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Pell's equation by computing the regulator

Given a positive non-square integer d, Pell's equation is x² − dy² = 1 and the goal is to find all integer solutions. The least solution can have exponentially many bits, so it cannot be written down; the computational problem is instead to compute the integer part of the regulator R = ln(x₁ + y₁√d), from which the solution can be recovered.

Attested & literatureUpdated

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Order-finding for 7 mod 15

3 counting qubits, 4 work qubits, finding the order of 7 modulo 15 (the order is 4: 7⁴ mod 15 = 1).

q0q1q2q3q4q5q6Step 1 of 5 · XXStep 2 of 5 · Hadamard layer(3)Hadamard layer(3)Step 3 of 5 · Controlled x7 mod 15Controlled x7 mod 15Step 4 of 5 · Controlled x4 mod 15Controlled x4 mod 15Step 5 of 5 · QFT inverse(3)QFT inverse(3)

Step 1 of 5 · X

Probability of each outcome after this step

  • 0001000100%
  1. Prepares the work register as |0001⟩ = 1.

    The whole state moves from 0000000 to 0001000 — one certain outcome before, one certain outcome after, no superposition either side.

  2. Spreads the 3 counting qubits into an equal superposition of all 8 values.

    Probability spreads from 1 outcome to 8. All 8 are equally likely.

  3. Multiplies the work register by 7 mod 15, controlled by the first counting qubit: the k=0 controlled power of the order-finding unitary.

    Probability moves: 4 outcomes appear that had none, 4 drop to zero, 8 carry probability now. Down: 0001001 12.5% → 0.0%, 0001011 12.5% → 0.0%. This is the step that entangles the qubits: from here on no single qubit has a state of its own, only the register as a whole does.

  4. Multiplies the work register by 4 mod 15 (7 squared, mod 15), controlled by the second counting qubit: the k=1 controlled power. The k=2 power would multiply by 7⁴ mod 15 = 1, so it is the identity and is left out entirely.

    Probability moves: 4 outcomes appear that had none, 4 drop to zero, 8 carry probability now. Up: 0100010 0.0% → 12.5%. Down: 0001010 12.5% → 0.0%, 0001110 12.5% → 0.0%.

  5. An inverse QFT on the counting register reads the phase found by the controlled multiplications into a 3-bit estimate.

    Probability moves: 12 outcomes appear that had none, 4 drop to zero, 16 carry probability now. Down: 0111001 12.5% → 0.0%, 0111101 12.5% → 0.0%.

Readout The counting register reads 000, 010, 100 or 110, each equally likely, corresponding to the four powers k = 0, 1, 2, 3 of the order r = 4; the work register ends entangled with the counting outcome, holding one of 1, 7, 4 or 13. Repeating this and applying the continued-fractions step of the full algorithm to a nonzero outcome recovers the order r = 4 exactly.

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  • Record typeLiterature reference
  • Speedup class (secondary source)Superpolynomial
  • Primary source on the speedupStated by the primary source: "The best algorithm for factoring integers has expected time L(1/3,b) for some constant b [LL93]. Assuming the GRH, the best algorithms for Pell's equation and the principal ideal problem have expected time L(1/2,b′), for some constant b′, so there is a sub-exponential gap between the best known classical algorithms."
  • Reported costPolynomial in log Δ and log δ, where Δ is the quadratic discriminant and δ the precision to which the regulator is approximated, with probability exponentially close to one.
  • Papers1

Given a positive non-square integer d, Pell's equation is x² − dy² = 1 and the goal is to find all integer solutions. The least solution can have exponentially many bits, so it cannot be written down; the computational problem is instead to compute the integer part of the regulator R = ln(x₁ + y₁√d), from which the solution can be recovered. Hallgren extends the hidden subgroup problem from finite groups to the group of real numbers. The regulator is an irrational period of a function defined on reduced ideals through a distance function, so the task becomes period finding where the period is not an integer and the group is not discrete. A discretized, pseudo-periodic version of that function is Fourier sampled twice over Z_q, and the two integer outputs are combined by a continued-fraction expansion to recover an integer close to the irrational period. Classical ideal composition and reduction on reduced quadratic ideals supply the function evaluations, which the paper shows can be done in time polynomial in log Δ. The framework is Shor's, applied to a group-like subset of the reals rather than to a group.

References

  • Polynomial-Time Quantum Algorithms for Pell's Equation and the Principal Ideal Problem

    Sean Hallgren · 2007

    Primary source, and the source of this record's cost claim. The full text is freely available from the author's page at the Pennsylvania State University; the version read for this record is the longer journal manuscript, whose own footnote says a preliminary version appeared at STOC 2002, which is the version the Quantum Algorithm Zoo cites. Consult it for the extension of the hidden subgroup problem to the reals, for the two Fourier samplings combined by continued fractions, and for the open question in section 3.1 about whether a fixed precision suffices for all ideals.

Attested & literature
  • Peer-reviewed paper
Method
Curation only. The problem statement was recorded from the literature; the speedup class is checked against the record's own primary paper, which states it; the primary reference's title, authors and submission year were read from its arXiv abs page; the complexity claim was taken from a clause of that paper's abstract (section 3.2, Theorem 2 of the J. ACM version (doi:10.1145/1206035.1206039): "There is a polynomial-time quantum algorithm that, given a quadratic discriminant ∆, approximates the regulator to within δ of the associated order O in time polynomial in log∆ and logδ with probability exponentially close to one."; the supporting evaluation bound is section 2, Theorem 1, which states that the discretized function can be evaluated in time polynomial in log∆ with high probability.). No circuit was constructed, simulated or run.
Result
Pass · the record's problem, speedup class and primary reference agree with the two sources named above.
Caveat
This is a literature record: nothing was constructed, compiled, simulated or run, and no instance of Pell's equation was solved here. What the algorithm returns is an approximation of the regulator to a requested precision, not the least solution and not an exact regulator; the paper says the approximation is refined afterwards using classical algorithms. The result holds for real quadratic fields — degree two over the rationals — and nothing here covers higher degree; the paper says so and treats the general case as later work. The paper flags a genuine gap in the period-finding-over-the-reals machinery it introduces, noting in section 3.1 that it is an open question whether some fixed precision works for all ideals, so the choice of working precision is not settled in general by this document. The quantum result itself is unconditional and that is the paper's point — it contrasts with the classical algorithms, whose running time and correctness both depend on the generalized Riemann hypothesis. But the sub-exponential gap quoted on this record is a gap against the best classical algorithms known, not a proved lower bound, and one side of that comparison is itself GRH-conditional. Computing the class group is a separate matter that the same paper says does need the GRH.
Polynomial-Time Quantum Algorithms for Pell's Equation and the Principal Ideal Problem ↗
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pell equationregulatorreal quadratic fieldhidden subgroup problemperiod finding

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