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Technical Document Summarizer

Medium

Problem Description

Create a prompt that generates concise and accurate summaries of technical documents. The prompt should: 1. Identify and extract the main topics and key points from the technical document 2. Summarize complex concepts in clear, accessible language 3. Maintain the original document's structure in the summary (e.g., sections, subsections) 4. Highlight any critical data, figures, or results 5. Include a brief conclusion or key takeaways section Your prompt will be tested with various types of technical documents and evaluated based on the accuracy, clarity, and conciseness of the generated summaries.

Your Goal

Create a prompt that successfully handles all test cases below. Your prompt will be evaluated based on accuracy, consistency, and quality of outputs.

Example 1

Input:
Title: Implementation of a Quantum Error Correction Code on a Superconducting Qubit Array Abstract: Quantum error correction is essential for the realization of large-scale quantum computing. In this paper, we report the experimental implementation of a distance-3 surface code on a superconducting qubit array. We demonstrate the ability to detect and correct both bit-flip and phase-flip errors, achieving a logical error rate that is lower than the physical error rate of the constituent qubits. 1. Introduction: Quantum computers promise exponential speedups for certain computational tasks, but they are highly susceptible to errors due to decoherence and imperfect control. Quantum error correction (QEC) is a technique that can protect quantum information by encoding it into a larger system of physical qubits. The surface code is a promising QEC scheme due to its high error threshold and compatibility with planar qubit architectures. 2. Experimental Setup: We used a 2D array of 9 superconducting transmon qubits arranged in a 3x3 grid. The qubits were coupled to their nearest neighbors via tunable couplers, allowing for the implementation of two-qubit gates. Single-qubit operations were performed using microwave pulses, while two-qubit operations used flux-tuning of the couplers. 3. Surface Code Implementation: We implemented a distance-3 surface code, which encodes one logical qubit into 9 physical qubits. The code consists of 4 X-stabilizers and 4 Z-stabilizers, which are measured repeatedly to detect errors. We used a modified version of the surface code that is tailored for our specific hardware constraints. 4. Error Detection and Correction: We induced artificial errors on the physical qubits and demonstrated the ability of the surface code to detect these errors through stabilizer measurements. We then applied correction operations based on the error syndromes. Both bit-flip (X) and phase-flip (Z) errors were successfully detected and corrected. 5. Results: We achieved a logical error rate of 1.5 × 10^-3 per round of error correction, which is lower than the average physical error rate of 2.3 × 10^-3 per qubit. This demonstrates that the surface code successfully protected the quantum information against errors. We also observed that the logical error rate scaled with the distance of the code, as predicted by theory. 6. Conclusion: Our results represent a significant step towards fault-tolerant quantum computing. We have shown that quantum error correction can indeed lower the effective error rate in a real quantum system. Future work will focus on scaling up to larger distances and implementing more complex quantum algorithms on error-corrected logical qubits.
Expected Output:
Summary: Implementation of Quantum Error Correction on Superconducting Qubits Key Points: 1. Successful implementation of a distance-3 surface code on a 3x3 grid of superconducting transmon qubits. 2. Demonstrated detection and correction of both bit-flip and phase-flip errors. 3. Achieved a logical error rate (1.5 × 10^-3) lower than the physical qubit error rate (2.3 × 10^-3). Structure: 1. Introduction: Explained the importance of quantum error correction for large-scale quantum computing. 2. Experimental Setup: Described the 2D array of 9 superconducting qubits and their coupling mechanism. 3. Surface Code Implementation: Outlined the distance-3 surface code encoding one logical qubit into 9 physical qubits. 4. Error Detection and Correction: Detailed the process of inducing, detecting, and correcting artificial errors. 5. Results: Presented the achieved logical error rate and its comparison to the physical error rate. Critical Data: - Logical error rate: 1.5 × 10^-3 per round of error correction - Physical error rate: 2.3 × 10^-3 per qubit Conclusion: The experiment represents a significant advancement towards fault-tolerant quantum computing by demonstrating that quantum error correction can effectively lower the error rate in a real quantum system. Future work will focus on scaling up the system and implementing more complex quantum algorithms on error-corrected logical qubits.

💡 The summary effectively condenses the technical document, highlighting key points, maintaining the original structure, and including critical data and conclusions.

Pro Tips

  • Be specific and clear in your prompt instructions
  • Include examples in your prompt to guide the AI
  • Define the desired output format and tone
  • Test with edge cases to ensure robustness

Prompt Editor

Write and test your prompt below

💡 Use placeholder like {input} to reference test inputs

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Test Case 1

Tests the prompt's ability to summarize a technical report on emerging technology

Input:
Title: Advances in Solid-State Battery Technology for Electric Vehicles [Previous content shown...]

Test Case 2

Tests the prompt's ability to summarize complex cryptographic security analysis

Input:
Title: Security Analysis of Zero-Knowledge Proof Implementations in Blockchain Networks [Technical document about blockchain security protocols and implementations...]

Test Case 3

Tests the prompt's ability to summarize system architecture documentation

Input:
Title: Performance Optimization Techniques for Large-Scale Distributed Systems [Technical document about system architecture and optimization...]