Source-linked AI summary
Generic Characteristic-Zero Equivalence Between Derivative B\'ezout Inversion and Multipoint Evaluation
Zijian Zeng
TL;DR
Computing the normalized Bézout pair from distinct nodes has a classical product-tree bound of O(M_K(m) log m), leaving a logarithmic gap when multiplication is quasi-linear. The paper reconstructs the root polynomial from the pair in generic characteristic zero and proves a complexity equivalence with arbitrary-node evaluation and interpolation; the all-field, all-input question remains open.
Problem
The classical product-tree method costs O(M_K(m) log m), so even quasi-linear multiplication gives O(m log^2 m) rather than the sought O(m log m) total operations.
Source: §1 · p. 1, §2.2 · p. 3Method
Results
Takeaways & Limitations
The characteristic-zero Bézout problem is reduced to the corresponding arbitrary-node evaluation and interpolation problem, with an Ω(m log m) nonscalar lower bound in the generic model.
Source: §7 · p. 6
Abstract
from arXiv · showhide
Let $a_1,\ldots,a_m$ be distinct elements of a field $K$, and let $Z(X)=\prod_{i=1}^m (X-a_i)$. We study the arithmetic complexity of computing the unique normalized Bezout pair $s,t$ satisfying $sZ+tZ'=1$, with $\deg t<m$ and $\deg s<m-1$. The classical product-tree approach requires $O(M_K(m)\log m)$ field operations, where $M_K(m)$ denotes the cost of multiplying degree-$<m$ polynomials over $K$. Thus, even when $M_K(m)=O(m\log m)$, the resulting bound is $O(m\log^2 m)$ rather than $O(m\log m)$. Over an infinite field of characteristic zero, we prove that, in the generic rational straight-line-program model, computing all coefficients of the canonical Bezout pair is equivalent, up to an additive $O(M_K(m))$ cost, to arbitrary-node multipoint polynomial evaluation and to interpolation. The main ingredient is an explicit differential reconstruction that recovers $Z$ from $(s,t)$ in $O(M_K(m))$ arithmetic operations on a nonempty Zariski-open subset. Combining this reconstruction with automatic differentiation and transposition yields the complexity equivalence. We further transfer Strassen's lower bound for the elementary symmetric functions to the Bezout problem, obtaining an $\Omega(m\log m)$ nonscalar lower bound. Hence an $O(m\log m)$ algorithm, if it exists in this model, would be asymptotically optimal. The reconstruction is genuinely characteristic-dependent: in characteristic $p$, all squarefree polynomials $X^p+cX+d$, with fixed $c\ne 0$, have the same normalized Bezout pair $(0,c^{-1})$. Therefore the all-field, all-input $O(m\log m)$ problem remains open; generically in characteristic zero, however, it is reduced to the corresponding arbitrary-node multipoint evaluation and interpolation problem.
1 Introduction
The introduction asks whether the normalized Bézout pair can be computed from distinct nodes in O(m log m) field operations. It presents a characteristic-zero reconstruction and complexity equivalence, while emphasizing that the general all-input problem remains unresolved.
1 Introduction
- The open target is computing all 2m −1 coefficients of the pair in O(m log m) field operations, beyond the classical O(m log^2 m) total-operation bound.The distinction matters because the classical algorithms’ O(m log m) multiplication count does not bound their total arithmetic operations.Source: §1 · p. 1
- On a nonempty open set in characteristic zero, a differential reconstruction recovers the root polynomial Z from its canonical pair in O(M_F(m)) operations.Source: §1 · p. 2
- Generic Bézout-pair computation, arbitrary-node evaluation, and arbitrary-node interpolation have the same complexity up to an additive polynomial-multiplication cost.The equivalence combines reconstruction with automatic differentiation and transposition.Source: §1 · p. 2
- The paper transfers Strassen’s Ω(m log m) nonscalar lower bound for elementary symmetric functions to the Bézout pair and gives a positive-characteristic family illustrating the reconstruction’s limits.Source: §1 · p. 2
- The result is neither an O(m log m) algorithm for general nodes nor a lower bound ruling one out.Source: §1 · p. 2
2 Models and the classical upper bound
The section specifies the arithmetic and generic-program models, then derives the classical Bézout-pair algorithm from the canonical form. Its product-tree bound retains an extra logarithmic factor even when polynomial multiplication is quasi-linear.
2.1 Arithmetic and bit models
- A generic rational straight-line program may be defined only on a nonempty Zariski-open subset, and total size counts all four arithmetic operations unless nonscalar complexity is specified.Source: §2.1 · p. 2
- Field-operation bounds do not by themselves bound bit complexity, which also depends on field-element representation and growth, inversion, and output writing.For a fixed finite field F_q, distinctness requires m ≤ q; an asymptotic claim must specify a family of fields or extensions.Source: §2.1 · p. 2
2.2 Canonical form and interpolation
- The canonical pair is obtained by inverting Z′ modulo Z, interpolating t from its values at the nodes, then exactly dividing to recover s.Source: §2.2 · pp. 2–3
- When M_F(m) = O(m log m), the classical product-tree bound is O(m log^2 m), not O(m log m).With the stated arbitrary-algebra multiplication bound, the total-operation estimate is O(m log^2 m log log m).Source: §2.2 · p. 3
3 Recovering the root polynomial
In characteristic zero, the canonical Bézout pair generically determines the root polynomial through a differential reconstruction costing O(MK(m)). The reconstruction requires an open-set condition and does not extend uniformly to all distinct-node inputs.
