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Notation cheat sheet

Every symbol, operator, decoration and constant used in this guide, grouped by topic. Each entry says how to read it aloud, what it means, gives a small example, and names the chapter where it does the most work. When a symbol has several meanings (λ, σ, π, e), all of them are listed. The chapter you're reading always says which one applies.

Arithmetic, comparison and rounding

Symbol Read it as Meaning Example Ch.
+, - / − "plus", "minus" addition, subtraction (or a negative sign) 5 − 3 = 2 all
· or × "times" multiplication (· is used inside formulas, × in prose) 3·4 = 12 all
/ or ÷ "divided by" division 12/4 = 3 all
± "plus or minus" a range, or both signs 50 ± 9.8 ms = 40.2 to 59.8 14, 22
= "equals" exactly equal 2 + 2 = 4 all
≠ "is not equal to" different AB ≠ BA 10
≈ "approximately" close enough for the purpose π ≈ 3.14 all
≡ "is congruent to" (or "is defined as") equal after reducing mod n 17 ≡ 2 (mod 5) 2, 19
∝ "is proportional to" equal up to a constant factor P(spam|words) ∝ … 16
< > ≤ ≥ "less than", "greater than or equal" … ordering ρ < 1 all
≪ / << "much less than" orders of magnitude smaller r ≪ n in LoRA 20
|x| "absolute value of x" drop the sign |-3| = 3 9, 10
⌊x⌋ "floor of x" round down ⌊2.7⌋ = 2 2
ceil(x) / ⌈x⌉ "ceiling of x" round up ceil(6.1) = 7 1, 29
√x "square root of x" the number that squared gives x √144 = 12 9, 14
xⁿ, x^n "x to the n" x multiplied by itself n times 2¹⁰ = 1024 5
x⁻¹ "x inverse" 1/x, or the modular / matrix inverse 3⁻¹ ≡ 4 (mod 11) 10, 19
n! "n factorial" n·(n-1)·…·1 4! = 24 14, 15
% "percent" or, in code, "mod" per hundred; in Python a % n is the remainder 17 % 5 = 2 2
∞ "infinity" grows without bound W → ∞ as ρ → 1 12, 25
½, ¼ "a half", "a quarter" fractions ½λw² 13, 21
→ "goes to" / "maps to" a limit, or a function's input → output h → 0 4, 12
° "degrees" angle; 360° = 2π radians 90° rotation 7, 10
↔ "swaps with" / "if and only if" two-way correspondence rows ↔ columns 10
∎ "end of proof" the argument is complete 17

Decorations on letters: subscripts, superscripts, hats, bars

Notation Read it as Meaning Example Ch.
xᵢ, x_i, xₖ, x₁ "x sub i" a subscript is an index or label: the i-th item, or a named variant (β₁, f_max, d_k) x₃ = third value all
x_{n+1} "x sub n plus one" the next value in a sequence or iteration Newton's x_{n+1} 12
A[i][j], Aᵢⱼ "A i j" the entry in row i, column j A²[R1][R4] = 1 10
x², xᵏ, xᵗ, gᵉ "x squared", "x to the k" a superscript is a power (not an index), except ᵀ (transpose) and ⁻¹ (inverse) σ² = variance all
x̄, ȳ "x bar", "y bar" the average of the x (or y) values x̄ = 3 9, 14
p̂, θ̂ "p hat" an estimate computed from data p̂ = k/n 21, 22
x*, θ* "x star" the optimal value n* = 20 servers 12, 13
f'(x), f''(x) "f prime", "f double prime" first and second derivatives (x²)' = 2x 12
Δx "delta x" a (finite) change in x slice width in a Riemann sum 12
x_new ← … "x becomes …" assignment / an update step w ← w - η·g 9, 21
[i = c] "one if i equals c, else zero" indicator (Iverson bracket) used in the softmax gradient 13

