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Paper 1
Code switching revisited: Low-overhead magic state preparation using color codes
Lucas Daguerre, Isaac H. Kim
- Year
- 2024
- Journal
- arXiv preprint
- DOI
- arXiv:2410.07327
- arXiv
- 2410.07327
We propose a protocol to prepare a high-fidelity magic state on a two-dimensional (2D) color code using a three-dimensional (3D) color code. Our method modifies the known code switching protocol with (i) a recently discovered transversal gate between the 2D and the 3D code and (ii) a judicious use of flag-based postselection. We numerically demonstrate that these modifications lead to a significant improvement in the fidelity of the magic state. For instance, subjected to a uniform circuit-level noise of $10^{-3}$ (excluding idling noise), our code switching protocol yields a magic state encoded in the distance-$3$ 2D color code with a logical infidelity of $4.6\times 10^{-5}\pm 1.6 \times 10^{-5}$ (quantified by an error-corrected logical state tomography) with an $84\%$ of acceptance rate. Used in conjunction with a postselection approach, extrapolation from a polynomial fit suggests a fidelity improvement to $5.1 \times 10^{-7}$ for the same code. Our protocol is aimed for architectures that allow nonlocal connectivity and should be readily implementable in near-term devices. Finally, we also present a simulation technique akin to an extended stabilizer simulator which effectively incorporates the non-Clifford $T$-gate, that permits to simulate the protocol without resorting to a resource intensive state-vector simulation.
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Quantum Simulation of Nonlinear Dynamical Systems Using Repeated Measurement
Joseph Andress, Alexander Engel, Yuan Shi, Scott Parker
- Year
- 2024
- Journal
- arXiv preprint
- DOI
- arXiv:2410.03838
- arXiv
- 2410.03838
We present a quantum algorithm based on repeated measurement to solve initial-value problems for nonlinear ordinary differential equations (ODEs), which may be generated from partial differential equations in plasma physics. We map a dynamical system to a Hamiltonian form, where the Hamiltonian matrix is a function of dynamical variables. To advance in time, we measure expectation values from the previous time step, and evaluate the Hamiltonian function classically, which introduces stochasticity into the dynamics. We then perform standard quantum Hamiltonian simulation over a short time, using the evaluated constant Hamiltonian matrix. This approach requires evolving an ensemble of quantum states, which are consumed each step to measure required observables. We apply this approach to the classic logistic and Lorenz systems, in both integrable and chaotic regimes. Out analysis shows that solutions' accuracy is influenced by both the stochastic sampling rate and the nature of the dynamical system.
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