3 Recovering the root polynomial
- For m ≥ 3 in characteristic zero, the differential reconstruction recovers every coefficient of Z in O(MK(m)) operations.The theorem applies where τ ≠ 0, a nonempty Zariski-open subset of the distinct-node locus.Source: §3 · pp. 3–4
- Integration in characteristic zero and the normalization A(0) = 1 recover A, whose reversal gives Z.On τ ≠ 0, T and A are units in K[[x]]; the truncated inversion, integration, and exponential steps cost O(MK(m)).Source: §3 · p. 3
- For distinct rational real nodes, positivity of every summand ensures the rational function in (8) is not identically zero.This supplies a setting where the nonvanishing condition can be verified.Source: §3 · p. 4
- The open-set condition is necessary: for nodes 0, 1, r, the relevant quantity vanishes when r^2 − r + 1 has a root in the field.The small cases m = 1, 2 are direct and do not affect asymptotic generic complexity.Source: §3 · p. 4
4 Equivalence with evaluation and interpolation
In the generic rational-SLP model, Bézout-pair computation, arbitrary-node evaluation, and interpolation are linked by reductions with polynomial-multiplication overhead. Under quasi-linear multiplication, an O(m log m) algorithm for any one exists exactly when it exists for the other two.
4 Equivalence with evaluation and interpolation
- The reductions treat the nodes as input, with no preprocessing of a fixed special node set.The evaluation map takes the node tuple and polynomial coefficients as input.Source: §4 · p. 4
- Forward differentiation of a Bézout-pair program, composed with reconstruction of Z, supplies the route from pair computation toward evaluation.Each node receives an independent tangent, and every tangent remains linear in the tangent vector.Source: §4 · pp. 4–5
- The generic complexity equivalence links Bézout-pair computation, arbitrary-node evaluation, and interpolation up to an additive polynomial-multiplication cost.Evaluation and interpolation are equivalent up to a constant number of polynomial multiplications [2, Theorems 1 and 2]; transposition adds O(MK(m)) operations [2, Section 6].Source: §4 · pp. 4–5
- When MK(m) = O(m log m), generic Bézout-pair computation has an O(m log m) algorithm if and only if arbitrary-node evaluation and interpolation do.The equivalence does not assert that any of these target-time algorithms is known.Source: §4 · p. 5
- The equivalence is generic rather than an all-input conclusion; the stated exceptional example prevents that immediate extension.A generic rational SLP need only be defined on a nonempty Zariski-open subset.Source: §4 · p. 5
5 Optimality in nonscalar complexity
The paper transfers Strassen’s nonscalar lower bound for elementary symmetric functions to canonical Bézout-pair computation. The resulting Ω(m log m) lower bound applies to generic rational straight-line programs, but does not rule out an algorithm of that order.
5 Optimality in nonscalar complexity
- Strassen’s measure counts multiplications and divisions in a branch-free rational computation, while additions, subtractions, and constant multiplications are free.The reconstruction has O(m) nonscalar cost, allowing the elementary-symmetric-function lower bound to transfer to the Bézout pair.Source: §5 · p. 5
- The canonical Bézout pair requires Ω(m log m) nonscalar operations, and therefore at least Ω(m log m) total operations, in the generic rational-SLP model.The transfer uses the reconstruction to compute the elementary symmetric functions from the pair; the lower bound is stated for sufficiently large m.Source: §5 · pp. 5–6
- The lower bound matches the target order in this generic branch-free model, but neither excludes an O(m log m) algorithm nor asserts bounds for branching or finite-domain models.Source: §5 · p. 6
6 Positive characteristic and finite fields
In positive characteristic, the canonical pair may fail to determine the root polynomial. The paper exhibits a squarefree family with identical pairs and notes a finite-field edge case.
6 Positive characteristic and finite fields
- For fixed nonzero c in characteristic p, the squarefree polynomials X^p + cX + d all have canonical pair (0, c^-1), independent of d.Source: §6 · p. 6
- Thus, in this family, the pair need not determine Z, so the reconstruction’s hard direction does not extend verbatim to positive characteristic.Source: §6 · p. 6
- When m=q and the nodes are all of Fq, Z=X^q-X and its canonical pair is (0, -1).This finite-field case does not settle complexity for growing families with m<q.Source: §6 · p. 6
7 Complexity consequences and unresolved scope
The paper’s results leave the all-field, all-distinct-input question open. Its rigorous endpoint is a generic characteristic-zero equivalence and a matching lower bound within the generic branch-free rational-SLP model.
7 Complexity consequences and unresolved scope
- The original all-field, all-distinct-input question remains open.Source: §7 · p. 6
- In characteristic zero on a nonempty Zariski-open set, Bézout-pair computation is equivalent to arbitrary-node evaluation and interpolation.Source: §7 · p. 6
- The same generic branch-free rational-SLP model has a matching Ω(m log m) lower bound.Source: §7 · p. 6
Reproducibility and disclosure
The authors report diagnostic algebraic checks and disclose language-model assistance; the checks are not proofs. Table 1 concerns arithmetic-complexity conclusions, not bit bounds.
Reproducibility and disclosure
- Exact rational instances and symbolic low-degree cases were checked by two independent scripts in the supplementary source archive, as diagnostics rather than proofs.Source: Reproducibility and disclosure · p. 7
- Language-model assistance was used for literature triage, symbolic diagnostics, and editorial revision; no empirical data were collected.Source: Reproducibility and disclosure · p. 7
- Table 1 summarizes arithmetic-complexity conclusions, and no bit bound follows without field-representation and coefficient-height analysis.Source: Reproducibility and disclosure · p. 7, Table 1 · p. 7