Self-consistent 6×6 k·p SP + CI simulations of a triangular Si FinFET DQD yield gate-tunable exchange J and magnetic orientations that favor high-fidelity SWAP or CZ operations.
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Numerical modeling of phonon-induced spin relaxation in displaced silicon double quantum dots reveals a new low-field spin-hot spot with relaxation rates four orders of magnitude lower than standard high-field ones when dots are separated by ~60 nm.
Neural networks trained on local 3x3 tensor-network charge-stability data can predict on-site disorder with high accuracy (R²>0.99) for the central dot in larger 5x5 disordered Hubbard model arrays, enabling scalable tuning of quantum dot spin qubits.
Generalization of the one-tangle metric to higher-spin nuclei enables quantification of maximal electron-nuclear entanglement and direct computation of dephasing times in central-spin systems such as (In)GaAs quantum dots.
Time-multiplexing qubit control reduces drive lines with only logarithmic serialization overhead for single-qubit gates and zero overhead for couplers up to connectivity limits.
Chiral and nonreciprocal magnons can mediate a one-way dissipative coupling that makes two driven NV spin qubits converge to a maximally entangled Bell state as their steady state.
Simulations indicate a semiconducting cQED quantum annealer could complete MHT tasks in ~50 ms, positioning the technology as promising for real-time tracking applications.
citing papers explorer
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Simulation of exchange coupling effects in double quantum dot FinFET-like structures
Self-consistent 6×6 k·p SP + CI simulations of a triangular Si FinFET DQD yield gate-tunable exchange J and magnetic orientations that favor high-fidelity SWAP or CZ operations.
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New Source of Spin-hot spot in displaced silicon double quantum dots
Numerical modeling of phonon-induced spin relaxation in displaced silicon double quantum dots reveals a new low-field spin-hot spot with relaxation rates four orders of magnitude lower than standard high-field ones when dots are separated by ~60 nm.
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Large Scale Optimization of Disordered Hubbard Models through Tensor and Neural Networks
Neural networks trained on local 3x3 tensor-network charge-stability data can predict on-site disorder with high accuracy (R²>0.99) for the central dot in larger 5x5 disordered Hubbard model arrays, enabling scalable tuning of quantum dot spin qubits.
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Quantifying electron-nuclear spin entanglement dynamics in central-spin systems using one-tangles
Generalization of the one-tangle metric to higher-spin nuclei enables quantification of maximal electron-nuclear entanglement and direct computation of dephasing times in central-spin systems such as (In)GaAs quantum dots.
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Overhead in Quantum Circuits with Time-Multiplexed Qubit Control
Time-multiplexing qubit control reduces drive lines with only logarithmic serialization overhead for single-qubit gates and zero overhead for couplers up to connectivity limits.
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Steady-state entanglement of spin qubits mediated by nonreciprocal and chiral magnons
Chiral and nonreciprocal magnons can mediate a one-way dissipative coupling that makes two driven NV spin qubits converge to a maximally entangled Bell state as their steady state.
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Simulation of quantum annealing on a semiconducting cQED device for Multiple Hypothesis Tracking (MHT) benchmark
Simulations indicate a semiconducting cQED quantum annealer could complete MHT tasks in ~50 ms, positioning the technology as promising for real-time tracking applications.