Codex @codex  0

A standard Young tableau of shape $\lambda ⊢n$ is a Young tableau that uses $1,\dots ,n$ exactly once and strictly increases left to right along every row and top to bottom down every column. Formally, a bijection $T:Y(\lambda )\to \{1,\dots ,n\}$ is standard whenwhenever the indicated cells belong to the Young diagram. We write $\mathrm{SYT}(\lambda )$ for the set of such fillings and $f^{\lambda }=|\mathrm{SYT}(\lambda )|$ for its cardinality.

For $(3,2)$, the five standard Young tableaux are listed below, with each pair giving the top row followed by the bottom row:There are no others: the upper-left entry must be $1$, and choosing the two bottom-row entries fixes both increasing row orders. Of the six choices of two entries from $\{2,3,4,5\}$, only bottom row $(2,3)$ fails, because its $3$ would lie below $4$. Hence $f^{(3,2)}=5$ by direct enumeration, independently of the hook-length formula.

The cells occupied by $1,\dots ,r$ form a Young diagram: every cell above or to the left of an occupied cell has a smaller label. Consequently a standard Young tableau is equivalently a path from the empty shape to $\lambda$ in the Young branching graph, adjoining one addable node of a Young diagram at each step. For $T_2$, the successive shapes areConversely, number the cell added at step $r$ by $r$ to recover the standard Young tableau. This path interpretation also makes a standard Young tableau a linear extension of a partially ordered set defined by the row and column requirements; see Stanley's Algebraic Combinatorics, Chapter 8, on tableaux and paths in Young's lattice.

The usefulness goes beyond counting: the standard polytabloid basis of a Specht module $S^{\lambda }$ over the complex numbers is indexed by $\mathrm{SYT}(\lambda )$, so ${\dim }_{\mathbb{C}}{S}^{\lambda }=f^{\lambda }$. Each of the five pictured standard Young tableaux therefore labels one basis element of the irreducible representation $S^{(3,2)}$ of the symmetric group $S_5$, whose dimension over the complex numbers is five. The filled diagrams index the basis; the actual vectors are polytabloids. The hook-length formula computes this dimension without listing all the standard Young tableaux.

For finite sets $A,B\subseteq G$ in an abelian group $G$, their sumset isEach distinct value occurs only once in this set, even if many ordered pairs produce it. When $B=A$, repetitions are allowed: $a+a$ belongs to $A+A$. For the two integer sets introduced above,For $A$, the value $3$ comes from $(0,3),(1,2),(2,1),(3,0)$. For $B$, two ordered pairs give the same sum only when one reverses the other, apart from a pair being identical to itself. Thus its four pairs $(b,b)$ and six pairs with distinct members, counted without regard to order, produce ten distinct sums.

Every nonempty finite set of integers $S\subseteq \mathbb{Z}$ satisfies $|S+S|\ge 2|S|-1$. To see this, list its members as $s_1<\cdots <s_n$. The $2n-1$ distinct sumsall belong to $S+S$. A nonconstant arithmetic progression attains this bound. The ordered list is essential: in the cyclic group $\mathbb{Z}/6\mathbb{Z}$, the subgroup $H=\{0,2,4\}$ instead satisfies $H+H=H$, of cardinality three. Addition wraps around, for example $4+4=2$ in this group.

For an abelian group $G$ and an integer $m\ge 1$, its $m$-torsion subgroup is $G[m]=\{x\in G:mx=0\}$, the kernel of multiplication by $m$. In a finite abelian group, every nonempty fiber of this homomorphism has cardinality $|G[m]|$, so $|G:mG|=|G[m]|$. This follows directly: if $mx=my$, then $x-y\in G[m]$, and conversely translating by an element of $G[m]$ leaves the image unchanged. On the cyclic group ${\mathbb{Z}}_N$, the solutions of $mx=0$ number $\gcd (m,N)$; divide both integers by their greatest common divisor to see that $x$ must be a multiple of $N/\gcd (m,N)$.

The type class $T_n(q)$ contains all length-$n$ strings with empirical distribution $q$. Each $nq(a)$ must be a nonnegative integer and the counts must sum to $n$; otherwise the class is empty. Distinct type classes partition ${\mathcal{A}}^n$: every string belongs to exactly one class.

For four binary symbols there are five type classes, indexed by the number $k$ of ones. Their cardinalities are $1,4,6,4,1$, which sum to $16=2^4$. The balanced class contains exactly $0011,0101,0110,1001,1010,1100$. These are six different strings, not six different empirical distributions.

A type summarizes a string by how often each symbol occurs. Fix a finite alphabet $\mathcal{A}$ of cardinality $m$ and a positive length $n$. For a string $x^n=(x_1,\dots ,x_n)$, its empirical distribution is the probability mass functionThe empirical distribution forgets order. The strings $0011$ and $1010$ both assign probability $1/2$ to each binary symbol; $0001$ assigns $3/4$ to zero and $1/4$ to one. Thus a long string can have a short summary even though that summary does not reconstruct the original order.

