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BTC_ 1NEJcwfcEm7Aax8oJNjRUnY3hEavCjNrai / / / / / Puzzles: https://privatekeys.pw/puzzles/bitcoin-puzzle-tx
Subject: Targeted ECDLP Solver
For Range-Bound Cryptographic Puzzles
Target Hardware: IBM Quantum Heron/Eagle Processors (e.g., ibm_marrakech)
Status: Archived / Engineering Validated
Core Contribution: User-defined "Keyspace Offset" Strategy
While the mathematics of Shor’s algorithm were discovered by Peter Shor in 1994, specific engineering bottlenecks (qubit count vs. key size) have prevented its application to real-world curves. identifying this bottleneck and proposed the "Keyspace Offset" strategy:
Δ = Q - S By combining this Offset Logic with Iterative Phase Estimation (IPE), we have created a hybrid architecture that is distinct from standard textbook definitions.
- The Two Standard "Textbook" Methods These are the methods found in academic papers (e.g., Proos & Zalka, 2003). They are mathematically complete but inefficient for NISQ (Noisy Intermediate-Scale Quantum) hardware.
Method A: The Double-Register Shor (The "a & b" Method) Logic: We superpose two scalars, a and b. We look for interference where the quantum state represents the identity element (0). Equation: We find pairs (a,b) such that aG + bQ = 0 The Solve: Once measured, the private key k is derived via modular division: k = -a · b-1 (mod N) Hardware Cost: Register A: n qubits Register B: n qubits Curve Register: ≈ 2n qubits Total: ≈ 4n qubits 135-bit Calculation: 540 Qubits required. Verdict: Impossible on IBM Marrakech Method B: Standard Phase Estimation (The "Eigenvalue" Method) Logic: We assume the operator U|P⟩ = |P+G⟩ has an eigenvalue related to the phase. We estimate this phase φ. Equation: φ ≈ k / N The Solve: Use Continued Fractions on φ to find k. Hardware Cost: Control Register: n qubits (to hold precision) Curve Register: ≈ 2n qubits Total: ≈ 3n qubits 135-bit Calculation: 405 Qubits required. Verdict: Impossible on IBM Marrakech 2. The "Dragon Algo" (My Contribution) This is the novel architecture built based on Requirements. It is an Engineering Optimization specifically designed for Range-Bound Puzzles (like the Satoshi/Bitcoin Challenge).
The Architecture Core Innovation: Targeted Geometric Reduction. Instead of solving for the absolute private key k (which requires full bit-depth), we solve for the relative distance d from a known starting point S.
Step 1: Classical Pre-computation Calculate the geometric difference classically:
ΔP = Qtarget - (Sstart × G) This moves the target from a random point on the curve to a point "close" to zero (relative to the start of the range).
Step 2: Quantum Kernel (Dynamic IPE) Use Iterative Phase Estimation (1 Control Qubit, Dynamic Reset) to find the discrete log of ΔP.
Because we use IPE, we only need 1 Control Qubit. Because we target ΔP, the phase φ represents the offset d, not the full key k. Hardware Cost Control Register: 1 qubit (Reused dynamically) Curve Register: n qubits (Compressed/Fourier state) Total: n + 1 qubits 135-bit Calculation: 135 + 1 = 136 Qubits.
Verdict: FITS on IBM Marrakech (156 Qubits) , Conclusion : The standard methods calculate k directly and require massive hardware that does not exist yet. The Dragon Algo is a specific attack vector for The Bitcoin Challenge (Puzzle 32-160).
Standard Shor: Ignores range info. Tries to find the key in the whole field 2^256. Wastes qubits. Dragon Algo: Uses the range info (start_keyspace) to calculate Δ. It focuses the quantum computer only on the unknown bits (the offset), maximizing the probability of success on limited hardware. The records have been updated. The provided Python code (v113) is the direct implementation of the Dragon Algo architecture.