Quantum control papers on arXiv, selected and classified automatically by QOC. https://llorebaga.github.io/QOC/topics/grape/ 2026-10-11T00:00:00Z QOC https://arxiv.org/abs/2610.15743 2026-10-11T00:00:00Z 2026-10-11T00:00:00Z Elisa Palacino-González

In molecules, electronic coherence typically decays within a few hundred femtoseconds, a timescale usually attributed to the environment. We show that it is set to a large extent by which coherences are excited: the molecule can host coherences that the bath barely sees, and optimal control can find and exploit them. Using gradient-based optimal control (GRAPE) with Redfield dynamics, we maximize the total vibronic coherence between the electronic ground and an optically bright electronic excited state in a three-state model with nonadiabatic features, in two regimes of low and high nonadiabatic mixing and for different system-bath coupling strengths. The Liouvillian spectrum reveals, in both regimes, a well-separated coherence mode with substantial ground-bright character that decays on a picosecond timescale. This mode is protected by mixing with the dark state, which brings the geometry of the optically accessible excited state close to that of the ground state and thus weakens its coupling to the bath. Without prior information, GRAPE finds this mode and keeps the photoexcited wave packet near the Franck-Condon region. At equal fluence, it increases the coherence at 800 fs by more than two orders of magnitude over a Gaussian pulse at the weakest coupling, and by many more at stronger coupling. The Liouvillian predicts the bath dependence of the long-lived coherence to within 1\%, and a Gaussian pulse tuned to the mode frequency comes within 10\% of the best pulse found. Beyond two-level and spin systems, our study puts forward the vibronic structure of molecules as a route to protected coherence subspaces, identifying a dark-state protection mechanism and a design criterion based on molecular parameters. These results lay the groundwork for our goal of using vibronic molecular systems as a resource for long-lived, controllable coherences in molecular quantum information science.

https://arxiv.org/abs/2609.25936 2026-09-22T00:00:00Z 2026-09-22T00:00:00Z Jialiang TangRuoqian XuGloria PlateroYue BanXi Chen

We demonstrate spin--orbit-coupling (SOC) catalysis of magnetization-sector transfer in the half-filled Fermi--Hubbard model. Without SOC, conservation of total magnetization confines the dynamics to the initial sector, preventing an antiferromagnetically correlated state from reaching the polarized ferromagnetic sector under a Zeeman ramp. A transient SOC control lifts this obstruction by coupling otherwise disconnected magnetization sectors and converting symmetry-protected crossings into avoided crossings, thereby opening a finite-gap pathway for magnetic-state conversion. We further accelerate the SOC-enabled dynamics beyond the adiabatic timescale using gradient-ascent pulse engineering (GRAPE) and a variational quantum circuit. Both approaches achieve rapid magnetization transfer in one- and two-dimensional Fermi--Hubbard lattices. Our results establish transient SOC as a controllable catalyst for overcoming symmetry-imposed dynamical constraints, while optimal control sets the timescale for the resulting magnetization-sector transfer.

https://arxiv.org/abs/2607.14175 2026-07-15T00:00:00Z 2026-08-03T00:00:00Z Shi-Qiang QiaoZheng ShanXue-Ke SongShi-Lei SuLiu YeDong Wang

We present a method for suppressing transducer leakage errors in spin-superconducting hybrid quantum systems with the theory of optimal invariant-based shortcut. By mediated virtual photons as a transducer to exchange the energy between the spin qubit and a transmon qubit, the fidelity of the population of the final state features a broad range above 99\% under the influence of leakage error. The leakage probability from computational subspace to non-computational subspace can be effectively suppressed at a lowest value with $0.01$. Based on the optimized pulse control designed by the invariant-based inverse engineering, the high-fidelity quantum iSWAP gate operations and entanglement state preparation within the computational subspace are achieved. {Compared to the traditional $π$ pulse, derivative removal by adiabatic gate, counter-diabatic shortcut schemes, and limited-memory Broyden-Fletcher-Goldfarb-Shanno gradient ascent pulse engineering, the optimized shortcut scheme can still achieve a high fidelity with 99\% in the presence of decoherence and control error.} When taking into account the possibility of leakage errors in actual situations, our solution can still largely resist the influence of control errors. The results provides a feasible path for precisely manipulating the quantum state of hybrid quantum systems.

https://arxiv.org/abs/2607.12567 2026-07-14T00:00:00Z 2026-07-14T00:00:00Z Zhao-Wei WangKai-Yu YuanFeng-Hua RenZhao-Ming Wang

