implications of energy conservation in the information loss paradox.

Event horizons are the defining feature of classical black holes. They are the key ingredient of the information loss paradox which, as paradoxes in quantum foundations, is built on a combination of predictions of quantum theory and counterfactual classical features: neither horizon formation nor its crossing by a test body can be detected by a distant observer. Furthermore, horizons are unnecessary for the production of Hawking-like radiation. We demonstrate that when this radiation is taken into account, it can prevent horizon crossing/formation in a large class of models. We conjecture that horizon avoidance is a general feature of collapse. The nonexistence of event horizons dispels the paradox, but opens up important questions about thermodynamic properties of the resulting objects and correlations between different degrees of freedom.

For distant observers, black holes are trapped spacetime domains bounded by apparent horizons. We review properties of the near-horizon geometry emphasizing the consequences of two common implicit assumptions of semiclassical physics. The first is a consequence of the cosmic censorship conjecture, namely, that curvature scalars are finite at apparent horizons. The second is that horizons form in finite asymptotic time (i.e. according to distant observers), a property implicitly assumed in conventional descriptions of black hole formation and evaporation. Taking these as the only requirements within the semiclassical framework, we find that in spherical symmetry only two classes of dynamic solutions are admissible, both describing evaporating black holes and expanding white holes. We review their properties and present the implications. The null energy condition is violated in the vicinity of the outer horizon and satisfied in the vicinity of the inner apparent/anti-trapping horizon. Apparent and anti-trapping horizons are timelike surfaces of intermediately singular behavior, which manifests itself in negative energy density firewalls. These and other properties are also present in axially symmetric solutions. Different generalizations of surface gravity to dynamic spacetimes are discordant and do not match the semiclassical results. We conclude by discussing signatures of these models and implications for the identification of observed ultra-compact objects.

I argue that an approach which uses an appropriate admixture of both classical and semiclassical effects is essential for understanding the ultimate fate of gravitational collapse and the nature of black holes (BHs). I provide an example of a problem which pushes the boundaries of what is known in both the classical and semiclassical approaches: the evolution of the inner horizon of a BH. I show that solving this problem requires considering perturbations of both classical and semiclassical origins. In fact, it has been found that classical mass inflation might be counteracted by a semiclassical tendency for the inner horizon to inflate outward.

Synthetic data generators are one of the methods used in privacy preserving data mining for ensuring the privacy of the individuals when their data are published. Synthetic data generators construct artificial data from some models obtained from the original data. Such models are mainly based on statistics and, typically, do not take into account other aspects of interest in artificial intelligence.

In this paper we study whether one family of such synthetic data generators (the IPSO family) preserves the properties of the data that are of interest when users plan to apply clustering techniques. In particular, we study the effect of such synthetic data generators on fuzzy clustering. That is, we study the information loss data suffer when the original data are replaced by the synthetic ones.

Nowadays, big data publishing is the emerging trend since they have good potential for the decision support in the applications, such as a hospital, government, industries, etc. Existing algorithms have many problems in preserving the privacy of the data when the data is in large size. To avoid these problems, this paper introduces a novel anonymity model for the data publishing based on K-DDD measure and MapReduce. This paper presents the Duplicate-Divergence-Different properties enabled dragon Genetic (DDDG) algorithm based on the k-DDD anonymization and the dragon operator based genetic algorithm. The proposed DDDG algorithm allows the privacy preservation in the big data by modifying the MapReduce techniques with the proposed DDDG algorithm. The performance of the proposed anonymity model is analyzed with the metrics such as information loss (IL) and the classification accuracy (CA). The adult database from the UC Irvine dataset is used for the simulation. The simulation results show that the proposed DDDG algorithm achieved the lowest IL of 0.0191 and the highest CA with the value of 0.8977 than the existing algorithms for k value of 2.

