Projector Quantum Variational Ansatz

• URL: http://arxiv.org/abs/2606.07084v1
• Date: Fri, 05 Jun 2026 09:23:56 GMT
• Title: Projector Quantum Variational Ansatz
• Abstract summary: Variational Quantum Eigensolver (VQE) algorithms are used to compute the ground state of a problem Hamiltonian.<n>In this work, we propose a VQE ansatz whose structure is more similar to that of an FTQC algorithm.<n>Our experimental results show that this first proposal of Projector Variational Ansatz converges with a shallower ansatz than the usual ADAPT-VQE.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Quantum computing offers several algorithms to compute the ground state of a problem Hamiltonian. The most desirable algorithms belong to the Fault Tolerant QuantumComputing (FTQC) regime, such as quantum algorithms with repetitive structure like Quantum Phase Estimation (QPE) and Quantum Signal Processing (QSP). However, in the Noisy In-termediate Scale Quantum (NISQ) regime, the most realistic approaches involve Variational Quantum Eigensolver (VQE) algorithms and their variants. VQE is an algorithm that searches for a parametrized unitary matrix called an ansatz whose purposeis to transform an easily prepared initial state into the groundstate of a given Hamiltonian. Adaptive Derivative-AssembledPseudo-Trotter (ADAPT)-VQE is a variant of VQE that im-proves this approach by constructing the ansatz iteratively so that the associated quantum circuit is as shallow as possible. A major difference between FTQC (i.e. not variational) algorithms and VQE is that FTQC algorithms do not construct a state transitiondirectly. Instead, they construct a projector that identifies the ground state using ancillary qubits that flag the good solution. The desired state is then obtained via amplitude amplification orpost-selection. In this work, we propose a VQE ansatz whose structure is more similar to that of an FTQC algorithm. Depending on its parametrization, this ansatz can be equivalent to either an Intermediate Scale Quantum (ISQ)-QSP or to an ADAPT-VQE quantum circuit structure. Our experimental results show that this first proposal of Projector Variational Ansatz (PVA) converges with a shallower ansatz than the usual ADAPT-VQE.

Related papers

• Excited-CAFQA: A classical simulation bootstrap for the variational estimation of molecular excited states [0.0]
  Variational Quantum Algorithms (VQAs) are iterative algorithms suited to implementation on current-era quantum devices.<n>CAFQA protocol runs a discrete search through a classically simulatable subset of the entire state space.<n> Excited-CAFQA achieves 90 to 99+% accuracy across a variety of bond lengths and excited states for H2 and HeH+ molecular systems.
  arXiv  Detail & Related papers  (2025-09-24T22:01:23Z)
• RhoDARTS: Differentiable Quantum Architecture Search with Density Matrix Simulations [44.13836547616739]
  Variational Quantum Algorithms (VQAs) are a promising approach to leverage Noisy Intermediate-Scale Quantum (NISQ) computers.<n> choosing optimal quantum circuits that efficiently solve a given VQA problem is a non-trivial task.<n>Quantum Architecture Search (QAS) algorithms enable automatic generation of quantum circuits tailored to the provided problem.
  arXiv  Detail & Related papers  (2025-06-04T08:30:35Z)
• 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)
• Benchmarking Variational Quantum Eigensolvers for Entanglement Detection in Many-Body Hamiltonian Ground States [37.69303106863453]
  Variational quantum algorithms (VQAs) have emerged in recent years as a promise to obtain quantum advantage. We use a specific class of VQA named variational quantum eigensolvers (VQEs) to benchmark them at entanglement witnessing and entangled ground state detection. Quantum circuits whose structure is inspired by the Hamiltonian interactions presented better results on cost function estimation than problem-agnostic circuits.
  arXiv  Detail & Related papers  (2024-07-05T12:06:40Z)
• Warm-Starting the VQE with Approximate Complex Amplitude Encoding [0.26217304977339473]
  The Variational Quantum Eigensolver (VQE) is a quantum algorithm to determine the ground state of quantum-mechanical systems. We propose a warm-starting technique, that utilizes an approximation to generate beneficial initial parameter values for the VQE. Such warm-starts open the path to fruitful combinations of classical approximation algorithms and quantum algorithms.
  arXiv  Detail & Related papers  (2024-02-27T10:15:25Z)
• Quantum Subroutine for Variance Estimation: Algorithmic Design and Applications [80.04533958880862]
  Quantum computing sets the foundation for new ways of designing algorithms. New challenges arise concerning which field quantum speedup can be achieved. Looking for the design of quantum subroutines that are more efficient than their classical counterpart poses solid pillars to new powerful quantum algorithms.
  arXiv  Detail & Related papers  (2024-02-26T09:32:07Z)
• Quantum Annealing for Single Image Super-Resolution [86.69338893753886]
  We propose a quantum computing-based algorithm to solve the single image super-resolution (SISR) problem. The proposed AQC-based algorithm is demonstrated to achieve improved speed-up over a classical analog while maintaining comparable SISR accuracy.
  arXiv  Detail & Related papers  (2023-04-18T11:57:15Z)
• QNEAT: Natural Evolution of Variational Quantum Circuit Architecture [95.29334926638462]
  We focus on variational quantum circuits (VQC), which emerged as the most promising candidates for the quantum counterpart of neural networks. Although showing promising results, VQCs can be hard to train because of different issues, e.g., barren plateau, periodicity of the weights, or choice of architecture. We propose a gradient-free algorithm inspired by natural evolution to optimize both the weights and the architecture of the VQC.
  arXiv  Detail & Related papers  (2023-04-14T08:03:20Z)
• Study of Adaptative Derivative-Assemble Pseudo-Trotter Ansatzes in VQE through qiskit API [0.0]
  Variational Quantum Algorithms (VQAs) were designed to answer the problem of Quantum Phase Estimation Algorithm. ADAPT-VQE determines a quasi-optimal ansatz with a minimal number of parameters. We will compare all of these algorithms on different criterions such as the number of parameters, the accuracy or the number of CNOT gate used on H2 and LiH molecules.
  arXiv  Detail & Related papers  (2022-10-25T16:53:14Z)
• A prescreening method for variational quantum state eigensolver [0.0]
  We propose a method to derive all of the states with high accuracy by using the Variational Quantum State Eigensolver (VQSE) and Subspace-Search VQE (SSVQE) methods. We show that by using the VQSE and the SSVQE prescreening methods, we can derive all of the hydrogen molecules states correctly.
  arXiv  Detail & Related papers  (2021-11-03T18:13:33Z)
• Q-Match: Iterative Shape Matching via Quantum Annealing [64.74942589569596]
  Finding shape correspondences can be formulated as an NP-hard quadratic assignment problem (QAP) This paper proposes Q-Match, a new iterative quantum method for QAPs inspired by the alpha-expansion algorithm. Q-Match can be applied for shape matching problems iteratively, on a subset of well-chosen correspondences, allowing us to scale to real-world problems.
  arXiv  Detail & Related papers  (2021-05-06T17:59:38Z)
• Improving the variational quantum eigensolver using variational adiabatic quantum computing [0.0]
  variational quantumsampling (VAQC) is a hybrid quantum-classical algorithm for finding a Hamiltonian minimum eigenvalue of a quantum circuit. We show that VAQC can provide more accurate solutions than "plain" VQE, for the evaluation.
  arXiv  Detail & Related papers  (2021-02-04T20:25:50Z)

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.