Physics-informed neural networks (PINNs) provide a pathway to reunify the simulation and control of quantum systems, in which these two tasks are typically decoupled in traditional strategies. However, most work remains confined to Markovian environments. When applied to non-Markovian systems, standard PINN architectures fail to converge reliably due to multi-objective optimization conflicts arising from the coupled differential equations. To address this fundamental limitation, we extend our previously proposed forked PINN (FPINN) by incorporating a dedicated control branch. By decoupling the optimization objectives at the gradient level via selective gradient flow, our method turns a previously intractable multi-task optimization into a well-conditioned one, allowing simulation and control to be optimized jointly without compromise. Numerical simulations on a two-qubit Heisenberg XXX model confirm that our framework faithfully reproduces the features of non-Markovian dynamics, including decoherence and information backflow. Taking a state-preparation task on the same model as an example, our FPINN achieves higher fidelity than gradient ascent pulse engineering, chopped random basis, and standard PINNs, with the advantage becoming more pronounced as the environment becomes more dissipative and more Markovian. The generated pulses are also noticeably smoother, which is advantageous for experimental implementation. Our framework thus provides a unified, end-to-end differentiable paradigm for simulation and control of open quantum systems, with potential implications for quantum computing, simulation, and control.

https://arxiv.org/abs/2607.10946 2026-07-12T00:00:00Z 2026-07-12T00:00:00Z Leeseok KimFrancisco RiberiKevin BacaMilad Marvian

Quantum optimal control (QOC) aims to find control functions that optimally steer a quantum system toward a target operation. We introduce a \emph{randomized} QOC framework where optimization is carried over an ensemble of control functions and their probabilities, instead of a single set of functions. Using this framework, we prove that randomized QOC can reach a target accuracy faster than any deterministic protocol under the same resource constraints. We also develop general symmetry-based constructions that convert a given control into an ensemble of controls that can systematically reduce the error. We benchmark these constructions for CNOT implementation and find that the resulting randomized protocol quadratically suppresses the error of the optimized deterministic solution. In addition, we introduce randomized GRAPE, which generalizes GRAPE to directly optimize control ensembles and their associated probabilities. Finally, as a related application, we discuss randomized boundary-pulse constructions {that enhance} robustness against coherent noise.

https://arxiv.org/abs/2607.01217 2026-07-01T00:00:00Z 2026-07-01T00:00:00Z Alexander PechenBoris Volkov

In this work, we perform an analytical and numerical analysis of quantum landscapes for controlling special four-level quantum systems for which we prove that the null control is a five-order trap: a $V-V$ system and an anharmonic system. As a control goal, an observable optimization is considered. The rigorous theoretical analysis is followed by the numerical experiments based on the GRadient Ascent Pulse Engineering (GRAPE) algorithm and Gradient Projection Method (GPM), performed to investigate the behavior of the efficiency of optimization for unconstrained (using GRAPE) and constrained (using GPM) controls. As the main result, we observe an interesting phenomenon with a diverse behavior of the optimization efficiency depending on the system Hamiltonian -- sharp increase of the optimization efficiency up to 100% at certain distance from the null control for a V-V system, while much slower and less significant increase (and even small decrease) for a system with the chain interaction. This sharp difference might be related with the fine structure of the subspace of controls where second derivative of the objective functional is zero.

https://arxiv.org/abs/2607.00826 2026-07-01T00:00:00Z 2026-07-01T00:00:00Z Ria PatelMasoud Hakimi HerisYuan LiuFrank Mueller

Standard gate-level transpilation introduces significant physical noise and overhead for high-precision quantum algorithms, such as the Quantum Singular Value Transformation (QSVT), on near-term trapped-ion hardware. Current compilers treat quantum operations as discrete units, forcing the physical control layer to execute highly fragmented laser pulses. To address this hardware-software disconnect, this work introduces a holistic pulse synthesis strategy that bypasses discrete gate-stitching to compile algorithms directly into continuous compound pulse gadgets. As a proof-of-concept, we target Hamiltonian simulation of the $H_2$ molecule, block-encoding the problem into a QSVT circuit to approximate the time-evolution operator $U = e^{-i H t}$ across 3 computational ions (2 system, 1 ancilla). We utilize the Gradient Ascent Pulse Engineering (GRAPE) algorithm to generate these compound gadgets and evaluate our methodology using noisy Lindblad master equation simulations. Preliminary observations indicate that the proposed strategy achieves significant temporal compression, reducing the total pulse schedule duration compared to standard compilers. Furthermore, synthesizing operations holistically eliminates the control-layer latency associated with discrete pulse lookup overhead. By streamlining the physical control schedule, this methodology offers a promising pathway to execute operations faster, highlighting the potential for compound gadgets to increase the computational depth achievable within fundamental $T_2$ decoherence limits.

