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Blum–Shub–Smale machines over R\mathbb{R}R

Definition
SmaleNinth_BSSMachine

by ORdos · Sep 6, 2026 · Mathlib c5ea003 (Lean v4.30.0)

bss-machinecomputational-complexitylinear-programmingreal-computation

A machine over the real numbers, in the sense of Blum, Shub and Smale, is the model of computation in which exact real arithmetic is available at unit cost. This module fixes one concrete such model.

Configurations. The memory is a tape, a bi-infinite family of real registers indexed by the integers, written x=(xk)k∈Zx = (x_k)_{k \in \mathbb{Z}}x=(xk​)k∈Z​ with xk∈Rx_k \in \mathbb{R}xk​∈R. A configuration is a pair consisting of a program counter p∈Np \in \mathbb{N}p∈N and a tape.

Programs. A program is a finite list of instructions, each of one of the following kinds, where the addresses d,i,j∈Zd, i, j \in \mathbb{Z}d,i,j∈Z are fixed inside the instruction:

  • xd:=cx_d := cxd​:=c, loading a machine constant c∈Rc \in \mathbb{R}c∈R, which may be an arbitrary real number;
  • xd:=xi∗xjx_d := x_i \ast x_jxd​:=xi​∗xj​ for ∗∈{+,−,×,÷}\ast \in \{+, -, \times, \div\}∗∈{+,−,×,÷}, an exact field operation on two registers;
  • a left shift replacing the tape xxx by k↦xk+1k \mapsto x_{k+1}k↦xk+1​, and a right shift replacing it by k↦xk−1k \mapsto x_{k-1}k↦xk−1​;
  • a sign-test branch: if xi≤0x_i \le 0xi​≤0 set the counter to a fixed target, otherwise advance it by one;
  • the two halting instructions accept\mathsf{accept}accept and reject\mathsf{reject}reject.

Every non-branching, non-halting instruction advances the counter by one. The shifts are what give a finite list of instructions, whose addresses are hard-coded, access to unboundedly many registers.

Execution and cost. One step executes the instruction at the current counter; a configuration whose counter carries accept\mathsf{accept}accept, carries reject\mathsf{reject}reject, or points past the end of the program is a fixed point, so execution simply stalls there. Running a program on an initial tape means iterating this step from counter 000. A program decides in time TTT with verdict β∈{true,false}\beta \in \{\text{true}, \text{false}\}β∈{true,false} if for some t≤Tt \le Tt≤T the configuration after exactly ttt steps has its counter on accept\mathsf{accept}accept (when β\betaβ is true) or on reject\mathsf{reject}reject (when β\betaβ is false). Cost is the number of executed instructions: one unit per arithmetic operation, constant load, shift, or comparison, irrespective of the magnitude of the reals involved. This is the point of the model — no bit lengths enter the accounting.

Input convention for linear systems. An instance of linear feasibility, given by A∈Rm×nA \in \mathbb{R}^{m \times n}A∈Rm×n and b∈Rmb \in \mathbb{R}^mb∈Rm, is presented on the tape as: cell 000 holds mmm, cell 111 holds nnn, cells 2,…,mn+12, \dots, mn + 12,…,mn+1 hold the entries of AAA in row-major order, cells mn+2,…,mn+m+1mn+2, \dots, mn+m+1mn+2,…,mn+m+1 hold bbb, and every remaining cell — including every negative one — holds 000. The instance therefore occupies mn+m+2mn + m + 2mn+m+2 cells, the quantity in which running times are measured.

Conventions and their cost. Division is totalized as x/0=0x/0 = 0x/0=0 and the branch test is the non-strict xi≤0x_i \le 0xi​≤0; both are harmless, since a program may guard divisions by sign tests at no asymptotic cost. Halting requires the counter to rest on an actual halting instruction: running off the end of the program is not a verdict. Crucially, a program is a single finite list with no dependence on mmm or nnn, so any statement quantifying over programs quantifies over uniform algorithms; non-uniform families of decision trees, one per input size, are not expressible here, and it is exactly this restriction that makes polynomial-time questions in this model nontrivial.

