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Equation 1 · Variational Evolution: How Quantum Computers Learn Their Answers

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θ\theta

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θ\theta

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This is the variational algorithm, and by 2026 it is not one technique among several — it is close to the entire working repertoire of near-term quantum hardware. The archetype is the variational quantum eigensolver (VQE), first demonstrated in 2014 on a photonic quantum processor, where Alberto Peruzzo and coauthors used the loop to compute the ground-state molecular energy of the helium hydride cation, HeH+, to within chemical accuracy [ 1 ] . The demonstration used only a small photonic chip, but its structural claim was the important part: instead of demanding the long coherent evolution that quantum phase estimation requires, VQE splits the work. The quantum processor’s only job is to…
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This is the variational algorithm, and by 2026 it is not one technique among several — it is close to the entire working repertoire of near-term quantum hardware. The archetype is the variational quantum eigensolver (VQE), first demonstrated in 2014 on a photonic quantum processor, where Alberto Peruzzo and coauthors used the loop to compute the ground-state molecular energy of the helium hydride cation, HeH+, to within chemical accuracy [ 1 ] . The demonstration used only a small photonic chip, but its structural claim was the important part: instead of demanding the long coherent evolution that quantum phase estimation requires, VQE splits the work. The quantum processor’s only job is to prepare a trial state, described by a vector of adjustable parameters θ\theta , and report the expectation value of the molecule’s Hamiltonian in that state,

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