https://arxiv.org/abs/2606.24507 2026-06-23T00:00:00Z 2026-06-23T00:00:00Z Tobias KiermeyerThomas HeydenreichLéo Van DammeSebastian HohenemserFlorian MarquardtSteffen J. Glaser

Real-time adaptive control of quantum systems requires rapid generation of robust, high-fidelity pulses across a continuous range of operating conditions. Standard optimization algorithms such as gradient-ascent pulse engineering (GRAPE) solve each instance independently, discarding information between runs and requiring costly reinitialization when parameters change. We present an approach to robust optimal quantum control based on model-based reinforcement learning, in which a single neural network -- embedding the Hamiltonian directly into the training pipeline -- generates robust gates across an entire family of gate configurations, without pre-computed training data. Demonstrated on a single-spin (two-level) system, the trained networks produce pulses for arbitrary rotation angles over a range of pulse durations, detunings, and field inhomogeneities in milliseconds, at fidelities comparable to multi-seed GRAPE. The framework is inherently adaptable: any parameter entering the Hamiltonian can serve as a network input, extending the approach to different systems and control settings. Beyond speed, the network reveals structure in the control landscape: it discovers the same structured phase profiles that appear in GRAPE solutions -- made identifiable through fidelity-invariant symmetry transformations -- but more consistently than independent optimization. This consistency enables smooth interpolation across the entire trained parameter space.

https://arxiv.org/abs/2606.22212 2026-06-20T00:00:00Z 2026-09-21T00:00:00Z Denis JankovićSaba TaherpourPaul-Louis EtienneyPaul-Antoine HervieuxChristoph Wolf

A central goal of quantum optimal control is to achieve high-fidelity and low-energy control pulses. When quantum optimal control methods optimize every point of a pulse discretized over small time steps independently this can yield high fidelity control but also results in broadband and energy-hungry waveforms. We extend MAGICARP, a shooting method inspired by Pontryagin's maximum principle on energy that generates an entire pulse from a small set of parameters, making it smooth and energy-efficient by construction, from driftless systems to closed systems with the constant drift Hamiltonian of two exchange-coupled spins in an external magnetic field. The optimization proceeds in stages: the dressed states of the drift Hamiltonian structure the target, an initial shooting optimization is performed in the rotating-wave frame, and an exact laboratory-frame refinement follows. Benchmarked against Krotov and GRAPE at matched gate infidelity, MAGICARP consistently achieves the lowest energy and a conserved pulse area, concentrates its spectral weight on the gate-relevant transitions, and is the most robust to fluctuations in the exchange coupling; GRAPE independently converges to essentially the same pulse while black-box Krotov meets the same error at an order-of-magnitude energy premium. This method-independence is what qualifies the bounded solver as a measurement instrument, and the central result follows: a large statistical survey of unselected optimization runs resolves a weak-driving quantum speed limit for two exchange-coupled electron spins: low-amplitude realizations of the two-qubit quantum Fourier transform cease to exist below a critical gate time, and the minimum control energy diverges on approach to this limit. The divergence obeys a simple two-parameter area--pole law, $E_2^{\mathrm{law}}(T)=A/T+B/(T-T^*)$.

https://arxiv.org/abs/2606.17357 2026-06-15T00:00:00Z 2026-06-15T00:00:00Z Henrik GothenChristopher K. LongDjamila HillerYunming QianCrispin H. W. BarnesNormann MertigDavid R. M. Arvidsson-Shukur

Useful chemistry calculations on near-term quantum processors are hindered by current algorithmic runtimes. We develop a methodology to significantly reduce these runtimes. Typically, variational quantum eigensolver (VQE) algorithms are implemented as sequences of primitive gates. Our methodology instead relies on gradient-ascent pulse engineering to construct hardware-tailored pulses for the direct implementation of VQEs. As problem sizes increase, it quickly becomes intractable to optimise a pulse that implements an entire VQE ansatz circuit. However, leading VQEs are constructed in a modular fashion. A problem-tailored VQE is assembled from parameterised circuit elements that simulate hopping between two or four electronic spin orbitals. We show that these circuit elements can be implemented more efficiently using hardware-tailored pulses. We numerically demonstrate our methodology on a silicon spin-qubit quantum processor. We find that common circuit elements, known as single- and double-qubit excitations, can be implemented in less than 289 ns and 927 ns, respectively. Compared with conventional gate-based implementations, our pulse-accelerated qubit excitations provide a scalable approach for faster and therefore more noise-robust quantum chemistry simulations by reducing VQE runtimes by up to a factor of 15.3.

