arXiv subjects

Felix Motzoi

Publications and source records attributed to Felix Motzoi.

At least 37 records · Page 2Linked to original sources

arXiv2025

$W$- and Dicke-state engineering using optimal global control in nearest-neighbor coupled ring-shaped qubit arrays

Motivated by a compelling need for time-efficient and robust schemes for quantum-state engineering in systems of neutral atoms in optical tweezers, we consider a ring-shaped array of qubits with nearest-neighbor Ising-type ($zz$) coupling and transverse ($x$ and $y$) global control fields. This system to a large extent mimics -- outside of the Rydberg-blockade regime -- a circular array of neutral atoms interacting through van-der-Waals type interaction. We investigate the preparation of $W$ and Dicke states in this system starting from the default initial state $|00\ldots 0\rangle$ using two different optimal-control approaches: (i) NMR-like pulse sequence, which consists of instantaneous (delta-shaped) control- and Ising-interaction pulses, and (ii) time-dependent control scheme, which entails shaped control pulses in the presence of always-on Ising interaction between adjacent qubits. By making use of the underlying dihedral symmetry of this system -- which allows one to use a symmetry-adapted computational basis with $\mathcal{O}(2^N / N)$ states in an $N$-qubit system -- and utilizing advanced global-optimization methods, we find optimal sequences of pulses for realizing $W$ and Dicke states within both approaches. In addition, we demonstrate robustness of these sequences against unavoidable control errors. Finally, using typical values of parameters in realistic Rydberg-atom systems, we show that our control schemes enable the preparation of the desired multiqubit states on time scales much shorter than the relevant coherence times of those systems.

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arXiv2025

Classical feature map surrogates and metrics for quantum control landscapes

We derive and analyze three feature map representations of parametrized quantum dynamics, which generalize variational quantum circuits. These are (i) a Lie-Fourier partial sum, (ii) a Taylor expansion, and (iii) a finite-dimensional sinc kernel regression representation. The Lie-Fourier representation is shown to have a dense spectrum with discrete peaks, that reflects control Hamiltonian properties, but that is also compressible in typically found symmetric systems. We prove boundedness in the spectrum and the cost function derivatives, and discrete symmetries of the coefficients, with implications for learning and simulation. We further show the landscape is Lipschitz continuous, linking global variation bounds to local Taylor approximation error - key for step size selection, convergence estimates, and stopping criteria in optimization. This also provides a new form of polynomial barren plateaux originating from the Lie-Fourier structure of the quantum dynamics. These results may find application in local and general surrogate model learning, which we benchmark numerically, in characterizations of hardness in the problem instances, and for meta-parameter heuristics in quantum optimizers.

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arXiv2025

Universal pulses for superconducting qudit ladder gates

Qudits, generalizations of qubits to multi-level quantum systems, offer enhanced computational efficiency by encoding more information per lattice cell, avoiding costly swap operations and providing even exponential speedup in some cases. Utilizing the $d$-level manifold, however, requires high-speed gate operations because of the stronger decoherence at higher levels. While analytical control methods have proven effective for qubits in achieving fast gates with minimal control errors, their extension to qudits is nontrivial due to the increased complexity of the energy level structure arising from additional ancillary states. In this work, we present a universal pulse construction for generating rapid, high-fidelity unitary rotations between adjacent qudit levels, thereby providing a prescription for any gate in $SU(d)$. Control errors in these operations are effectively analyzed within a four-level subspace, including two leakage levels with approximately opposite detuning. By identifying the optimal degrees of freedom, we derive concise analytical pulse schemes that suppress multiple control errors and outperform existing methods. Remarkably, our approach achieves consistent coherent error scaling across all levels, approaching the quantum speed limit independently of parameter variations between levels. Validation on transmon circuits demonstrates significant improvements in gate fidelity for various qudit sizes aiming for $10^{-4}$ error. This method provides a scalable solution for improving qudit control and can be broadly applied to other quantum systems with ladder structures or operations involving multiple ancillary levels.

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arXiv2025

Stochastic Schrödinger equation for a homodyne measurement setup of strongly correlated systems

Starting from an experimentally feasible atomic setup, we derive a stochastic Schrödinger equation that captures the homodyne detection record of a strongly interacting system. Applying the rotating wave approximation to the linear atom-light coupling, we arrive at a reduced equation formulated solely in terms of atomic operators. In the appropriate limit, this equation converges to that of Gaussian continuous quantum measurement -- revealing that the complexities of real-world detection can, under certain conditions, echo the elegance of idealized theory. To illustrate the utility of this framework, we numerically study the Bose-Hubbard model under continuous observation, showing that time-domain analysis of the measurement signal uncovers rich dynamical features, including quantum jumps, that are obscured in ensemble-averaged spectral data.

