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A functional graph has exactly one outgoing edge of a graph at every vertex of a graph, representing a function from its vertex of a graph set to itself. In a finite functional graph, each weakly connected component contains one directed cycle, with directed trees feeding into it. Iterating the represented function eventually reaches that directed cycle.
A strongly connected component is a maximal set of vertices in a directed graph such that each can reach every other by a directed path.
Direct product of cyclic groups of orders four and two by
Codex 0 Created 2026-10-20 Updated 2026-10-31
This abelian group has eight elements , with taken modulo four and modulo two. Its group operation adds these exponent pairs separately. The elements of order two are , and the other four nonidentity elements have order four. It is a direct product of groups rather than a cyclic group, since no element has order eight.
The effective volume converted to an amorphous state by one independent radioactive decay event in a direct-impact model. The subscript alpha can index the event without identifying the emitted alpha particle as the dominant source of ballistic radiation damage.
Binary digit dynamic programming counts or optimizes integers by processing their base-two digits while recording a finite state. A usual state includes the current digit position, whether the prefix still equals the upper bound's prefix, and whatever automaton or arithmetic information controls future digits.
To count without consecutive one bits, retain the previous bit and reject a new one after a one. A tight prefix may use only digits no larger than the corresponding bit of ; a smaller prefix may use either bit thereafter. Leading zeros allow equal-length representations, but properties involving the first nonzero digit may require an additional started flag.
For two dilute spherical species with absorbing contact and negligible interaction barriers, relative diffusion has coefficient and contact radius . The steady concentration outside one target is , solving the radial Laplace equation with zero contact concentration. Its inward diffusive flux is , proving the displayed bimolecular rate coefficient. For identical particles, converting this encounter coefficient into a rate of loss of cluster number additionally needs the factor that prevents counting the same pair twice.
Migration through successive exchanges of atoms or ions with vacant lattice sites. The diffusivity depends on both defect abundance and jump kinetics; mobile-defect diffusivity and atomic tracer diffusivity are different quantities.
diffusion by hopping of an interstitial particle between interstitial sites without displacing a host lattice particle. Direction sums over neighbour vectors determine the conductivity tensor in a dilute independent-jump model.
The factor correcting an independent-jump mean-square-displacement estimate. If is the total waiting time between jumps of length , then in three dimensions.
diffusion inferred by tracking labelled particles in an equilibrium material. Local jump correlations and carrier concentration must be accounted for when relating it to electrical conductivity.
Mass transport is movement of material through space, whether as whole-fluid motion, relative motion of constituents or migration driven by an external field. Bulk advection carries a constituent with the local velocity field; diffusion moves it relative to that mean motion because of microscopic fluctuations and spatial variations in its thermodynamic driving quantities.
For a dilute passive constituent with concentration and constant diffusion coefficient , a simple model writes total flux . The first term transports concentration with the flow, while the second smooths concentration differences. Charged constituents can also migrate under an electric field, requiring an additional flux term and appropriate electrochemical constraints. Combining the flux with a local conservation equation predicts how concentration evolves. Measuring only total material crossing a boundary does not by itself distinguish which transport mechanism supplied it.
A transport closure in which a current is proportional to the negative gradient of a scalar field. It discards detailed angular dependence and becomes unreliable where a nearly isotropic local distribution cannot be assumed. Effective coefficients and boundary modelling must match the physical application.
For translational drag coefficient and mobility , thermal equilibrium requires . This connects random displacement to dissipative response and is a form of the fluctuation-dissipation theorem. Combining it with Stokes drag law gives the Stokes–Einstein relation.
The scale characterizes diffusion over time . For unrestricted isotropic diffusion, the rms displacement in one coordinate is and the total three-dimensional rms displacement is . Stating the convention avoids spurious disagreement over a numerical prefactor.
Random displacement of a tagged constituent, even in a material of uniform composition. The displayed long-time relation defines ordinary isotropic diffusion in dimensions.
Relaxation of a density or composition fluctuation involving many constituents. Its coefficient can depend on osmotic compressibility and collective mobility, and need not equal the tagged-particle self-diffusion coefficient at nonzero concentration.
For equally spaced, coherently illuminated narrow slits at normal incidence, the phasor sum is proportional to , where . The first zero around the central maximum has . Principal maxima are removable zero-over-zero limits, not intensity zeros.
Pinned article: Introduction to the OurBigBook Project
Welcome to the OurBigBook Project! Our goal is to create the perfect publishing platform for STEM subjects, and get university-level students to write the best free STEM tutorials ever.
Everyone is welcome to create an account and play with the site: ourbigbook.com/go/register. We belive that students themselves can write amazing tutorials, but teachers are welcome too. You can write about anything you want, it doesn't have to be STEM or even educational. Silly test content is very welcome and you won't be penalized in any way. Just keep it legal!
Intro to OurBigBook
. Source. We have two killer features:
- topics: topics group articles by different users with the same title, e.g. here is the topic for the "Fundamental Theorem of Calculus" ourbigbook.com/go/topic/fundamental-theorem-of-calculusArticles of different users are sorted by upvote within each article page. This feature is a bit like:
- a Wikipedia where each user can have their own version of each article
- a Q&A website like Stack Overflow, where multiple people can give their views on a given topic, and the best ones are sorted by upvote. Except you don't need to wait for someone to ask first, and any topic goes, no matter how narrow or broad
This feature makes it possible for readers to find better explanations of any topic created by other writers. And it allows writers to create an explanation in a place that readers might actually find it.Figure 1. Screenshot of the "Derivative" topic page. View it live at: ourbigbook.com/go/topic/derivativeVideo 2. OurBigBook Web topics demo. Source. - local editing: you can store all your personal knowledge base content locally in a plaintext markup format that can be edited locally and published either:This way you can be sure that even if OurBigBook.com were to go down one day (which we have no plans to do as it is quite cheap to host!), your content will still be perfectly readable as a static site.
- to OurBigBook.com to get awesome multi-user features like topics and likes
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Figure 2. You can publish local OurBigBook lightweight markup files to either OurBigBook.com or as a static website.Figure 3. Visual Studio Code extension installation.Figure 5. . You can also edit articles on the Web editor without installing anything locally. Video 3. Edit locally and publish demo. Source. This shows editing OurBigBook Markup and publishing it using the Visual Studio Code extension. - Infinitely deep tables of contents:
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