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The 2-adic absolute value is the p-adic absolute value for the prime number $p=2$. It is defined on the rational numbers by $|x{|}_2=2^{-v_2(x)}$ for $x\ne 0$ and $|0{|}_2=0$, and extends to their P-adic number completion ${\mathbb{Q}}_2$. For a nonzero integer, count factors of two until the remaining factor is odd; for a rational number, subtract the denominator's count from the numerator's count.

The associated metric reverses a familiar comparison:Although $13$ is eight units from $5$ on the ordinary number line, it agrees with $5$ modulo $8$, whereas $6$ already disagrees modulo $2$. The 2-adic absolute value measures that agreement. The value $|3/8{|}_2=8$ also shows why this Non-Archimedean absolute value must be distinguished from the ordinary absolute value $|3/8|=3/8$.

In the left panel, differences farther from the diagonal grow in ordinary absolute value. In the right panel, nonzero even differences are closer than odd differences, and each further factor of two halves the 2-adic absolute value. The highlighted pairs have opposite distance rankings. The repeated pattern is the nested congruence class structure of an ultrametric space, visible without adding any new points.

Addition combines two numbers into their sum. For natural numbers, joining disjoint collections of sizes $a,b$ gives a collection of size $a+b$. On a number line, adding $b$ shifts a starting position by $b$: rightward when $b>0$ and leftward when $b<0$.

Starting at $2$ and adding $3$ reaches $5$. Starting there and adding $-3$ returns to $2$, because $3+(-3)=0$. Additive inverses turn this return move into an algebraic rule. With real numbers, addition is commutative and associative: exchanging two shifts or grouping several shifts differently leaves the final position unchanged.

The bottom panel applies $x\mapsto -3x/2$. Input $2$ becomes $-3$, and input $-2$ becomes $3$. Multiplication by a negative real number rescales distances from zero and reverses direction, giving a reflection in mathematics as well as a scale change. This is a different operation from shifting every input by one fixed amount.

Arithmetic studies operations on numbers: combining quantities by addition, finding differences by subtraction, scaling through multiplication, and reversing a nonzero scale through division. Its usefulness goes beyond producing an answer. A calculation can express how resources are shared, how a measurement changes with scale, or why two different descriptions of a quantity agree.

The allowed numbers matter. Start with the natural numbers $0,1,2,\dots$. Counting collections gives $2+3=5$, but removing three from two calls for the integer $-1$. Sharing three units equally between two recipients gives the rational number $3/2$. These operations motivate larger number systems: integers supply additive inverses, and rational numbers supply division by nonzero integers. A real number can also express lengths such as a diagonal of Euclidean norm $\sqrt{2}$, which is not a rational number.

The beauty is that bookkeeping, geometry, and algebra can check one another. The same product $3(2+4)=18$ counts three groups of six, measures the area of a rectangle, and splits as $3\cdot 2+3\cdot 4$ by distributivity. A number line makes negative integers visible as positions; a fraction records an exact share even when its decimal representation does not terminate. An arithmetic rule becomes easier to remember when these interpretations fit together.

An equivalence relation says which set elements should count as the same for a particular purpose. In modular arithmetic, for example, distinct integers with the same remainder are equivalent. The relation gathers interchangeable set elements into equivalence classes; the quotient set then treats each whole equivalence class as one object.

Formally, an equivalence relation on a set $X$ is a binary relation $R\subseteq X\times X$, written $x\sim y$, satisfying three conditions for all $x,y,z\in X$:These conditions make the equivalence classes a partition of a set: each set element belongs to exactly one class. ^[ref]

For a worked example, take the finite set $X=\{0,1,\dots ,8\}$ and restrict integer congruence modulo three to $X$:Reflexivity follows because $x-x=0$. The symmetric relation property follows by changing the sign of a difference, and transitivity follows by adding $x-y$ and $y-z$: divisibility by three is preserved in both steps. Thus $0\sim 3$ and $3\sim 6$ force $0\sim 6$. The three equivalence classes are $\{0,3,6\}$, $\{1,4,7\}$ and $\{2,5,8\}$. Their members alternate along the number line; membership in an equivalence class need not mean being close together.