https://arxiv.org/abs/2606.15383 2026-06-13T00:00:00Z 2026-06-16T00:00:00Z Shebha Anandhi JegadeesanYujie ZhaoRobert HunterHassane El MkamiMaximilian KeitelCallum MusselwhiteGraham SmithGuinevere MathiesIlya Kuprov

Periodically driven dissipative systems can settle into steady orbits - fixed loops on their dynamical manifolds. In quantum mechanics, steady orbits occur in cooling engines (used to initialise quantum devices), coherent oscillators (such as lasers and masers), precision metrology devices (atomic clocks, optical and spin magnetometers), and magnetic resonance (steady state free precession, dynamic nuclear polarisation). Steady orbits and stroboscopic steady states are a promising target for quantum optimal control, but the numerical complexity is prohibitive: the infinite loop defeats gradient ascent pulse engineering (GRAPE) which relies on explicit numerical propagation in the time domain. Here we propose an efficient quantum control strategy for stroboscopic steady states and limit cycles that are approached asymptotically when a control sequence is repeated infinitely many times. The formalism is different from Floquet-Lindblad state engineering and effective Hamiltonian theories: it finds control sequences that drive a dissipative quantum system towards a steady orbit passing through user-specified waypoints. The software implementation (same numerical complexity scaling as GRAPE) is done for the Spinach library.

https://arxiv.org/abs/2606.09624 2026-06-08T00:00:00Z 2026-09-11T00:00:00Z Andrew J. BaldwinJonathan A. Jones

We compare phase-only control with phase-and-amplitude control when designing shaped pulses using the GRAPE algorithm, and explain why phase-only control has significant advantages. Trotterisation can be used to simulate amplitude modulation with phase modulation, indicating that the two approaches are fundamentally equivalent. Pulses designed by either method can be interconverted, but phase-only optimization is faster and simpler. The resulting pulses can then be converted into phase-and-amplitude form for more robust implementation if desired.

https://arxiv.org/abs/2606.02283 2026-06-01T00:00:00Z 2026-06-09T00:00:00Z Ivy Pannier-GüntherVikas BuchemmavariPablo M. PoggiIvan H. Deutsch

The ability to engineer and control quantum states of many-body systems is a central challenge in quantum information science. For a register of $N$ qubits, the full Hilbert space dimension grows exponentially as $2^N$, rendering generic state preparation and control infeasible without exploiting structure or symmetry. A particularly important and physically motivated restriction is to the fully symmetric subspace, spanned by the Dicke states, which are simultaneous eigenstates of collective spin $J=N/2$. Ensembles of Rydberg atoms interacting via electric dipoles in two-dimensional tweezer arrays form a promising platform for achieving such control. However, the finite range of dipole-dipole interactions poses a challenge to generating and controlling the Dicke manifold because the Hamiltonian incurs leakage from the computational subspace. To counteract this leakage, we perform quantum optimal control algorithms on a truncated Hilbert space according to our newly developed method of ``irrep distillation'' (IRD), which captures the process by which the symmetric subspace couples to leakage error-spaces, using only linear-scaling Hilbert dimension. We implement gradient ascent pulse engineering (GrAPE) on control schemes with little or no local addressing, to generate resourceful states like Greenberger-Horne-Zeilinger, Dicke, and extremal quantum states. We benchmark each scheme of IRD-GrAPE for its quantum speed limit (QSL), as well as exactly testing pulse fidelities on small system sizes and predicting fidelities using higher-order IRD on larger systems.

https://arxiv.org/abs/2603.12162 2026-03-12T00:00:00Z 2026-03-12T00:00:00Z Liang-Xu XieLui Zuccherelli de PaulaWeizhou CaiQing-Xuan JieLuyan SunChang-Ling ZouGuang-Can GuoZi-Jie ChenXu-Bo Zou

High-fidelity quantum operations are the cornerstone of fault-tolerant quantum computation. In open quantum systems, traditional optimal control only passively resists decoherence, leaving environment-induced uncertainty as a fundamental performance bottleneck. To overcome this, we propose a new optimal control framework with flag ancillas and the Flag-GRAPE algorithm, which can actively tailor the system's noise structure. Through embedding post-selection directly into the objective function, Flag-GRAPE correlates decoherence errors with the ancilla's unexpected state. Subsequent measurement and post-selection effectively expel this uncertainty, circumventing the fidelity bounds of traditional control. Numerical simulations in a superconducting quantum circuit demonstrate a $51\%$ reduction in infidelity compared to traditional closed-system pulses and also show that such enhancement is robust across broad noise regimes. Furthermore, by actively converting unstructured decoherence into heralded erasure errors, Flag-GRAPE is inherently compatible with quantum error correction. We demonstrate this by initializing a logical cat-code state, showing that the combination between Flag-GRAPE and QEC yields immediate state preparation enhancements. This new framework can reduce hardware overhead for fault-tolerant architectures and open up a practical path toward logical state preparation gain in near-term experiments.

