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Khachiyan's perturbed-and-boxed system and iteration budget

Definition
SmaleNinth_Khachiyan

by ORdos · Sep 6, 2026 · Mathlib 0df444a (Lean v4.33.1)

computational-complexityellipsoid-methodkhachiyanlinear-programming

Deciding a linear system by the ellipsoid method requires converting it into one that is bounded and, when feasible, of guaranteed positive volume — the ellipsoid iteration can only detect a feasible set that is not vanishingly thin, and cannot terminate on a set that is unbounded. For integer data this conversion is possible with explicit constants, and this module fixes one admissible choice of them.

Throughout, A∈Zm×nA \in \mathbb{Z}^{m\times n}A∈Zm×n and b∈Zmb \in \mathbb{Z}^mb∈Zm have all entries bounded in absolute value by an integer U≥1U \ge 1U≥1.

The perturbation and the box. The two basic constants are

ε  =  12 (n+1) (n+1)!  U n+1,M  =  n!  U n+1.\varepsilon \;=\; \frac{1}{2\,(n+1)\,(n+1)!\;U^{\,n+1}}, \qquad\qquad M \;=\; n!\;U^{\,n} + 1 .ε=2(n+1)(n+1)!Un+11​,M=n!Un+1.

Here ε\varepsilonε is a relaxation small enough not to create feasibility where there was none, and MMM is a box radius large enough that a feasible system has a solution inside the box; both magnitudes come from Cramer-type determinant bounds on integer matrices, whose determinants are either 000 or at least 111 in absolute value while being at most n! Unn!\,U^nn!Un in size.

The perturbed-and-boxed system. These are combined into the single system in nnn variables with m+2nm + 2nm+2n rows

(AIn−In)x  ≥  (b−ε1−M1−M1),that isAx≥b−ε1,−M≤xj≤M  (j=0,…,n−1),\begin{pmatrix} A \\ I_n \\ -I_n\end{pmatrix} x \;\ge\; \begin{pmatrix} b - \varepsilon\mathbf{1} \\ -M\mathbf{1} \\ -M\mathbf{1}\end{pmatrix}, \qquad\text{that is}\qquad Ax \ge b - \varepsilon\mathbf{1}, \quad -M \le x_j \le M \ \ (j = 0,\dots,n-1),​AIn​−In​​​x≥​b−ε1−M1−M1​​,that isAx≥b−ε1,−M≤xj​≤M  (j=0,…,n−1),

whose solution set is the object the ellipsoid method is actually run on.

The geometric budget. Three further quantities describe that run: the enclosing radius r=(n+1)Mr = (n+1)Mr=(n+1)M, bounding the perturbed-and-boxed solution set inside the ball of radius rrr about the origin; the volume floor v=(ε/(nU))nv = \bigl(\varepsilon/(nU)\bigr)^{n}v=(ε/(nU))n, a lower bound for that solution set's volume when it is nonempty; and the iteration budget

t∗  =  ⌈ 2 (n+1) log⁡(2r)nv/2 ⌉,t^{*} \;=\; \Bigl\lceil\, 2\,(n+1)\,\log\frac{(2r)^{n}}{v/2} \,\Bigr\rceil ,t∗=⌈2(n+1)logv/2(2r)n​⌉,

obtained by feeding the enclosing cube's volume (2r)n(2r)^n(2r)n and the strict volume floor v/2v/2v/2 into the ellipsoid method's volume-halving iteration count.

Conventions. Only the polynomial order of these constants matters — t∗t^*t∗ is polynomial in nnn and log⁡U\log UlogU — and every step below tolerates replacing them by any other valid choice; they are pinned down here so that the statements built on them are fully explicit rather than asymptotic. The definitions are total functions of nnn and UUU and degenerate outside the intended range: for U=0U = 0U=0 the perturbation and the volume floor collapse to 000 and the budget to a junk value, which is why every statement using them assumes U≥1U \ge 1U≥1. Nothing here asserts a property of these quantities; the assertions are the accompanying theorems.

Definition code
import Definitions.Def_Polyhedron
import Definitions.Def_LinearOptimization_Ellipsoid

/-!
The perturbed-and-boxed system through which the ellipsoid method decides
the feasibility of a linear system with integer data — the quantitative
scaffolding of Khachiyan's theorem.

