基于3.3 Gbps SPAD的量子随机数发生器
A 3.3 Gbps SPAD-Based Quantum Random Number Generator
摘要：
量子随机数发生器是一种新兴的技术，用于各种应用，包括现代安全和加密系统。典型的方法利用熵源与提取或位生成电路相结合，以便产生随机串。在集成设计中，通常很少有熵源、电路提取和后处理的建模或分析描述。在这项工作中，我们首先讨论量子随机触发器（QRFF）的理论，阐明了电路缺陷的作用，体现在偏置和相关性。然后，Verilog-AMS模型的开发，以验证仿真分析模型。提出了一种新的晶体管实现的QRFF电路，它能够补偿熵固有的随机触发器的有限非对称转换的退化。最后，一个完整的系统包含两个独立的阵列的QRFF电路制造和测试在55纳米双极CMOS DMOS（BCD）技术节点，展示位生成统计，是相称的开发模型。当使用外部LED操作时，全芯片能够生成3.3 Gbps的数据，而单个QRFF可以生成25 Mbps的随机数据，同时保持香农熵界限> 0.997，这是迄今为止最高的每像素比特生成速率之一。NIST STS用于基准测试生成的位串，从而验证QRFF电路作为完全集成QRNG的优秀候选者。
英文摘要：
Quantum random number generators are a burgeoning technology used for a variety of applications, including modern security and encryption systems. Typical methods exploit an entropy source combined with an extraction or bit generation circuit in order to produce a random string. In integrated designs there is often little modelling or analytical description of the entropy source, circuit extraction and post-processing provided. In this work, we first discuss theory on the quantum random flip-flop (QRFF), which elucidates the role of circuit imperfections that manifest themselves in bias and correlation. Then, a Verilog-AMS model is developed in order to validate the analytical model in simulation. A novel transistor implementation of the QRFF circuit is presented, which enables compensation of the degradation in entropy inherent to the finite non-symmetric transitions of the random flip-flop. Finally, a full system containing two independent arrays of the QRFF circuit is manufactured and tested in a 55 nm Bipolar-CMOS-DMOS (BCD) technology node, demonstrating bit generation statistics that are commensurate to the developed model. The full chip is able to generate 3.3 Gbps of data when operated with an external LED, whereas an individual QRFF can generate 25 Mbps each of random data while maintaining a Shannon entropy bound > 0.997, which is one of the highest per pixel bit generation rates to date. NIST STS is used to benchmark the generated bit strings, thereby validating the QRFF circuit as an excellent candidate for fully-integrated QRNGs.
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