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arXiv2025

Optimizing two-qubit gates for ultracold atoms using Fermi-Hubbard models

Ultracold atoms trapped in optical lattices have emerged as a scalable and promising platform for quantum simulation and computation. However, gate speeds remain a significant limitation for practical applications. In this work, we employ quantum optimal control to design fast, collision-based two-qubit gates within a superlattice based on a Fermi-Hubbard description, reaching errors in the range of $10^{-3}$ for realistic parameters. Numerically optimizing the lattice depths and the scattering length, we effectively manipulate hopping and interaction strengths intrinsic to the Fermi-Hubbard model. Our results provide five times shorter gate durations by allowing for higher energy bands in the optimization, suggesting that standard modeling with a two-band Fermi-Hubbard model is insufficient for describing the dynamics of fast gates and we find that four to six bands are required. Additionally, we achieve non-adiabatic gates by employing time-dependent lattice depths rather than using only fixed depths. The optimized control pulses not only maintain high efficacy in the presence of laser intensity and phase noise but also result in negligible inter-well couplings.

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arXiv2025

Circuit Design for a Star-shaped Spin-Qubit Processor via Algebraic Decomposition and Optimal Control

As quantum processing units grow in size and precision we enter the stage where quantum algorithms can be tested on actual quantum devices. To implement a given quantum circuit on a given quantum device, one has to express the circuit in terms of the gates that can be efficiently realized on the device. We propose an algorithm based on algebraic circuit decomposition for tailored application of optimal-control gates for quantum computing platforms with star-shaped topologies. We then show numerically how the resulting circuits can be implemented on a quantum processing unit consisting of a nitrogen-vacancy center in diamond and surrounding nuclear spins.

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arXiv2025

Correction Formulas for the Mølmer-Sørensen Gate Under Strong Driving

The Mølmer-Sørensen gate is a widely used entangling gate for ion platforms with inherent robustness to trap heating. The gate performance is limited by coherent errors, arising from the Lamb-Dicke (LD) approximation and sideband errors. Here, we provide explicit analytical formulas for errors up to fourth order in the LD parameter, by using the Magnus expansion to match numerical precision, and overcome significant, orders-of-magnitude underestimation of errors by previous theory methods. We show that fourth order Magnus expansion terms are unavoidable, being in fact leading order in LD, and are therefore critical to include for typical experimental fidelity ranges. We show how these errors can be dramatically reduced compared to previous theory by using analytical renormalization of the drive strength, by calibration of the Lamb-Dicke parameter, and by the use of smooth pulse shaping.

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arXiv2025

Analytical solutions for optimal photon absorption into inhomogeneous spin memories

We investigate for optimal photon absorption a quantum electrodynamical model of an inhomogeneously-broadened spin ensemble coupled to a single-mode cavity. Solutions to this problem under experimental assumptions are developed in the Schrödinger picture without using perturbation theory concerning the cavity-spin interactions. Furthermore, we exploit the possibility of modulating the frequency and coupling rate of the resonator. We consider a one-photon input pulse and show some optimal scenarios, where exact formulas and numerical results are obtained for the absorption probabilities and the optimal pulse shapes. In particular, if the external loss dominates the internal loss of the cavity, we find the optimal cooperativity for different parameters and identify cases where absorption with a success probability larger than $99\%$ is achieved.

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arXiv2025

Hybrid discrete-continuous compilation of trapped-ion quantum circuits with deep reinforcement learning

Shortening quantum circuits is crucial to reducing the destructive effect of environmental decoherence and enabling useful algorithms. Here, we demonstrate an improvement in such compilation tasks via a combination of using hybrid discrete-continuous optimization across a continuous gate set, and architecture-tailored implementation. The continuous parameters are discovered with a gradient-based optimization algorithm, while in tandem the optimal gate orderings are learned via a deep reinforcement learning algorithm, based on projective simulation. To test this approach, we introduce a framework to simulate collective gates in trapped-ion systems efficiently on a classical device. The algorithm proves able to significantly reduce the size of relevant quantum circuits for trapped-ion computing. Furthermore, we show that our framework can also be applied to an experimental setup whose goal is to reproduce an unknown unitary process.

