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- W4386472945 abstract "The new quantum era is expected to have an unprecedented social impact, enabling the research of tomorrow in several pivotal fields. These perspectives require a physical system able to encode, process and store for a sufficiently long amount of time the quantum information. However, the optimal engineering of currently available quantum computers, which are small and flawed by several non-ideal phenomena, requires an efficacious methodology for exploring the design space. Hence, there is an unmet need for the development of reliable hardware-aware simulation infrastructures able to efficiently emulate the behaviour of quantum hardware that commits to looking for innovative systematic ways, with a bottom-up approach starting from the physical level, moving to the device level and up to the system level. This article discusses the development of a classical simulation infrastructure for semiconductor quantum-dot quantum computation based on compact models, where each device is described in terms of the main physical parameters affecting its performance in a sufficiently easy way from a computational point of view for providing accurate results without involving sophisticated physical simulators, thus reducing the requirements on CPU and memory. The effectiveness of the involved approximations is tested on a benchmark of quantum circuits — in the expected operating ranges of quantum hardware — by comparing the corresponding outcomes with those obtained via numeric integration of the Schrödinger equation. The achieved results give evidence that this work is a step forward towards the definition of a classical simulator of quantum computers." @default.
- W4386472945 created "2023-09-07" @default.
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- W4386472945 date "2023-01-01" @default.
- W4386472945 modified "2023-09-27" @default.
- W4386472945 title "Advances in Modelling of Noisy Quantum Computers: Spin Qubits in Semiconductor Quantum Dots" @default.
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- W4386472945 doi "https://doi.org/10.1109/access.2023.3312559" @default.
- W4386472945 hasPublicationYear "2023" @default.
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