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Ensuring correct network behavior is hard. This is the case even for simple networks, and adding middleboxes only complicates this task. In this paper, we demonstrate a fundamental property of networks. Namely, we show a way of using a network to emulate t ...
The exceptional points (EPs) of non-Hermitian Hamiltonians (NHHs) are spectral degeneracies associated with coalescing eigenvalues and eigenvectors, which are associated with remarkable dynamical properties. These EPs can be generated experimentally in ope ...
The Loschmidt echo is a measure of quantum irreversibility and is determined by the fidelity amplitude of an imperfect time-reversal protocol. Fidelity amplitude plays an important role both in the foundations of quantum mechanics and its applications, suc ...
A computationally affordable approach, based on quasi-harmonic lattice dynamics, is presented for the quantum-mechanical calculation of thermoelastic moduli of flexible, stimuli-responsive, organic crystals. The methodology relies on the simultaneous descr ...
A quantum machine may solve some complex problems that are intractable for even the most powerful classical computers. By exploiting quantum superposition and entanglement phenomena, quantum algorithms can achieve from polynomial to exponential speed up wh ...
Universal quantum algorithms that prepare arbitrary n-qubit quantum states require O(2n) gate complexity. The complexity can be reduced by considering specific families of quantum states depending on the task at hand. In particular, multipartite quantum st ...
Tucker's lemma states that if we triangulate the unit disc centered at the origin and color the vertices with {1, 1,2, 2} in an antipodal way (if vertical bar z vertical bar = 1, then the sum of the colors of z and -z is zero), then there must be an edge F ...
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Harnessing quantum randomness for the generation of random numbers is an important concept crucial for information security and many other computer-related applications. Quantum random number generators (QRNGs) are evolving from bulky, slow, and expensive ...
A key challenge for neural modeling is to explain how a continuous stream of multimodal input from a rapidly changing environment can be processed by stereotypical recurrent circuits of integrate-and-fire neurons in real time. We propose a new computationa ...
Including quantum mechanical effects on the dynamics of nuclei in the condensed phase is challenging, because the complexity of exact methods grows exponentially with the number of quantum degrees of freedom. Efforts to circumvent these limitations can be ...