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Carlos López

Publications and source records attributed to Carlos López.

3 recordsLinked to original sources

Unconditional representations of the Euler-Mascheroni constant and the Bernoulli numbers via the Taylor coefficients of the Riemann ξ-function, and a hierarchy of exact relations at the central point

We give a self-contained, numerically verified derivation of three equivalent unconditional representations of the Euler--Mascheroni constant $γ$ as a rapidly convergent series in the Taylor coefficients $a_{2n}$ of the Riemann $ξ$-function about its centre of symmetry $s=1/2$ (equivalently, in the Jensen coefficients $c_n$ or in the Csordas--Norfolk--Varga Turan moments $\hat{b}_n$). We also record the corresponding convergent formula for the even-indexed Bernoulli numbers $B_{2r}$, obtained by evaluating the (everywhere convergent) Taylor series of $ξ$ at $s=2r$. We then develop, from the evenness of $Ξ(x)=ξ(1/2+ix)$, an infinite hierarchy of exact relations at $s=1/2$: the even-order relations reduce the central logarithmic derivatives of $ζ$ to closed forms in $π$ and the odd zeta values (base case $2ζ'(1/2)/ζ(1/2)=γ+π/2+\log(8π)$), and the odd-order relations evaluate the power sums over the nontrivial zeros and link back to the coefficients $a_{2n}$. All of these identities hold whether or not the Riemann Hypothesis (RH) is true; consequently they carry no evidential weight for or against RH, and we make the correct, unconditional relationship of these coefficient sequences to the Jensen--Polya program precise. This note is a corrected version of an earlier preprint [arXiv:2112.11228v1]: we retain only the results that are correct, we remove a divergent series of Bernoulli numbers that was previously used as though it were convergent, we correct several attributions, and we withdraw the earlier claim that these computations support RH. A summary of the corrections is given in Section 7.

math.GM↗

Leader Election in Arbitrarily Connected Networks with Process Crashes and Weak Channel Reliability

A channel from a process p to a process q satisfies the ADD property if there are constants K and D, unknown to the processes, such that in any sequence of K consecutive messages sent by p to q, at least one of them is delivered to q at most D time units after it has been sent. This paper studies implementations of an eventual leader, namely, an Ω failure detector, in an arbitrarily connected network of eventual ADD channels, where processes may fail by crashing. It first presents an algorithm that assumes that processes initially know n, the total number of processes, sending messages of size O( log n). Then, it presents a second algorithm that does not assume the processes know n. Eventually the size of the messages sent by this algorithm is also O( log n). These are the first implementations of leader election in the ADD model. In this model, only eventually perfect failure detectors were considered, sending messages of size O(n log n).

cs.DC↗

Recognition of an obstacle in a flow using artificial neural networks

In this work a series of artificial neural networks (ANNs) have been developed with the capacity to estimate an obstacle's size and location obstructing the flow in a pipe. The ANNs learn the size and location of the obstacle by reading the profiles of the dynamic pressure $q$ or the $x$-component of the velocity $v_x$ of the fluid at certain distance from the obstacle. The data to train the ANN, was generated using numerical simulations with a 2D Lattice Boltzmann code. We analyzed various cases varying both the diameter and position of the obstacle on $y$-axis, obtaining good estimations using the $R^2$ coefficient for the cases of study. Although the ANN showed problems for the classification of the very small obstacles, the general results show a very good capacity of prediction.

physics.flu-dyn↗