One-Round Quantum Randomness Verification with Classical Hardware
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Solution Overview
Problem
Efficient certification of true randomness in quantum computing devices is challenging due to computational power limitations and restrictions imposed by quantum mechanics, making it difficult to verify the quantum behavior and certify randomness using finite computational power.
Innovation Solution
A classical computing device verifies quantum randomness using a physically unclonable function (PUF) to generate training data sets, trains regression models, and performs verification rounds based on a timestamp and predicted responses to challenge strings, leveraging hardware-based cryptographic functions and post-quantum cryptography.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If statistical tests (NIST, Diehard) are used to verify randomness, then randomness quality is improved, but computational power requirements increase beyond finite capabilities
Solution Approach 1:
The patent introduces a quantum computing device as an intermediary between the classical verifier and the randomness source. The quantum device performs the computationally intensive tasks of generating and verifying randomness properties, while the classical verifier only needs to perform simple statistical checks on the output. This mediator handles the heavy computational burden that would otherwise be impossible for finite classical computational power.
Solution Approach 2:
The verification process is segmented into two distinct parts: (1) the quantum computing device generates randomness and performs initial verification using quantum computational power, and (2) the classical verifier performs final statistical validation. This segmentation allows each component to operate within its computational capabilities, with the quantum device handling the intractable parts and the classical device handling the verifiable parts.
2Measurement precision
If quantum behavior verification is performed on quantum computing devices, then randomness certification is improved, but device complexity and access restrictions increase
Solution Approach 1:
The quantum computing device serves as an intermediary that bridges the gap between quantum randomness generation and classical verification. It internally performs complex quantum operations and state measurements, then outputs results in a form that classical verifiers can easily check. This mediator absorbs the device complexity and access restrictions, shielding the classical verifier from quantum system intricacies.
Solution Approach 2:
The patent implements a feedback mechanism where the quantum computing device receives verification challenges from the classical verifier, performs quantum computations to respond to these challenges, and returns results for validation. This interactive feedback loop allows the quantum device to demonstrate its quantum behavior through observable outcomes without requiring the classical verifier to directly access or understand the internal quantum state.
Data Source
AI summary
Methods, systems, and apparatus for verifying quantum randomness. In one aspect a computing device receives data from a quantum computer. The data includes a timestamp, a binary-valued vector, and a predicted response to a challenge string. The predicted response to the challenge string is generated using a regression model that has been trained to fit LPN instances as a linear function, where the LPN instances are constructed using a physically unclonable function. The computing device determines a parity of a random number output by a public source of randomness at a time specified by the timestamp and performs either a generation round or a test round based on the parity to verify the randomness of a bit generated by the quantum computer. The generation round uses the data to verify a preimage of the binary-valued vector and the test round uses the data to verify an equation.