Pulse engineering via projection of response functions at infinite nonlinear order

• URL: http://arxiv.org/abs/2607.24725v1
• Date: Mon, 27 Jul 2026 17:55:57 GMT
• Title: Pulse engineering via projection of response functions at infinite nonlinear order
• Abstract summary: We propose an algorithm for optimal control problems in quantum computing.<n>The proposed algorithm efficiently generates high-fidelity control protocols for multi-qubit systems.<n>The results indicate faster convergence regarding iteration steps and computational time.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Optimal control problems arise in a wide range of scientific disciplines, but the corresponding optimization algorithms often display a strong dependence on hyperparameters that significantly influence performance and convergence. For the optimal implementation of quantum algorithms, these challenges are further amplified by high-dimensional control landscapes and the need for high-fidelity operations. Here, we propose an algorithm for optimal control problems in quantum computing to efficiently generate high-fidelity control protocols for multi-qubit systems in a hyperparameter and gradient free manner. The method, referred to as Pulse Engineering via Projection of response functions at infinite nonlinear order (PEPRino), leverages the framework of response theory to navigate the control landscape to find high-fidelity implementations. This is achieved by determining the control landscape via response functions to infinite order, efficiently evaluated by resummation in terms of the first and second order response function. To demonstrate the approach, we apply it to quantum systems consisting of two and three qubits for the optimal implementation of the Quantum Fourier Transform (QFT). We benchmark the proposed algorithm against the Chopped Random Basis (CRAB) algorithm utilizing the Nelder-Mead method, focusing on the 2-qubit scenario. The results indicate faster convergence regarding iteration steps and computational time, highlighting the advantages of our approach.

