We propose a chirped-pulse driving protocol and reveal its exceptional property for quantum coherent control. The nonadiabatic passage generated by the driving protocol, which includes the population inversion and the nonadiabaticity-induced transition as its ingredients, is shown to be robust against pulse truncation. We further demonstrate that the protocol allows for universal manipulation on the qubit system through designing pulse sequences with either a properly adjusted sweeping frequency or pulsing intensity.We propose a chirped-pulse driving protocol and reveal its exceptional property for quantum coherent control. The nonadiabatic passage generated by the driving protocol, which includes the population inversion and the nonadiabaticity-induced transition as its ingredients, is shown to be robust against pulse truncation. We further demonstrate that the protocol allows for universal manipulation on the qubit system through designing pulse sequences with either a properly adjusted sweeping frequency or pulsing intensity.

arXiv:2403.08496Physical Review AApr 30, 20242 citations

Pulse sequence designed for robust C -phase gates in SiMOS and Si/SiGe double quantum dots

Utkan Güngördü, J. P. Kestner

We theoretically analyze the errors in one- and two-qubit gates in SiMOS and Si/SiGe spin qubit experiments and present a pulse sequence which can suppress the errors in exchange coupling due to charge noise using ideal local rotations. In practice, the overall fidelity of the pulse sequence will be limited only by the quality of the single-qubit gates available: The $C$ -phase infidelity comes out to be $\ensuremath{\approx}2.5\ifmmode\times\else\texttimes\fi{}$ the infidelity of the single-qubit operations. Based on experimental data, we model the errors and show that $C$ -phase gate infidelities can be suppressed by two orders in magnitude. Our pulse sequence is simple and we expect an experimental implementation would be relatively straightforward. We also evaluate the performance of this gate against $1/f$ noise. Assuming a soft ultraviolet cutoff, we show that the pulse sequence designed for quasistatic noise still performs well when the cutoff occurs below $\ensuremath{\sim}1$ MHz with experimentally achievable one-qubit Rabi frequencies, suppressing the infidelity by an order of magnitude compared to the existing direct adiabatic protocol. We also analyze the effects of nonadiabaticity during finite rise periods and find that adiabaticity is not a limitation for the current values of exchange coupling.We theoretically analyze the errors in one- and two-qubit gates in SiMOS and Si/SiGe spin qubit experiments and present a pulse sequence which can suppress the errors in exchange coupling due to charge noise using ideal local rotations. In practice, the overall fidelity of the pulse sequence will be limited only by the quality of the single-qubit gates available: The $C$-phase infidelity comes out to be $\ensuremath{\approx}2.5\ifmmode\times\else\texttimes\fi{}$ the infidelity of the single-qubit operations. Based on experimental data, we model the errors and show that $C$-phase gate infidelities can be suppressed by two orders in magnitude. Our pulse sequence is simple and we expect an experimental implementation would be relatively straightforward. We also evaluate the performance of this gate against $1/f$ noise. Assuming a soft ultraviolet cutoff, we show that the pulse sequence designed for quasistatic noise still performs well when the cutoff occurs below $\ensuremath{\sim}1$ MHz with experimentally achievable one-qubit Rabi frequencies, suppressing the infidelity by an order of magnitude compared to the existing direct adiabatic protocol. We also analyze the effects of nonadiabaticity during finite rise periods and find that adiabaticity is not a limitation for the current values of exchange coupling.

