Representation of Cyclotomic Fields and Their Subfields

Let \K be a finite extension of a characteristic zero field \F. We say that the pair of $n\times n$ matrices $(A,B)$ over \F represents \K if \K \cong \F[A]/ where \F[A] denotes the smallest subalgebra of M_n(\F) containing $A$ and $$ is an ideal in \F[A] generated by $B$. In particular, $A$ is said to represent the field \K if there exists an irreducible polynomial q(x)\in \F[x] which divides the minimal polynomial of $A$ and \K \cong \F[A]/. In this paper, we identify the smallest circulant-matrix representation for any subfield of a cyclotomic field. Furthermore, if $p$ is any prime and \K is a subfield of the $p$-th cyclotomic field, then we obtain a zero-one circulant matrix $A$ of size $p\times p$ such that (A,\J) represents \K, where \J is the matrix with all entries 1. In case, the integer $n$ has at most two distinct prime factors, we find the smallest 0-1 companion-matrix that represents the $n$-th cyclotomic field. We also find bounds on the size of such companion matrices when $n$ has more than two prime factors.Comment: 17 page

Depth First Search in the Semi-streaming Model

Depth first search (DFS) tree is a fundamental data structure for solving various graph problems. The classical algorithm for building a DFS tree requires O(m+n) time for a given undirected graph G having n vertices and m edges. In the streaming model, an algorithm is allowed several passes (preferably single) over the input graph having a restriction on the size of local space used. Now, a DFS tree of a graph can be trivially computed using a single pass if O(m) space is allowed. In the semi-streaming model allowing O(n) space, it can be computed in O(n) passes over the input stream, where each pass adds one vertex to the DFS tree. However, it remains an open problem to compute a DFS tree using o(n) passes using o(m) space even in any relaxed streaming environment. We present the first semi-streaming algorithms that compute a DFS tree of an undirected graph in o(n) passes using o(m) space. We first describe an extremely simple algorithm that requires at most ceil[n/k] passes to compute a DFS tree using O(nk) space, where k is any positive integer. For example using k=sqrt{n}, we can compute a DFS tree in sqrt{n} passes using O(n sqrt{n}) space. We then improve this algorithm by using more involved techniques to reduce the number of passes to ceil[h/k] under similar space constraints, where h is the height of the computed DFS tree. In particular, this algorithm improves the bounds for the case where the computed DFS tree is shallow (having o(n) height). Moreover, this algorithm is presented in form of a framework that allows the flexibility of using any algorithm to maintain a DFS tree of a stored sparser subgraph as a black box, which may be of an independent interest. Both these algorithms essentially demonstrate the existence of a trade-off between the space and number of passes required for computing a DFS tree. Furthermore, we evaluate these algorithms experimentally which reveals their exceptional performance in practice. For both random and real graphs, they require merely a few passes even when allowed just O(n) space

A Novel Method to Improve the Test Efficiency of VLSI Tests

This paper considers reducing the cost of test application by permuting test vectors to improve their defect coverage. Algorithms for test reordering are developed with the goal of minimizing the test cost. Best and worst case bounds are established for the performance of a reordered sequence compared to the original sequence of test application. SEMATECH test data and simulation results are used throughout to illustrate the ideas

Mass Hierarchy Determination via future Atmospheric Neutrino Detectors

We study the problem of determination of the sign of Delta m^2_{31}, or the neutrino mass hierarchy, through observations of atmospheric neutrinos in future detectors. We consider two proposed detector types : (a) Megaton sized water Cerenkov detectors, which can measure the survival rates of nu_\mu + \bar{\nu}_\mu and nu_e + \bar{\nu}_e and (b) 100 kton sized magnetized iron detectors, which can measure the survival rates of \nu_\mu and \bar{\nu}_\mu. For energies and path-lengths relevant to atmospheric neutrinos, these rates obtain significant matter contributions from P_{\mu e}, P_{\mu \mu} and P_{ee}, leading to an appreciable sensitivity to the hierarchy. We do a binned \chi^2 analysis of simulated data in these two types of detectors which includes the effect of smearing in neutrino energy and direction and incorporates detector efficiencies and relevant statistical, theoretical and systematic errors. We also marginalize the \chi^2 over the allowed ranges of neutrino parameters in order to accurately account for their uncertainties. Finally, we compare the performance of both types of detectors vis a vis the hierarchy determination.Comment: 36 pages, 13 figures, revised version accepted in Physical Review

Exploiting Don\u27t Cares to Enhance Functional Tests

In simulation based design verification, deterministic or pseudo-random tests are used to check functional correctness of a design. In this paper we present a technique generating tests by specifying the don’t care inputs in the functional specifications so as to improve their coverage of both design errors and manufacturing faults. The don’t cares are chosen to maximize sensitization of signals in the circuit. The tests generated in this way require only a fraction of pseudo-exhaustive test patterns to achieve a high multiplicity of fault coverage

Makrellundersøkelser i mai-juni 1980 med M/S "Karmøybas", R-95-K, Vedavågen

A new symbolic approach models the sensitization paths to selected primary output(s) as Boolean equations, with satisfying solutions representing the set of all sources of single and multiple sensitizations in the circuit. The paper discusses two applications of this idea: model-free fault diagnosis and input sensitization analysis