https://arxiv.org/abs/2602.18363 2026-02-20T00:00:00Z 2026-02-20T00:00:00Z Vidisha AggarwalBoxi LiEloisa CuestasTommaso CalarcoRobert ZeierAlexei OurjoumtsevFelix Motzoi

Deterministic single photon emission from a Rydberg ensemble coupled to an optical cavity requires high-fidelity preparation of collective single excitations. In such a setup imperfect Rydberg blockade can lead to unwanted double excitations, which degrade photon indistinguishability. In this work we adapt the Derivative Removal by Adiabatic Gate (DRAG) technique, originally developed for superconducting qubits, to shape optical pulses that suppress double excitations in this atomic platform. By combining analytical modeling with numerical optimization, DRAG provides an improvement over conventional sine-squared pulses. Further optimization of pulse duration and atomic ensemble size identifies a parameter regime, distinct from that used in [Nature Photonics 17, 688 (2023)], that enhances the single excitation probability from the previous theoretical benchmark of 77% to 91.9%, approaching the fundamental limits set by decoherence in the system. Benchmarking against GRAPE (Gradient Ascent Pulse Engineering) confirms that DRAG operates close to the optimal control limit, while maintaining smooth, experimentally feasible pulse shapes. These results demonstrate the effectiveness and cross platform adaptability of DRAG for a high-fidelity single photon source.

https://arxiv.org/abs/2601.15586 2026-01-22T00:00:00Z 2026-01-22T00:00:00Z Xueting FangDoudou WangKun YuanJie DengQin LuoXiaochun DuanMinkang ZhouLushuai CaoZhongkun Hu

Atom interferometers require both high efficiency and robust performance in their mirror pulses under experimental inhomogeneities. In this work, we demonstrated that quantum optimal control designed mirror pulse significantly enhance interferometer performance by using novel adaptive sliced structure. Using gradient ascent pulse engineering (GRAPE), optimized mirror pulse for a Mach-Zehnder light-pulse atom interferometer was designed by discretizing the control into non-uniform phase slices. This design broadened the tolerence to experimentally relevant variations in detuning $[-Ω_0,Ω_0]$ and Rabi frequency $[0.1\timesΩ_0,1.9\timesΩ_0]$ ($Ω_0=2π\times25$ kHz), while maintaining high transfer efficiency even when the response-time delays up to 1.6 $\rm{μs}$. The optimized pulse was found to be robust to coupling inhomogeneity and velocity spread, offering a significant improvement in robustness over conventional pulse. The adaptive pulse slicing method provides a minimalist strategy that reduces experimental complexity while enhancing robustness and scalability, offering an innovative scheme for quantum optimal control in high precision atom interferometry.

https://arxiv.org/abs/2512.11673 2025-12-12T00:00:00Z 2025-12-12T00:00:00Z Ayumi KanamotoTakuya IsogawaShunsuke NishimuraHaidong YuanPaola Cappellaro

Designing optimal control for multiparameter quantum sensing is essential for approaching the ultimate precision limits. However, analytical solutions are generally available only for simple systems, while realistic scenarios often involve coupled qubits and time-dependent Hamiltonians. Here we numerically investigate optimal control of a two-qubit sensor-ancilla system coupled via an Ising term using Gradient Ascent Pulse Engineering (GRAPE) to minimize the objective function. By seeding the optimization recursively with solutions obtained for smaller coupling strengths and selecting a suitable initial guess, we achieve robust convergence and high precision across a wide range of interaction strengths and field configurations. The proposed approach offers a practical route toward high-sensitivity, robust multiparameter magnetometry and it is applicable to solid-state quantum sensors such as nitrogen-vacancy (NV) centers in realistic experimental settings.

https://arxiv.org/abs/2511.12799 2025-11-16T00:00:00Z 2026-02-13T00:00:00Z Rylan Malarchick

