Energetic Considerations in Quantum Target Ranging
- URL: http://arxiv.org/abs/2011.03637v3
- Date: Tue, 23 Mar 2021 07:36:14 GMT
- Title: Energetic Considerations in Quantum Target Ranging
- Authors: Athena Karsa and Stefano Pirandola
- Abstract summary: An unknown return time makes a QI-based protocol difficult to realise.
Applying CPF to time bins, one finds an upper-bound on the error probability for quantum target ranging.
We show that for such a scheme a quantum advantage may not physically be realised.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: While quantum illumination (QI) can offer a quantum-enhancement in target
detection, its potential for performing target ranging remains unclear. With
its capabilities hinging on a joint-measurement between a returning signal and
its retained idler, an unknown return time makes a QI-based protocol difficult
to realise. This paper outlines a potential QI-based approach to quantum target
ranging based on recent developments in multiple quantum hypothesis testing and
quantum-enhanced channel position finding (CPF). Applying CPF to time bins, one
finds an upper-bound on the error probability for quantum target ranging.
However, using energetic considerations, we show that for such a scheme a
quantum advantage may not physically be realised.
Related papers
- Accelerated first detection in discrete-time quantum walks using sharp restarts [2.501693072047969]
We show how restarting monitored discrete-time quantum walks (DTQWs) affects the quantum hitting times.
We show that the restarted DTQWs outperform classical random walks in target searches.
Our study paves the way for more efficient use of DTQWs in quantum-walk-based search algorithms.
arXiv Detail & Related papers (2024-11-14T14:33:10Z) - Quantum metrological capability as a probe for quantum phase transition [1.5574423250822542]
The metrological capability quantified by the quantum Fisher information captivatingly shows an unique peak in the vicinity of the quantum critical point.
We show that the probing can be implemented by extracting quantum fluctuations of the interferometric generator.
arXiv Detail & Related papers (2024-08-19T08:18:03Z) - Quantum Illumination and Quantum Radar: A Brief Overview [0.0]
We present a broad overview of the field of quantum target detection focusing on QI and its potential as an underlying scheme for a quantum radar operating at microwave frequencies.
Our aim is to provide a balanced discussion on the state of theoretical and experimental progress towards realising a working QI-based quantum radar, and draw conclusions about its current outlook and future directions.
arXiv Detail & Related papers (2023-10-09T18:03:14Z) - Quantum Imitation Learning [74.15588381240795]
We propose quantum imitation learning (QIL) with a hope to utilize quantum advantage to speed up IL.
We develop two QIL algorithms, quantum behavioural cloning (Q-BC) and quantum generative adversarial imitation learning (Q-GAIL)
Experiment results demonstrate that both Q-BC and Q-GAIL can achieve comparable performance compared to classical counterparts.
arXiv Detail & Related papers (2023-04-04T12:47:35Z) - Adiabatic quantum learning [0.0]
This work proposes to execute some quantum learning protocols based entirely on adiabatic quantum evolution.
By contrast, the proposed adiabatic quantum learning here may be integrated with future adiabatic weak measurement protocols.
arXiv Detail & Related papers (2023-03-02T07:27:29Z) - Anticipative measurements in hybrid quantum-classical computation [68.8204255655161]
We present an approach where the quantum computation is supplemented by a classical result.
Taking advantage of its anticipation also leads to a new type of quantum measurements, which we call anticipative.
In an anticipative quantum measurement the combination of the results from classical and quantum computations happens only in the end.
arXiv Detail & Related papers (2022-09-12T15:47:44Z) - Recent Advances for Quantum Neural Networks in Generative Learning [98.88205308106778]
Quantum generative learning models (QGLMs) may surpass their classical counterparts.
We review the current progress of QGLMs from the perspective of machine learning.
We discuss the potential applications of QGLMs in both conventional machine learning tasks and quantum physics.
arXiv Detail & Related papers (2022-06-07T07:32:57Z) - Theory of Quantum Generative Learning Models with Maximum Mean
Discrepancy [67.02951777522547]
We study learnability of quantum circuit Born machines (QCBMs) and quantum generative adversarial networks (QGANs)
We first analyze the generalization ability of QCBMs and identify their superiorities when the quantum devices can directly access the target distribution.
Next, we prove how the generalization error bound of QGANs depends on the employed Ansatz, the number of qudits, and input states.
arXiv Detail & Related papers (2022-05-10T08:05:59Z) - On exploring the potential of quantum auto-encoder for learning quantum systems [60.909817434753315]
We devise three effective QAE-based learning protocols to address three classically computational hard learning problems.
Our work sheds new light on developing advanced quantum learning algorithms to accomplish hard quantum physics and quantum information processing tasks.
arXiv Detail & Related papers (2021-06-29T14:01:40Z) - Noncyclic nonadiabatic holonomic quantum gates via shortcuts to
adiabaticity [5.666193021459319]
We propose a fast and robust scheme to construct high-fidelity holonomic quantum gates for universal quantum systems via shortcuts to adiabaticity.
Our scheme is readily realizable in physical system currently pursued for implementation of quantum computation.
arXiv Detail & Related papers (2021-05-28T15:23:24Z) - Direct Quantum Communications in the Presence of Realistic Noisy
Entanglement [69.25543534545538]
We propose a novel quantum communication scheme relying on realistic noisy pre-shared entanglement.
Our performance analysis shows that the proposed scheme offers competitive QBER, yield, and goodput.
arXiv Detail & Related papers (2020-12-22T13:06:12Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.