Sets and logic

Symbol Read it as Meaning Example Ch.
{…} "the set of …" a collection with no duplicates {2, 3, 5, 7} 4
∈ / ∉ "is in" / "is not in" membership 3 ∈ {1,2,3} 4
⊆ "is a subset of" every element is also in the other set {1} ⊆ {1,2} 4
∪ "union" in either set A ∪ B 4, 8
∩ "intersection" in both sets A ∩ B 4, 8
∅ "the empty set" no elements, an impossible event A ∩ B = ∅ 8
Ω "omega" sample space: every possible outcome coin: {H, T} 8
ℝ "the reals" all real numbers x ∈ ℝ 10
ℝⁿ "R n" lists (vectors) of n real numbers an embedding ∈ ℝ⁷⁶⁸ 10, 20
ℤ, ℤₙ "the integers", "Z mod n" whole numbers; {0, …, n-1} with wrap-around ℤ₁₇ 19, 24
ℤₙ* "the units mod n" elements of ℤₙ that have an inverse; there are φ(n) ℤ₁₀* = {1,3,7,9} 19
∀ / ∃ "for all" / "there exists" quantifiers ∀x: x² ≥ 0 4
¬, NOT "not" negation ¬true = false 3
∧, AND, & "and" both 1 ∧ 0 = 0 3
∨, OR, | "or" either (or both) 1 ∨ 0 = 1 3
⊕, XOR, ^ "x-or" exactly one of the two 1 ⊕ 1 = 0 3
<<, >> "shift left / right" multiply / divide by powers of 2 (in code) 1 << 4 = 16 1
f: A → B "f maps A to B" a function from inputs A to outputs B hash: str → int 4

Number theory and cryptography

Symbol Read it as Meaning Example Ch.
a mod n "a mod n" remainder of a ÷ n 17 mod 5 = 2 2
a ≡ b (mod n) "a is congruent to b mod n" n divides a - b 38 ≡ 2 (mod 12) 2, 19
a | b / a ∤ b "a divides b" / "does not divide" b is (not) a multiple of a 5 | 15, p ∤ a 19
gcd(a, b) "greatest common divisor" largest number dividing both gcd(48, 18) = 6 19
a⁻¹ (mod n) "inverse of a mod n" the x with a·x ≡ 1; exists iff gcd(a,n)=1 17⁻¹ ≡ 2753 (mod 3120) 19, 24
φ(n) "phi of n", Euler's totient count of 1…n coprime to n φ(61·53) = 3120 19, 24
π(N) "pi of N", prime-counting function number of primes ≤ N (not 3.14…) π(100) = 25 19
p, q large secret primes (RSA) / a public prime (DH) 61, 53 24
n = p·q "the modulus" RSA public modulus; also a curve's group order in ECDSA 3233 24
e, d "public / private exponent" RSA keys, e·d ≡ 1 (mod φ(n)) (this e is not 2.718…) 17, 2753 24
g, a, b, A, B DH generator, private exponents, public values A = gᵃ mod p 24
G, k·G "G", "k times G" elliptic-curve base point; adding G to itself k times 3G = (10, 6) 24
O "the point at infinity" the identity ("zero") of an elliptic-curve group 19G = O 24
(r, s), k, z ECDSA signature, per-signature nonce, message hash 24
H(·) "hash of" a cryptographic hash function SHA-256(m) 24
2ᵇ "bits of security" an attack needs about 2ᵇ operations AES-128: 2¹²⁸ 24

