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We demonstrate the application of pattern recognition algorithms via hidden Markov models (HMM) for qubit readout. This scheme provides a state-path trajectory approach capable of detecting qubit state transitions and makes for a robust…

Quantum Physics · Physics 2021-01-04 Luis A. Martinez , Yaniv J. Rosen , Jonathan L. DuBois

Qubit readout schemes often deviate from ideal projective measurements, introducing critical issues that limit quantum computing performance. In this work, we model charge-sensing-based readout for semiconductor spin qubits in double…

In semiconductor spin quantum bits (qubits), the radio-frequency (RF) gate-based readout is a promising solution for future large-scale integration, as it allows for a fast, frequency-multiplexed readout architecture, enabling multiple…

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

High-fidelity readout of spin qubits in semiconductor quantum dots can be achieved by combining a radio-frequency (RF) charge sensor together with spin-to-charge conversion and Pauli spin blockade. However, reaching high readout fidelities…

Projective measurement of single electron spins, or spin readout, is among the most fundamental technologies for spin-based quantum information processing. Implementing spin readout with both high-fidelity and scalability is indispensable…

Mesoscale and Nanoscale Physics · Physics 2024-10-07 Haruki Kiyama , Danny van Hien Hien , Arne Ludwig , Andreas D. Wieck , Akira Oiwa

Determination of qubit initialisation and measurement fidelity is important for the overall performance of a quantum computer. However, the method by which it is calculated in semiconductor qubits varies between experiments. In this paper…

Quantum Physics · Physics 2019-09-04 D. Keith , S. K. Gorman , L. Kranz , Y. He , J. G. Keizer , M. A. Broome , M. Y. Simmons

The readout of semiconductor spin qubits based on spin blockade is fast but suffers from a small charge signal. Previous work suggested large benefits from additional charge mapping processes, however uncertainties remain about the…

A hidden Markov model (HMM) scheme for tracking continuous-wave gravitational radiation from neutron stars in low-mass X-ray binaries (LMXBs) with wandering spin is extended by introducing a frequency-domain matched filter, called the…

Instrumentation and Methods for Astrophysics · Physics 2017-11-29 S. Suvorova , P. Clearwater , A. Melatos , L. Sun , W. Moran , R. J. Evans

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 Hidden Quantum Markov Model (HQMM) has significant potential for analyzing time-series data and studying stochastic processes in the quantum domain as an upgrading option with potential advantages over classical Markov models. In this…

Quantum Physics · Physics 2024-11-01 Xiao-Yu Li , Qin-Sheng Zhu , Yong Hu , Hao Wu , Guo-Wu Yang , Lian-Hui Yu , Geng Chen

Gravitational wave searches for continuous-wave signals from neutron stars are especially challenging when the star's spin frequency is unknown a priori from electromagnetic observations and wanders stochastically under the action of…

Instrumentation and Methods for Astrophysics · Physics 2016-07-13 S. Suvorova , L. Sun , A. Melatos , W. Moran , R. J. Evans

Ultra-wideband (UWB) multistatic radar can be used for target detection and tracking in buildings and rooms. Target detection and tracking relies on accurate knowledge of the bistatic delay. Noise, measurement error, and the problem of…

Other Computer Science · Computer Science 2012-12-06 Merrick McCracken , Neal Patwari

The engineering of electron spin qubits in a compact unit cell embedding all quantum functionalities is mandatory for large scale integration. In particular, the development of a high-fidelity and scalable spin readout method remains an…

High fidelity qubit readout is critical in order to obtain the thresholds needed to implement quantum error correction protocols and achieve fault-tolerant quantum computing. Large-scale silicon qubit devices will have densely-packed arrays…

Single-shot spin-state discrimination is essential for semiconductor spin qubits, but conventional threshold-based analysis of spin readout traces becomes unreliable under noisy conditions. Although recent neural-network-based methods…

Mesoscale and Nanoscale Physics · Physics 2026-02-04 Yui Muto , Motoya Shinozaki , Hideaki Yuta , Tatsuo Tsuzuki , Kotaro Taga , Akira Oiwa , Takafumi Fujita , Tomohiro Otsuka

The hidden Markov model (HMM) is a fundamental tool for sequence modeling that cleanly separates the hidden state from the emission structure. However, this separation makes it difficult to fit HMMs to large datasets in modern NLP, and they…

Computation and Language · Computer Science 2020-11-10 Justin T. Chiu , Alexander M. Rush

An important requirement for spin-based quantum information processing is reliable and fast readout of electron spin states, allowing for feedback and error correction. However, common readout techniques often require additional gate…

Mesoscale and Nanoscale Physics · Physics 2021-05-04 F. Borjans , X. Mi , J. R. Petta

In this article, we use the theory of quantum channels and open quantum systems to provide an efficient unitary characterization of a class of stochastic generators known as quantum hidden Markov models (QHMMs). By utilizing the unitary…

Quantum Physics · Physics 2025-02-27 Vanio Markov , Vladimir Rastunkov , Amol Deshmukh , Daniel Fry , Charlee Stefanski

Hidden Quantum Markov Models (HQMMs) can be thought of as quantum probabilistic graphical models that can model sequential data. We extend previous work on HQMMs with three contributions: (1) we show how classical hidden Markov models…

Machine Learning · Statistics 2017-10-26 Siddarth Srinivasan , Geoff Gordon , Byron Boots
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