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arXiv2025

Self-Adaptive Physics-Informed Quantum Machine Learning for Solving Differential Equations

Chebyshev polynomials have shown significant promise as an efficient tool for both classical and quantum neural networks to solve linear and nonlinear differential equations. In this work, we adapt and generalize this framework in a quantum machine learning setting for a variety of problems, including the 2D Poisson's equation, second-order linear differential equation, system of differential equations, nonlinear Duffing and Riccati equation. In particular, we propose in the quantum setting a modified Self-Adaptive Physics-Informed Neural Network (SAPINN) approach, where self-adaptive weights are applied to problems with multi-objective loss functions. We further explore capturing correlations in our loss function using a quantum-correlated measurement, resulting in improved accuracy for initial value problems. We analyse also the use of entangling layers and their impact on the solution accuracy for second-order differential equations. The results indicate a promising approach to the near-term evaluation of differential equations on quantum devices.

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arXiv2024

Neutral atom transport and transfer between optical tweezers

We focus on the optimization of neutral atom transport and transfer between optical tweezers, both critical steps towards the implementation of quantum processors and simulators. We consider four different types of experimentally relevant pulses: piece-wise linear, piece-wise quadratic, minimum jerk, and a family of hybrid linear and minimum jerk ramps. We also develop a protocol using Shortcuts to Adiabaticity (STA) techniques that allows us to include the effects of static traps. By computing a measure of the error after transport and two measures of the heating for transient times, we provide a systematic characterization of the performance of all the considered pulses and show that our proposed STA protocol outperforms the experimentally inspired pulses. After pulse shape optimization we find a lower threshold for the total time of the protocol that is compatible with the limit below which the increase in the vibrational excitations exceeds half of the amount of states hosted by the moving tweezer. Since the obtained lower bound for the atom capturing or releasing stage is 9 times faster than the one reported in state-of-the-art experiments, we interpret our results as a wake-up call towards the importance of the inclusion and optimization of the transfer between tweezers, which may be the largest bottleneck to speed. For the two pulses having the best performance (minimum jerk and STA), we determine optimal regions in the experimentally accessible parameters to implement high fidelity transport pulses. Finally, our STA results prove that a modulation in the depth of the moving tweezer designed to counteract the effect of the static traps reduces errors and allows for shorter pulse duration. To motivate the use of our STA pulse in future experiments, we provide a simple analytical approximation for the tweezer position and depth controls.

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arXiv2024

Experimental error suppression in Cross-Resonance gates via multi-derivative pulse shaping

While quantum circuits are reaching impressive widths in the hundreds of qubits, their depths have not been able to keep pace. In particular, cloud computing gates on multi-qubit, fixed-frequency superconducting chips continue to hover around the 1% error range, contrasting with the progress seen on carefully designed two-qubit chips, where error rates have been pushed towards 0.1%. Despite the strong impetus and a plethora of research, experimental demonstration of error suppression on these multi-qubit devices remains challenging, primarily due to the wide distribution of qubit parameters and the demanding calibration process required for advanced control methods. Here, we achieve this goal, using a simple control method based on multi-derivative, multi-constraint pulse shaping, which acts simultaneously against multiple error sources. Our approach establishes a two to fourfold improvement on the default calibration scheme, demonstrated on four qubits on the IBM Quantum Platform with limited and intermittent access, enabling these large-scale fixed-frequency systems to fully take advantage of their superior coherence times. The achieved CNOT fidelities of 99.7(1)% on those publically available qubits come from both coherent control error suppression and accelerated gate time.

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arXiv2024

Long distance spin shuttling enabled by few-parameter velocity optimization

Spin qubit shuttling via moving conveyor-mode quantum dots in Si/SiGe offers a promising route to scalable miniaturized quantum computing. Recent modeling of dephasing via valley degrees of freedom and well disorder dictate a slow shutting speed which seems to limit errors to above correction thresholds if not mitigated. We increase the precision of this prediction, showing that typical errors for 10 $μ$m shuttling at constant speed results in O(1) error, using fast, automatically differentiable numerics and including improved disorder modeling and potential noise ranges. However, remarkably, we show that these errors can be brought to well below fault-tolerant thresholds using trajectory shaping with very simple parametrization with as few as 4 Fourier components, well within the means for experimental in-situ realization, and without the need for targeting or knowing the location of valley near degeneracies.

