Physicists dating back to Feynman have lamented the difficulties of applying the variational principle to quantum field theories. In nonrelativistic quantum field theories, the challenge is to parametrize and optimize over the infinitely many n-particle wave functions comprising the state's Fock-space representation. Here we approach this problem by introducing neural-network quantum field states, a deep learning ansatz that enables application of the variational principle to nonrelativistic quantum field theories in the continuum.
View Article and Find Full Text PDFParametrized quantum circuits can be used as quantum neural networks and have the potential to outperform their classical counterparts when trained for addressing learning problems. To date, much of the results on their performance on practical problems are heuristic in nature. In particular, the convergence rate for the training of quantum neural networks is not fully understood.
View Article and Find Full Text PDFOne of the most common and deadly brain tumors is Glioblastoma multiforme (GBM). Due to recent advances in angiogenesis and its related key factors, this process as a hallmark in glioblastoma has attracted more consideration from the research community. Temozolomide (TMZ) as the first-line treatment used to treat GBM but, resistance to TMZ limits its effectiveness and the need for better treatments is still felt.
View Article and Find Full Text PDFAim And Objective: Methyldopa is one of the medications that is used for the treatment of hypertension. Therefore, the determination of methyldopa in the presence of other biological components is essential. In this work, a promising electrochemical sensor based on CoFeO magnetic nanoparticles modified glassy carbon electrode (CoFeO/GCE) was developed for electrochemical determination of methyldopa in the presence of uric acid.
View Article and Find Full Text PDFOver the past two decades, several molecules have been explored as possible building blocks of a quantum computer, a device that would provide exponential speedups for a number of problems, including the simulation of large, strongly correlated chemical systems. Achieving strong interactions and entanglement between molecular qubits remains an outstanding challenge. Here, we show that the TbPc single-molecule magnet has the potential to overcome this obstacle because of its sensitivity to electric fields stemming from the hyperfine Stark effect.
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