研究生: |
陳映如 Chen, Ying-Ru |
---|---|
論文名稱: |
以真空噪音機制之量子亂數產生器 Quantum Random Number Generator by Sampling Vacuum Noise |
指導教授: |
李瑞光
Lee, Ray-Kuang |
口試委員: |
李明昌
Lee, Ming-Chang 鄭皓中 Cheng, Hao-Chung |
學位類別: |
碩士 Master |
系所名稱: |
電機資訊學院 - 光電工程研究所 Institute of Photonics Technologies |
論文出版年: | 2024 |
畢業學年度: | 111 |
語文別: | 中文 |
論文頁數: | 63 |
中文關鍵詞: | 量子光學 、真空態 、量子亂數產生器 |
外文關鍵詞: | Quantum optics, Vacuum state, Quantum random number generator |
相關次數: | 點閱:57 下載:0 |
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亂數被廣泛運用於現今社會當中,如電腦模擬、賭博遊戲以及密碼學 等。現在廣泛使用的偽亂數產生器 (pseudo random number generators),將稱 為種子 (seed) 的初始值,利用某種演算法的計算,生成出具有近似於隨機 性的數列。
雖然偽亂數產生器具有快速和可再生性的優勢,但因為其存在週期性的 問題。隨著量子電腦的發展,電腦的運算能力將大幅提升,偽亂數在例如 密碼學的應用當中,就會產生被破解的安全性的疑慮,因此能夠有效率的 產生真正隨機的亂數,變成一個很重要的議題。
真亂數產生器 (true random number generators),是藉由物理世界裡的隨 機過程,如電路雜訊、混沌系統、量子現象等來產生真正隨機的亂數。其 中量子現象,是利用量子力學內在具有的機率性質,來當作亂數隨機性的 來源。
本研究利用平衡零差偵測器 (balanced homodyne detectors) 量測真空態, 實現可產生速度約 80Mbps 之量子亂數產生器 (quantum random number gen- erator),並探討不同實驗參數對原始資料隨機性的影響,以優化原始資料的 隨機性。
Random numbers have lots of application these days, such as simulations, gam- bling and cryptography. Widely used pseudo random number generators expands a random seed by some deterministic algorithm to random-like sequences. Since it's generated by a deterministic algorithm, there exist patterns behind these sequences. The development of quantum computers poses a threat to the security of pseudo random number generators because of its powerful computing power. Therefore, it is important to develop an efficient way to generate quality random numbers using true random processes.
The true random number generators are realized by unpredictable physical processes such as electronic noise in a circuit, chaotic systems, and quantum phenomena. Among these processes, quantum phenomena exploits the probabilistic nature of quantum mechanics as the source of randomness, which means that it is naturally random.
In this work, we demonstrate a quantum random number generator that can reach a 80Mbps generation rate by sampling vacuum state with a balanced homodyne detector. We also study the influence of different experiment parameters on the autocorrelation function of the raw data in order to improve the randomness.
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