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Robust quantum computational advantage with programmable 3050-photon Gaussian boson sampling
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Robust quantum computational advantage with programmable 3050-photon Gaussian boson sampling
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The creation of large-scale, high-fidelity quantum computers is not only a fundamental scientific endeavour in itself, but also provides increasingly robust proofs of quantum computational advantage (QCA) in the presence of unavoidable noise and the dynamic competition with classical algorithm improvements. To overcome the biggest challenge of photon-based QCA experiments, photon loss, we report new Gaussian boson sampling (GBS) experiments with 1024 high-efficiency squeezed states injected into a hybrid spatial-temporal encoded, 8176-mode, programmable photonic quantum processor, Jiuzhang 4.0, which produces up to 3050 photon detection events. Our experimental results outperform all classical spoofing algorithms, particularly the matrix product state (MPS) method, which was recently proposed to utilise photon loss to reduce the classical simulation complexity of GBS. Using the state-of-the-art MPS algorithm on the most powerful supercomputer EI Capitan, it would take > $10^{42}$ years to construct the required tensor network for simulation, while our Jiuzhang 4.0 quantum computer takes 25.6 $\mu$s to produce a sample. This work establishes a new frontier of QCA and paves the way to fault-tolerant photonic quantum computing hardware.
Forward citations
Cited by 12 Pith papers
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Boson Sampling with a reconfigurable 128 modes 3D integrated photonic circuit
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Matrix phase-space representations include quantum symmetries via basis projection to unify prior methods and reduce sampling errors in many-body simulations, shown for GBS verification with parity symmetry.
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General framework for anticoncentration and linear cross-entropy benchmarking in photonic quantum advantage experiments
A representation-theoretic framework computes LXEB scores and proves anticoncentration for Fock-state Boson Sampling in the saturated regime using irrep decompositions of bosonic spaces.
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Efficient simulation of low-entanglement bosonic Gaussian states in polynomial time
A new algorithm converts low-entanglement bosonic Gaussian states to matrix product states in polynomial time without hafnian calculations, yielding speedups on experimental boson sampling data.
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Quantum-to-Classical Computability Transition via Negative Markov Chains
For unitaries from local or pairwise interactions, depolarizing noise above a critical strength makes open quantum spin chain dynamics exactly classically simulable by halting growth in the negative Markov chain repre...
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Gaussian boson sampling: Benchmarking quantum advantage
A new classical algorithm for Gaussian boson sampling produces outputs closer to exact results than quantum experiments up to 1152 modes and scales efficiently, indicating hardware errors enable classical simulation.
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Boosting Gaussian Boson Sampling using Optical Parametric Amplification Networks
An OPA-based nonlinear interferometer is proposed that keeps GBS entanglement linear in the number of modes under realistic photon loss, which the authors argue prevents efficient classical simulation.
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Matrix product state approach to lossy boson sampling and noisy IQP sampling
Lossy boson sampling and noisy IQP sampling are classically simulable with matrix product states, with the same known noise thresholds and accuracy controlled by bond dimension.
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Phase-Sensitive Crystal-Edge Effects in Linear Optical Parametric Oscillators: Why Nominally Identical Squeezers Behave Differently
Microscopic phase contributions from crystal edges produce large threshold variations in nominally identical linear OPOs, traced via SHG and threshold measurements on three devices.
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Tensor Networks with Belief Propagation Cannot Feasibly Simulate Google's Quantum Echoes Experiment
Tensor networks with belief propagation fail to simulate Google's quantum echoes OTOC experiment because the circuits produce largely incompressible entanglement.
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Entanglement and circuit complexity in finite-depth random linear optical networks
In finite-depth random linear optical circuits, entanglement grows at most diffusively and robust circuit complexity scales similarly, with depth bounds ensuring near-maximal subsystem entanglement and closeness to Ha...
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Probing the Planck scale with quantum computation
A 500-logical-qubit quantum computer could reject laboratory-confined theories by surpassing the Planck-scale operation rate of 2^491 m^{-3} s^{-1}, with a 1600-qubit machine limited by the observable universe.
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