Explosive growth of information in the Internet has raised threats for individual privacy. k-Anonymity and l-diversity are two known techniques proposed to address the threats. They use concept hierarchy tree (CHT)-based generalization/suppression. For a given attribute several CHTs can be constructed. An appropriate CHT is to be chosen for attribute anonymization to be effective. This paper discusses an on the fly approach for constructing CHT which can be used for generalization/suppression. Furthermore to improve anonymization the CHT can be dynamically adjusted for a given k value. Performance evaluation is done for the proposed approach and a comparative study is performed against known methods, k-member clustering anonymization and mondrian multi-dimensional algorithm using (1) improved on the fly hierarchy (IOTF) (Campan et al., 2011), (2) on the fly hierarchy (OTF) (Campan and Cooper, 2010), (3) hierarchy free (HF) (LeFevre et al., 2006), (4) predefined hierarchy (PH) (Iyengar, 2002) (5) CHU (Chu and Chiang, 1994) and (6) HAN (Han and Fu, 1994) methods. The metrics used for evaluation are (a) information loss, (b) discernibility metric, (c) normalized average equivalence size metric. Experimental results indicate that our approach is more effective and flexible and the utility is 12% better than IOTF, 16% better than OTF and CHU, 17% better than PH and 21% better than HAN methods when applied on mondrain multi-dimensional algorithm. Experiments are conducted on k-member clustering technique and it is observed that our approach improved utility 1% better than IOTF, 2% better than OTF, 3% better than CHU, 5% better than PH and 14% better than HAN methods.

We consider an elementary collision model of a molecular reservoir upon which an external field is applied and the work is dissipated into heat. To realize macroscopic irreversibility at the microscopic level, we introduce a "graceful" irreversible map which randomly mixes the identities of the molecules. This map is expected to generate informatic entropy exactly equal to the independently calculable irreversible thermodynamic entropy.

We formulate entropic measurements uncertainty relations (MURs) for a spin-1/2 system. When incompatible observables are approximatively jointly measured, we use relative entropy to quantify the information lost in approximation and we prove positive lower bounds for such a loss: there is an unavoidable information loss. Firstly we allow only for covariant approximate joint measurements and we find state-dependent MURs for two or three orthogonal spin-1/2 components. Secondly we consider any possible approximate joint measurement and we find state-independent MURs for two or three spin-1/2 components. In particular we study how MURs depend on the angle between two spin directions. Finally, we extend our approach to infinitely many incompatible observables, namely to the spin components in all possible directions. In every scenario, we always consider also the characterization of the optimal approximate joint measurements.

Recently, Ashtekar and Bojowald proposed a resolution of the Hawking Information Loss Puzzle based on their qualitative picture of the evaporation process. Here, we examine the puzzle in the solvable (and hence, mathematically precise) context of the Callen-Giddings-Harvey-Strominger (CGHS) toy model of black holes in 2 spacetime dimensions. The CGHS model is known to admit a non- perturbative quantization. We show that the resolution of the puzzle in the context of this quantization exhibits features of the Ashtekar-Bojowald paradigm and, therefore, provides a useful setting from which lessons for the 4 dimensional case may be learned. This article is a report of joint work with A. Ashtekar.

If there exists a classical, i.e. deterministic theory underlying quantum mechanics, an explanation must be found of the fact that the Hamiltonian, which is defined to be the operator that generates evolution in time, is bounded from below. The mechanism that can produce exactly such a constraint is identified in this paper. It is the fact that not all classical data are registered in the quantum description. Large sets of values of these data are assumed to be indistinguishable, forming equivalence classes. It is argued that this should be attributed to information loss, such as what one might suspect to happen during the formation and annihilation of virtual black holes.

The nature of the equivalence classes is further elucidated, as it follows from the positivity of the Hamiltonian. Our world is assumed to consist of a very large number of subsystems that may be regarded as approximately independent, or weakly interacting with one another. As long as two (or more) sectors of our world are treated as being independent, they all must be demanded to be restricted to positive energy states only. What follows from these considerations is a unique definition of energy in the quantum system in terms of the periodicity of the limit cycles of the deterministic model.

k-anonymity is a widely used technology for privacy protection. In order to prevent attackers from digging out private information based on data published and his(her) background knowledge, a k-anonymity method is proposed, which uses the idea of clustering partition. Two different types of quasi-identifier attributes are individually subjected to a generalization process. The distance between tuples as well as the distance between a tuple and an equivalence class is also defined. In the process of clustering partition, some tuples are selected to constitute equivalence classes one by one, according to the principle of minimum distance value. k-anonymization is then completed, finally, by a separate generalization process. Through experiments comparing the performance of our method with that of an existing anonymization algorithm, EBKC, the effectiveness of the approach is verified.

Great interest was generated when it was announced that Hawking had admitted that he had lost a bet with Susskind. The bet had been about the “information loss paradox” in which Hawking had tried to show that quantum theory, in its merger with gravity, is incomplete and both quantum theory and relativity need to be modified. Susskind had refuted the argument using quantum arguments why the information would not be lost. In the process he formulated a “black hole complementarity principle”. It turns out that work of Wheeler and I leads to the same conclusions qualitatively and there is reason to believe that introducing the uncertainty principle might give a quantitative result with no further quantum input.