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Meng-Xue Tsai

Publications and source records attributed to Meng-Xue Tsai.

4 recordsLinked to original sources

POLARIS: A Sparse Radial Neutrino Telescope Design for the Pacific Ocean

The cubic-kilometer neutrino telescopes have opened neutrino astronomy as an observational discipline. The recent detection of KM3-230213A, the highest-energy neutrino ever observed at ~220 PeV, as a near-horizontal muon track underscores that the ultra-high-energy frontier is accessed through horizontal directions where the Earth's opacity above ~100 TeV confines the observable sky to a narrow band around and above the horizon. Yet extending general-purpose detector architectures into this regime requires disproportionate increases in instrumentation, cost, and logistical complexity. A compelling alternative is to deploy specialized detectors that target this natural geometry. POLARIS (Pacific Ocean Large Area Radial Instrumented Sparse array) is a sparse planar deep-water Cherenkov array optimized for neutrino-induced muon tracks from horizontal directions in the multi-TeV to PeV regime. By rotating the conventional vertical string layout into a radial planar configuration, the detector presents maximal cross-section to horizontal tracks while naturally suppressing the down-going atmospheric background. With only 1100 optical modules, the five-arm design reaches point source and diffuse flux sensitivities at PeV energies competitive with detectors deploying several times more instrumentation. As a dedicated $ν_μ$ track detector, POLARIS provides the muon-flavor channel that tau-optimized experiments such as TAMBO and Trinity do not cover, enabling full flavor composition measurements from astrophysical sources. Using the Prometheus simulation framework, this study demonstrates that targeted sparse geometries can open new discovery space at the high-energy frontier at a fraction of the cost of general-purpose arrays.

astro-ph.HE↗

General Mechanism of Evolution Shared by Proteins and Words

Complex systems, such as life and languages, are governed by principles of evolution. The analogy and comparison between biology and linguistics\cite{alphafold2, RoseTTAFold, lang_virus, cell language, faculty1, language of gene, Protein linguistics, dictionary, Grammar of pro_dom, complexity, genomics_nlp, InterPro, language modeling, Protein language modeling} provide a computational foundation for characterizing and analyzing protein sequences, human corpora, and their evolution. However, no general mathematical formula has been proposed so far to illuminate the origin of quantitative hallmarks shared by life and language. Here we show several new statistical relationships shared by proteins and words, which inspire us to establish a general mechanism of evolution with explicit formulations that can incorporate both old and new characteristics. We found natural selection can be quantified via the entropic formulation by the principle of least effort to determine the sequence variation that survives in evolution. Besides, the origin of power law behavior and how changes in the environment stimulate the emergence of new proteins and words can also be explained via the introduction of function connection network. Our results demonstrate not only the correspondence between genetics and linguistics over their different hierarchies but also new fundamental physical properties for the evolution of complex adaptive systems. We anticipate our statistical tests can function as quantitative criteria to examine whether an evolution theory of sequence is consistent with the regularity of real data. In the meantime, their correspondence broadens the bridge to exchange existing knowledge, spurs new interpretations, and opens Pandora's box to release several potentially revolutionary challenges. For example, does linguistic arbitrariness conflict with the dogma that structure determines function?

q-bio.PE↗

Self-organizing Pattern in Multilayer Network for Words and Syllables

One of the ultimate goals for linguists is to find universal properties in human languages. Although words are generally considered as representing arbitrary mapping between linguistic forms and meanings, we propose a new universal law that highlights the equally important role of syllables, which is complementary to Zipf's. By plotting rank-rank frequency distribution of word and syllable for English and Chinese corpora, visible lines appear and can be fit to a master curve. We discover the multi-layer network for words and syllables based on this analysis exhibits the feature of self-organization which relies heavily on the inclusion of syllables and their connections. Analytic form for the scaling structure is derived and used to quantify how Internet slang becomes fashionable, which demonstrates its usefulness as a new tool to evolutionary linguistics.

cs.CL↗

Power-law ansatz in complex systems: excessive loss of information

The ubiquity of power-law relations in empirical data displays physicists' love of simple laws and uncovering common causes among seemingly unrelated phenomena. However, many reported power laws lack statistical support and mechanistic backings, not to mention discrepancies with real data are often explained away as corrections due to finite size or other variables. We propose a simple experiment and rigorous statistical procedures to look into these issues. Making use of the fact that the occurrence rate and pulse intensity of crumple sound obey power law with an exponent that varies with material, we simulate a complex system with two driving mechanisms by crumpling two different sheets together. The probability function of crumple sound is found to transit from two power-law terms to a {\it bona fide} power law as compaction increases. In addition to showing the vicinity of these two distributions in the phase space, this observation nicely demonstrates the effect of interactions to bring about a subtle change in macroscopic behavior and more information may be retrieved if the data are subject to sorting. Our analyses are based on the Akaike information criterion that is a direct measurement of information loss and emphasizes the need to strike a balance between model simplicity and goodness of fit. As a show of force, the Akaike information criterion also found the Gutenberg-Richter law for earthquakes and the scale-free model for brain functional network, 2-dimensional sand pile, and solar flare intensity to suffer excessive loss of information. They resemble more the crumpled-together ball at low compactions in that there appear to be two driving mechanisms that take turns occurring.

physics.soc-ph↗