Related papers

• Analytical Series Expansion for Efficient Gradient Evaluation in Multi-Qubit Optimal Control [42.97938764966747]
  We present a unifying framework for gradient-based quantum optimal control.<n>For the case of unitary propagators, we derive a series expansion involving time-independent commutators and time-dependent coefficients.<n>The method is particularly suited for simulating optimal control tasks in quantum systems with local interactions.
  arXiv  Detail & Related papers  (2026-07-29T12:50:52Z)
• Diverse efficiency of observable optimization for four-level quantum systems with higher-order traps [46.08419608239004]
  We perform an analytical and numerical analysis of quantum landscapes for controlling special four-level quantum systems.<n>As a control goal, an observable optimization is considered.<n>We observe an interesting phenomenon with a diverse behavior of the optimization efficiency depending on the system Hamiltonian.
  arXiv  Detail & Related papers  (2026-07-01T17:54:33Z)
• Differentiable Quantum Computing for Large-scale Linear Control [26.118874431217165]
  We introduce an end-to-end quantum algorithm for linear-quadratic control with provable speedups. Our algorithm, based on a policy gradient method, incorporates a novel quantum subroutine for solving the matrix Lyapunov equation.
  arXiv  Detail & Related papers  (2024-11-03T00:54:33Z)
• Bayesian Parameterized Quantum Circuit Optimization (BPQCO): A task and hardware-dependent approach [49.89480853499917]
  Variational quantum algorithms (VQA) have emerged as a promising quantum alternative for solving optimization and machine learning problems. In this paper, we experimentally demonstrate the influence of the circuit design on the performance obtained for two classification problems. We also study the degradation of the obtained circuits in the presence of noise when simulating real quantum computers.
  arXiv  Detail & Related papers  (2024-04-17T11:00:12Z)
• Pulse engineering via projection of response functions [0.0]
  We present an iterative optimal control method of quantum systems, aimed at an implementation of a desired operation with optimal fidelity.<n>The update step of the method is based on the linear response of the fidelity to the control operators, and its projection onto the mode functions of the corresponding operator.<n>We demonstrate this approach, and compare it to the standard GRAPE algorithm, for the example of a quantum gate on two qubits, demonstrating a clear improvement in convergence and optimal fidelity of the generated protocol.
  arXiv  Detail & Related papers  (2024-04-16T11:02:49Z)
• Optimal control in large open quantum systems: the case of transmon readout and reset [44.99833362998488]
  We present a framework that combines the adjoint-state method together with reverse-time backpropagation to solve prohibitively large open-system quantum control problems.<n>We apply this framework to optimize two inherently dissipative operations in superconducting qubits.<n>Our results show that while standard pulses for dispersive readout are nearly optimal, adding a transmon drive during the protocol can yield 2x improvements in fidelity and duration.
  arXiv  Detail & Related papers  (2024-03-21T18:12:51Z)
• Efficient DCQO Algorithm within the Impulse Regime for Portfolio Optimization [41.94295877935867]
  We propose a faster digital quantum algorithm for portfolio optimization using the digitized-counterdiabatic quantum optimization (DCQO) paradigm. Our approach notably reduces the circuit depth requirement of the algorithm and enhances the solution accuracy, making it suitable for current quantum processors. We experimentally demonstrate the advantages of our protocol using up to 20 qubits on an IonQ trapped-ion quantum computer.
  arXiv  Detail & Related papers  (2023-08-29T17:53:08Z)
• GRAPE optimization for open quantum systems with time-dependent decoherence rates driven by coherent and incoherent controls [77.34726150561087]
  The GRadient Ascent Pulse Engineering (GRAPE) method is widely used for optimization in quantum control. We adopt GRAPE method for optimizing objective functionals for open quantum systems driven by both coherent and incoherent controls. The efficiency of the algorithm is demonstrated through numerical simulations for the state-to-state transition problem.
  arXiv  Detail & Related papers  (2023-07-17T13:37:18Z)
• Binary Control Pulse Optimization for Quantum Systems [2.887393074590696]
  Quantum control aims to manipulate quantum systems toward specific quantum states or desired operations. We apply different optimization algorithms and techniques to improve computational efficiency and solution quality. Our algorithms can obtain high-quality control results, as demonstrated by numerical studies on diverse quantum control examples.
  arXiv  Detail & Related papers  (2022-04-12T12:58:55Z)
• Recommender System Expedited Quantum Control Optimization [0.0]
  Quantum control optimization algorithms are routinely used to generate optimal quantum gates or efficient quantum state transfers. There are two main challenges in designing efficient optimization algorithms, namely overcoming the sensitivity to local optima and improving the computational speed. Here, we propose and demonstrate the use of a machine learning method, specifically the recommender system (RS), to deal with the latter challenge.
  arXiv  Detail & Related papers  (2022-01-29T10:25:41Z)
• Optimizing quantum control pulses with complex constraints and few variables through Tensorflow [0.0]
  We show how to apply optimal control algorithms on realistic quantum systems by incorporating multiple constraints into the gradient optimization. We test our algorithm by finding smooth control pulses to implement single-qubit and two-qubit gates for superconducting transmon qubits with always-on interaction. Our algorithm provides a promising optimal quantum control approach that is friendly to complex and optional physical constraints.
  arXiv  Detail & Related papers  (2021-10-11T14:59:28Z)
• Direct Optimal Control Approach to Laser-Driven Quantum Particle Dynamics [77.34726150561087]
  We propose direct optimal control as a robust and flexible alternative to indirect control theory. The method is illustrated for the case of laser-driven wavepacket dynamics in a bistable potential.
  arXiv  Detail & Related papers  (2020-10-08T07:59:29Z)
• Adaptive pruning-based optimization of parameterized quantum circuits [62.997667081978825]
  Variisy hybrid quantum-classical algorithms are powerful tools to maximize the use of Noisy Intermediate Scale Quantum devices. We propose a strategy for such ansatze used in variational quantum algorithms, which we call "Efficient Circuit Training" (PECT) Instead of optimizing all of the ansatz parameters at once, PECT launches a sequence of variational algorithms.
  arXiv  Detail & Related papers  (2020-10-01T18:14:11Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.