A Unified Local Light-shifts Encoding For Solving Optimization Problems on a Rydberg Annealer
Kapil Goswami, Peter Schmelcher

TL;DR
This paper introduces a unified quantum encoding framework for solving various NP-hard optimization problems on a Rydberg quantum platform, enhancing scalability and resource efficiency.
Contribution
It presents a direct mapping of QUBO problems onto Rydberg systems with optimized annealing protocols, broadening application scope and improving scalability.
Findings
Demonstrated a direct mapping from QUBO to Rydberg platform
Reduced resource overhead through distance-dependent interactions
Introduced a generalized hardness parameter for problem complexity
Abstract
Combinatorial optimization problems play a central role in computer science with many real world applications. A number of relevant problems remain computationally difficult to solve as they lie in the NP-hard complexity class. We present a unified framework for solving such optimization problems represented in the quadratic unconstrained binary optimization (QUBO) formalism, namely two-SAT, XOR-SAT, mixed-two-XOR-SAT, set packing, quadratic assignment, binary clustering, and protein folding, by expanding the domain of applications of \textit{PRR, 6(2), 023031}. A direct mapping from the QUBO form of these problems onto the Rydberg quantum platform is demonstrated as our first step. This mapping to the Rydberg system depends on distance-dependent long-range interactions and configurable local detuning, thus reducing resource overhead and improving scalability. Following-up on the…
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