Quantum State Engineering Under Multiple Expectation-Value Constraints

• URL: http://arxiv.org/abs/2605.02367v1
• Date: Mon, 04 May 2026 09:11:28 GMT
• Title: Quantum State Engineering Under Multiple Expectation-Value Constraints
• Abstract summary: This work introduces a formulation of quantum state engineering termed expectation-value targeting.<n>It subsumes standard ground-state preparation problems in quantum chemistry and many-body physics.<n>We introduce QUEST, a framework purpose-built for expectation-value targeting.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: This work introduces a formulation of quantum state engineering termed expectation-value targeting: the task of preparing a pure state whose expectation values with respect to a prescribed set of observables attain specified targets. This formulation subsumes standard ground-state preparation problems in quantum chemistry and many-body physics, while extending beyond variational energy minimization to multi-constraint state synthesis. The problem amounts to solving a system of nonlinear constraints on an exponentially large state space, for which no general efficient classical approaches are known. Variational quantum algorithms tackle this problem by restricting the search to a low-dimensional parameter space, and relying on classical optimization techniques for solutions. However, these approaches can become extremely ineffective for the present problem, where competing constraints can induce rugged landscapes and vanishing gradients (barren plateaus). Adaptive variational methods, in which the ansatz is constructed iteratively from a pool of candidate operators rather than fixed in advance, have been developed primarily for ground-state preparation. However, we show that the present problem also admits a similar construction. We introduce QUEST (Quantum Unitary Engineering of States to Target), a framework purpose-built for expectation-value targeting, in which the engineered state is constructed as a depth-adaptive sequence of Pauli rotations, with each rotation chosen to descend a sum-of-squared-residuals cost. QUEST provides a constructive route to expectation-value targeting, building the engineered state one Pauli rotation at a time, and establishes adaptive synthesis as a primitive for state preparation under multiple, potentially inconsistent target constraints.

Related papers

• Generalized Neural Operator for Parametric and Boundary-Value Problems [39.8019405552335]
  Current deep learning approaches largely face a structural trade-off between condition-agnostic deployment and physical fidelity.<n>Our framework demonstrates the theoretical benefits of explicitly conditioning on PDE parameters and boundary conditions.
  arXiv  Detail & Related papers  (2026-07-24T03:10:32Z)
• A Variational Surrogate Approach to Finite-Horizon Quantum Control via Hardware-Efficient Ansatz [2.033424698590539]
  We present a variational quantum framework for finite-horizon quantum control based on hardware-efficient anstze.<n>The objective is to steer a quantum system from a given initial state to a desired target state over a fixed time horizon by minimizing a terminal cost defined in terms of state fidelity.
  arXiv  Detail & Related papers  (2026-07-14T14:17:02Z)
• Scalable Ground-State Certification of Quantum Spin Systems via Structured Noncommutative Polynomial Optimization [3.4234084547821477]
  A fundamental challenge in quantum physics is determining the ground-state properties of many-body systems.<n>In this article, we demonstrate that leveraging the inherent structures of the system can significantly mitigate these scalability challenges.
  arXiv  Detail & Related papers  (2026-04-02T03:00:01Z)
• SpinGQE: A Generative Quantum Eigensolver for Spin Hamiltonians [42.007194397302825]
  Ground state search is central to quantum computing.<n>We present SpinGQE, an extension of the Generative Quantum Eigensolver framework to spin Hamiltonians.<n>We employ a transformer-based decoder to learn over quantum circuits that produce low-energy states.
  arXiv  Detail & Related papers  (2026-03-25T13:38:15Z)
• Constraint-Aware Quantum Optimization via Hamming Weight Operators [1.1463843149836523]
  Constrained optimization with strict linear constraints underpins applications in drug discovery, power grids, logistics, and finance.<n>We introduce Hamming Weight Operators, a new class of constraint-aware operators that confine quantum evolution strictly within the feasible subspace.<n>We validate our approach on benchmark tasks from both finance and high-energy physics, specifically portfolio optimization and two-jet clustering with energy balance.
  arXiv  Detail & Related papers  (2026-01-04T12:58:04Z)
• Variational Quantum Subspace Construction via Symmetry-Preserving Cost Functions [36.94429692322632]
  We propose a variational strategy based on symmetry-preserving cost functions to iteratively construct a reduced subspace for extraction of low-lying energy states.<n>As a proof of concept, we test the proposed algorithms on H4 chain and ring, targeting both the ground-state energy and the charge gap.
  arXiv  Detail & Related papers  (2024-11-25T20:33:47Z)
• Compact fermionic quantum state preparation with a natural-orbitalizing variational quantum eigensolving scheme [0.0]
  Near-term quantum state preparation is typically realized by means of the variational quantum eigensolver (VQE) algorithm. We present a refined VQE scheme that consists in topping VQE with state-informed updates of the elementary fermionic modes. For a fixed circuit structure, the method is shown to enhance the capabilities of the circuit to reach a state close to the target state without incurring too much overhead from shot noise.
  arXiv  Detail & Related papers  (2024-06-20T10:23:28Z)
• Unleashed from Constrained Optimization: Quantum Computing for Quantum Chemistry Employing Generator Coordinate Inspired Method [9.95432381301196]
  We introduce an adaptive scheme that robustly constructs the many-body basis sets from a pool of the Unitary Coupled Cluster excitation generators.<n>This scheme supports the development of a hierarchical ADAPT quantum-classical strategy, enabling a balanced interplay between subspace expansion and ansatz optimization.
  arXiv  Detail & Related papers  (2023-12-12T19:36:51Z)
• Multiobjective variational quantum optimization for constrained problems: an application to Cash Management [45.82374977939355]
  We introduce a new method for solving optimization problems with challenging constraints using variational quantum algorithms. We test our proposal on a real-world problem with great relevance in finance: the Cash Management problem. Our empirical results show a significant improvement in terms of the cost of the achieved solutions, but especially in the avoidance of local minima.
  arXiv  Detail & Related papers  (2023-02-08T17:09:20Z)
• Randomized adaptive quantum state preparation [0.0]
  A cost function is minimized to prepare a desired quantum state through an adaptively constructed quantum circuit. We provide theoretical arguments and numerical evidence that convergence to the target state can be achieved for almost all initial states.
  arXiv  Detail & Related papers  (2023-01-10T20:32:49Z)
• A Quantum Optimal Control Problem with State Constrained Preserving Coherence [68.8204255655161]
  We consider a three-level $Lambda$-type atom subjected to Markovian decoherence characterized by non-unital decoherence channels. We formulate the quantum optimal control problem with state constraints where the decoherence level remains within a pre-defined bound.
  arXiv  Detail & Related papers  (2022-03-24T21:31:34Z)
• Dynamical learning of a photonics quantum-state engineering process [48.7576911714538]
  Experimentally engineering high-dimensional quantum states is a crucial task for several quantum information protocols. We implement an automated adaptive optimization protocol to engineer photonic Orbital Angular Momentum (OAM) states. This approach represents a powerful tool for automated optimizations of noisy experimental tasks for quantum information protocols and technologies.
  arXiv  Detail & Related papers  (2022-01-14T19:24:31Z)

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.