The transitivity requirement rules out a tempting alternative. On $\{0,1,2\}$, define nearness by the absolute value condition $|x-y|\le 1$. This binary relation is reflexive and symmetric, but $0$ is near $1$ and $1$ is near $2$ while $0$ is not near $2$. Its neighborhoods $\{0,1\}$, $\{0,1,2\}$ and $\{1,2\}$ overlap without being equal. They are not equivalence classes or a partition of a set.

Floating-point arithmetic represents a real number by a sign, a fixed number of significant digits, and a scale. It trades exactness for a compact representation spanning many orders of magnitude. The picture shows the essential compromise: with the same precision, large numbers have wider gaps between representable neighbors. Thus accuracy is naturally relative to magnitude, rather than a fixed distance along the number line.

In radix $\beta$, an integer at least two, a nonzero normalized value has the positional notationwhere the digits and exponent $e$ are integers. The parenthesized factor is the significand; $p$ counts all its significant digits, including the leading digit. Normalization means $d_0\ne 0$, so the same value has one such representation. The allowed exponents satisfy $e_{\min }\le e\le e_{\max }$. Finite precision restricts the available digits, while the exponent bounds restrict the range. Zero needs a separate representation. This scales a digit string in positional notation by a power of its base.^[ref]

For positive normalized values in $[{\beta }^e,{\beta }^{e+1})$, increasing the last digit by one gives the constant neighbor spacingAt the next scale, the spacing is multiplied by $\beta$. In the binary numeral system with $p=4$, the values in $[1,2)$ are $1,1.125,1.25,\dots ,1.875$; those in $[2,4)$ are $2,2.25,\dots ,3.75$; those in $[4,8)$ are $4,4.5,\dots ,7.5$. The respective gaps are $1/8$, $1/4$, and $1/2$. Although absolute resolution deteriorates with magnitude, ${\Delta }_e/y$ stays between ${\beta }^{-p}$ and ${\beta }^{1-p}$. This scale invariance is why floating-point arithmetic suits both microscopic and astronomical calculations.

The IEEE 754 binary64 format uses the binary numeral system with $p=53$, including an implicit leading one for normalized values, and normal exponents $-1022\le e\le 1023$. Its 64 stored binary digits comprise one sign digit, 11 exponent digits and 52 trailing significand digits. Subnormal numbers extend the range toward zero with a different leading-digit rule. In rounding to nearest, an operation returns the representable value closest to its exact result; a tie goes to the value whose last significant binary digit is even. Machine epsilon describes the gap just above one, whereas unit roundoff bounds a single relative rounding error in the normal range. These format and rounding rules are presented in MIT's floating-point lecture.^[ref]

Even an ordinary terminating decimal can require rounding in the binary numeral system. The rational number $0.1=1/10$ has the repeating positional notation $0.0001100110011\dots {}_2$. Every finite binary fraction has a reduced denominator that is a power of two, so the factor five in $10$ prevents an exact finite binary representation. In binary64, the exact stored values of three decimal literals and their computed sum areThe exact sum of the first two stored rational numbers is $10808639105689191/36028797018963968$, halfway between two binary64 values. The even-last-digit tie rule rounds it upward. The printed result is 0.30000000000000004, one step $2^{-54}$ above stored 0.3, so 0.1 + 0.2 == 0.3 is false. Both conversion of the inputs and rounding of the addition matter here.

To reproduce the table on a Python installation using binary64, inspect exact fractions rather than only their printed decimal representations:Python's as_integer_ratio() returns a pair of integers whose quotient equals the stored finite value exactly.^[ref] Exact rational numbers are also useful for checking floating-point arithmetic: a short decimal printout can hide the approximation being made.

