Operator-ready prompt for reuse, tuning, and workspace runs.
This item is set up for developers who want to inspect the original language, fork it into Workspace, and adapt the evidence model without losing the source prompt structure.
Implementation handoffs, eval setup, and prompt tuning where you need the original structure intact.
Inspect first, copy once, then fork into Workspace when you want variants, notes, and model settings attached to the same run.
Swap domain facts, examples, and any hard-coded entities for your own context.
Tighten the evidence or verification requirement if this is headed toward production.
Decide which failure mode you want to evaluate first before you branch the prompt.
This prompt already carries implementation detail, tool context, and a final-output instruction. Keep that structure intact when you tune it, or your comparison runs get noisy fast.
Open this prompt inside Workspace when you want a live iteration loop.
Copy for quick reuse, or run it in Workspace to keep prompt variants, model settings, and prompt-history changes in one place.
Structured source with 1 active lines to adapt.
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Prompt content
Original prompt text with formatting preserved for inspection and clean copy.
Develop a simulation of the BB84 QKD protocol between two nodes, including photon loss, detector noise, and quantum bit errors. Implement error correction and privacy amplification to derive a secure shared key. Then, use `BoTorch` to optimize a QKD source parameter (e.g., photon pulse intensity or repetition rate) to maximize the secure key rate while maintaining the Quantum Bit Error Rate (QBER) below a specified threshold (e.g., 5%).
Adaptation plan
Keep the source stable, then branch your edits in a predictable order so the next prompt run is easier to evaluate.
Hold the task contract and output shape stable so generated implementations remain comparable.
Update libraries, interfaces, and environment assumptions to match the stack you actually run.
Test failure handling, edge cases, and any code paths that depend on hidden context or secrets.
Copy once for a pristine source snapshot, then move the prompt into Workspace when you want variants, run history, and side-by-side tuning without losing the original.
Prompt diagnostics
Quick signals for how structured this prompt already is and where adaptation work is likely to happen first.
This prompt is mostly narrative and instruction-driven, so you can adapt examples and output constraints first without disturbing the structure.
Build a Hybrid QKD/PQC Simulator with Secure Key Management using GPT-5 Pro and BoTorch
This challenge focuses on designing and simulating a hybrid secure communication network. Participants will implement a system that leverages Post-Quantum Cryptography (PQC) for initial secure channel establishment and classical data encryption, complemented by a simulated Quantum Key Distribution (QKD) layer for generating and distributing truly quantum-secure keys between multiple 'cities' or nodes. The system must demonstrate secure key negotiation, lifecycle management, and integration with a simulated application layer. The solution should incorporate advanced optimization techniques for QKD channel parameter selection and utilize modern AI tools for secure key management policy generation and network performance analysis. This challenge bridges the gap between theoretical quantum security and practical, scalable deployment in a classical network infrastructure.
Use the challenge page to recover the original task boundaries before you tune the prompt. That keeps your variants grounded in the same evaluation target instead of drifting into a different problem.