Hybrid Self-Testing Quantum Random Number Generator
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Solution Overview
Problem
Current quantum random number generators (QRNGs) face challenges in estimating entropy generated by quantum processes due to technical noise, requiring complex setups and achieving low bit rates, which limits their application in high-throughput applications like cryptography and scientific simulations.
Innovation Solution
A hybrid approach for self-testing QRNGs that generates a raw bit stream at up to 10 Gb/s, using a fraction of bits for entropy estimation, with two parallel extractors providing certified and true random bits at rates of up to 10 Mb/s and 100 Mb/s respectively, utilizing integrated photonic chips to reduce costs and resource requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If quantum random number generators use complex setups to estimate entropy and separate it from technical noise, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent segments the raw bit stream into two separate streams: one dedicated to entropy estimation and another to random number generation. This segmentation allows the system to use a fraction of bits for entropy measurement while maintaining high throughput for application use, resolving the contradiction between precise entropy measurement and device complexity
Solution Approach 2:
The QRNG system performs self-testing and self-certification by using its own output to estimate entropy and validate randomness quality. The system automatically separates entropy estimation from noise without requiring external complex measurement equipment, achieving precise entropy measurement while keeping the device relatively simple
2Reliability
If quantum random number generators implement rigorous entropy estimation and self-testing, then reliability is improved, but productivity decreases due to low bit rates
Solution Approach 1:
The patent divides the bit stream processing into parallel pathways: one for entropy estimation and validation, another for high-speed random number generation. By processing different fractions of bits through different pathways, the system achieves both rigorous reliability verification and high productivity output
Solution Approach 2:
The system applies partial action by using only a fraction of the generated bits for entropy estimation and validation, while the majority of bits are available for high-speed random number generation. This partial validation approach maintains reliability without sacrificing overall productivity
3Ease of manufacture
If quantum random number generators use integrated photonic chips to reduce hardware requirements, then ease of manufacture is improved, but measurement precision may worsen due to technical noise
Solution Approach 1:
The integrated photonic chip system performs self-characterization and self-validation, using its own operational data to estimate entropy and separate quantum noise from technical noise. This self-service approach compensates for the simplified hardware architecture, maintaining measurement precision without requiring complex external equipment
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables full self-testing certification at reasonable rates with improved randomness and quality, reducing the need for powerful hardware and complex setups, while maintaining high bit rates suitable for various applications.
Implementation Method 1
an emitting device adapted to be triggered by a signal representing an input bit x and adapted to generate and send a stream of one of two possible non-orthogonal quantum states determined by a plurality of said input bit x
Implementation Method 2
a measurement device adapted to detect each quantum state of the stream of quantum states sent by the emitting device and to generate an output b based on the detected quantum state
Data Source
AI summary
Quantum Random Number Generator comprising an emitting device (1) adapted to be triggered by a signal representing an input bit x and adapted to generate and send a stream of one of two possible non-orthogonal quantum states determined by a plurality of said input bit x at a rate in the range of Mb/s up to 10 Gb/s, a measurement device (2) adapted to detect each quantum state of the stream of quantum states sent by the emitting device (1) and to generate an output b based on the detected quantum state, a random selection device (3) adapted to receive said output b and carries out a random selection on said output b so as to select and pick out a first fraction of the bits b′ and a second fraction of the bit b-b′ sent to an entropy (I) estimation module (4, 4′), wherein the entropy (I) estimation module (4, 4′) is adapted to receive the input x, the output b′ and the output b-b′ over a certain number of rounds N and to estimate the entropy (I) of each output for each quantum state of the stream of quantum states, validating or not an extraction ratio, and at least two parallel randomness extraction devices (5, 5′) adapted to carry out a hybrid extraction protocol generating two final random output bit strings via a first extractor (5′) which extracts the first fraction of the bits b′ with bit block sizes in a first range and generates a string of certified random bits r′ at a first rate; and a second extractor (5) which extracts the second fraction of the bits b-b′ with bit block sizes in a second range, higher than the first range, and generates a string of true random bits r at a second rate, higher than the first rate.