Historically, David Goldberg's March 1991 ACM Computing Surveys paper explained representation, rounding and catastrophic cancellation together with the IEEE standard's design choices. Oracle provides an authorized edited reprint. Its enduring lesson is practical: use the spacing to understand roundoff error, and inspect intermediate values when mathematically equivalent algorithms behave differently.^[ref]

An integer is a whole number, positive, negative, or zero. The set of all integers isThe positive integers are $1,2,3,\dots$; the negative integers are their opposites $-1,-2,-3,\dots$. Zero is neither positive nor negative. The nonnegative integers include zero and all the positive integers. On a number line, consecutive integers are one unit apart, negative integers lie to the left of zero, and positive integers lie to its right. ^[ref]

The integers let counting describe changes in both directions. If a counter starts at $-3$ and increases by five, it reaches $2$: $-3+5=2$. Decreasing that result by four gives $2+(-4)=-2$. In addition on the number line, the sign of the added integer chooses the direction and its absolute value gives the distance. The additive inverse $-a$ reverses the change made by $a$.

The integers have closure under a binary operation for addition, subtraction and multiplication: whenever $a,b\in \mathbb{Z}$, the results $a+b$, $a-b$ and $ab$ are still integers. Together these operations give the integers their ring structure.^[ref] For instance, $-3+5=2$, $-3-5=-8$, and $(-3)\cdot 5=-15$. General division has no such closure: $1/2$ is a rational number but not an integer. Some divisions are exact, such as $(-6)/3=-2$; division by zero is undefined. Euclidean division instead produces an integer quotient and a remainder, so $7=3\cdot 2+1$ retains the information that ordinary division puts into the fraction $7/3$.

An integer is the value, whereas its written numeral is an encoding. The decimal representation $205_{10}$ and the binary representation $11001101_2$ name the same integer. Changing positional notation changes how that value is displayed and how calculations are organized; it does not change the value itself.

Modular arithmetic performs addition and multiplication on integers while remembering only their remainders for a fixed positive integer modulus $m$. The relation $a\equiv b(\mathrm{mod}m)$ means that $m$ divides $a-b$: the two integers lie in the same congruence class. For example, $-3$, $2$ and $7$ represent one class modulo $5$. Choosing the least nonnegative residue gives exactly $m$ representatives, $0,1,\dots ,m-1$, even though each congruence class contains infinitely many integers.

A clock supplies a familiar example. Represent the twelve positions by $0,1,\dots ,11$, with $0$ at the position usually labelled twelve. Starting at ten and moving seven positions givesThe integer congruence records the final position; it discards the number of complete revolutions. Adding another twelve changes the elapsed count while preserving the position. The picture also shows a single congruence class modulo five spread along the number line.

The useful surprise is that discarding this information still preserves the arithmetic. If $a\equiv a^{\prime }$ and $b\equiv b^{\prime }$ modulo $m$, then $a+b\equiv a^{\prime }+b^{\prime }$ and $ab\equiv a^{\prime }{b}^{\prime }$ modulo $m$. Thus a large calculation can reduce its intermediate integers after every step. For instance,Replacing $10$ by $-2$ gives the same answers with smaller intermediate values. The congruence classes with these operations form the quotient ring $\mathbb{Z}/m\mathbb{Z}$; their addition alone forms a cyclic group. This passage from integers to a finite arithmetic system is the setting for modular exponentiation, primality testing and the RSA cryptosystem. ^[ref]

Multiplicative cancellation needs extra care. Modulo six, $2\cdot 1\equiv 2\cdot 4$, but $1\not\equiv 4$: multiplication by two has merged distinct congruence classes. Cancelling a factor while retaining the integer modulus is justified when that factor has a modular multiplicative inverse, equivalently when it is coprime to the integer modulus. A linear congruence can consequently have no solutions, one solution class, or several solution classes. The Chinese remainder theorem supplies a complementary operation: splitting a calculation across coprime integer moduli and reconstructing its class modulo their product.

Small remainders can also certify impossibility. A perfect square has residue zero or one modulo four, as checking the four congruence classes shows. Therefore an integer equation $x^2=4k+2$ has no solution. The converse direction needs care: a permitted residue does not guarantee an integer solution, since $5\equiv 1(\mathrm{mod}4)$ but five is not a perfect square. Such local tests provide necessary conditions for Diophantine equations without replacing the full problem.