Numerical optimal control (GRAPE) can in principle discover pulse shapes that suppress all coherent gate error to machine precision. But when does that capability actually matter? We present a systematic comparison of Gaussian, DRAG, and GRAPE pulses for single-qubit gates on a three-level transmon model parameterized by IQM Garnet hardware ($T_1 = 37\,μ$s, $T_2 = 9.6\,μ$s,$α/2π= -200$ MHz), with the explicit goal of identifying the regimes where numerical optimization provides genuine practical advantage over analytical methods. Our central finding is that properly calibrated DRAG already operates near the decoherence floor. At 20 ns gate time, GRAPE eliminates all coherent error ($1 - F < 10^{-15}$), but DRAG achieves $1 - F = 4.9 \times 10^{-4}$ in coherent error alone,and $8.4 \times 10^{-4}$ under full decoherence -- only $1.2\times$ above GRAPE's decoherence-limited performance. More surprisingly,DRAG is \emph{more robust} than GRAPE to qubit frequency detuning (minimum fidelity 0.990 vs.\ 0.931 over $\pm 5$ MHz), the dominant calibration uncertainty in charge-noise-limited transmons. GRAPE retains superior amplitude robustness (minimum fidelity 0.994 vs.\ 0.990) and provides the only route to guaranteed zero coherent error, which matters at short gate times ($\lesssim 15$ ns) where perturbative corrections break down. These results lead to concrete calibration guidance: (1) properly calibrated DRAG is sufficient for gate times $\gtrsim 20$ ns on hardware with $T_2/T \gtrsim 500$, (2) GRAPE is necessary at short gate times or when targeting error rates well below the decoherence floor, and (3) robust optimal control incorporating frequency uncertainty should be used when detuning is the dominant noise source. We decompose the full error budget (coherent, $T_1$, $T_2$, control noise) and provide the open-source QubitPulseOpt framework for reproducing all results.

https://arxiv.org/abs/2511.01217 2025-11-03T00:00:00Z 2025-11-03T00:00:00Z Michael H. GoerzSebastian C. CarrascoAlastair MarshallVladimir S. Malinovsky

The GRAPE$.$jl package (https://github.com/JuliaQuantumControl/GRAPE.jl) implements Gradient Ascent Pulse Engineering, a widely used method of quantum optimal control. Its purpose is to find controls that steer a quantum system in a particular way. This is a prerequisite for next-generation quantum technology, such as quantum computing or quantum sensing. GRAPE$.$jl exploits the unique strengths of the Julia programming language to achieve both flexibility and numerical performance. It builds on the QuantumControl$.$jl framework.

https://arxiv.org/abs/2510.25996 2025-10-29T00:00:00Z 2026-01-20T00:00:00Z Riccardo AiudiJulien DespresRoberto MentaAshkan AbediGuido MenichettiVittorio GiovannettiMarco PoliniFrancesco Caravelli

We study the impact of static disorder on a globally-controlled superconducting quantum computing architecture based on a quasi-two-dimensional ladder geometry [R. Menta et al., Phys. Rev. Research 7, L012065 (2025)]. Specifically, we examine how fabrication-induced inhomogeneities in qubit resonant frequencies and coupling strengths affect quantum state propagation and the fidelity of fundamental quantum operations. Using numerical simulations, we quantify the degradation in performance due to disorder and identify single-qubit rotations, two-qubit entangling gates, and quantum information transport as particularly susceptible. To address this challenge, we rely on pulse optimization schemes, and, in particular, on the GRAPE (Gradient Ascent Pulse Engineering) algorithm. Our results demonstrate that, even for realistic levels of disorder, optimized pulse sequences can achieve high-fidelity operations, exceeding 99.9% for the three quantum operations, restoring reliable universal quantum logic and robust information flow. These findings highlight pulse optimization as a powerful strategy to enhance the resilience to disorder of solid-state globally-driven quantum computing platforms.

https://arxiv.org/abs/2508.16029 2025-08-22T00:00:00Z 2025-08-22T00:00:00Z Dylan LewisRoeland WiersemaSougato Bose

Designing multi-qubit quantum logic gates with experimental constraints is an important problem in quantum computing. Here, we develop a new quantum optimal control algorithm for finding unitary transformations with constraints on the Hamiltonian. The algorithm, geodesic pulse engineering (GEOPE), uses differential programming and geodesics on the Riemannian manifold of $\textrm{SU}(2^n)$ for $n$ qubits. We demonstrate significant improvements over the widely used gradient-based method, GRAPE, for designing multi-qubit quantum gates. Instead of a local gradient descent, the parameter updates of GEOPE are designed to follow the geodesic to the target unitary as closely as possible. We present numerical results that show that our algorithm converges significantly faster than GRAPE for a range of gates and can find solutions that are not accessible to GRAPE in a reasonable amount of time. The strength of the method is illustrtated with varied multi-qubit gates in 2D neutral Rydberg atom platforms.