Definition code
import Mathlib.Data.Real.Basic
import Mathlib.Data.Matrix.Mul
import Mathlib.Logic.Function.Iterate

/-!
A register machine over the real numbers (Blum–Shub–Smale style), with
unit-cost exact real arithmetic — the model in which Smale poses his 9th
problem.

Source: S. Smale, *Mathematical problems for the next century*, Mathematical
Intelligencer 20(2):7–15, 1998, Problem 9: "Is there a polynomial-time
algorithm over the real numbers which decides the feasibility of the linear
system of inequalities $Ax \ge b$?" — where "algorithm over the real
numbers" is the machine model of L. Blum, M. Shub, S. Smale, *On a theory of
computation and complexity over the real numbers*, Bull. AMS 21(1):1–46,
1989.

The model formalized here:

- The machine state is a program counter together with a **bi-infinite tape**
  `ℤ → ℝ` of real registers (the state space `ℝ_∞` of BSS §1; a bi-infinite
  tape with two-sided shifts is the standard presentation giving full
  Turing-style access to unboundedly many registers).
- A program is a finite list of instructions. Arithmetic instructions
  (`const`, `add`, `sub`, `mul`, `div`) act on tape cells at **fixed**
  addresses hard-coded in the instruction — together with the two shift
  instructions this yields exactly the BSS computation nodes (rational maps
  with built-in real machine constants, applied in a finite window that the
  shifts move along the tape). `jle i target` is the BSS branch node
  (branch on the sign test `x_i ≤ 0`); `accept` / `reject` are output nodes.
- Division is Lean-total (`x / 0 = 0`), a benign totalization: a genuine BSS
  machine can guard every division by a sign test at no asymptotic cost.
- **Cost = number of executed instructions** (unit cost per arithmetic
  operation, comparison, or shift — the algebraic/arithmetic complexity
  measure). The input is `k` real numbers laid out in tape cells `0, …, k−1`;
  "polynomial time" means a step count polynomial in `k`.

`encodeLP` fixes the input convention for the LP feasibility problem: for an
`m × n` system `Ax ≥ b`, the tape holds `m` and `n` (as reals) in cells
`0, 1`, the entries of `A` row-major in cells `2, …, mn+1`, and `b` in cells
`mn+2, …, mn+m+1`; all other cells are `0`.
-/

namespace SmaleNinth

/-- An instruction of a BSS register machine over `ℝ`: real-constant loads,
field arithmetic on fixed tape addresses, two-sided tape shifts, a sign-test
branch, and the two output instructions. -/
inductive BSSInstr : Type
  /-- `x[dst] := c` — load a machine constant (an arbitrary real, per BSS). -/
  | const (dst : ℤ) (c : ℝ)
  /-- `x[dst] := x[i] + x[j]`. -/
  | add (dst i j : ℤ)
  /-- `x[dst] := x[i] − x[j]`. -/
  | sub (dst i j : ℤ)
  /-- `x[dst] := x[i] * x[j]`. -/
  | mul (dst i j : ℤ)
  /-- `x[dst] := x[i] / x[j]` (Lean-total: division by zero yields `0`). -/
  | div (dst i j : ℤ)
  /-- Shift the whole tape one cell to the left: new `x[k] = ` old `x[k+1]`. -/
  | shiftL
  /-- Shift the whole tape one cell to the right: new `x[k] = ` old `x[k−1]`. -/
  | shiftR
  /-- If `x[i] ≤ 0` jump to instruction `target`, else fall through. -/
  | jle (i : ℤ) (target : ℕ)
  /-- Halt and accept. -/
  | accept
  /-- Halt and reject. -/
  | reject

/-- A BSS program: a finite list of instructions, executed from position `0`. -/
abbrev BSSProgram := List BSSInstr

