arXiv subjects

Wolfgang Orthuber

Publications and source records attributed to Wolfgang Orthuber.

5 recordsLinked to original sources

arXiv2018

Why informatics and general science need a conjoint basic definition of information

First the basic definition of information as a selection from a set of possibilities resp. domain is recalled. This also applies to digital information. The bits of digital information are parts of number sequences which represent a selection from a set of possibilities resp. domain. For faultless conversation sender and receiver of information must have the same definition of the domain (e.g. of language vocabulary). Up to now the definition of the domain and of its elements is derived from context and knowledge. The internet provides an additional important possibility: A link to a conjoint uniform definition of the domain at unique location on the internet. The associated basic information structure is called "Domain Vector" (DV) and has the structure "UL (of the domain definition) plus sequence of numbers". The "UL" is not only "Uniform Locator" of the domain definition. It also identifies a certain kind of information for later comparison and search. It can be a Uniform Resource Locator (URL) or an abbreviated equivalent, e.g. a hierarchic numeric pointer or a short local pointer to a table with global internet pointers. The DV structure can be used as general carrier of information which is language independent and more precise than language. A domain which contains DVs is called "Domain Space" (DS) and is defined as metric space. This allows similarity search according to user defined criteria, so that any kind of definable information can be made comparable and searchable according to user selected (relevant) and objectifiable (globally uniform) criteria. DS definitions can be reused in new DS definitions. Their elements, the DVs, are automatically globally uniformly identified and defined. Obviously such conjoint definition of comparable information has great potential. It also can avoid interoperability problems and redundant programming and so save high costs.

cs.DL↗

arXiv2016

Uniform definition of comparable and searchable information on the web

Basically information means selection within a domain (value or definition set) of possibilities. For objectifiable, comparable and precise information the domain should be the same for all. Therefore the global (online) definition of the domain is proposed here. It is advantageous to define an ordered domain, because this allows using numbers for addressing the elements and because nature is ordered in many respects. The original data can be ordered in multiple independent ways. We can define a domain with multiple independent numeric dimensions to reflect this. Because we want to search information in the domain, for quantification of similarity we define a distance function or metric. Therefore we propose "Domain Spaces" (DSs) which are online defined nestable metric spaces. Their elements are called "Domain Vectors" (DVs) and have the simple form: URL (of common DS definition) plus sequence of numbers At this the sequence must be given so that the mapping of numbers to the DS dimensions is clear. By help of appropriate software DVs can be represented e.g. as words and numbers. Compared to words, however, DVs have (as original information) important objectifiable advantages (clear definition, objectivity, information content, range, resolution, efficiency, searchability). Using DSs users can define which information they make searchable and how it is searchable. DSs can be also used to make quantitative (numeric) data as uniform DVs interoperable, comparable and searchable. The approach is demonstrated in an online database with search engine (http://NumericSearch.com). The search procedure is called "Numeric Search". It consists of two systematic steps: 1. Selection of the appropriate DS e.g. by conventional word based search within the DS definitions. 2. Range and/or similarity search of DVs in the selected DS.

cs.IR↗

arXiv2003

A discrete approach to the vacuum Maxwell equations and the fine structure constant

We recommended consequent discrete combinatorial research in mathematical physics. Here we show an example how discretization of partial differential equations can be done and that quickly unexpected new findings can result from research in this up to now unexplored area. We transformed the vacuum Maxwell equations into finite-difference equations, provided simple initial conditions and studied the development of the electromagnetic fields using special software (see http://www.orthuber.com). The development is wave-like as expected. But it is not trivial, the wave maxima have different heights. If all (by definition minimal) finite differences of the location coordinates are multiplied by numbers (coupling factors) whose squares are equal to the fine structure constant, we noticed: 1. The first two wave maxima have nearly the same height. Of course this can be also coincidental. 2. The following maxima are at first slightly decreasing and then, beginning with the 6th maximum, exponentially increasing.

quant-ph↗

arXiv2002

A discrete and finite approach to past proper time

The function $γ(x)=\frac{1}{\sqrt{1-x^2}}$ plays an important role in mathematical physics, e.g. as factor for relativistic time dilation in case of $x=β$ with $β=\frac{v}{c}$ or $β=\frac{pc}{E}$. Due to former considerations it is reasonable to study the power series expansion of $γ(x)$. Here its relationship to the binomial distribution is shown, especially the fact, that the summands of the power series correspond to the return probabilities to the starting point (local coordinates, configuration or state) of a Bernoulli random walk. So $γ(x)$ and with that also proper time is proportional to the sum of the return probabilities. In case of $x=1$ or $v=c$ the random walk is symmetric. Random walks with absorbing barriers are introduced in the appendix. Here essentially the basic mathematical facts are shown and references are given, most interpretation is left to the reader.

quant-ph↗

arXiv2001

To the finite information content of the physically existing reality

Every physical measuring needs a finite, different from zero measurement time and provides information in form of the choice of a measurement result from all possible measurement results. If infinitely many (different) measurement results would be possible, the choice of a measurement result could deliver an infinite quantity of information. But the results of physical measurings (of finite duration) never deliver an infinite quantity of information, they describe past, finite reality. Therefore the set of all possible measurement results a priori is finite. In the physical reality only a finite information quantity can be processed within a finite time interval. For mathematical models whose representation requires a processing of an infinite quantity of information, for example irrational numbers, no (exact) equivalent exists in the physical reality. So mathematical calculations, which have an equivalent in physical reality, can include only rational (finitely many elementary) combinations of rational numbers. Conclusions arise from this for the foundations of mathematical physics.

quant-ph↗