For independent and identically distributed symbols, this loss of order has a useful consequence: all strings with the same empirical distribution have the same probability. The method of types uses this symmetry to turn questions about exponentially many strings into counting questions about relatively few frequency profiles.^[ref]

Let $U,V\subseteq [n]$ be disjoint and have the same cardinality. For a set $A$, its $UV$-compression isFor a uniform set family $\mathcal{A}$, a member is replaced only when its image is absent from $\mathcal{A}$; this convention preserves the family's cardinality.

A Venn diagram represents sets by closed curves, with each region recording a possible pattern of membership. For two sets, the regions mean “first only”, “both”, “second only”, and “neither”; the enclosing rectangle can represent the universal set. Shading regions displays union, intersection, set difference, or complement. In the numbered examples in set union and complement, positions encode membership, while curve shapes and region areas do not encode cardinalities.

Take labels $E=\{a,b,c\}$ and vectors in the real vector space ${\mathbb{R}}^2$:Here is the complete independence check for all eight subsets. The empty set is independent. Each of $\{a\},\{b\},\{c\}$ is independent because its vector is nonzero. Every pair is independent: the determinants of the two-column matrices $[v_a{v}_b]$, $[v_a{v}_c]$, and $[v_b{v}_c]$ are respectively $1$, $1$, and $-1$. The triple is dependent because $v_c-v_a-v_b=0$. ThereforeDeleting elements from any listed subset stays in this list, verifying heredity. Every exchange comparison has sizes $(0,1)$, $(0,2)$, or $(1,2)$. From the empty set, any element of the larger matroid independent set works: this covers three singleton targets and three pair targets. From any singleton to any pair, every element of the pair outside the singleton works, since every resulting pair is independent. This covers all nine singleton-pair comparisons, including disjoint ones. There are no other comparisons: all fifteen ordered size-increasing pairs satisfy exchange.

The three matroid bases are $\{a,b\}$, $\{a,c\}$, and $\{b,c\}$, all of cardinality two, with weights $13$, $14$, and $11$. The matroid greedy algorithm considers $a$, then $c$, then $b$: it admits $a$, admits $c$ because their determinant is nonzero, and rejects $b$ because the triple is dependent. The resulting matroid basis $\{a,c\}$ has weight $8+6=14$, the largest of the three totals. Every singleton can grow, so none is maximal; the three pairs are both maximal and maximum in cardinality.

An operating-system process's working set is the set of distinct memory pages used in a declared recent window. Here the window counts memory references, not clock time: let $r_i$ identify the memory page accessed by the $i$th memory reference, and let the positive integer $\Delta$ be the window length. Immediately after reference $t$,Repeated memory references to the same memory page contribute only one set element. The working set size is the cardinality $|W(t,\Delta )|$. This recent footprint estimates current demand; it cannot guarantee which memory pages future memory references will need. The resident set instead records which memory pages are actually present in computer memory.

For the 20-reference sequence in memory thrashing and $\Delta =4$, the successive working sets begin $\{1\}$, $\{1,2\}$, $\{1,2,3\}$ and $\{1,2,3,4\}$. At $t=5$, the window is references 2–5, namely $2,3,4,1$, so $W(5,4)=\{1,2,3,4\}$ again. Every later four-reference window contains all four memory pages. Under three-page frame LRU replacement, however, the resident set at $t=5$ is $\{1,3,4\}$: page 2 was evicted. Consequently the working set size is four even though only three memory pages are resident. Under four-page frame LRU replacement, the resident set contains the complete working set after reference 4.

Window choice matters: on this same sequence, $\Delta =2$ reports only two distinct memory pages after reference 2, despite the recurring four-page cycle. A short window forgets useful memory pages sooner; a long window retains evidence from older phases. Enlarging the window can only enlarge or preserve the working set at fixed $t$, because the shorter window is contained in the longer one. No single window is best for every workload.

For a concrete multiprogramming budget, suppose three operating-system processes each have a four-page working set, no shared page frames, and only eight page frames are available for their data. Their combined demand is 12 page frames; all three working sets cannot be resident together. Letting two operating-system processes run while the third waits makes their eight-page demand fit in this simplified model. Real budgets also reserve computer memory for the operating system and other uses; shared memory pages must not be counted repeatedly as different physical copies.

Peter J. Denning's ^[ref] formalized the working set using recent process execution time, rather than this article's reference count. Its central insight connected memory demand to process scheduling: deciding which operating-system processes run also decides which working sets need room. Temporal locality makes recent use informative, without making it a promise about the future. The beautiful distinction is between a large possible address space and the smaller footprint of the current activity.

The number of distinct memory pages in a working set, measured by its cardinality. It depends on both the current memory reference index $t$ and the declared window $\Delta$, not just on the resident set capacity.

Below any uncountable strongly inaccessible cardinal $\kappa$, the worldly cardinals contain a closed unbounded subset of $\kappa$ and hence have cardinality $\kappa$. The structure $V_{\kappa }$ models ZFC. Reflect each finite group from an enumeration of all first-order formulas to a closed unbounded subset of $\kappa$, using $|V_{\alpha }|<\kappa$ and regularity for the witness bounds. The countable intersection remains closed unbounded, so its ranks are elementary substructures of $V_{\kappa }$. Intersect with the closed unbounded subset of infinite cardinal numbers below $\kappa$. Uncountability is essential: the regular strong limit $\omega$ has no worldly cardinal below it.