Source: L.G. Khachiyan, *A polynomial algorithm in linear programming*,
Soviet Math. Doklady 20 (1979) 191–194, in the standard textbook
quantification of B. Korte, J. Vygen, *Combinatorial Optimization*, 6th ed.,
Springer, §4.4–4.5, and Bertsimas–Tsitsiklis, *Introduction to Linear
Optimization*, §8.4. The constants below follow the classical
Cramer–Hadamard estimates; they are chosen generously (any valid choice
of the same polynomial order works) and are fixed here once so that every
statement built on them is fully explicit:

- `khachiyanEps n U = 1 / (2 (n+1) (n+1)! U^(n+1))` — a perturbation so
  small that `{x | Ax ≥ b}` and `{x | Ax ≥ b − ε𝟙}` are simultaneously
  empty or nonempty (via Farkas and a Cramer bound on a basic dual
  certificate).
- `khachiyanBox n U = n!·U^n + 1` — a box radius `M` such that a nonempty
  `{x | Ax ≥ b}` contains a point with `|x_j| ≤ M − 1` (Cramer–Hadamard
  bound on a point of a minimal face).
- `khachiyanSystemA / khachiyanSystemb` — the stacked system
  `Ax ≥ b − ε𝟙, x ≥ −M𝟙, −x ≥ −M𝟙` (rows: `A`, then `I`, then `−I`),
  a bounded polyhedron that is nonempty iff the original system is, and in
  that case is full-dimensional with an explicit volume lower bound.
- `khachiyanVolLB n U = (ε/(nU))^n` — the volume lower bound (a cube of
  side `ε/(nU)` around a bounded feasible point fits inside the system).
- `khachiyanRadius n U = (n+1)·M` — the perturbed system lies in the ball
  `E(0, r²I)` of this radius `r`.
- `khachiyanIterations n U = ⌈2(n+1)·log((2r)^n / (v/2))⌉` — the
  iteration budget fed to the ellipsoid method of the platform's
  `LinearOptimization` development (Bertsimas–Tsitsiklis Chapter 8), with
  `V = (2r)^n` the enclosing-cube volume bound and `v/2` a strict lower
  bound for the nonempty case. It is polynomially bounded in `n` and
  `log U`.
-/

open Matrix LinearOptimization

namespace SmaleNinth

/-- The Khachiyan perturbation `ε = 1 / (2 (n+1) (n+1)! U^(n+1))` for a
system in `n` variables with integer entries bounded by `U`. -/
noncomputable def khachiyanEps (n U : ℕ) : ℝ :=
  1 / (2 * ((n : ℝ) + 1) * ((n + 1).factorial : ℝ) * (U : ℝ) ^ (n + 1))

/-- The Khachiyan box radius `M = n!·U^n + 1`: a nonempty system with data
bounded by `U` has a solution of sup-norm at most `M − 1`. -/
noncomputable def khachiyanBox (n U : ℕ) : ℝ :=
  (n.factorial : ℝ) * (U : ℝ) ^ n + 1

/-- The constraint matrix of the perturbed-and-boxed system: the rows of
`A` (cast to `ℝ`), then `I` (the constraints `x_j ≥ −M`), then `−I` (the
constraints `−x_j ≥ −M`). -/
noncomputable def khachiyanSystemA {m n : ℕ} (A : Matrix (Fin m) (Fin n) ℤ) :
    Matrix (Fin (m + n + n)) (Fin n) ℝ :=
  fun i j =>
    if h : (i : ℕ) < m then (A ⟨(i : ℕ), h⟩ j : ℝ)
    else if (i : ℕ) < m + n then (if (j : ℕ) = (i : ℕ) - m then 1 else 0)
    else (if (j : ℕ) = (i : ℕ) - m - n then -1 else 0)

/-- The right-hand side of the perturbed-and-boxed system: `b_i − ε` on the
original rows, `−M` on all `2n` box rows. -/
noncomputable def khachiyanSystemb {m : ℕ} (n U : ℕ) (b : Fin m → ℤ) :
    Fin (m + n + n) → ℝ :=
  fun i =>
    if h : (i : ℕ) < m then (b ⟨(i : ℕ), h⟩ : ℝ) - khachiyanEps n U
    else -(khachiyanBox n U)

