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Algorithms · Hidden-period / factoring

Resource counts for elliptic-curve discrete logarithms

Carry Shor's discrete-logarithm algorithm through concretely for the group of points on an elliptic curve over GF(p), and count the qubits and operations it needs, so that the cost of attacking elliptic-curve cryptography can be compared with the cost of attacking RSA at an equivalent classical security level.

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.

Open in Studio
  • Record typeLiterature reference
  • Speedup class (secondary source)Various
  • Primary source on the speedupStated by the primary source: "The classical complexity of this problem seems to depend strongly on the underlying group… for discrete logarithms over elliptic curves, nothing better than "generic" algorithms are known… e.g. the Pollard ρ algorithm [3], have truly exponential complexity."
  • Reported costAbout 6n **logical** qubits and order n³ operations for an n-bit prime field, given as roughly 360n³ n-bit additions against about 4kn³ for factoring. Concretely the paper's table pairs a 160-bit elliptic-curve key at around 1000 logical qubits on a machine the authors twice call perfect and noise-free, with the security-equivalent 1024-bit RSA modulus at about 2000, and it gives the same pairing at 512, 2048, 3072 and 15360-bit RSA against 110, 224, 256 and 512-bit curves.
  • Papers1

Carry Shor's discrete-logarithm algorithm through concretely for the group of points on an elliptic curve over GF(p), and count the qubits and operations it needs, so that the cost of attacking elliptic-curve cryptography can be compared with the cost of attacking RSA at an equivalent classical security level. The algorithm is Shor's two-dimensional hidden-subgroup construction: build the superposition over |x, y, xP + yQ⟩ using double-and-add point arithmetic on the curve, then apply a two-dimensional quantum Fourier transform and read the discrete logarithm off the dual lattice. The work is in the arithmetic. Each group operation decomposes into modular divisions and multiplications, and each division needs a reversible extended Euclidean algorithm — whose classical running time depends on its input, which is the obstacle the authors call the quantum halting problem. Their contribution is a piecewise-reversible implementation that lets different branches of the superposition desynchronize and move through the algorithm's five basic operations at their own pace instead of in lockstep, taking that subroutine from cubic to quadratic. Sharing registers between intermediate values then brings the qubit count down further.

References

  • Shor's discrete logarithm quantum algorithm for elliptic curves

    John Proos, Christof Zalka · 2003

    Primary source, and the source of this record's cost claim. The qubit and operation counts are in section 6, with the RSA-versus-curve table in section 6.3; the reversible extended Euclidean algorithm that the whole cost turns on is in section 5. Consult section 6.3 in particular before quoting any number from this record: it is where the authors say that error correction or fault tolerance is very probably necessary and that each logical qubit would then become several physical ones, which is the overhead none of the published figures include.

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 (abstract of arXiv:quant-ph/0301141: "A 160 bit elliptic curve cryptographic key could be broken on a quantum computer using around 1000 qubits while factoring the security-wise equivalent 1024 bit RSA modulus would require about 2000 qubits."; section 6.2: "the DLP algorithm requires either f(n) = 7n + 4 log₂ n + ǫ or f′(n) = 5n + 8√n + 4 log₂ n + ǫ bits depending o[n] whether register sharing is used"; section 6.1: "the discrete logarithm algorithm is O(n³) … has a running time of approximately 360kn³ compared to only about 4kn³ for factoring."). 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: no circuit was built, compiled, simulated or run here, and no key was broken. The famous headline number is a count of **logical** qubits on an idealised machine, and the paper says so in both places it matters — parenthetically, that this is on a perfect, noise free, quantum computer, and in section 6.3, that for large scale quantum computation error correction or full fault tolerance is very probably necessary, so each logical qubit has to be encoded into several physical qubits, possibly dozens, and each logical gate becomes many physical ones. **None of the counts here include that overhead**, so "around 1000 qubits" is not a statement about any machine anyone would build. The figures are also estimates rather than a gate-level tally: section 6.1 says outright that the authors do not go to the lowest level and count gates but count n-bit additions instead, and the factor converting quantum-quantum to classical-quantum additions is estimated from networks in another paper. The scope is curves over GF(p) only; the abstract says curves over GF(2^n) and other fields are not yet considered. Parallelisation is not analysed, and the authors note factoring may parallelise more easily, which would move the comparison. Finally, this record covers one strand of the Zoo's "Quantum Cryptanalysis" heading — the elliptic-curve resource analysis. That heading cites **23** papers, not the eight an earlier reading of it reported: the pinned index this repository measures against had been truncating every reference list at eight, so the shortfall was understated by a factor of three. Three are carried: Shor 1995 and its FOCS 1994 predecessor, by the shor-period-finding and discrete-logarithm records, and Proos and Zalka by this one. The other twenty are covered by no record here — Boneh and Lipton on hidden linear functions; Childs, Jao and Soukharev on isogenies; Eldar and Hallgren on lattices, with the Ducas and van Woerden note disputing it; Chen and Gao and two successors on multivariate and Boolean systems; five papers on Grover-based key search and hash collisions; three on Grover speedups of public-key attacks; and five on superposition-query attacks against block ciphers.
Shor's discrete logarithm quantum algorithm for elliptic curves ↗
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elliptic curve cryptographydiscrete logarithmresource estimationmodular arithmeticcryptanalysis

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