Inside the Hypercube

Bernstein\u27s CubeHash is a hash function family that includes four functions submitted to the NIST Hash Competition. A CubeHash function is parametrized by a number of rounds r, a block byte size b, and a digest bit length h (the compression function makes r rounds, while the finalization function makes 10r rounds). The 1024-bit internal state of CubeHash is represented as a five-dimensional hypercube. The submissions to NIST recommends r=8, b=1, and h in {224,256,384,512}. This paper presents the first external analysis of CubeHash, with: improved standard generic attacks for collisions and preimages; a multicollision attack that exploits fixed points; a study of the round function symmetries; a preimage attack that exploits these symmetries; a practical collision attack on a weakened version of CubeHash; a study of fixed points and an example of nontrivial fixed point; high-probability truncated differentials over 10 rounds. Since the first publication of these results, several collision attacks for reduced versions of CubeHash were published by Dai, Peyrin, et al. Our results are more general, since they apply to any choice of the parameters, and show intrinsic properties of the CubeHash design, rather than attacks on specific versions

Portfolio selection using neural networks

In this paper we apply a heuristic method based on artificial neural networks in order to trace out the efficient frontier associated to the portfolio selection problem. We consider a generalization of the standard Markowitz mean-variance model which includes cardinality and bounding constraints. These constraints ensure the investment in a given number of different assets and limit the amount of capital to be invested in each asset. We present some experimental results obtained with the neural network heuristic and we compare them to those obtained with three previous heuristic methods.Comment: 12 pages; submitted to "Computers & Operations Research

Multi-qubit stabilizer and cluster entanglement witnesses

One of the problems concerning entanglement witnesses (EWs) is the construction of them by a given set of operators. Here several multi-qubit EWs called stabilizer EWs are constructed by using the stabilizer operators of some given multi-qubit states such as GHZ, cluster and exceptional states. The general approach to manipulate the multi-qubit stabilizer EWs by exact(approximate) linear programming (LP) method is described and it is shown that the Clifford group play a crucial role in finding the hyper-planes encircling the feasible region. The optimality, decomposability and non-decomposability of constructed stabilizer EWs are discussed.Comment: 57 pages, 2 figure

The component structure of dense random subgraphs of the hypercube

Given $p \in (0,1)$, we let $Q_p= Q_p^d$ be the random subgraph of the $d$-dimensional hypercube $Q^d$ where edges are present independently with probability $p$. It is well known that, as $d \rightarrow \infty$, if $p>\frac12$ then with high probability $Q_p$ is connected; and if $p<\frac12$ then with high probability $Q_p$ consists of one giant component together with many smaller components which form the `fragment'. Here we fix $p \in (0,\frac12)$, and investigate the fragment, and how it sits inside the hypercube. In particular we give asymptotic estimates for the mean numbers of components in the fragment of each size, and describe their asymptotic distributions and indeed their joint distribution, much extending earlier work of Weber

Bell-states diagonal entanglement witnesses for relativistic and non-relativistic multispinor systems in arbitrary dimensions

Two kinds of Bell-states diagonal (BSD) entanglement witnesses (EW) are constructed by using the algebra of Dirac $\gamma$ matrices in the space-time of arbitrary dimension $d$, where the first kind can detect some BSD relativistic and non-relativistic $m$-partite multispinor bound entangled states in Hilbert space of dimension $2^{m\lfloor d/2\rfloor}$, including the bipartite Bell-type and iso-concurrence type states in the four-dimensional space-time ($d=4$). By using the connection between Hilbert-Schmidt measure and the optimal EWs associated with states, it is shown that as far as the spin quantum correlations is concerned, the amount of entanglement is not a relativistic scalar and has no invariant meaning. The introduced EWs are manipulated via the linear programming (LP) which can be solved exactly by using simplex method. The decomposability or non-decomposability of these EWs is investigated, where the region of non-decomposable EWs of the first kind is partially determined and it is shown that, all of the EWs of the second kind are decomposable. These EWs have the preference that in the bipartite systems, they can determine the region of separable states, i.e., bipartite non-detectable density matrices of the same type as the EWs of the first kind are necessarily separable. Also, multispinor EWs with non-polygon feasible regions are provided, where the problem is solved by approximate LP, and in contrary to the exactly manipulatable EWs, both the first and second kind of the optimal approximate EWs can detect some bound entangled states. Keywords: Relativistic entanglement, Entanglement Witness, Multispinor, Linear Programming, Feasible Region. PACs Index: 03.65.UdComment: 62 page