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20242026
most citedTowards Arbitrary QUBO Optimization: Analysis of Classical and Quantum-Activated Feedforward Neural Networks

5 citations · 12 across the 14 of their papers we have counts for

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quant-ph2026

Belief Propagation-based Disentanglers for Tensor Network State Preparation

Tomasz Szołdra, Peter Schmelcher

We develop a quantum circuit synthesis method for preparing a class of tensor network states. The scheme applies to states tractable with belief propagation (BP), a tensor network…

quant-ph2026

Spin Textures and Eigenstate Evolution of Isospectrally Patterned Lattices

Peter Schmelcher

Isospectrally patterned lattices exhibit a composite band structure with a tunable ratio of localized versus delocalized eigenstates that is controlled by the underlying phase grad…

quant-ph2026

A Unified Local Light-shifts Encoding For Solving Optimization Problems on a Rydberg Annealer

Kapil Goswami, Peter Schmelcher

Combinatorial optimization problems play a central role in computer science with many real world applications. A number of relevant problems remain computationally difficult to sol…

quant-ph2026

High-fidelity non-adiabatic dark state gates for neutral atoms

Nader Mostaan, Kapil Goswami, Peter Schmelcher +1

Rydberg blockade gates are the most experimentally mature entangling operations in neutral-atom quantum processors, combining fast gate times with simple control, but their perform…

quant-ph2026

Scalable Preparation of Matrix Product States with Sequential and Brick Wall Quantum Circuits

Tomasz Szołdra, Rick Mukherjee, Peter Schmelcher

Preparing arbitrary quantum states requires exponential resources. Matrix Product States (MPS) admit more efficient constructions, particularly when accuracy is traded for circuit…