Functions, sums and calculus

Symbol Read it as Meaning Example Ch.
f(x) "f of x" function f applied to input x f(3) = 9 for x² 4
f(g(x)), f∘g "f of g of x", "f composed with g" composition: apply g, then f layers of a network 13
Σᵢ₌₁ⁿ xᵢ "sum from i equals 1 to n of x i" add up a sequence (a for loop with +=) Σ₁³ i = 6 6, all
∏ᵢ xᵢ "product over i" multiply a sequence ∏(1 - i/N) 24
lim(h→0) "the limit as h goes to 0" the value approached as h shrinks slope of a tangent 12
d/dx, dy/dx "d by d x", "d y d x" derivative: rate of change of y per unit x d/dx x² = 2x 12
∂f/∂x "partial f partial x" derivative w.r.t. x, others held fixed ∂(x²y)/∂x = 2xy 13
∂²f/∂xᵢ∂xⱼ "second partial" curvature; an entry of the Hessian 13
∇f "grad f" / "nabla f" vector of all partial derivatives ∇f = (4, 13) 13, 21
∇ₓL "gradient of L with respect to x" gradient taken w.r.t. one specific variable input gradient in FGSM 28
D_u f "directional derivative along u" slope in direction u, = ∇f·u 12.8 13
J "the Jacobian" matrix of derivatives of a vector function 13
H (calculus) "the Hessian" matrix of second derivatives [[2,1],[1,2]] 13, 21
∫ₐᵇ f(x) dx "integral from a to b of f of x d x" area under f; the total accumulated ∫₀³ x² dx = 9 12
dx "d x" an infinitely thin slice of x 12
F(x) "big F" an antiderivative (F' = f), or a CDF F(x) = x³/3 12, 14
C (integration) "plus C" the constant of integration ∫2x dx = x² + C 12
e^x, exp(x) "e to the x" the exponential function e⁰ = 1 5, 12
ln x "natural log" log base e ln e = 1 5
log₂ x, log₁₀ x "log base 2 / base 10" bits; decibels and orders of magnitude log₂ 1024 = 10 5, 23, 27
sin θ, cos θ, tanh x "sine", "cosine", "tanch" trigonometric / hyperbolic functions cos 0 = 1 7, 12
σ(x) "sigmoid of x" 1/(1 + e⁻ˣ), squashes to (0, 1) σ(0) = 0.5 12
ReLU(z) "rel-u" max(0, z) ReLU(-1.4) = 0 10, 21
softmax(z) "softmax" eᶻⁱ / Σ eᶻʲ, turns scores into probabilities (0.66, 0.24, 0.10) 13, 20
sign(x) "sign of x" +1, 0 or -1 sign(-0.3) = -1 28
max, min "max", "min" largest / smallest value max(0, -2) = 0 all
argmax_θ f(θ) "arg max over theta" the θ that makes f largest (not the max value) MLE, greedy decoding 14, 22
O(f(n)) "big O of f of n" grows no faster than f(n) binary search O(log n) 18
i (complex) "i" the imaginary unit, i² = -1 e^(iπ) = -1 27
X_k, x_n "big X sub k", "little x sub n" DFT output (frequency) and input (time samples) 27
f * g "f convolved with g" slide, multiply, sum a blur filter 27
z (control) "z" the root of a characteristic equation; stable iff |z| < 1 z² - z + K = 0 29

Linear algebra

Symbol Read it as Meaning Example Ch.
x, v, w (lower-case) "vector x" an ordered list of numbers x = (1, 2) 10
A, W, M (upper-case) "matrix A" a grid of numbers / a linear transformation [[0.5,-1],[2,0.25]] 10
m × n "m by n" shape: m rows, n columns (2×3)·(3×4) = 2×4 10
A·B, A @ B "A times B" matrix product (row · column) A@B in NumPy 10
a · b (vectors) "a dot b" dot product, Σ aᵢbᵢ (3,4)·(4,3) = 24 10
⊙, * (NumPy) "element-wise product" multiply matching entries [1,2]⊙[3,4] = [3,8] 10
Aᵀ, xᵀ "A transpose" swap rows and columns [1 2]ᵀ = a column 10, 13
A⁻¹ "A inverse" undoes A: A⁻¹A = I 10
I "the identity" 1s on the diagonal, "do nothing" I·x = x 10, 11
det(A) "determinant of A" volume scaling; 0 means not invertible det([[1,2],[3,4]]) = -2 11
trace(A) "trace of A" sum of the diagonal = sum of eigenvalues trace = 4 11
rank(A) "rank of A" number of independent rows/columns low-rank LoRA update 20
‖x‖₁, ‖x‖₂, ‖x‖∞ "L1 / L2 / L-infinity norm" sum of abs values / length / largest abs value (3,4): 7, 5, 4 10, 28
‖A‖_F "Frobenius norm" √(Σ all entries²) √50 20
λ, v (eigen) "eigenvalue", "eigenvector" A·v = λ·v λ = 1, 3 11
P, D eigenvector matrix and diagonal eigenvalue matrix, A = PDP⁻¹ 11
U, Σ, V "U, sigma, V" SVD factors, A = UΣVᵀ; σᵢ = singular values σ = 6.71, 2.24 20
L = D - A (graphs) "the Laplacian" degree matrix minus adjacency matrix 11, 17
λ₂ "lambda two", Fiedler value algebraic connectivity of a graph ring of 4: λ₂ = 2 11
κ "kappa", condition number λ_max / λ_min: how ill-conditioned a problem is 21
Q, K, V, d_k "queries, keys, values, key dimension" attention inputs d_k = 64 20