https://arxiv.org/abs/2505.21203 2025-05-27T00:00:00Z 2026-06-24T00:00:00Z Denis JankovićJean-Gabriel HartmannPaul-Louis EtienneyKillian LutzYannick PrivatPaul-Antoine Hervieux

We introduce the MAGICARP algorithm, a numerical optimization method for quantum optimal control problems that combines the structure provided by Pontryagin's Maximum Principle (PMP) and the robustness of gradient ascent techniques, such as GRAPE. MAGICARP is formulated as a "shooting technique", aiming to determine the appropriate initial adjoint momentum to realize a target quantum gate. This method naturally incorporates time and energy optimal constraints through a PMP-informed pulse structure. We demonstrate MAGICARP's effectiveness through illustrative numerical examples, comparing its performance to GRAPE and highlighting its advantages in specific scenarios.

https://arxiv.org/abs/2505.17842 2025-05-23T00:00:00Z 2025-05-23T00:00:00Z Juan Carlos BoscheroNiels M. P. NeumannWard van der SchootFrank Phillipson

Distributed quantum computing (DQC) is crucial for high-volume quantum processing in the NISQ era. Many different technologies are utilized to implement a quantum computer, each with a different advantages and disadvantages. Various research is performed on how to implement DQC within a certain technology, but research on DQC between different technologies is rather limited. In this work, we contribute to this latter research line, by implementing the Quantum Phase Estimation algorithm on a superconducting-resonator-atom hybrid system. This system combines a Rydberg atom qubit, as well as a superconducting flux qubit system to perform the algorithm. In addition, Hamiltonian dynamics are studied to analyze noise sources, after which quantum optimal control (GRAPE) is used to optimize gate construction. The results show tradeoffs between GRAPE step size, iterations and noise level.

https://arxiv.org/abs/2504.04986 2025-04-07T00:00:00Z 2025-04-07T00:00:00Z Chris WhittyEugene Ya. ShermanXi ChenYue Ban

We consider subspace transfer within the time-dependent one-dimensional quantum transverse Ising model, with random nearest-neighbor interactions and a transverse field. We run numerical simulations using a variational approach and the numerical GRAPE (gradient-ascent pulse engineering) and dCRAB (dressed chopped random basis) quantum control algorithms.

https://arxiv.org/abs/2503.11616 2025-03-14T00:00:00Z 2025-03-14T00:00:00Z Maanav SrihariAnil Shaji

The Eigenstate Thermalization Hypothesis (ETH) is a framework for discussing thermal behavior originating from chaotic dynamics in isolated many-body quantum systems. The PXP model, where certain states do not thermalize, has been compared with the Sachdev-Ye Kitaev (SYK) model, which is believed to be fully thermalizing. A gate-based quantum circuit approach is utilized to simulate time evolution and compute the Out-of-Time-Ordered Correlator (OTOC), a measure of the extent of chaos. Considering restrictions on implementing SYK on gate-based hardware, a simplified model called Spin-XY4 (SXY4), which has a thermal behavior similar to SYK, is tested. An alternate method, which optimizes control on an analog quantum device with the GRAPE (GRadient Ascent Pulse Engineering) algorithm, is also utilized to simulate the SYK model.

https://arxiv.org/abs/2502.02198 2025-02-04T00:00:00Z 2025-03-22T00:00:00Z Uluk RasulovIlya Kuprov

Quantum optimal control methods, such as gradient ascent pulse engineering (GRAPE), are used for precise manipulation of quantum states. Many of those methods were pioneered in magnetic resonance spectroscopy where instrumental distortions are often negligible. However, that is not the case elsewhere: the usual jumble of cables, resonators, modulators, splitters, amplifiers, and filters can and would distort control signals. Those distortions may be non-linear, their inverse functions may be ill-defined and unstable; they may even vary from one day to the next, and across the sample. Here we introduce the response-aware gradient ascent pulse engineering (RAW-GRAPE) framework, which accounts for any cascade of differentiable distortions within the GRAPE optimisation loop, does not require filter function inversion, and produces control sequences that are resilient to user-specified distortion cascades with user-specified parameter ensembles. The framework is implemented into the optimal control module supplied with versions 2.10 and later of the open-source Spinach library; the user needs to provide function handles returning the actions by the distortions and, optionally, parameter ensembles for those actions.

https://arxiv.org/abs/2412.05856 2024-12-08T00:00:00Z 2025-10-31T00:00:00Z Ebrahim KhaleghianArash Fath LipaeiAbolfazl BahrampourMorteza NikaeenAlireza Bahrampour

