Qip2021 The Quantum Wasserstein Distance Of Order 1 Giacomo De Palma
Pdf Quantum Wasserstein 1 Distance We propose a generalization of the wasserstein distance of order 1 to the quantum states of n qudits. the proposal recovers the hamming distance for the vectors of the canonical basis, and more generally the classical wasserstein distance for quantum states diagonal in the canonical basis. Abstract: we propose a generalization of the wasserstein distance of order 1 to the quantum states of n qudits. the proposal recovers the hamming distance for the vectors of the canonical basis, and more generally the classical wasserstein distance for quantum states diagonal in the canonical basis.
Order 2 Quantum Wasserstein Distance Advances State Discrimination For We conclude in section x by discussing other possible applications of the defined quantum w1 distance in quantum machine learning, quantum information, and quantum many body systems. The notion of quantum lipschitz constant allows us to compute the proposed distance with a semidefinite program. we prove a quantum version of marton’s transportation inequality and a quantum gaussian concentration inequality for the spectrum of quantum lipschitz observables. Shallow quantum circuits • expand w1 distance by at most twice the size of the largest light cone of a qudit. De palma, giacomo, marvian, milad, trevisan, dario and lloyd, seth. 2021. "the quantum wasserstein distance of order 1." ieee transactions on information theory, 67 (10). version: author's final manuscript.
The Algebraic Degree Of The Wasserstein Distance Mathrepo 2025 10 08 Shallow quantum circuits • expand w1 distance by at most twice the size of the largest light cone of a qudit. De palma, giacomo, marvian, milad, trevisan, dario and lloyd, seth. 2021. "the quantum wasserstein distance of order 1." ieee transactions on information theory, 67 (10). version: author's final manuscript. We propose a generalization of the wasserstein distance of order 1 to the quantum states of n 𝑛 n qudits. the proposal recovers the hamming distance for the vectors of the canonical basis, and more generally the classical wasserstein distance for quantum states diagonal in the canonical basis. We propose a generalization of the wasserstein distance of order 1 to the quantum states of n qudits. the proposal recovers the hamming distance for the vectors of the canonical basis, and. The proposal recovers the hamming distance for the vectors of the canonical basis, and more generally the classical wasserstein distance for quantum states diagonal in the canonical basis. We conclude in section x by discussing other possible applications of the defined quantum w1 distance in quantum machine learning, quantum information, and quantum many body systems.
Microcloud Hologram Wasserstein Distance Quantum Theory Detroit Chinatown We propose a generalization of the wasserstein distance of order 1 to the quantum states of n 𝑛 n qudits. the proposal recovers the hamming distance for the vectors of the canonical basis, and more generally the classical wasserstein distance for quantum states diagonal in the canonical basis. We propose a generalization of the wasserstein distance of order 1 to the quantum states of n qudits. the proposal recovers the hamming distance for the vectors of the canonical basis, and. The proposal recovers the hamming distance for the vectors of the canonical basis, and more generally the classical wasserstein distance for quantum states diagonal in the canonical basis. We conclude in section x by discussing other possible applications of the defined quantum w1 distance in quantum machine learning, quantum information, and quantum many body systems.
Microcloud Hologram Wasserstein Distance Quantum Theory Detroit Chinatown The proposal recovers the hamming distance for the vectors of the canonical basis, and more generally the classical wasserstein distance for quantum states diagonal in the canonical basis. We conclude in section x by discussing other possible applications of the defined quantum w1 distance in quantum machine learning, quantum information, and quantum many body systems.
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