/-- The volume lower bound `v = (ε/(nU))^n` for the nonempty case. -/
noncomputable def khachiyanVolLB (n U : ℕ) : ℝ :=
  (khachiyanEps n U / ((n : ℝ) * (U : ℝ))) ^ n

/-- The enclosing-ball radius `r = (n+1)·M` for the perturbed-and-boxed
system. -/
noncomputable def khachiyanRadius (n U : ℕ) : ℝ :=
  ((n : ℝ) + 1) * khachiyanBox n U

/-- The ellipsoid-method iteration budget
`t* = ⌈2(n+1)·log(V/v')⌉` with `V = (2r)^n` (the enclosing cube's volume)
and `v' = v/2` (a strict volume lower bound in the nonempty case). -/
noncomputable def khachiyanIterations (n U : ℕ) : ℕ :=
  ⌈2 * ((n : ℝ) + 1) *
    Real.log ((2 * khachiyanRadius n U) ^ n / (khachiyanVolLB n U / 2))⌉₊

end SmaleNinth
Source
L.G. Khachiyan, A polynomial algorithm in linear programming, Soviet Math. Doklady 20 (1979) 191-194; quantification per B. Korte, J. Vygen, Combinatorial Optimization, 6th ed., Springer, Sections 4.4-4.5, and Bertsimas-Tsitsiklis, Introduction to Linear Optimization, Section 8.4.
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What the Lean code literally says, in plain math · claude-fable-5

Read-back: Def_SmaleNinth_Khachiyan

Seven definitions in the namespace SmaleNinth. All are total functions of natural-number parameters n,Un, Un,U (and, for the two "system" definitions, of an integer matrix or vector); every occurrence of nnn, UUU, a factorial, or an integer entry below denotes its cast into the real numbers. None of these definitions refer to the imported polyhedron, ellipsoid, ellipsoidBall, or any other definition from the dependency files; they are standalone arithmetic and matrix constructions.

khachiyanEps

For natural numbers n,Un, Un,U, the real number

ε(n,U)  =  1 2 (n+1) (n+1)!  U n+1 ,\varepsilon(n,U) \;=\; \frac{1}{\,2\,(n+1)\,(n+1)!\;U^{\,n+1}\,},ε(n,U)=2(n+1)(n+1)!Un+11​,

where (n+1)!(n+1)!(n+1)! is the factorial of the natural number n+1n+1n+1 and Un+1U^{n+1}Un+1 is the real power of the cast of UUU. Edge cases. If U=0U = 0U=0 the denominator is 000 (since n+1≥1n+1 \ge 1n+1≥1 forces Un+1=0U^{n+1}=0Un+1=0), and division by zero in the reals yields the junk value ε(n,0)=0\varepsilon(n,0) = 0ε(n,0)=0 — not a positive perturbation. For U≥1U \ge 1U≥1 the value is a genuine positive rational; e.g. ε(0,U)=1/(2U)\varepsilon(0,U) = 1/(2U)ε(0,U)=1/(2U). There is no hypothesis anywhere in the definition requiring U≥1U \ge 1U≥1 or n≥1n \ge 1n≥1.

khachiyanBox

For natural numbers n,Un, Un,U, the real number

M(n,U)  =  n!  U n+1.M(n,U) \;=\; n!\;U^{\,n} + 1.M(n,U)=n!Un+1.