arXiv:1806.01262Physical review. B./Physical review. BOct 1, 201820 citations

Inverse Design of Quantum Control Sequences with Fourier Neural Operators

Anastasia Pipi, Valentin Duruisseaux, Emily Been +4 more

Quantum optimal control is a key tool for steering quantum dynamics, but its computational cost grows rapidly with the Hilbert space dimension. Here, we introduce a Fourier Neural Operator (FNO)-based framework for learning high dimensional molecular quantum dynamics and accelerating the inverse design of control protocols. Given an initial molecular population distribution, laser frequency, and polarization, the FNO predicts molecular-motional population dynamics up to $10^7$ times faster than GPU-accelerated numerical propagation with CUDA-Q Dynamics. Using this fast and differentiable surrogate, we develop the FNO stochastic pulse-measurement planner (FNO-SPMP), which constructs pulse sequences to purify an initially mixed Boltzmann distribution. We demonstrate the protocol in an 888-dimensional subspace of the hydronium molecule at 20 K, achieving a target-state population of 0.98 with a sequence success rate of up to 86.2%. In a shared discrete control space, FNO-SPMP achieves nearly twice the success rate of a reinforcement-learning baseline while using roughly half as many quantum control pulses and reducing pulse-sequence generation time from approximately 10 hours to 10-20 minutes. These results show that operator-learning surrogates can enable inverse design in quantum systems whose Hilbert spaces are too large for conventional direct optimization.Quantum optimal control is a key tool for steering quantum dynamics, but its computational cost grows rapidly with the Hilbert space dimension. Here, we introduce a Fourier Neural Operator (FNO)-based framework for learning high dimensional molecular quantum dynamics and accelerating the inverse design of control protocols. Given an initial molecular population distribution, laser frequency, and polarization, the FNO predicts molecular-motional population dynamics up to $10^7$ times faster than GPU-accelerated numerical propagation with CUDA-Q Dynamics. Using this fast and differentiable surrogate, we develop the FNO stochastic pulse-measurement planner (FNO-SPMP), which constructs pulse sequences to purify an initially mixed Boltzmann distribution. We demonstrate the protocol in an 888-dimensional subspace of the hydronium molecule at 20 K, achieving a target-state population of 0.98 with a sequence success rate of up to 86.2%. In a shared discrete control space, FNO-SPMP achieves nearly twice the success rate of a reinforcement-learning baseline while using roughly half as many quantum control pulses and reducing pulse-sequence generation time from approximately 10 hours to 10-20 minutes. These results show that operator-learning surrogates can enable inverse design in quantum systems whose Hilbert spaces are too large for conventional direct optimization.

quant-pharXiv:2608.03702Aug 5, 20260 citations

Robust Hamiltonian engineering with subensemble control

Wenjie Gong, Matteo Votto, Soonwon Choi

We present a robust protocol to reshape interactions in a spin ensemble based on global control pulse sequences applied to multiple subensembles in parallel. This setting arises naturally from ensembles of solid-state defects or multi-species atomic arrays. We show that it is provably computationally hard to find pulse sequences that simultaneously engineer interactions both within and between subensembles. Despite its formal hardness, we identify a set of necessary or sufficient conditions under which one can synthesize a target Hamiltonian from the native one. Moreover, we introduce efficient numerical strategies for designing pulse sequences that engineer target Hamiltonians robust against common control imperfections. As a specific application, we discuss the robust generation of two-mode spin squeezing in dual-species atomic ensembles, which is a challenging task without subensemble control. Our results provide a practical toolbox to design novel quantum simulation and sensing experiments with minimal control overhead.We present a robust protocol to reshape interactions in a spin ensemble based on global control pulse sequences applied to multiple subensembles in parallel. This setting arises naturally from ensembles of solid-state defects or multi-species atomic arrays. We show that it is provably computationally hard to find pulse sequences that simultaneously engineer interactions both within and between subensembles. Despite its formal hardness, we identify a set of necessary or sufficient conditions under which one can synthesize a target Hamiltonian from the native one. Moreover, we introduce efficient numerical strategies for designing pulse sequences that engineer target Hamiltonians robust against common control imperfections. As a specific application, we discuss the robust generation of two-mode spin squeezing in dual-species atomic ensembles, which is a challenging task without subensemble control. Our results provide a practical toolbox to design novel quantum simulation and sensing experiments with minimal control overhead.

quant-pharXiv:2609.03045Sep 4, 20260 citations

Fast Pulse Sequences

Springer eBooksMay 17, 20060 citations

C

-phase infidelity comes out to be $\ensuremath{\approx}2.5\ifmmode\times\else\texttimes\fi{}$ the infidelity of the single-qubit operations. Based on experimental data, we model the errors and show that

C

-phase gate infidelities can be suppressed by two orders in magnitude. Our pulse sequence is simple and we expect an experimental implementation would be relatively straightforward. We also evaluate the performance of this gate against

1/f

noise. Assuming a soft ultraviolet cutoff, we show that the pulse sequence designed for quasistatic noise still performs well when the cutoff occurs below $\ensuremath{\sim}1$ MHz with experimentally achievable one-qubit Rabi frequencies, suppressing the infidelity by an order of magnitude compared to the existing direct adiabatic protocol. We also analyze the effects of nonadiabaticity during finite rise periods and find that adiabaticity is not a limitation for the current values of exchange coupling.

10^7

times faster than GPU-accelerated numerical propagation with CUDA-Q Dynamics. Using this fast and differentiable surrogate, we develop the FNO stochastic pulse-measurement planner (FNO-SPMP), which constructs pulse sequences to purify an initially mixed Boltzmann distribution. We demonstrate the protocol in an 888-dimensional subspace of the hydronium molecule at 20 K, achieving a target-state population of 0.98 with a sequence success rate of up to 86.2%. In a shared discrete control space, FNO-SPMP achieves nearly twice the success rate of a reinforcement-learning baseline while using roughly half as many quantum control pulses and reducing pulse-sequence generation time from approximately 10 hours to 10-20 minutes. These results show that operator-learning surrogates can enable inverse design in quantum systems whose Hilbert spaces are too large for conventional direct optimization.