/-- A machine configuration: program counter and the real-register tape. -/
structure BSSConfig where
  /-- The program counter (an index into the program list). -/
  pc : ℕ
  /-- The bi-infinite tape of real registers. -/
  tape : ℤ → ℝ

/-- One execution step. A configuration whose `pc` carries `accept`/`reject`
(or points outside the program) is halted: the step leaves it unchanged. -/
noncomputable def BSSStep (P : BSSProgram) (s : BSSConfig) : BSSConfig :=
  match P[s.pc]? with
  | none => s
  | some ins =>
    match ins with
    | .const dst c => ⟨s.pc + 1, Function.update s.tape dst c⟩
    | .add dst i j => ⟨s.pc + 1, Function.update s.tape dst (s.tape i + s.tape j)⟩
    | .sub dst i j => ⟨s.pc + 1, Function.update s.tape dst (s.tape i - s.tape j)⟩
    | .mul dst i j => ⟨s.pc + 1, Function.update s.tape dst (s.tape i * s.tape j)⟩
    | .div dst i j => ⟨s.pc + 1, Function.update s.tape dst (s.tape i / s.tape j)⟩
    | .shiftL => ⟨s.pc + 1, fun k => s.tape (k + 1)⟩
    | .shiftR => ⟨s.pc + 1, fun k => s.tape (k - 1)⟩
    | .jle i target => if s.tape i ≤ 0 then ⟨target, s.tape⟩ else ⟨s.pc + 1, s.tape⟩
    | .accept => s
    | .reject => s

/-- The configuration reached after `t` steps of `P` from initial tape `x`
(program counter starting at `0`). -/
noncomputable def BSSRun (P : BSSProgram) (x : ℤ → ℝ) (t : ℕ) : BSSConfig :=
  (BSSStep P)^[t] ⟨0, x⟩

/-- The configuration `s` is halted with boolean output `b` — its program
counter carries `accept` (for `b = true`) or `reject` (for `b = false`).
Halted configurations are fixed points of `BSSStep`. -/
def BSSHaltedWith (P : BSSProgram) (s : BSSConfig) (b : Bool) : Prop :=
  P[s.pc]? = some (if b then BSSInstr.accept else BSSInstr.reject)

/-- `P`, run on initial tape `x`, halts with output `b` within `T` steps.
`T` is the unit-cost (arithmetic) running time bound. -/
def BSSDecidesInTime (P : BSSProgram) (x : ℤ → ℝ) (T : ℕ) (b : Bool) : Prop :=
  ∃ t ≤ T, BSSHaltedWith P (BSSRun P x t) b

/-- The `k`th entry of the row-major listing of a matrix (junk value `0` out
of range): `matrixEntryRM A (i*n + j) = A i j`. -/
noncomputable def matrixEntryRM {m n : ℕ} (A : Matrix (Fin m) (Fin n) ℝ)
    (k : ℕ) : ℝ :=
  if h : k < m * n ∧ 0 < n then
    A ⟨k / n, by
        have h1 := h.1
        rw [Nat.mul_comm] at h1
        exact Nat.div_lt_of_lt_mul h1⟩
      ⟨k % n, Nat.mod_lt _ h.2⟩
  else 0

/-- The input tape encoding the LP feasibility instance `∃x, Ax ≥ b`:
cell `0` holds `m`, cell `1` holds `n`, cells `2, …, mn+1` hold `A`
row-major, cells `mn+2, …, mn+m+1` hold `b`, and every other cell is `0`.
The input occupies `mn + m + 2` cells. -/
noncomputable def encodeLP {m n : ℕ} (A : Matrix (Fin m) (Fin n) ℝ)
    (b : Fin m → ℝ) : ℤ → ℝ :=
  fun k =>
    if k = 0 then (m : ℝ)
    else if k = 1 then (n : ℝ)
    else if 2 ≤ k ∧ k < 2 + (m : ℤ) * n then matrixEntryRM A (k - 2).toNat
    else if h : 2 + (m : ℤ) * n ≤ k ∧ k < 2 + (m : ℤ) * n + m then
      b ⟨(k - (2 + (m : ℤ) * n)).toNat, by omega⟩
    else 0

end SmaleNinth
Source
L. Blum, M. Shub, S. Smale, On a theory of computation and complexity over the real numbers, Bull. AMS 21(1):1-46, 1989, Section 1 (machines over R, state space R_infinity, computation/branch/shift nodes); S. Smale, Mathematical problems for the next century, Mathematical Intelligencer 20(2):7-15, 1998, Problem 9.
Read-back