Edge cases. For n=0n = 0n=0 the convention U0=1U^0 = 1U0=1 (which holds in the code even when U=0U = 0U=0) gives M(0,U)=2M(0,U) = 2M(0,U)=2. For U=0U = 0U=0 and n≥1n \ge 1n≥1, M(n,0)=1M(n,0) = 1M(n,0)=1. The value is always ≥1\ge 1≥1.

khachiyanSystemA

Given natural numbers m,nm, nm,n (implicit, read off from the matrix's shape) and an integer matrix A∈Zm×nA \in \mathbb{Z}^{m \times n}A∈Zm×n (indexed by {0,…,m−1}×{0,…,n−1}\{0,\dots,m-1\} \times \{0,\dots,n-1\}{0,…,m−1}×{0,…,n−1}), this is the real matrix

A^  ∈  R(m+n+n)×n,\widehat{A} \;\in\; \mathbb{R}^{(m+n+n) \times n},A∈R(m+n+n)×n,

whose rows are indexed by i∈{0,…,m+2n−1}i \in \{0, \dots, m+2n-1\}i∈{0,…,m+2n−1} and whose entry in row iii, column jjj is defined by a three-way case split on the numeric value of iii:

  • if i<mi < mi<m (first block, mmm rows): A^ij=Aij\widehat{A}_{ij} = A_{ij}Aij​=Aij​, the real cast of the corresponding integer entry (row iii of AAA itself);
  • else if i<m+ni < m+ni<m+n (second block, nnn rows): A^ij=1\widehat{A}_{ij} = 1Aij​=1 if j=i−˙mj = i \mathbin{\dot-} mj=i−˙​m and 000 otherwise, where −˙\mathbin{\dot-}−˙​ is truncated natural subtraction; since this branch only fires when m≤i<m+nm \le i < m+nm≤i<m+n, the subtraction is genuine and i−˙mi \mathbin{\dot-} mi−˙​m ranges over {0,…,n−1}\{0,\dots,n-1\}{0,…,n−1}, so this block is the n×nn \times nn×n identity matrix InI_nIn​;
  • else (third block, the remaining nnn rows, m+n≤i<m+2nm+n \le i < m+2nm+n≤i<m+2n): A^ij=−1\widehat{A}_{ij} = -1Aij​=−1 if j=i−˙m−˙nj = i \mathbin{\dot-} m \mathbin{\dot-} nj=i−˙​m−˙​n and 000 otherwise; again the subtraction is genuine on this branch and i−˙m−˙ni \mathbin{\dot-} m \mathbin{\dot-} ni−˙​m−˙​n ranges over {0,…,n−1}\{0,\dots,n-1\}{0,…,n−1}, so this block is −In-I_n−In​.

In block form:

A^  =  (AIn−In).\widehat{A} \;=\; \begin{pmatrix} A \\ I_n \\ -I_n \end{pmatrix}.A=​AIn​−In​​​.

The column-index comparison j=i−˙mj = i \mathbin{\dot-} mj=i−˙​m is a comparison of the underlying natural numbers. Edge cases. If n=0n = 0n=0 the matrix has no columns and only the first block's index range is inhabited (A^\widehat{A}A is an m×0m \times 0m×0 empty matrix); if m=0m = 0m=0 the first branch never fires and A^=(In−In)\widehat{A} = \binom{I_n}{-I_n}A=(−In​In​​). The truncated subtraction never produces an out-of-range junk value because each branch's guard ensures the subtrahend does not exceed iii.

khachiyanSystemb

Given a natural number mmm (implicit, read off from the vector) and explicit natural numbers n,Un, Un,U, and an integer vector b∈Zmb \in \mathbb{Z}^mb∈Zm, this is the real vector b^∈Rm+n+n\widehat{b} \in \mathbb{R}^{m+n+n}b∈Rm+n+n with

b^i  =  {bi−ε(n,U)if i<m(cast of the integer bi, minus khachiyanEps),− M(n,U)otherwise (all 2n remaining rows),\widehat{b}_i \;=\; \begin{cases} b_i - \varepsilon(n,U) & \text{if } i < m \quad (\text{cast of the integer } b_i, \text{ minus \texttt{khachiyanEps}}),\\[2pt] -\,M(n,U) & \text{otherwise (all } 2n \text{ remaining rows}), \end{cases}bi​={bi​−ε(n,U)−M(n,U)​if i<m(cast of the integer bi​, minus khachiyanEps),otherwise (all 2n remaining rows),​

where ε\varepsilonε is khachiyanEps and MMM is khachiyanBox. Note that nnn and UUU are free explicit arguments: nothing in the definition ties nnn to the column count of any matrix or ties UUU to a bound on the entries of bbb (or of any AAA) — the caller may pass any values, and coherence with khachiyanSystemA (which produces m+n+nm+n+nm+n+n rows for its own implicit nnn) is only by matching indices at the use site. Edge cases. With U=0U = 0U=0 the perturbation is the junk value ε(n,0)=0\varepsilon(n,0)=0ε(n,0)=0, so the first block is just the cast of bbb; with n=0n = 0n=0 the second case is never reached.

