scholarly journals Flying qubit carrying a spin qubit

2013 ◽  
Vol 7 (4) ◽  
pp. 336-336
Author(s):  
Noriaki Horiuchi
Keyword(s):  
Spin Qubit ◽  
Flying Qubit

Engineering Electronic Structure to Protect Phase Memory in Molecular Qubits by Minimising Orbital Angular Momentum

2018 ◽  
Author(s):  
Ana Maria Ariciu ◽  
David H. Woen ◽  
Daniel N. Huh ◽  
Lydia Nodaraki ◽  
Andreas Kostopoulos ◽  
...  
Keyword(s):  
Electron Spin ◽  
Quantum Coherence ◽  
Quantum Information Processing ◽  
Pulse Sequences ◽  
Grover Algorithm ◽  
Ligand Shell ◽  
Information Strategies ◽  
Spin Qubit ◽  
Molecular Spin ◽  
The Impact

Using electron spins within molecules for quantum information processing (QIP) was first proposed by Leuenberger and Loss (1), who showed how the Grover algorithm could be mapped onto a Mn12 cage (2). Since then several groups have examined two-level (S = ½) molecular spin systems as possible qubits (3-12). There has also been a report of the implementation of the Grover algorithm in a four-level molecular qudit (13). A major challenge is to protect the spin qubit from noise that causes loss of phase information; strategies to minimize the impact of noise on qubits can be categorized as corrective, reductive, or protective. Corrective approaches allow noise and correct for its impact on the qubit using advanced microwave pulse sequences (3). Reductive approaches reduce the noise by minimising the number of nearby nuclear spins (7-11), and increasing the rigidity of molecules to minimise the effect of vibrations (which can cause a fluctuating magnetic field via spin-orbit coupling) (9,11); this is essentially engineering the ligand shell surrounding the electron spin. A protective approach would seek to make the qubit less sensitive to noise: an example of the protective approach is the use of clock transitions to render spin states immune to magnetic fields at first order (12). Here we present a further protective method that would complement reductive and corrective approaches to enhancing quantum coherence in molecular qubits. The target is a molecular spin qubit with an effective 2S ground state: we achieve this with a family of divalent rare-earth molecules that have negligible magnetic anisotropy such that the isotropic nature of the electron spin renders the qubit markedly less sensitive to magnetic noise, allowing coherent spin manipulations even at room temperature. If combined with the other strategies, we believe this could lead to molecular qubits with substantial advantages over competing qubit proposals.<br>

scholarly journals Robust and fast post-processing of single-shot spin qubit detection events with a neural network

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Tom Struck ◽  
Javed Lindner ◽  
Arne Hollmann ◽  
Floyd Schauer ◽  
Andreas Schmidbauer ◽  
...  
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Bayesian Inference ◽  
Rabi Oscillation ◽  
Detection Methods ◽  
Measured Signal ◽  
Single Shot ◽  
Post Processing ◽  
Readout Signal ◽  
Spin Qubit

AbstractEstablishing low-error and fast detection methods for qubit readout is crucial for efficient quantum error correction. Here, we test neural networks to classify a collection of single-shot spin detection events, which are the readout signal of our qubit measurements. This readout signal contains a stochastic peak, for which a Bayesian inference filter including Gaussian noise is theoretically optimal. Hence, we benchmark our neural networks trained by various strategies versus this latter algorithm. Training of the network with 106 experimentally recorded single-shot readout traces does not improve the post-processing performance. A network trained by synthetically generated measurement traces performs similar in terms of the detection error and the post-processing speed compared to the Bayesian inference filter. This neural network turns out to be more robust to fluctuations in the signal offset, length and delay as well as in the signal-to-noise ratio. Notably, we find an increase of 7% in the visibility of the Rabi oscillation when we employ a network trained by synthetic readout traces combined with measured signal noise of our setup. Our contribution thus represents an example of the beneficial role which software and hardware implementation of neural networks may play in scalable spin qubit processor architectures.

scholarly journals Fundamental limits of electron and nuclear spin qubit lifetimes in an isolated self-assembled quantum dot

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
George Gillard ◽  
Ian M. Griffiths ◽  
Gautham Ragunathan ◽  
Ata Ulhaq ◽  
Callum McEwan ◽  
...  
Keyword(s):  
Quantum Dot ◽  
Spin Relaxation ◽  
Nuclear Spin ◽  
Operating Conditions ◽  
External Control ◽  
Spin Qubits ◽  
Fundamental Limits ◽  
Trade Offs ◽  
Wide Range ◽  
Spin Qubit

AbstractCombining external control with long spin lifetime and coherence is a key challenge for solid state spin qubits. Tunnel coupling with electron Fermi reservoir provides robust charge state control in semiconductor quantum dots, but results in undesired relaxation of electron and nuclear spins through mechanisms that lack complete understanding. Here, we unravel the contributions of tunnelling-assisted and phonon-assisted spin relaxation mechanisms by systematically adjusting the tunnelling coupling in a wide range, including the limit of an isolated quantum dot. These experiments reveal fundamental limits and trade-offs of quantum dot spin dynamics: while reduced tunnelling can be used to achieve electron spin qubit lifetimes exceeding 1 s, the optical spin initialisation fidelity is reduced below 80%, limited by Auger recombination. Comprehensive understanding of electron-nuclear spin relaxation attained here provides a roadmap for design of the optimal operating conditions in quantum dot spin qubits.

