Quantum Computing on Arduino
DQPU, the decentralized quantum simulator
During my Quantum Computing journey, I often needed to simulate some quantum circuits; sometimes they are small, but some other times they are bigger enough to be impossible to run on my 8 GB ram computer.
I started trying Quantum cloud providers, both simulators and real quantum computers, like the servces offered by AWS and IBMQ. But after the free-tiers, I come out to an idea: why don’t pay random people to perform my quantum computations, exploiting their quantum computers or classical simulators?
The answer is trivial: we can’t trust them. But after some research on blind quantum computing and related protocols, I came across to the concept of trap qubits. This concept is based on a simple idea: before delegating the execution of the quantum circuit, you can add some sort of hidden computations that you’re able to verify from results, using classical resources; if the delegated user try to cheat, you will be able to detect it.
DQPU
Using this approach, I created the DQPU.io system (Decentralized Quantum Processing Unit) which addresses the challenge of securely and reliably delegating the execution of quantum computations in a trustless and transparent manner, encouraging competition between independent quantum resource providers. This is achieved by exploiting a decentralized smart contract (currently) running on the Near blockchain.
The operating workflow is really easy:
- Client Submits Job: A Client sends a quantum circuit along with a reward to the DQPU smart contract
- Verifier Validates Circuit: A Verifier validates the submitted circuit adding trap qubits
- Simulation or Hardware Execution: A Sampler executes the job retrieved from the waiting list and submit the result
- Verifier Checks Result: The Verifier checks result validity and the rewards are distributed
- Client Receives Result: The Client can retrieve the final result from the smart contract.
The whole process requires only few seconds.
The current MVC is already a fully working system, and it also integrate a qiskit backend, so you can use it as any other provider. You can read the Quickstart Tutorial.
from dqpu.backends.qiskit import DQPUBackend
backend = DQPUBackend()
backend.load_account("dqpu_alice.testnet")
job = backend.run(quantum_circuit, shots=1024)
counts = job.result().get_counts(circ)
Every user can track the realtime flow of jobs inside the smart contract:
Conclusions
While the current implementation is already functional and integrates with popular frameworks like Qiskit, the DQPU project holds promise for further development and expansion. As quantum computing continues to evolve, decentralized approaches like DQPU could play a crucial role in democratizing access to these powerful computational resources, enabling a wide range of applications and accelerating the pace of innovation in various fields.
The absence of a centralized pricing structure ensures that the costs of executing quantum computations on DQPU are organically shaped by the interplay of resource availability and computational demand. Providers are incentivized to offer competitive rates to attract clients, while clients can leverage the market dynamics to access the most favorable pricing options.
Follow the project on github, and stay tuned on DQPU updates.
Links:
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