arXiv subjects

Eli Moore

Publications and source records attributed to Eli Moore.

3 recordsLinked to original sources

arXiv2024

The early Earth as an analogue for exoplanetary biogeochemistry

Planet Earth has evolved from an entirely anoxic planet with possibly a different tectonic regime to the oxygenated world with horizontal plate tectonics that we know today. For most of this time, Earth has been inhabited by a purely microbial biosphere albeit with seemingly increasing complexity over time. A rich record of this geobiological evolution over most of Earth's history provides insights into the remote detectability of microbial life under a variety of planetary conditions. We leverage Earth's geobiological record with the aim of a) illustrating the current state of knowledge and key knowledge gaps about the early Earth as a reference point in exoplanet science research; b) compiling biotic and abiotic mechanisms that controlled the evolution of the atmosphere over time; and c) reviewing current constraints on the detectability of Earth's early biosphere with state-of-the-art telescope technology. We highlight that life may have originated on a planet with a different tectonic regime and strong hydrothermal activity, and under these conditions, biogenic CH$_4$ gas was perhaps the most detectable atmospheric biosignature. Oxygenic photosynthesis, which is responsible for essentially all O$_2$ gas in the modern atmosphere, appears to have emerged concurrently with the establishment of modern plate tectonics and the continental crust, but O$_2$ accumulation to modern levels only occurred late in Earth's history, perhaps tied to the rise of land plants. Nutrient limitation in anoxic oceans, promoted by hydrothermal Fe = fluxes, may have limited biological productivity and O$_2$ production. N$_2$O is an alternative biosignature that was perhaps significant on the redox-stratified Proterozoic Earth. We conclude that the detectability of atmospheric biosignatures on Earth was not only dependent on biological evolution but also strongly controlled by the evolving tectonic context.

astro-ph.EP↗

arXiv2020

Using noise to probe recurrent neural network structure and prune synapses

Many networks in the brain are sparsely connected, and the brain eliminates synapses during development and learning. How could the brain decide which synapses to prune? In a recurrent network, determining the importance of a synapse between two neurons is a difficult computational problem, depending on the role that both neurons play and on all possible pathways of information flow between them. Noise is ubiquitous in neural systems, and often considered an irritant to be overcome. Here we suggest that noise could play a functional role in synaptic pruning, allowing the brain to probe network structure and determine which synapses are redundant. We construct a simple, local, unsupervised plasticity rule that either strengthens or prunes synapses using only synaptic weight and the noise-driven covariance of the neighboring neurons. For a subset of linear and rectified-linear networks, we prove that this rule preserves the spectrum of the original matrix and hence preserves network dynamics even when the fraction of pruned synapses asymptotically approaches 1. The plasticity rule is biologically-plausible and may suggest a new role for noise in neural computation.

q-bio.NC↗

arXiv2017

Sequence Pairs with Lowest Combined Autocorrelation and Crosscorrelation

Pursley and Sarwate established a lower bound on a combined measure of autocorrelation and crosscorrelation for a pair $(f,g)$ of binary sequences (i.e., sequences with terms in $\{-1,1\}$). If $f$ is a nonzero sequence, then its autocorrelation demerit factor, $\text{ADF}(f)$, is the sum of the squared magnitudes of the aperiodic autocorrelation values over all nonzero shifts for the sequence obtained by normalizing $f$ to have unit Euclidean norm. If $(f,g)$ is a pair of nonzero sequences, then their crosscorrelation demerit factor, $\text{CDF}(f,g)$, is the sum of the squared magnitudes of the aperiodic crosscorrelation values over all shifts for the sequences obtained by normalizing both $f$ and $g$ to have unit Euclidean norm. Pursley and Sarwate showed that for binary sequences, the sum of $\text{CDF}(f,g)$ and the geometric mean of $\text{ADF}(f)$ and $\text{ADF}{(g)}$ must be at least $1$. For randomly selected pairs of long binary sequences, this quantity is typically around $2$. In this paper, we show that Pursley and Sarwate's bound is met for binary sequences precisely when $(f,g)$ is a Golay complementary pair. We also prove a generalization of this result for sequences whose terms are arbitrary complex numbers. We investigate constructions that produce infinite families of Golay complementary pairs, and compute the asymptotic values of autocorrelation and crosscorrelation demerit factors for such families.

cs.IT↗