What the Lean code literally says, in plain math · claude-fable-5

Read-back: Def_SmaleNinth_BSSMachine.lean (namespace SmaleNinth)

BSSInstr. An inductive type with exactly ten constructors, each carrying the listed data:

  • const(dst,c)\mathsf{const}(dst, c)const(dst,c) with dst∈Zdst \in \mathbb{Z}dst∈Z and c∈Rc \in \mathbb{R}c∈R;
  • add(dst,i,j)\mathsf{add}(dst, i, j)add(dst,i,j), sub(dst,i,j)\mathsf{sub}(dst, i, j)sub(dst,i,j), mul(dst,i,j)\mathsf{mul}(dst, i, j)mul(dst,i,j), div(dst,i,j)\mathsf{div}(dst, i, j)div(dst,i,j), each with dst,i,j∈Zdst, i, j \in \mathbb{Z}dst,i,j∈Z;
  • shiftL\mathsf{shiftL}shiftL and shiftR\mathsf{shiftR}shiftR, carrying no data;
  • jle(i,target)\mathsf{jle}(i, target)jle(i,target) with i∈Zi \in \mathbb{Z}i∈Z and target∈Ntarget \in \mathbb{N}target∈N;
  • accept\mathsf{accept}accept and reject\mathsf{reject}reject, carrying no data.

At the level of the type itself these are pure data; the constructors acquire operational meaning only through BSSStep below. Note that the constant ccc in const\mathsf{const}const may be any real number, with no restriction (e.g. to rationals or computable reals), and the addresses dst,i,jdst, i, jdst,i,j may be any integers, including negative ones. The jump target of jle\mathsf{jle}jle is a natural number and is not required to lie within any program.

BSSProgram. Definitionally, a finite list of BSSInstr values (possibly empty). Instructions are indexed by their position in the list, starting at 000.

BSSConfig. A structure with two fields: a program counter pc∈Npc \in \mathbb{N}pc∈N, and a tape tape:Z→Rtape : \mathbb{Z} \to \mathbb{R}tape:Z→R, i.e. an assignment of one real number to every integer address (a bi-infinite tape of real registers). There is no constraint relating pcpcpc to any program, and the tape is an arbitrary function with no finiteness or support condition.

BSSStep. A (noncomputable) total function taking a program PPP and a configuration s=(pc,x)s = (pc, x)s=(pc,x), where x:Z→Rx : \mathbb{Z} \to \mathbb{R}x:Z→R is the tape, and returning a new configuration, by case analysis on the optional lookup of the pcpcpc-th element of the list PPP:

