Efficient measures to determine the similarity of quantum states, such as the fidelity metric, have been widely studied. In this paper, we address the problem of defining a similarity measure for quantum operations th...
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Efficient measures to determine the similarity of quantum states, such as the fidelity metric, have been widely studied. In this paper, we address the problem of defining a similarity measure for quantum operations that can be efficiently estimated. Given two quantum operations, U1 and U2, represented in their circuit forms, we first develop a quantum sampling circuit to estimate the normalized Schatten 2-norm of their difference (∥U1−U2∥S2) with precision ε, using only one clean qubit and one classical random variable. We prove a Poly(1ε) upper bound on the sample complexity, which is independent of the size of the quantum system. We then show that such a similarity metric is directly related to a functional definition of similarity of unitary operations using the conventional fidelity metric of quantum states (F): If ∥U1−U2∥S2 is sufficiently small (e.g., ≤ε1+2(1/δ−1)) then the fidelity of states obtained by processing the same randomly and uniformly picked pure state |ψ〉 is as high as needed [F(U1|ψ〉,U2|ψ〉)≥1−ε] with probability exceeding 1−δ. We provide example applications of this efficient similarity metric estimation framework to quantum circuit learning tasks, such as finding the square root of a given unitary operation.
We developed a lensless microscope with small, inexpensive form factor, large field-of-view (FOV) and cellular resolution for fluorescence imaging. Proof-of-principle measurements with "Bio-FlatScope" are pr...
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Alloy scattering in random AlGaN alloys drastically reduces the electron mobility and therefore the power-electronics figure of merit. As a result, Al compositions greater than 75% are required to obtain even a two-fo...
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Weakly supervised semantic segmentation (WSSS) methods are often built on pixel-level localization maps obtained from a classifier. However, training on class labels only, classifiers suffer from the spurious correlat...
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This paper presents state of the art methods for addressing three important challenges in automated fake news detection: fake news detection, domain identification, and bot identification in tweets. The proposed solut...
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We demonstrate a single-shot miniature 3D computational microscope with an optimized phase encoder. Our method uses sparsity-based reconstruction to achieve a 2.76µm lateral and 15µm axial resolution across ...
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We report the first observation of cascaded forward stimulated Brillouin scattering in a microresonator platform. We have demonstrated 25 orders of intramodal Stokes beams separated by a Brillouin shift of 34.5 MHz at...
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In this work we evaluated the performance of a camera-based rigid body motion correction solution using a 2D checkerboard marker and a 3D encoded marker. The context of the results presented is in PET/MR imaging, but ...
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ISBN:
(数字)9781665421133
ISBN:
(纸本)9781665421140
In this work we evaluated the performance of a camera-based rigid body motion correction solution using a 2D checkerboard marker and a 3D encoded marker. The context of the results presented is in PET/MR imaging, but in principle this motion compensation method could be used in any type of medical imaging modality. A high precision, computer-controlled motion stage with four degrees of freedom was used to control the marker positions and orientations (a.k.a. ‘poses’). Still images of the markers taken in different poses mimicking a patient moving her/his head from side to side, were used to assess performance of this method. Comparing the known stage motion to the estimated motion, our results indicate that the 2D marker achieves better angular accuracy while the 3D marker’s translational (linear) accuracy is superior. For all axes, the angular error was less than 0.96, 0.35 [deg], and the translational error was less than 2.24, 4.76 [mm] for the 3D and 2D markers, respectively.
Artificial intelligence (AI) has advanced rapidly and is becoming a cornerstone technology that drives innovation and efficiency in various industries. This paper examines the real-world application of AI in multiple ...
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