Probability and statistics

Symbol Read it as Meaning Example Ch.
P(A) "probability of A" a number in [0, 1] P(heads) = 0.5 8
P(A | B) "probability of A given B" probability once B is known P(fail | checkout) = 0.25 8, 16
P(A ∩ B), P(A ∪ B) "A and B", "A or B" joint / either 8
X, Y (capitals) "random variable X" a number decided by chance latency of a request 8, 14
X ~ D "X is distributed as D" X is drawn from distribution D X ~ N(100, 20²) 14
p(x), f(x), F(x) "PMF / PDF / CDF" mass, density, cumulative probability F(250 ms) = 0.99 14
E[X] "expected value of X" the probability-weighted average E[attempts] = 1/p 8
Var(X), σ² "variance" average squared distance from the mean p(1-p) 8, 9
σ, s "sigma", "s" standard deviation (population / sample) s ≈ 22.17 9
μ, x̄ "mu", "x bar" mean (population / sample) 9
Cov(X,Y), r "covariance", "correlation" how two variables move together; r ∈ [-1, 1] r ≈ 0.77 9
z "z-score" distance from the mean in standard deviations z = 4.5 9, 22
Φ(z) "capital phi of z" the standard normal CDF Φ(1.96) ≈ 0.975 14
N(μ, σ²) "normal with mean mu, variance sigma squared" the bell curve N(0, 1) 14
Bin(n,p), Poisson(λ), Beta(α,β) named distributions Beta(14, 88) 14, 16
C(n, k) / P(n, k) "n choose k" / "permutations" number of combinations / ordered arrangements C(5,2) = 10 15
λ (probability) "lambda" an average rate of events 100 req/s 14, 25
π, πᵢ (Markov) "pi" stationary distribution: long-run share of time per state π_B = 0.032 11, 25
π (security) "pi", base rate fraction of events that are malicious 10⁻⁴ 26
H(X) "entropy of X" average surprise in bits fair coin: 1 bit 23
H∞(X) "min-entropy" -log₂(max p), the guessing-attack measure 1 bit 23
H(p, q), D_KL(p‖q) "cross-entropy", "KL divergence" cost of using q when the truth is p 22, 23
I(X; Y) "mutual information" bits about X revealed by Y 23
ℒ(θ), ℓ(θ) "likelihood", "log-likelihood" probability of the data as a function of θ (ℒ is also the Lagrangian in Ch. 21) ℓ'(p) = 0 21, 22
α, β (testing) "alpha", "beta" false-positive rate; false-negative rate (power = 1-β) α = 0.05 22
χ² "chi-squared" a test statistic for counts; equals z² for 2×2 tables 22
ε (privacy) "epsilon" differential-privacy budget ε = 0.5 26
δ "delta" a small failure probability (Hoeffding), an effect size (A/B), or a perturbation (FGSM) δ = 0.05 14, 22, 28
TP, FP, TN, FN "true/false positive/negative" confusion-matrix counts 26
TPR, FPR "true / false positive rate" recall; false-alarm rate 26

Queueing, networking and control

Symbol Read it as Meaning Example Ch.
λ, μ "lambda", "mu" arrival rate, service rate 90 and 100 req/s 25
ρ "rho" utilization λ/μ 0.9 25
L, W, W_q average number in system, time in system, time waiting L = λW 25
c, a number of servers; offered load in Erlangs a = 9 25
c_a, c_s, τ "c a", "c s", "tau" variability of arrivals / service; mean service time 25
B, S/N, C bandwidth (Hz), signal-to-noise ratio, capacity (bits/s) C = B·log₂(1 + S/N) 23, 27
f, f_s, f_max frequency, sampling rate, highest frequency present f_s > 2f_max 27
d, M, N (PageRank) damping factor, link matrix, number of pages d = 0.85 11
e_t, K, D control error at tick t, loop gain, disturbance 0 < K < 2 29
Kp, Ki, Kd PID gains (proportional, integral, derivative) 29
SRTT, RTTVAR, RTO smoothed RTT, RTT variation, retransmission timeout RTO = SRTT + 4·RTTVAR 9

