Equivalence of maximal and generic reachability for non-universal Variational Quantum Circuits
quant-ph
Submitted: 2026-09-22
Updated: 2026-09-22
Comments: 13 pages, 3 figures, 3 tables
License: http://creativecommons.org/licenses/by/4.0/
The gist: Employing problem-specific non-universal Variational Quantum Circuits aligned with a suitable state preparation has become a standard approach to counter the difficulty in training universal ansätze.
Terminology
Abstract
Employing problem-specific non-universal Variational Quantum Circuits aligned with a suitable state preparation has become a standard approach to counter the difficulty in training universal ansätze. However, due to their non-universality, diagnosing their reachability and trainability remains reference-state-specific. In this work, we establish the equivalence of maximal reachability and generic reachability over arbitrary reference states as a consequence of the principal orbit-type theorem. Thereafter, assuming that the global minimum of the cost function is achieved on a subset that can be described as the image of a smooth function, we derive necessary and sufficient conditions for non-zero probability of reachability under generically sampled reference states. Furthermore, when the solution set is assumed to be realised through a real analytic map that embeds a solution manifold, we show that local surjectivity is generically obtained on the entire solution manifold if it is attained at a single point. As a practical design rule, the need for local surjectivity automatically translates to a necessary dimensional criterion: reachability requires the target set's topological dimension to be at least as large as the co-dimension of the generic orbit. Numerical simulations show that finite-depth optimisation consistently fails when the dimensional obstruction applies, while unobstructed cases show improved convergence.
Sources
- Training variational quantum algorithms is NP-hard
- Beyond Barren Plateaus: Quantum Variational Algorithms Are Swamped With Traps
- Barren Plateaus in Variational Quantum Computing
- Cost Function Dependent Barren Plateaus in Shallow Parametrized Quantum Circuits
- Reachability Deficits in Quantum Approximate Optimization
- Capacity and quantum geometry of parametrized quantum circuits
- Ground-state reachability for variational quantum eigensolvers: a Rydberg-atom case study
- Reachability Constraints in Variational Quantum Circuits: Optimization within Polynomial Group Module
- Lie-algebraic classical simulations for quantum computing
- Symmetry Principles in Quantum Systems Theory
- Subspace Controllability and Clebsch-Gordan Decomposition of Symmetric Quantum Networks
- Exploring entanglement and optimization within the Hamiltonian Variational Ansatz
- Exploiting symmetry in variational quantum machine learning
- Building spatial symmetries into parameterized quantum circuits for faster training
- PennyLane: Automatic differentiation of hybrid quantum-classical computations
- Trainability and Expressivity of Hamming-Weight Preserving Quantum Circuits for Machine Learning
- On the gauge orbit space stratification (a review)
- Classification of dynamical Lie algebras for translation-invariant 2-local spin systems in one dimension
- On the dynamical Lie algebras of quantum approximate optimization algorithms
- Full classification of Pauli Lie algebras
Related papers
- Reconquering Bell sampling on qudits: stabilizer learning and testing, quantum pseudorandomness bounds, and more
- Encrypted clones can leak: Classification of informative subsets in Quantum Encrypted Cloning
- Polynomial-time classical and quantum simulation of quantum impurity models
- A quasiparticle-protected superconducting qubit
- Theory of quantum-enhanced interferometry with general Markovian light sources
- A convergent hierarchy of spectral gap certificates for qubit Hamiltonians