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From the 1 of 7 linked papers with an AI index.

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7 papers

quant-ph2026

Stabilizer Statistical Mechanics: A Framework for Efficient Quantification and Classification of Magic States

William E. Salazar, Gaurav Saxena, Jack S. Baker +2

The partition function is statistical mechanics' answer to an exponentially large spectrum, distilling it into a single analytic object whose temperature dependence resolves the fu…

quant-ph2026

Designing quantum technologies with a quantum computer

Juan Naranjo, Thi Ha Kyaw, Gaurav Saxena +2

The paper presents a quantum‑computer‑aided framework for simulating solid‑state spin systems, using advanced qudit‑to‑qubit mappings and a selected quantum Krylov fast‑forwarding…

quant-ph2026

Efficient Quantum Circuits for Coherent Conversion Between General First- and Second-Quantized Many-Body Representations

Jack S. Baker, Gaurav Saxena, Thi Ha Kyaw

Quantum simulation at fixed particle number admits two equivalent descriptions, a first-quantized (particle) representation and a second-quantized (occupation-number) representatio…

quant-ph2026

Physics-Inspired Extrapolation for efficient error mitigation and hardware certification

Pablo Díez-Valle, Gaurav Saxena, Jack S. Baker +2

Quantum error mitigation (QEM) is essential for the noisy intermediate-scale quantum era, and will remain relevant for early fault-tolerant quantum computers, where logical error r…

quant-ph2025

Error-Mitigation Enabled Multicomponent Quantum Simulations Beyond the Born-Oppenheimer Approximation

Delmar G. A. Cabral, Brandon Allen, Fabijan Pavošević +6

We introduce a multicomponent unitary coupled cluster framework for quantum simulations of molecular systems that incorporate both electronic and nuclear quantum effects beyond the…

quant-ph2025

Universal initial state preparation for first quantized quantum simulations

Jack S. Baker, Gaurav Saxena, Thi Ha Kyaw

Preparing symmetry-adapted initial states is a principal bottleneck in first-quantized quantum simulation. We present a universal approach that efficiently maps any polynomial-size…