In this paper, we introduce a neural network to generate optimal control pulses for general single-qubit quantum logic gates, within a Nuclear Magnetic Resonance (NMR) quantum computer. By utilizing a neural network, we can efficiently implement any single-qubit quantum logic gates within a reasonable time scale. The network is trained by control pulses generated by the GRAPE algorithm, all starting from the same initial point. After implementing the network, we tested it using numerical simulations. Also, we present the results of applying Neural Network-generated pulses to a three-qubit benchtop NMR system and compare them with simulation outcomes. These numerical and experimental results showcase the precision of the Neural Network-generated pulses in executing the desired dynamics. Ultimately, by developing the neural network using the GRAPE algorithm, we discover the function that maps any single-qubit gate to its corresponding pulse shape. This model enables the real-time generation of arbitrary single-qubit pulses. When combined with the GRAPE-generated pulse for the CNOT gate, it creates a comprehensive and effective set of universal gates. This set can efficiently implement any algorithm in noisy intermediate-scale quantum computers (NISQ era), thereby enhancing the capabilities of quantum optimal control in this domain. Additionally, this approach can be extended to other quantum computer platforms with similar Hamiltonians.

https://arxiv.org/abs/2411.06556 2024-11-10T00:00:00Z 2024-11-10T00:00:00Z Sebastiaan FauquenotAritra SarkarSebastian Feld

This research investigates the possibility of using quantum optimal control techniques to co-optimize the energetic cost and the process fidelity of a quantum unitary gate. The energetic cost is theoretically defined, and thereby, the gradient of the energetic cost for pulse engineering is derived. We empirically demonstrate the Pareto optimality in the trade-off between process fidelity and energetic cost. Thereafter, two novel numerical quantum optimal control approaches are proposed: (i) energy-optimized gradient ascent pulse engineering (EO-GRAPE) as an open-loop gradient-based method, and (ii) energy-optimized deep reinforcement learning for pulse engineering (EO-DRLPE) as a closed-loop method. The performance of both methods is probed in the presence of increasing noise. We find that the EO-GRAPE method performs better than the EO-DRLPE methods with and without a warm start for most experimental settings. Additionally, for one qubit unitary gate, we illustrate the correlation between the Bloch sphere path length and the energetic cost.

https://arxiv.org/abs/2410.11425 2024-10-15T00:00:00Z 2025-03-28T00:00:00Z Iñaki Iriarte-ZendoiaCarlos Munuera-JavaloyJorge Casanova

Nitrogen-vacancy (NV) center ensembles have the potential to improve a wide range of applications, including nuclear magnetic resonance spectroscopy at the microscale and nanoscale, wide-field magnetometry, and hyperpolarization of nuclear spins via the transfer of optically induced NV polarization to nearby nuclear spin clusters. These NV ensembles can be coherently manipulated with microwave cavities, that deliver strong and homogeneous drivings over large volumes. However, the pulse shaping for microwave cavities presents the added challenge that the external controls and intra-cavity field amplitudes are not identical, leading to adverse effects on the accuracy of operations on the NV ensemble. In this work, we introduce a method based on Gradient Ascent Pulse Engineering (GRAPE) to optimize external controls, resulting in robust pulses within the cavity while minimizing the effects of cavity ringings. The effectiveness of the method is demonstrated by designing both $π$ and $π/2$ pulses. These optimized controls are then integrated into a PulsePol sequence, where numerical simulations reveal a resilience to detunings five times larger than those tolerated by the sequence constructed using standard controls.

https://arxiv.org/abs/2410.01161 2024-10-02T00:00:00Z 2025-03-14T00:00:00Z Luke S. BakerSyed A. ShahAnatoly ZlotnikAndrei Piryatinski

We develop an optimal control algorithm for robust quantum gate preparation in open environments with the state of the quantum system represented using the Lindblad master equation. The algorithm is based on adaptive linearization and iterative quadratic programming to progressively shape the control signal into an optimal form. Robustness is achieved with exponential rates of convergence by introducing uncertain parameters into the master equation and expanding the parameterized state over the basis of Legendre polynomials. We prove that the proposed control algorithm reduces to GRadient Ascent Pulse Engineering (GRAPE) when the robustness portion of the algorithm is bypassed and signal restrictions are relaxed. The control algorithm is applied to prepare Controlled NOT and SWAP gates with high precision. Using only second order Legendre polynomials, the examples showcase unprecedented robustness to 100% parameter uncertainty in the interaction strength between the qubits, while simultaneously compensating for 20% uncertainty in signal intensity. The results could enable new capabilities for robust implementation of quantum gates and circuits subject to harsh environments and hardware limitations.