Tensor network investigation of the hard-square model

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Publications associées (32)

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Accessing the thermal transport properties of glasses is a major issue for the design of production strategies of glass industry, as well as for the plethora of applications and devices where glasses are employed. From the computational standpoint, the che ...

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Parametric amplifiers play a crucial role in modern quantum technology by enabling the enhancement of weak signals with minimal added noise. Traditionally, Josephson junctions have been the primary choice for constructing parametric amplifiers. Nevertheles ...

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Quantum Error Correction and Simulation in Open Bosonic Systems

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Quantum computers have the potential to surpass conventional computing, but they are hindered by noise which induces errors that ultimately lead to the loss of quantum information. This necessitates the development of quantum error correction strategies fo ...

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The activity of subsurface microorganisms can be harnessed for engineering projects. For instance, the Swiss radioactive waste repository design can take advantage of indigenous microorganisms to tackle the issue of a hydrogen gas (H2) phase pressure build ...

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Simulating the dynamics of large quantum systems is a formidable yet vital pursuit for obtaining a deeper understanding of quantum mechanical phenomena. While quantum computers hold great promise for speeding up such simulations, their practical applicatio ...

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Macrocycles provide an attractive modality for drug development but the identification of ligands to targets of interest is hindered by the lack of large macrocyclic compound libraries for high-throughput screening. A strategy to efficiently synthesize lar ...

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Much attention has been paid to dynamical simulation and quantum machine learning (QML) independently as applications for quantum advantage, while the possibility of using QML to enhance dynamical simulations has not been thoroughly investigated. Here we d ...

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In the rapidly evolving landscape of machine learning research, neural networks stand out with their ever-expanding number of parameters and reliance on increasingly large datasets. The financial cost and computational resources required for the training p ...

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Kontsevich and Soibelman reformulated and slightly generalised the topological recursion of [43], seeing it as a quantisation of certain quadratic Lagrangians in T*V for some vector space V. KS topological recursion is a procedure which takes as initial da ...

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Combining superconducting resonators and quantum dots has triggered tremendous progress in quantum information, however, attempts at coupling a resonator to even charge parity spin qubits have resulted only in weak spin-photon coupling. Here, we integrate ...

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