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Yuga Kodama

Publications and source records attributed to Yuga Kodama.

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Computing with many encoded logical qubits beyond break-even

High-rate quantum error correcting (QEC) codes encode many logical qubits in a given number of physical qubits, making them promising candidates for quantum computation. Implementing high-rate codes at a scale that both frustrates classical computing and improves performance by encoding requires both high fidelity gates and long-range qubit connectivity -- both of which are offered by trapped-ion quantum computers. Here, we demonstrate computations that outperform their unencoded counterparts in the high-rate $[[ k+2,\, k,\, 2 ]]$ iceberg quantum error detecting (QED) and $[[ (k_2 + 2)(k_1 + 2),\, k_2k_1,\, 4 ]]$ two-level concatenated iceberg QEC codes, using the 98-qubit Quantinuum Helios trapped-ion quantum processor. Utilizing new gadgets for encoded operations, we realize this "beyond break-even" performance with reasonable postselection rates across a range of fault-tolerant (FT) and partially-fault-tolerant (pFT) component and application benchmarks with between $48$ and $94$ logical qubits. These benchmarks include FT state preparation and measurement, QEC cycle benchmarking, logical gate benchmarking, GHZ state preparation, and a pFT quantum simulation of the three-dimensional $XY$ model of quantum magnetism. Additionally, we illustrate that postselection rates can be suppressed by increasing the code distance via concatenation. Our results represent state-of-the-art logical component and state fidelities and provide evidence that high-rate QED/QEC codes are viable on contemporary quantum computers for near-term beyond-classical-scale computation.

quant-ph

Quantum coherent control of linear and nonlinear thermoelectricity on graphene nanostructure heat engines

We theoretically show how structural modifications and controlling quantum coherency can enhance linear and nonlinear thermoelectric performance in graphene nanostructure heat engines. Although graphene has emerged as a promising material for a nanoscale heat engine due to its high coherency and tunable electronic properties, its large lattice thermal transport often limits its thermal efficiency. Using the density-functional tight-binding method, we demonstrate that one can suppress lattice thermal transport degrading the thermal efficiency by deliberately manipulating the junction's bending angle at low temperatures. We further argue that applying an optimal local gate voltage unleashes its great potential in achieving excellent efficiency and reasonably high output power that persist in the fully nonlinear regime.

cond-mat.mes-hall