Perturbed random Floquet-Clifford circuits exhibit operator-space fragmentation into wall-separated sectors for p < 1, yielding exact local integrals of motion, tunable operator spreading length, an entanglement bottleneck, and a pre-RMT fragmentation timescale at p = 1.
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Numerical eigenstates of three particles in a circular trap reveal scarred states and towers of states explained by an unstable classical trajectory.
The chaotic phase of the tilted Bose-Hubbard model is identified via eigenstate structure and energy spectrum statistics as a function of energy, tilt strength, and interaction, with moderate tilt enhancing chaos and a phase diagram provided for homogeneous density setups.
A comprehensive review of scaling paths for superconducting quantum computers, with resource and sensitivity analyses for utility-scale applications under realistic error distributions.
citing papers explorer
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Operator space fragmentation in perturbed Floquet-Clifford circuits
Perturbed random Floquet-Clifford circuits exhibit operator-space fragmentation into wall-separated sectors for p < 1, yielding exact local integrals of motion, tunable operator spreading length, an entanglement bottleneck, and a pre-RMT fragmentation timescale at p = 1.
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Quantum scar affecting the motion of three interacting particles in a circular trap
Numerical eigenstates of three particles in a circular trap reveal scarred states and towers of states explained by an unstable classical trajectory.
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Characterization of the chaotic phase in the tilted Bose-Hubbard model
The chaotic phase of the tilted Bose-Hubbard model is identified via eigenstate structure and energy spectrum statistics as a function of energy, tilt strength, and interaction, with moderate tilt enhancing chaos and a phase diagram provided for homogeneous density setups.
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How to Build a Quantum Supercomputer: Scaling from Hundreds to Millions of Qubits
A comprehensive review of scaling paths for superconducting quantum computers, with resource and sensitivity analyses for utility-scale applications under realistic error distributions.