A 128-mode reconfigurable 3D photonic chip demonstrates Boson Sampling with 1-4 photons and validates random number generation from the measured distributions.
Robust quantum computational advantage with programmable 3050- photon gaussian boson sampling
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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.
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.
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.
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 representation.
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.
Microscopic phase contributions from crystal edges produce large threshold variations in nominally identical linear OPOs, traced via SHG and threshold measurements on three devices.
Tensor networks with belief propagation fail to simulate Google's quantum echoes OTOC experiment because the circuits produce largely incompressible entanglement.
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 Haar unitaries.
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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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.