scholarly journals Dynamics of a spin qubit in an optical dipole trap

2021 ◽  
Vol 103 (6) ◽  
Author(s):  
L. V. Gerasimov ◽  
R. R. Yusupov ◽  
I. B. Bobrov ◽  
D. Shchepanovich ◽  
E. V. Kovlakov ◽  
...  
Keyword(s):  
Dipole Trap ◽  
Optical Dipole Trap ◽  
Spin Qubit

Coupled Spin-Orbit Interactions in Flying Qubit Architectures

2021 ◽  
Author(s):  
Gaurab Panda ◽  
Ryan S. Aridi ◽  
Haozhi Dong ◽  
Virginia M. Ayres ◽  
Harry C. Shaw
Keyword(s):  
Spin Orbit ◽  
Spin Orbit Interactions ◽  
Flying Qubit

Towards Compact Modeling of Noisy Quantum Computers: A Molecular-Spin-Qubit Case of Study

2022 ◽  
Vol 18 (1) ◽  
pp. 1-26
Author(s):  
Mario Simoni ◽  
Giovanni Amedeo Cirillo ◽  
Giovanna Turvani ◽  
Mariagrazia Graziano ◽  
Maurizio Zamboni
Keyword(s):  
Physical Simulation ◽  
Quantum Circuits ◽  
Compact Modeling ◽  
Quantum Computers ◽  
Expected Performance ◽  
Classical Simulation ◽  
Spin Qubit ◽  
Compact Models ◽  
Standard Formalism ◽  
Definition Of

Classical simulation of Noisy Intermediate Scale Quantum computers is a crucial task for testing the expected performance of real hardware. The standard approach, based on solving Schrödinger and Lindblad equations, is demanding when scaling the number of qubits in terms of both execution time and memory. In this article, attempts in defining compact models for the simulation of quantum hardware are proposed, ensuring results close to those obtained with standard formalism. Molecular Nuclear Magnetic Resonance quantum hardware is the target technology, where three non-ideality phenomena—common to other quantum technologies—are taken into account: decoherence, off-resonance qubit evolution, and undesired qubit-qubit residual interaction. A model for each non-ideality phenomenon is embedded into a MATLAB simulation infrastructure of noisy quantum computers. The accuracy of the models is tested on a benchmark of quantum circuits, in the expected operating ranges of quantum hardware. The corresponding outcomes are compared with those obtained via numeric integration of the Schrödinger equation and the Qiskit’s QASMSimulator. The achieved results give evidence that this work is a step forward towards the definition of compact models able to provide fast results close to those obtained with the traditional physical simulation strategies, thus paving the way for their integration into a classical simulator of quantum computers.

Superconducting spin qubit

Science ◽  
2021 ◽  
Vol 373 (6553) ◽  
pp. 405.14-407
Author(s):  
Ian S. Osborne
Keyword(s):  
Spin Qubit

scholarly journals Dynamics of Entanglement between a Quantum Dot Spin Qubit and a Photon Qubit inside a Semiconductor High-Q Nanocavity

2010 ◽  
Vol 2010 ◽  
pp. 1-31 ◽  
Author(s):  
Hubert Pascal Seigneur ◽  
Gabriel Gonzalez ◽  
Michael Niklaus Leuenberger ◽  
Winston Vaughan Schoenfeld
Keyword(s):  
Quantum Dot ◽  
Single Photon ◽  
Hyperfine Interactions ◽  
Interaction Time ◽  
Network Node ◽  
Quantum Network ◽  
Entanglement Dynamics ◽  
High Q ◽  
Spin Qubit

We investigate in this paper the dynamics of entanglement between a QD spin qubit and a single photon qubit inside a quantum network node, as well as its robustness against various decoherence processes. First, the entanglement dynamics is considered without decoherence. In the small detuning regime (Δ=78 μeV), there are three different conditions for maximum entanglement, which occur after 71, 93, and 116 picoseconds of interaction time. In the large detuning regime (Δ=1.5 meV), there is only one peak for maximum entanglement occurring at 625 picoseconds. Second, the entanglement dynamics is considered with decoherence by including the effects of spin-nucleus and hole-nucleus hyperfine interactions. In the small detuning regime, a decent amount of entanglement (35% entanglement) can only be obtained within 200 picoseconds of interaction. Afterward, all entanglement is lost. In the large detuning regime, a smaller amount of entanglement is realized, namely, 25%. And, it lasts only within the first 300 picoseconds.

scholarly journals Enhancing the Coherence of a Spin Qubit by Operating it as a Feedback Loop That Controls its Nuclear Spin Bath

2010 ◽  
Vol 105 (21) ◽  
Author(s):  
Hendrik Bluhm ◽  
Sandra Foletti ◽  
Diana Mahalu ◽  
Vladimir Umansky ◽  
Amir Yacoby
Keyword(s):  
Nuclear Spin ◽  
Feedback Loop ◽  
Spin Bath ◽  
Spin Qubit
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