Truncated-Binary Encoding: Spectral Degree Reduction of Combinatorial Optimization Problems for Quantum Hardware
Tristan Zaborniak

TL;DR
This paper introduces truncated-binary encoding (TBE), a method to reduce spectral degree in combinatorial optimization problems for quantum hardware, balancing accuracy and hardware constraints.
Contribution
It proposes TBE as a modification of exact-binary encoding, providing bounds, conditions, and criteria for effective spectral degree reduction in quantum optimization.
Findings
TBE drops high-degree monomials to reduce circuit complexity.
Bounds on truncation error and conditions for preserving minima are established.
A criterion for selecting the cutoff degree based on Walsh transform decay is derived.
Abstract
Exact-binary encoding compiles a discrete cost function network (CFN) into a higher-order unconstrained binary optimization (HUBO) problem whose maximum monomial degree grows with the cardinalities of the underlying CFN variables. Given that quantum optimization hardware generally favours quadratic unconstrained binary optimization or low-degree HUBO Hamiltonians, high-cardinality CFNs therefore incur substantial overhead in the form of circuit depth, or ancilla qubits when degree-reduction techniques are employed. To ameliorate these issues, we propose \textit{truncated-binary encoding} (TBE): a modification of exact-binary encoding in which Ising-basis monomials exceeding a chosen cutoff are dropped from the encoded cost. We establish a tight bound on the truncation error in terms of the omitted couplings, derive sufficient conditions on the energy gap and on…
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