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We report energy selective tunneling readout-based Hamiltonian parameter estimation of a two-electron spin qubit in a GaAs quantum dot array. Optimization of readout fidelity enables a single-shot measurement time of 16 on average, with…

We demonstrate a method to obtain the spectra of $1/f$ noises in spin-qubit devices from randomized benchmarking, assisted by supervised learning. The noise exponent, which indicates the correlation within the noise, is determined by…

Quantum Physics · Physics 2019-04-17 Chengxian Zhang , Xin Wang

We propose a scheme to read out the spin of a single electron quantum bit in a surface Paul trap using oscillating magnetic field gradients. The readout sequence is composed of cooling, driving, amplification and detection of the electron's…

Quantum Physics · Physics 2017-01-18 Pai Peng , Clemens Matthiesen , Hartmut Häffner

High-precision optical phase stabilization in quantum networks is fundamentally constrained by the strict photon-flux and duty-cycle limits required to avoid disturbing fragile quantum states. This challenge becomes especially critical when…

Bias-tailored quantum error correcting codes (QECCs) offer a higher error threshold than standard QECCs and have the potential to achieve lower logical errors with less space overhead. The spin-cat qubit, encoded in a large nuclear spin-$F$…

In this work, to improve the spin readout efficiency of the nitrogen vacancy (NV) center, a real-time Bayesian estimation algorithm is proposed, which combines both the prior probability distribution and the fluorescence likelihood function…

The measurement of a quantum two-level system, or a qubit in modern terminology, often involves an electromagnetic field that interacts with the qubit, before the field is measured continuously and the qubit state is inferred from the noisy…

Quantum Physics · Physics 2014-08-27 Shilin Ng , Mankei Tsang

Rapid, high-fidelity single-shot readout of quantum states is a ubiquitous requirement in quantum information technologies, playing a crucial role in quantum computation, quantum error correction, and fundamental tests of non-locality.…

Fast and high-fidelity qubit measurement is essential for realizing quantum error correction, which is in turn a key ingredient to universal quantum computing. For electron spin qubits, fast readout is one of the significant road blocks…

Quantum Physics · Physics 2024-04-15 Chon-Fai Kam , Xuedong Hu

The performance of a wide range of quantum computing algorithms and protocols depends critically on the fidelity and speed of the employed qubit readout. Examples include gate sequences benefiting from mid-circuit, real-time,…

Despite the fact that neural networks are widely used for speech-driven head motion synthesis, it is well-known that the output of neural networks is noisy or discontinuous due to the limited capability of deep neural networks in predicting…

Signal Processing · Electrical Eng. & Systems 2019-07-26 JinHong Lu , Hiroshi Shimodaira

Single electron spins confined in silicon quantum dots hold great promise as a quantum computing architecture with demonstrations of long coherence times, high-fidelity quantum logic gates, basic quantum algorithms and device scalability.…

Mesoscale and Nanoscale Physics · Physics 2020-08-12 J. Yoneda , K. Takeda , A. Noiri , T. Nakajima , S. Li , J. Kamioka , T. Kodera , S. Tarucha

For solid-state spin qubits, single-gate RF readout can help minimise the number of gates required for scale-up to many qubits since the readout sensor can integrate into the existing gates required to manipulate the qubits (Veldhorst 2017,…

Mesoscale and Nanoscale Physics · Physics 2018-12-05 P. Pakkiam , A. V. Timofeev , M. G. House , M. R. Hogg , T. Kobayashi , M. Koch , S. Rogge , M. Y. Simmons

Bayesian neural networks offer better estimates of model uncertainty compared to frequentist networks. However, inference involving Bayesian models requires multiple instantiations or sampling of the network parameters, requiring…

Neural and Evolutionary Computing · Computer Science 2024-01-30 Prabodh Katti , Anagha Nimbekar , Chen Li , Amit Acharyya , Bashir M. Al-Hashimi , Bipin Rajendran

Spiking Neural Networks (SNN) are more closely related to brain-like computation and inspire hardware implementation. This is enabled by small networks that give high performance on standard classification problems. In literature, typical…

Neural and Evolutionary Computing · Computer Science 2016-12-08 Anmol Biswas , Sidharth Prasad , Sandip Lashkare , Udayan Ganguly

Fast and high-fidelity qubit measurement is crucial for achieving quantum error correction, a fundamental element in the development of universal quantum computing. For electron spin qubits, fast readout stands out as a major obstacle in…

Mesoscale and Nanoscale Physics · Physics 2024-01-09 Chon-Fai Kam , Xuedong Hu

The construction of robust and scalable quantum gates is a uniquely hard problem in the field of quantum computing. Real-world quantum computers suffer from many forms of noise, characterized by the decoherence and relaxation times of a…

Quantum Physics · Physics 2025-07-14 Diego Fuentealba , Jack Dahn , James Steck , Elizabeth Behrman

Noise characterization methods such as randomized benchmarking (RB) are critical for the development of scalable quantum computers. Modern RB protocols for multiqubit systems extract physically relevant error rates by exploiting the…

Quantum Physics · Physics 2026-04-15 Yale Fan , Riley Murray , Thaddeus D. Ladd , Kevin Young , Robin Blume-Kohout

Single-shot readout is a key component for scalable quantum information processing. However, many solid-state qubits with favorable properties lack the single-shot readout capability. One solution is to use the repetitive…

Quantum Physics · Physics 2019-07-30 Genyue Liu , Mo Chen , Yi-Xiang Liu , David Layden , Paola Cappellaro

Quantum simulation, the study of strongly correlated quantum matter using synthetic quantum systems, has been the most successful application of quantum computers to date. It often requires determining observables with high precision, for…