Blockchain with proof of quantum work
- URL: http://arxiv.org/abs/2503.14462v1
- Date: Tue, 18 Mar 2025 17:37:22 GMT
- Title: Blockchain with proof of quantum work
- Authors: Mohammad H. Amin, Jack Raymond, Daniel Kinn, Firas Hamze, Kelsey Hamer, Joel Pasvolsky, William Bernoudy, Andrew D. King, Samuel Kortas,
- Abstract summary: We propose a blockchain architecture in which mining requires a quantum computer.<n>We have refined the blockchain framework to incorporate the probabilistic nature of quantum mechanics.<n>This work highlights the potential for other near-term quantum computing applications using existing technology.
- Score: 0.4643589635376552
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: We propose a blockchain architecture in which mining requires a quantum computer. The consensus mechanism is based on proof of quantum work, a quantum-enhanced alternative to traditional proof of work that leverages quantum supremacy to make mining intractable for classical computers. We have refined the blockchain framework to incorporate the probabilistic nature of quantum mechanics, ensuring stability against sampling errors and hardware inaccuracies. To validate our approach, we implemented a prototype blockchain on four D-Wave$^{\rm TM}$ quantum annealing processors geographically distributed within North America, demonstrating stable operation across hundreds of thousands of quantum hashing operations. Our experimental protocol follows the same approach used in the recent demonstration of quantum supremacy [1], ensuring that classical computers cannot efficiently perform the same computation task. By replacing classical machines with quantum systems for mining, it is possible to significantly reduce the energy consumption and environmental impact traditionally associated with blockchain mining. Beyond serving as a proof of concept for a meaningful application of quantum computing, this work highlights the potential for other near-term quantum computing applications using existing technology.
Related papers
- Standardized test of many-body coherence in gate-based quantum platforms [3.983816213148414]
We propose a method to define a many-body quantum coherence length scale using anyon interference effects in a spin-chain setup.<n>We demonstrate how this approach can be implemented on gate-based quantum platforms to estimate and compare the quantum coherence of current devices.
arXiv Detail & Related papers (2025-03-16T17:01:14Z) - Q-PnV: A Quantum Consensus Mechanism for Security Consortium Blockchains [10.20686832651113]
We propose a novel quantum consensus mechanism, named Q-PnV.<n>This consensus mechanism is based on the classical Proof of Vote (PoV), integrating quantum voting, quantum digital signature and quantum random number generators (QRNGs)<n>Compared to the classical method, the quantum blockchain based on Q-PnV can resist quantum attacks and shows significant improvements in security and fairness, making it better suit-ed for the future quantum era.
arXiv Detail & Related papers (2024-12-09T09:24:04Z) - Cloud-based Semi-Quantum Money [8.252999068253603]
In the 1970s, Wiesner introduced the concept of quantum money, where quantum states generated according to specific rules function as currency.
Quantum computers capable of minting and preserving quantum money have not yet emerged.
Existing quantum channels are not stable enough to support the efficient transmission of quantum states for quantum money.
arXiv Detail & Related papers (2024-07-16T07:40:17Z) - A Quantum-Classical Collaborative Training Architecture Based on Quantum
State Fidelity [50.387179833629254]
We introduce a collaborative classical-quantum architecture called co-TenQu.
Co-TenQu enhances a classical deep neural network by up to 41.72% in a fair setting.
It outperforms other quantum-based methods by up to 1.9 times and achieves similar accuracy while utilizing 70.59% fewer qubits.
arXiv Detail & Related papers (2024-02-23T14:09:41Z) - Quantum data learning for quantum simulations in high-energy physics [55.41644538483948]
We explore the applicability of quantum-data learning to practical problems in high-energy physics.
We make use of ansatz based on quantum convolutional neural networks and numerically show that it is capable of recognizing quantum phases of ground states.
The observation of non-trivial learning properties demonstrated in these benchmarks will motivate further exploration of the quantum-data learning architecture in high-energy physics.
arXiv Detail & Related papers (2023-06-29T18:00:01Z) - From Portfolio Optimization to Quantum Blockchain and Security: A
Systematic Review of Quantum Computing in Finance [0.0]
We provide an overview of the recent work in the quantum finance realm from various perspectives.
The applications in consideration are Portfolio Optimization, Fraud Detection, and Monte Carlo methods for derivative pricing and risk calculation.
We give a comprehensive overview of the applications of quantum computing in the field of blockchain technology.
arXiv Detail & Related papers (2023-06-12T19:53:23Z) - Classical Verification of Quantum Learning [42.362388367152256]
We develop a framework for classical verification of quantum learning.
We propose a new quantum data access model that we call "mixture-of-superpositions" quantum examples.
Our results demonstrate that the potential power of quantum data for learning tasks, while not unlimited, can be utilized by classical agents.
arXiv Detail & Related papers (2023-06-08T00:31:27Z) - Simple Tests of Quantumness Also Certify Qubits [69.96668065491183]
A test of quantumness is a protocol that allows a classical verifier to certify (only) that a prover is not classical.
We show that tests of quantumness that follow a certain template, which captures recent proposals such as (Kalai et al., 2022) can in fact do much more.
Namely, the same protocols can be used for certifying a qubit, a building-block that stands at the heart of applications such as certifiable randomness and classical delegation of quantum computation.
arXiv Detail & Related papers (2023-03-02T14:18:17Z) - Quantum Machine Learning: from physics to software engineering [58.720142291102135]
We show how classical machine learning approach can help improve the facilities of quantum computers.
We discuss how quantum algorithms and quantum computers may be useful for solving classical machine learning tasks.
arXiv Detail & Related papers (2023-01-04T23:37:45Z) - Optimal Stochastic Resource Allocation for Distributed Quantum Computing [50.809738453571015]
We propose a resource allocation scheme for distributed quantum computing (DQC) based on programming to minimize the total deployment cost for quantum resources.
The evaluation demonstrates the effectiveness and ability of the proposed scheme to balance the utilization of quantum computers and on-demand quantum computers.
arXiv Detail & Related papers (2022-09-16T02:37:32Z) - Recent Advances for Quantum Neural Networks in Generative Learning [98.88205308106778]
Quantum generative learning models (QGLMs) may surpass their classical counterparts.
We review the current progress of QGLMs from the perspective of machine learning.
We discuss the potential applications of QGLMs in both conventional machine learning tasks and quantum physics.
arXiv Detail & Related papers (2022-06-07T07:32:57Z) - Quantum Proof of Work with Parametrized Quantum Circuits [0.0]
There is still a dearth of practical applications for quantum computers with a small number of noisy qubits.
We proposed a scheme for quantum-computer compatible proof of work (cryptographic mechanism used in Bitcoin mining) and verified it on a 4-qubit superconducting quantum node.
arXiv Detail & Related papers (2022-04-22T11:26:16Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.