  • If pc≥∣P∣pc \ge |P|pc≥∣P∣ (the lookup returns nothing), the result is sss itself, unchanged.
  • If the instruction at position pcpcpc is:
    • const(dst,c)\mathsf{const}(dst, c)const(dst,c): the new configuration is (pc+1,  x[dst↦c])(pc+1,\; x[dst \mapsto c])(pc+1,x[dst↦c]), where x[dst↦v]x[dst \mapsto v]x[dst↦v] denotes the function equal to xxx everywhere except at address dstdstdst, where it takes the value vvv;
    • add(dst,i,j)\mathsf{add}(dst,i,j)add(dst,i,j): (pc+1,  x[dst↦xi+xj])(pc+1,\; x[dst \mapsto x_i + x_j])(pc+1,x[dst↦xi​+xj​]); similarly sub\mathsf{sub}sub gives x[dst↦xi−xj]x[dst \mapsto x_i - x_j]x[dst↦xi​−xj​], mul\mathsf{mul}mul gives x[dst↦xi⋅xj]x[dst \mapsto x_i \cdot x_j]x[dst↦xi​⋅xj​], and div\mathsf{div}div gives x[dst↦xi/xj]x[dst \mapsto x_i / x_j]x[dst↦xi​/xj​]. In all four cases the operands xi,xjx_i, x_jxi​,xj​ are read from the old tape (so even when dst=idst = idst=i or dst=jdst = jdst=j the old values are used), and the division is Lean's total real division, under which r/0=0r / 0 = 0r/0=0 for every real rrr;
    • shiftL\mathsf{shiftL}shiftL: (pc+1,  k↦xk+1)(pc+1,\; k \mapsto x_{k+1})(pc+1,k↦xk+1​) — every cell takes the old value of its right neighbour;
    • shiftR\mathsf{shiftR}shiftR: (pc+1,  k↦xk−1)(pc+1,\; k \mapsto x_{k-1})(pc+1,k↦xk−1​) — every cell takes the old value of its left neighbour;
    • jle(i,target)\mathsf{jle}(i, target)jle(i,target): if xi≤0x_i \le 0xi​≤0 then (target,  x)(target,\; x)(target,x), otherwise (pc+1,  x)(pc+1,\; x)(pc+1,x); the tape is unchanged in both branches;
    • accept\mathsf{accept}accept or reject\mathsf{reject}reject: the result is sss itself, unchanged.

Thus a configuration whose counter sits on accept\mathsf{accept}accept, on reject\mathsf{reject}reject, or beyond the end of the program is a fixed point of the step function. A jle\mathsf{jle}jle may jump to a position outside the program, after which the configuration is likewise fixed.

BSSRun. For a program PPP, an initial tape x:Z→Rx : \mathbb{Z} \to \mathbb{R}x:Z→R, and t∈Nt \in \mathbb{N}t∈N, BSSRun(P,x,t)\mathrm{BSSRun}(P, x, t)BSSRun(P,x,t) is the ttt-fold iterate of BSSStep(P,⋅)\mathrm{BSSStep}(P, \cdot)BSSStep(P,⋅) applied to the configuration (0,x)(0, x)(0,x) — i.e. the configuration after exactly ttt steps, starting with program counter 000 and tape xxx. For t=0t = 0t=0 it is (0,x)(0, x)(0,x) itself.

BSSHaltedWith. For a program PPP, a configuration sss, and a Boolean bbb, the proposition asserting that the lookup of the instruction at position s.pcs.pcs.pc in PPP yields exactly accept\mathsf{accept}accept when b=trueb = \mathrm{true}b=true, and exactly reject\mathsf{reject}reject when b=falseb = \mathrm{false}b=false. In particular a configuration whose counter points outside the program does not satisfy this for either value of bbb, even though it is a fixed point of the step function; and a configuration on any other instruction satisfies it for neither value of bbb.

BSSDecidesInTime. For a program PPP, an initial tape xxx, a time bound T∈NT \in \mathbb{N}T∈N, and a Boolean bbb, the proposition

∃ t≤T,BSSHaltedWith(P,  BSSRun(P,x,t),  b),\exists\, t \le T,\quad \mathrm{BSSHaltedWith}\big(P,\; \mathrm{BSSRun}(P, x, t),\; b\big),∃t≤T,BSSHaltedWith(P,BSSRun(P,x,t),b),

i.e. there exists some number of steps ttt with 0≤t≤T0 \le t \le T0≤t≤T (the bound is non-strict, and t=0t = 0t=0 is allowed) such that the configuration reached from (0,x)(0, x)(0,x) after exactly ttt steps has its program counter on accept\mathsf{accept}accept (if b=trueb = \mathrm{true}b=true) or on reject\mathsf{reject}reject (if b=falseb = \mathrm{false}b=false). Nothing in this definition asserts uniqueness of ttt or of bbb, and nothing counts instructions in any other way: "time" here is precisely the number of iterations of the step function, each iteration costing one unit regardless of the instruction executed.

