Results 41 to 50 of about 737,908 (337)
Constructing Optimal Contraction Trees for Tensor Network Quantum Circuit Simulation [PDF]
One of the key problems in tensor network based quantum circuit simulation is the construction of a contraction tree which minimizes the cost of the simulation, where the cost can be expressed in the number of operations as a proxy for the simulation ...
Cameron Ibrahim+4 more
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Optimizing Tensor Network Contraction Using Reinforcement Learning [PDF]
Quantum Computing (QC) stands to revolutionize computing, but is currently still limited. To develop and test quantum algorithms today, quantum circuits are often simulated on classical computers.
E. Meirom+3 more
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Calculating contracted tensor Feynman integrals [PDF]
A recently derived approach to the tensor reduction of 5-point one-loop Feynman integrals expresses the tensor coefficients by scalar 1-point to 4-point Feynman integrals completely algebraically. In this letter we derive extremely compact algebraic expressions for the contractions of the tensor integrals with external momenta.
Fleischer, Jochem, Riemann, Tord
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The slice-wise multiplication of two tensors is required in a variety of tensor decompositions (including PARAFAC2 and PARATUCK2) and is encountered in many applications, including the analysis of multidimensional biomedical data (EEG, MEG, etc.) or ...
Kristina Naskovska+3 more
doaj +1 more source
Spectral asymptotics for contracted tensor ensembles
v3: updated to incorporate feedback from referees, including a shorter proof of Proposition 4.2; 31 pages, 7 ...
Au, Benson, Garza-Vargas, Jorge
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Simulating Quantum Circuits Using Efficient Tensor Network Contraction Algorithms with Subexponential Upper Bound. [PDF]
We derive a rigorous upper bound on the classical computation time of finite-ranged tensor network contractions in d≥2 dimensions. Consequently, we show that quantum circuits of single-qubit and finite-ranged two-qubit gates can be classically simulated ...
T. Wahl, Sergii Strelchuk
semanticscholar +1 more source
Algorithms for tensor network contraction ordering
Abstract Contracting tensor networks is often computationally demanding. Well-designed contraction sequences can dramatically reduce the contraction cost. We explore the performance of simulated annealing and genetic algorithms, two common discrete optimization techniques, to this ordering problem.
Schindler, Frank, Jermyn, Adam S
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In this paper, we use the previously introduced Canonical Polyadic (CP)-Multiple Shift Block Inverse Iteration (MSBII) eigensolver [S. D. Kallullathil and T. Carrington, J. Chem. Phys. 155, 234105 (2021)] in conjunction with a contraction tree to compute
Sangeeth Das Kallullathil, T. Carrington
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Verifying Quantum Advantage Experiments with Multiple Amplitude Tensor Network Contraction. [PDF]
The quantum supremacy experiment, such as Google Sycamore [F. Arute et al., Nature (London) 574, 505 (2019).NATUAS0028-083610.1038/s41586-019-1666-5], poses a great challenge for classical verification due to the exponentially increasing compute cost ...
Yong Liu+13 more
semanticscholar +1 more source
Contractive homomorphisms and tensor product norms [PDF]
For any complex domain \(\Omega\), one can ask if all contractive algebra homomorphisms of \({\mathcal A}(\Omega)\) (into the algebra of Hilbert space operators) are completely contractive or not. By Ando's Theorem, this has an affirmative answer for \(\Omega= \mathbb{D}^2\), the bi-disc -- while the answer is unknown for \(\Omega= (\ell^1(2))_1\), the
Gadadhar Misra, Bhaskar Bagchi
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