In Disquisitiones arithmeticae (1801), Carl Friedrich Gauss defines integer congruence in article 1 and adopts the symbol $\equiv$ in article 2. Article 12 derives divisibility tests from powers of ten and explains checking arithmetic by its remainders. These passages show a systematic treatment of the same idea; they are not a claim that remainders were first used in 1801. ^[ref]

Fix a prime number $p$. Write a nonzero rational number as $x=p^{k}a/b$, where $k\in \mathbb{Z}$ and the nonzero integers $a,b$ are not divisible by $p$. The exponent $k$ is uniquely determined. Its P-adic valuation is this signed exponent $v_p(x)=k$: equivalently, for any nonzero integer numerator $A$ and denominator $B$,Factors of $p$ in the numerator decrease the p-adic absolute value; factors in the denominator increase it. For $p=2$ the computations are:

This is an absolute value on a field measuring divisibility, rather than the magnitude on a real number number line. It satisfiesThe proof comes directly from P-adic valuations: exponents add in a product of numbers, and extracting a common power of $p$ from a sum gives $v_p(x+y)\ge \min \{v_p(x),v_p(y)\}$. If the two P-adic valuations differ, the remaining term with smaller exponent cannot cancel modulo $p$, so equality holds. Thus the p-adic absolute value is a Non-Archimedean absolute value. ^[ref]

The metric $d_p(x,y)=|x-y{|}_p$ makes two rational numbers close when their difference contains a high power of $p$. This packages successive modular congruences into a numerical error estimate, allowing convergence in a metric space and convergent series to encode exact arithmetic information.

A real number is an element of the complete ordered field $\mathbb{R}$.

Subtraction adds the additive inverse: $a-b=a+(-b)$. On the number line, $2-3=-1$ is a shift three units left from $2$. Reversing the two inputs changes the sign: $3-2=1$, so subtraction is generally not commutative. Solving $x+3=2$ gives the same answer $x=-1$ by adding $-3$ to both sides; the operation preserves equality while undoing the added amount.

An ultrametric space is a metric space whose metric satisfies the ultrametric inequality. The rational numbers with $d_p(x,y)=|x-y{|}_p$, and their P-adic number completion, are examples. Their geometry organizes points into nested clusters rather than measuring separation along a number line.

For integers $a,b$ and $k\ge 0$, the definition of the P-adic valuation givesThus a closed ball of radius $p^{-k}$ in the integers is a congruence class modulo $p^k$. In the p-adic integers the same closed ball is $a+p^k{\mathbb{Z}}_p$. More shared low-order digits mean a smaller p-adic absolute value of the difference.

The binary tree first splits the sixteen integers into even and odd congruence classes, then refines modulo $4$, $8$, and $16$. Each node fixes one more low-order digit. The leaves $5$ and $13$ share the class $5$ modulo $8$, then separate modulo $16$, so their distance is exactly $1/8$. The leaves are deliberately ordered by their low-order digits; horizontal spacing and edge lengths are layout choices, not the metric. The singleton leaves describe this finite sample; a congruence class modulo $16$ in all p-adic integers remains infinite.

The ultrametric inequality also explains the unusual behavior of balls. Every point of an open ball can serve as its center: if $d(a,b)<r$, then $d(a,x)<r$ if and only if $d(b,x)<r$. Two open balls that intersect are nested, since a point of their intersection serves as a common center and their radii can be compared. The same nesting rule holds for closed balls and for a pair consisting of one open ball and one closed ball.

Every open ball is a clopen set. For a point $y$ outside $B(a,r)$, the open ball $B(y,d(a,y))$ stays outside $B(a,r)$: if $d(y,z)<d(a,y)$, the ultrametric inequality forces $d(a,z)=d(a,y)\ge r$. Hence the complement is an open set. Also every closed ball of positive radius is an open set, because $B(b,r)$ lies in the closed ball of radius $r$ around $a$ whenever $d(a,b)\le r$. A radius-zero closed ball is a singleton and need not be an open set. Distinct points can therefore be separated by a clopen set, proving that an ultrametric space is totally disconnected. These ball properties turn distance thresholds into a hierarchy of compatible clusters. ^[ref]