arXiv subjects

Rick Huang

Publications and source records attributed to Rick Huang.

3 recordsLinked to original sources

arXiv2025

Quantum Gambling: Best-Arm Strategies for Generator Selection in Adaptive Variational Algorithms

Adaptive variational algorithms suffer from prohibitively high measurement costs during the generator selection step, since energy gradients must be estimated for a large operator pool. This scaling bottleneck limits their applicability to larger molecular systems on near-term quantum devices. We address this challenge by reformulating generator selection as a Best Arm Identification (BAI) problem, where the goal is to identify the generator with the largest energy gradient using as few measurements as possible. To solve it, we employ the Successive Elimination algorithm, which adaptively allocates measurements and discards unpromising candidates early. Numerical experiments on molecular systems demonstrate that this approach substantially reduces the number of measurements required while preserving ground-state energy accuracy. By cutting measurement overhead without sacrificing performance, our method makes adaptive variational algorithms more practical for near-term quantum simulations.

quant-ph↗

arXiv2025

Quantum Seniority-based Subspace Expansion: Linear Combinations of Short-Circuit Unitary Transformations for the Electronic Structure Problem

Quantum SENiority-based Subspace Expansion (Q-SENSE) is a hybrid quantum-classical algorithm that interpolates between the Variational Quantum Eigensolver (VQE) and Configuration Interaction (CI) methods. It constructs Hamiltonian matrix elements on a quantum device and solves the resulting eigenvalue problem classically. Unlike other expansion-based methods -- such as Quantum Subspace Expansion (QSE), Quantum Krylov Algorithms, and the Non-Orthogonal Quantum Eigensolver -- Q-SENSE introduces seniority operators as artificial symmetries to construct orthogonal basis states. This seniority-symmetry-based approach reduces one of the primary limitations of VQE on near-term quantum hardware -- circuit depth -- at the cost of measuring additional matrix elements. The artificial symmetries also reduce the number of Hamiltonian terms that must be measured, as only a small fraction of the terms couple basis states in different seniority subspaces. With all these merits, Q-SENSE offers a scalable and resource-efficient route to quantum advantage on near-term quantum devices and in the early fault-tolerant regime.

quant-ph↗

arXiv2025

Planted Solutions in Quantum Chemistry: Generating Non-Trivial Hamiltonians with Known Ground States

Generating large, non-trivial quantum chemistry test problems with known ground-state solutions remains a core challenge for benchmarking electronic structure methods. Inspired by planted-solution techniques from combinatorial optimization, we introduce four classes of Hamiltonians with embedded, retrievable ground states. These Hamiltonians mimic realistic electronic structure problems, support adjustable complexity, and are derived from reference systems. Crucially, their ground-state energies can be computed exactly, provided the construction parameters are known. To obscure this structure and control perceived complexity, we introduce techniques such as killer operators, balance operators, and random orbital rotations. We showcase this framework using examples based on homogeneous catalysts of industrial relevance and validate tunable difficulty through density matrix renormalization group (DMRG) convergence behavior. Beyond enabling scalable, ground-truth benchmark generation, our approach offers a controlled setting to explore the limitations of electronic structure methods and investigate how Hamiltonian structure influences ground state solution difficulty.

quant-ph↗