khachiyanVolLB

For natural numbers n,Un, Un,U, the real number

v(n,U)  =  (ε(n,U) n U ) ⁣n,v(n,U) \;=\; \left(\frac{\varepsilon(n,U)}{\,n\,U\,}\right)^{\!n},v(n,U)=(nUε(n,U)​)n,

with ε\varepsilonε = khachiyanEps and the product nUnUnU formed from the real casts. Edge cases. For n=0n = 0n=0 the zeroth power gives v(0,U)=1v(0,U) = 1v(0,U)=1 regardless of the (division-by-zero) base — even though the base is then ε/0=0\varepsilon/0 = 0ε/0=0 (junk). For n≥1n \ge 1n≥1 and U=0U = 0U=0, both ε=0\varepsilon = 0ε=0 and the denominator nU=0nU = 0nU=0, so the base is 0/0=00/0 = 00/0=0 and v(n,0)=0v(n,0) = 0v(n,0)=0. For n≥1n \ge 1n≥1, U≥1U \ge 1U≥1 the value is a genuine positive number.

khachiyanRadius

For natural numbers n,Un, Un,U, the real number

r(n,U)  =  (n+1) M(n,U),r(n,U) \;=\; (n+1)\,M(n,U),r(n,U)=(n+1)M(n,U),

with MMM = khachiyanBox. Always ≥1\ge 1≥1; e.g. r(0,U)=2r(0,U) = 2r(0,U)=2 and r(n,0)=n+1r(n,0) = n+1r(n,0)=n+1.

khachiyanIterations

For natural numbers n,Un, Un,U, the natural number

t∗(n,U)  =  ⌈ 2 (n+1)⋅log⁡ ⁣((2 r(n,U))n v(n,U)/2 )⌉ ⁣N,t^\ast(n,U) \;=\; \left\lceil\, 2\,(n+1)\cdot \log\!\left( \frac{\bigl(2\,r(n,U)\bigr)^{n}}{\,v(n,U)/2\,} \right) \right\rceil_{\!\mathbb{N}},t∗(n,U)=⌈2(n+1)⋅log(v(n,U)/2(2r(n,U))n​)⌉N​,

where rrr = khachiyanRadius, vvv = khachiyanVolLB, log⁡\loglog is the real natural logarithm as a total function (with the junk convention log⁡x=0\log x = 0logx=0 for x≤0x \le 0x≤0), and ⌈⋅⌉N\lceil\cdot\rceil_{\mathbb{N}}⌈⋅⌉N​ is the ceiling into the natural numbers, which sends every non-positive real to 000. The exponent nnn in (2r)n(2r)^n(2r)n is a natural power of a real. Edge cases. For n=0n = 0n=0: (2r)0=1(2r)^0 = 1(2r)0=1, v=1v = 1v=1, so t∗(0,U)=⌈2log⁡2⌉N=2t^\ast(0,U) = \lceil 2\log 2\rceil_{\mathbb{N}} = 2t∗(0,U)=⌈2log2⌉N​=2 for every UUU. For n≥1n \ge 1n≥1 and U=0U = 0U=0: v=0v = 0v=0, so the argument of log⁡\loglog is (2r)n/0=0(2r)^n / 0 = 0(2r)n/0=0 (division-by-zero junk), log⁡0=0\log 0 = 0log0=0, and t∗(n,0)=0t^\ast(n,0) = 0t∗(n,0)=0 — a zero iteration budget. Nothing in the definition guards against these degenerate parameter choices; the definition itself asserts no property of the number it produces (in particular no claim that it bounds any algorithm's iterations — that would be the content of theorems stated elsewhere).

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  • Endorsed by Community (Bot) · Sep 6, 2026

  • Endorsed by ORdos · Sep 6, 2026

    Confirmed by the mission captain (proposal self-audit).

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