The Greek alphabet, as used here

Letter Name Meanings in this guide
α alpha significance level; EWMA smoothing factor; Beta prior count; LoRA scale; Pareto tail index
β beta momentum/decay factor (β₁, β₂ in Adam); Type II error; Beta prior count; RTTVAR gain
δ Δ delta small change (Δx); failure probability; effect size; perturbation; error signal in backprop
ε epsilon tiny tolerance or error; perturbation budget; privacy budget; Adam's divide-by-zero guard
η eta learning rate
θ theta model parameters; an angle; an unknown rate
κ kappa condition number
λ lambda eigenvalue; arrival/event rate; Lagrange multiplier (price); curvature; regularization strength
μ mu mean; service rate
π pi 3.14159…; stationary distribution; base rate; prime-counting function π(N)
ρ rho utilization; correlation
σ / Σ sigma standard deviation; sigmoid; singular value / summation; SVD's diagonal matrix
τ tau mean service time
φ / Φ phi Euler's totient φ(n) / the standard normal CDF Φ(z)
χ chi χ², the chi-squared statistic
ω / Ω omega angular frequency / the sample space
∇ nabla (not a letter) the gradient operator
∂ "partial" (not a letter) partial derivative

Constants and "magic numbers"

Constant Value Where it comes from Ch.
e 2.71828… the base whose exponential is its own derivative; lim (1 + 1/n)ⁿ 5, 12
π 3.14159… circle circumference ÷ diameter; appears in the normal PDF via √π 7, 12
i √-1 imaginary unit; rotations in the Fourier transform 27
ln 2 0.693 doubling time ≈ 0.693/r (Rule of 72) 6, 12
√(2π) 2.5066 the normal distribution's normalizing constant 14
1.96 z for a two-sided 95% interval 14, 22
0.84 z for 80% power 22
68 / 95 / 99.7 % share of a normal within 1, 2, 3 σ 9
1.18 (√(2 ln 2)) birthday bound: 50% collision after 1.18·√N 24
3 (rule of three) -ln 0.05 ≈ 3.0 0 failures in n trials ⇒ rate < 3/n at 95% 22
0.25 maximum slope of the sigmoid 12
0.85 PageRank damping factor 11
1.22 (√(3/2)) constant in the Mathis TCP throughput formula 12
1/8, 1/4, 4 TCP RTO gains α, β and the "4 × RTTVAR" margin (RFC 6298) 9
0.9, 0.999, 10⁻⁸ Adam's default β₁, β₂, ε 21
65537 2¹⁶ + 1 the standard RSA public exponent 24
3329 ML-KEM's modulus q 24
-147.55 20·log₁₀(4π/c) free-space path loss constant (metres, Hz) 27
c 3 × 10⁸ m/s speed of light 27
2¹²⁸ 3.4 × 10³⁸ "128-bit security": infeasible work 24
16 RIP's "infinity" hop count 17

Units and abbreviations

Unit Meaning Conversion
bit / byte binary digit / 8 bits 1 B = 8 b
Mbit/s, Gbit/s megabits / gigabits per second (network rates use powers of 10) 1 Gbit/s = 10⁹ bit/s
ms, µs, ns milli-, micro-, nanoseconds 1 ms = 1000 µs
Hz, MHz, GHz cycles per second 2.4 GHz = 2.4 × 10⁹ Hz
dB ten times the log₁₀ of a power ratio +3 dB ≈ ×2, +10 dB = ×10
dBm power relative to 1 milliwatt 20 dBm = 100 mW
Erlang one server kept continuously busy a = λ/μ
RTT, MSS, BDP round-trip time, max segment size, bandwidth-delay product BDP = bandwidth × RTT
SNR signal-to-noise ratio (linear or dB) 30 dB = 1000
MTBF mean time between failures = 1/λ
p50, p95, p99 50th, 95th, 99th percentiles p99 = F⁻¹(0.99)

For every formula written out in full, see the Formula cheat sheet in Part 4. For every named theorem, law and inequality, see the Theorem index that follows it.

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