Monte Carlo on noisy quantum computers
summary
Claims that quantum Monte Carlo (amplitude/phase estimation) can run on noisy hardware by splitting deep phase‑estimation circuits into many shallow circuits and executing them in parallel, turning a catastrophic serial error collapse into a still‑useful linear signal. Demonstrates with numbers: originally projected 250 qubits but ~100 million operations serially is infeasible; parallelization lowers gate depth, makes a 10‑bit resolution require ~1,000 independent runs that can be run concurrently, and shows empirical error‑slope correction from measured flip rates. Results: prototype circuits and analysis indicate resilience and practical speedups.
AI-written summary · about
chapters (5)
related talks
24mQuantum meets AI: Unlocking Tomorrow’s Potentials
01h 02mQuantum Computing Deep Dive
01h 20mVerifiable Quantum Supremacy: What I Hope Will Be Done
41mQuantum Computing deep dive
01h 01mEmpowering the Quantum revolution with Q#
59mDiving Into Q#
57mGod really plays dice - Introduction to Quantum Computing with Q#
41mState of Quantum Computing in programming