Quantum Computers Generate Certified Random Numbers

Recent advances in quantum computing have enabled the generation of truly random numbers certified by quantum mechanics. Researchers at the Raman Research Institute used IBM’s cloud-based quantum processors to demonstrate that even current noisy quantum devices can produce randomness impossible for classical computers. This breakthrough promises enhanced security for cryptography and other applications relying on unpredictability.

Importance of Randomness

Random numbers are crucial in encryption, simulations, and secure communications. Most classical random numbers are pseudorandom, generated by algorithms that can be predicted if the initial conditions are known. True randomness is essential to prevent security breaches but is difficult to achieve with conventional hardware.

Limitations of Classical and Physical Random Number Generators

Classical pseudorandom number generators rely on deterministic algorithms. Physical generators use unpredictable processes like electronic noise or radioactive decay but face issues such as hardware degradation and trust in manufacturers. Certifying their randomness remains challenging.

Quantum Mechanics and Intrinsic Randomness

Quantum physics inherently produces unpredictable outcomes. Measurements on quantum particles, such as electron spin, are fundamentally random. Quantum systems can violate mathematical constraints called Bell inequalities, proving intrinsic randomness. However, these tests require entangled particles separated by distance, limiting practical use.

Leggett-Garg Inequality as an Alternative Test

The Leggett-Garg inequality (LGI) tests randomness over time on a single quantum system rather than space. If LGI is violated under the ‘no signalling in time’ condition, the results are certified as truly random. This method is more feasible for current quantum computers.

Experimental Implementation on IBM Quantum Computers

The research team constructed simple quantum circuits using one qubit and sequences of single-qubit gates. They performed measurements at three different times to check for LGI violation and independence. The experiments showed consistent LGI violations, confirming certified quantum randomness despite noise.

Implications for Quantum Computing and Security

This approach requires minimal quantum resources and no complex laboratory setups. It enables secure random number generation accessible via cloud quantum platforms. Certified randomness enhances cryptographic security and scientific simulations by providing unpredictability beyond classical limits.

Role of Error Mitigation and Future Prospects

Error correction techniques improved the reliability of results, denoting the importance of mitigating noise in current quantum devices. The method can benchmark individual qubits and aid in testing future quantum hardware. It also reinforces foundational quantum theory by confirming LGI violations in new contexts.

Broader Impact on Quantum Technology

The study demonstrates practical benefits of quantum mechanics . It opens pathways for secure communication and data protection. The ability to certify randomness device-independently marks step towards trustworthy quantum applications accessible to end users globally.

Questions for UPSC:

1. Point out the challenges in generating true random numbers using classical and physical methods and how quantum mechanics addresses these challenges.
2. Critically analyse the significance of the Leggett-Garg inequality in testing quantum randomness and its advantages over Bell inequalities, with suitable examples.
3. Estimate the impact of certified quantum randomness on national security and data encryption technologies in the digital age.
4. Underline the role of error mitigation in quantum computing and discuss how it influences the reliability of emerging quantum technologies.

Answer Hints:

1. Point out the challenges in generating true random numbers using classical and physical methods and how quantum mechanics addresses these challenges.

1. Classical pseudorandom generators use deterministic algorithms, making sequences predictable if the seed is known.
2. Physical random number generators rely on processes like electronic noise or radioactive decay but face hardware degradation and trust issues with manufacturers.
3. Certifying true randomness in classical and physical methods is difficult due to potential predictability and hidden biases.
4. Quantum mechanics provides intrinsic randomness from fundamental quantum phenomena, such as electron spin measurement outcomes.
5. Quantum tests like Bell inequalities and Leggett-Garg inequality certify randomness beyond classical limits, ensuring unpredictability.
6. Quantum methods do not rely on assumptions about hardware trustworthiness, offering device-independent certification possibilities.

2. Critically analyse the significance of the Leggett-Garg inequality in testing quantum randomness and its advantages over Bell inequalities, with suitable examples.

1. Leggett-Garg inequality (LGI) tests temporal correlations in a single quantum system rather than spatial correlations between entangled particles.
2. LGI requires measurements at different times on one qubit, making it practical for current quantum computers unlike Bell tests needing spatially separated entangled qubits.
3. Violation of LGI under ‘no signalling in time’ conditions certifies intrinsic quantum randomness without complex entanglement setups.
4. Example – IBM Quantum’s superconducting qubits successfully violated LGI, demonstrating certified randomness on noisy intermediate-scale devices.
5. LGI enables randomness certification with minimal hardware—only one qubit and shallow circuits—enhancing accessibility and scalability.
6. Unlike Bell inequalities, LGI is suited for benchmarking and error mitigation in existing quantum platforms, broadening its practical impact.

3. Estimate the impact of certified quantum randomness on national security and data encryption technologies in the digital age.

1. Certified quantum randomness ensures unpredictability essential for cryptographic keys, making encryption more secure against attacks.
2. Quantum-generated random numbers prevent predictability vulnerabilities inherent in classical pseudorandom methods.
3. Enhanced security protocols protect sensitive information in communications, finance, defense, and government sectors.
4. Device-independent certification reduces reliance on hardware trust, mitigating risks of backdoors or pre-recorded sequences.
5. Availability via cloud quantum platforms democratizes access to secure randomness, strengthening cybersecurity infrastructure nationally.
6. Overall, quantum randomness can boost resilience against cyber threats in the digital age.

4. Underline the role of error mitigation in quantum computing and discuss how it influences the reliability of emerging quantum technologies.

1. Quantum devices are prone to noise and errors due to fragile qubits and environmental interference.
2. Error mitigation techniques like readout error correction improve measurement accuracy and reduce classical noise effects.
3. Mitigation enables clearer observation of quantum phenomena such as LGI violation, validating genuine quantum randomness.
4. Improved reliability through error control enhances trust in quantum computations and outputs for real-world applications.
5. Error mitigation is crucial for scaling quantum hardware and extending device capabilities despite current noisy intermediate-scale limitations.
6. It supports benchmarking and quality assessment of qubits, guiding development of more robust quantum technologies.