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A universal qudit quantum processor with trapped ions
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Today's quantum computers operate with a binary encoding that is the quantum analog of classical bits. Yet, the underlying quantum hardware consists of information carriers that are not necessarily binary, but typically exhibit a rich multilevel structure, which is artificially restricted to two dimensions. A wide range of applications from quantum chemistry to quantum simulation, on the other hand, would benefit from access to higher-dimensional Hilbert spaces, which conventional quantum computers can only emulate. Here we demonstrate a universal qudit quantum processor using trapped ions with a local Hilbert space dimension of up to 7. With a performance similar to qubit quantum processors, this approach enables native simulation of high-dimensional quantum systems, as well as more efficient implementation of qubit-based algorithms.
Forward citations
Cited by 5 Pith papers
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Measurement-based simulation of lattice gauge theory dynamics with adaptive quantum circuits on a trapped-ion processor
A trapped-ion experiment demonstrates adaptive measurement-based simulation of real-time Z2 lattice gauge theory dynamics, with one-form-symmetry syndromes used for postselection.
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Maximal stabilizer Rényi entropy for two-qutrit states is ln(81/17), achieved at 18 degenerate maxima; a general prime-d formula ln[d⁴/(2d²−1)] is conjectured and verified for d=2,3,5.
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Non-Abelian dynamics on a cube: improving quantum compilation through qudit-based simulations
A qudit-based circuit for SU(2) lattice gauge theory on a cube, with improved decompositions for uniformly-controlled rotations and new elementary-gate resource estimates.
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Fault-Tolerant Resource Comparison of Qudit and Qubit Encodings for Diagonal Quadratic Operators
The paper derives explicit finite-d break-even synthesis costs for qudit vs. qubit encodings of diagonal quadratic operators in product-formula and LCU simulations, identifying low-d regions where qudits yield savings.
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Arbitrary state preparation in quantum harmonic oscillators using neural networks
A neural network predicts pulse sequences that prepare arbitrary qubit, qutrit, and qudit states in a harmonic oscillator, reaching 99.9% average fidelity for qubits and 97% for qutrits in simulation.
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