matrixEntryRM. For natural numbers m,nm, nm,n (implicit), a real matrix A∈Rm×nA \in \mathbb{R}^{m \times n}A∈Rm×n (indexed by {0,…,m−1}×{0,…,n−1}\{0,\dots,m-1\} \times \{0,\dots,n-1\}{0,…,m−1}×{0,…,n−1}), and k∈Nk \in \mathbb{N}k∈N, this returns

matrixEntryRM(A,k)  =  {A⌊k/n⌋,  k mod nif k<mn and 0<n,0otherwise,\mathrm{matrixEntryRM}(A, k) \;=\; \begin{cases} A_{\lfloor k/n \rfloor,\; k \bmod n} & \text{if } k < m n \text{ and } 0 < n,\\[2pt] 0 & \text{otherwise,}\end{cases}matrixEntryRM(A,k)={A⌊k/n⌋,kmodn​0​if k<mn and 0<n,otherwise,​

where ⌊k/n⌋\lfloor k/n \rfloor⌊k/n⌋ and k mod nk \bmod nkmodn are natural-number division and remainder (the stated side conditions guarantee both indices are in range). So it is the kkk-th entry of the row-major enumeration of AAA, with junk value 000 whenever k≥mnk \ge mnk≥mn or n=0n = 0n=0 (in particular it is identically 000 when m=0m = 0m=0 or n=0n = 0n=0).

encodeLP. For natural numbers m,nm, nm,n (implicit), a matrix A∈Rm×nA \in \mathbb{R}^{m \times n}A∈Rm×n, and a vector b∈Rmb \in \mathbb{R}^mb∈Rm (a function on {0,…,m−1}\{0,\dots,m-1\}{0,…,m−1}), this is the tape Z→R\mathbb{Z} \to \mathbb{R}Z→R defined by cases on the address k∈Zk \in \mathbb{Z}k∈Z, tested in the following order:

  1. if k=0k = 0k=0: the value is the real number mmm (the natural number mmm cast to R\mathbb{R}R);
  2. else if k=1k = 1k=1: the value is the real number nnn;
  3. else if 2≤k2 \le k2≤k and k<2+mnk < 2 + mnk<2+mn (with m,nm, nm,n cast to Z\mathbb{Z}Z): the value is matrixEntryRM(A,(k−2)≥0)\mathrm{matrixEntryRM}(A, (k-2)_{\ge 0})matrixEntryRM(A,(k−2)≥0​), where (⋅)≥0(\cdot)_{\ge 0}(⋅)≥0​ is the truncation of an integer to a natural number (here k−2≥0k - 2 \ge 0k−2≥0, so no truncation occurs); by the previous paragraph this equals the row-major entry A⌊(k−2)/n⌋, (k−2) mod nA_{\lfloor (k-2)/n \rfloor,\, (k-2) \bmod n}A⌊(k−2)/n⌋,(k−2)modn​;
  4. else if 2+mn≤k2 + mn \le k2+mn≤k and k<2+mn+mk < 2 + mn + mk<2+mn+m: the value is b(k−(2+mn))≥0b_{(k - (2+mn))_{\ge 0}}b(k−(2+mn))≥0​​, the index lying in {0,…,m−1}\{0, \dots, m-1\}{0,…,m−1} by the range condition;
  5. otherwise (in particular for every negative kkk and every k≥2+mn+mk \ge 2 + mn + mk≥2+mn+m): the value is 000.

Edge cases the definition silently includes: when mn=0mn = 0mn=0 case 3 is an empty range, and when m=0m = 0m=0 case 4 is empty, so for m=0m = 0m=0 or n=0n = 0n=0 the tape holds only the two header cells (which then contain 000 where the dimension is zero) and is 000 elsewhere. There is no marker distinguishing genuine zero entries of AAA or bbb from the ambient zero padding beyond the dimensions stored in cells 000 and 111.

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