Reducing Computational Complexity of Quantum Correlations
Titas Chanda, Tamoghna Das, Debasis Sadhukhan, Amit Kumar Pal, Aditi, Sen De, and Ujjwal Sen

TL;DR
This paper introduces a constrained optimization approach to efficiently compute quantum correlation measures like discord and work deficit, reducing computational resources while maintaining low error across various quantum states and systems.
Contribution
It develops a method for calculating quantum correlations using restricted local measurements, enabling closed-form solutions and faster computations in higher-dimensional systems.
Findings
Constrained optimization reduces computational error with increasing measurement set size.
Quantum work deficit optimization generally requires more resources than quantum discord.
Method applies effectively to quantum spin models and bound entangled states.
Abstract
We address the issue of reducing the resource required to compute information-theoretic quantum correlation measures like quantum discord and quantum work deficit in two qubits and higher dimensional systems. We show that determination of the quantum correlation measure is possible even if we utilize a restricted set of local measurements. We find that the determination allows us to obtain a closed form of quantum discord and quantum work deficit for several classes of states, with a low error. We show that the computational error caused by the constraint over the complete set of local measurements reduces fast with an increase in the size of the restricted set, implying usefulness of constrained optimization, especially with the increase of dimensions. We perform quantitative analysis to investigate how the error scales with the system size, taking into account a set of plausible…
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