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arXiv2024

Reinforcement learning pulses for transmon qubit entangling gates

The utility of a quantum computer depends heavily on the ability to reliably perform accurate quantum logic operations. For finding optimal control solutions, it is of particular interest to explore model-free approaches, since their quality is not constrained by the limited accuracy of theoretical models for the quantum processor - in contrast to many established gate implementation strategies. In this work, we utilize a continuous-control reinforcement learning algorithm to design entangling two-qubit gates for superconducting qubits; specifically, our agent constructs cross-resonance and CNOT gates without any prior information about the physical system. Using a simulated environment of fixed-frequency, fixed-coupling transmon qubits, we demonstrate the capability to generate novel pulse sequences that outperform the standard cross-resonance gates in both fidelity and gate duration, while maintaining a comparable susceptibility to stochastic unitary noise. We further showcase an augmentation in training and input information that allows our agent to adapt its pulse design abilities to drifting hardware characteristics, importantly with little to no additional optimization. Our results exhibit clearly the advantages of unbiased adaptive-feedback learning-based optimization methods for transmon gate design.

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arXiv2024

Quantum state preparation via engineered ancilla resetting

In this theoretical investigation, we study the effectiveness of a protocol that incorporates periodic quantum resetting to prepare ground states of frustration-free parent Hamiltonians. This protocol uses a steering Hamiltonian that enables local coupling between the system and ancillary degrees of freedom. At periodic intervals, the ancillary system is reset to its initial state. For infinitesimally short reset times, the dynamics can be approximated by a Lindbladian whose steady state is the target state. For finite reset times, however, the spin chain and the ancilla become entangled between reset operations. To evaluate the performance of the protocol, we employ Matrix Product State simulations and quantum trajectory techniques, focusing on the preparation of the spin-1 Affleck-Kennedy-Lieb-Tasaki state. Our analysis considers convergence time, fidelity, and energy evolution under different reset intervals. Our numerical results show that ancilla system entanglement is essential for faster convergence. In particular, there exists an optimal reset time at which the protocol performs best. Using a simple approximation, we provide insights into how to optimally choose the mapping operators applied to the system during the reset procedure. Furthermore, the protocol shows remarkable resilience to small deviations in reset time and dephasing noise. Our study suggests that stroboscopic maps using quantum resetting may offer advantages over alternative methods, such as quantum reservoir engineering and quantum state steering protocols, which rely on Markovian dynamics.

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arXiv2024

Gate-set evaluation metrics for closed-loop optimal control on nitrogen-vacancy center ensembles in diamond

A recurring challenge in quantum science and technology is the precise control of their underlying dynamics that lead to the desired quantum operations, often described by a set of quantum gates. These gates can be subject to application-specific errors, leading to a dependence of their controls on the chosen circuit, the quality measure and the gate-set itself. A natural solution would be to apply quantum optimal control in an application-oriented fashion. In turn, this requires the definition of a meaningful measure of the contextual gate-set performance. Therefore, we explore and compare the applicability of quantum process tomography, linear inversion gate-set tomography, randomized linear gate-set tomography, and randomized benchmarking as measures for closed-loop quantum optimal control experiments, using a macroscopic ensemble of nitrogen-vacancy centers in diamond as a test-bed. Our work demonstrates the relative trade-offs between those measures and how to significantly enhance the gate-set performance, leading to an improvement across all investigated methods.

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arXiv2024

Large spin shuttling oscillations enabling high-fidelity single qubit gates

Semiconductor quantum dots have shown impressive breakthroughs in the last years, with single and two qubit gate fidelities matching other leading platforms and scalability still remaining a relative strength. However, due to qubit wiring considerations, mobile electron architectures have been proposed to facilitate upward scaling. In this work, we examine and demonstrate the possibility of significantly outperforming static EDSR-type single-qubit pulsing by taking advantage of the larger spatial mobility to achieve larger Rabi frequencies and reduce the effect of charge noise. Our theoretical results indicate that fidelities are ultimately bottlenecked by spin-valley physics, which can be suppressed through the use of quantum optimal control, and we demonstrate that, across different potential regimes and competing physical models, shuttling based single-qubit gates retain significant advantage over existing alternatives.

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arXiv2024

Exponentiation of Parametric Hamiltonians via Unitary interpolation

The effort to generate matrix exponentials and associated differentials, required to determine the time evolution of quantum systems, frequently constrains the evaluation of problems in quantum control theory, variational circuit compilation, or Monte-Carlo sampling. We introduce two ideas for the time-efficient approximation of matrix exponentials of linear multi-parametric Hamiltonians. We modify the Suzuki-Trotter product formula from an approximation to an interpolation schemes to improve both accuracy and computational time. This allows us to achieve high fidelities within a single interpolation step, which can be computed directly from cached matrices. We furthermore define the interpolation on a grid of system parameters, and show that the infidelity of the interpolation converges with $4^\mathrm{th}$ order in the number of interpolation bins.

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