402 research outputs found

    Fast simulation of quantum algorithms using circuit optimization

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    Classical simulators play a major role in the development and benchmark of quantum algorithms and practically any software framework for quantum computation provides the option of running the algorithms on simulators. However, the development of quantum simulators was substantially separated from the rest of the software frameworks which, instead, focus on usability and compilation. Here, we demonstrate the advantage of co-developing and integrating simulators and compilers by proposing a specialized compiler pass to reduce the simulation time for arbitrary circuits. While the concept is broadly applicable, we present a concrete implementation based on the Intel Quantum Simulator, a high-performance distributed simulator. As part of this work, we extend its implementation with additional functionalities related to the representation of quantum states. The communication overhead is reduced by changing the order in which state amplitudes are stored in the distributed memory, a concept analogous to the distinction between local and global qubits for distributed Schroedinger-type simulators. We then implement a compiler pass to exploit the novel functionalities by introducing special instructions governing data movement as part of the quantum circuit. Those instructions target unique capabilities of simulators and have no analogue in actual quantum devices. To quantify the advantage, we compare the time required to simulate random circuits with and without our optimization. The simulation time is typically halved

    On connectivity-dependent resource requirements for digital quantum simulation of dd-level particles

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    A primary objective of quantum computation is to efficiently simulate quantum physics. Scientifically and technologically important quantum Hamiltonians include those with spin-ss, vibrational, photonic, and other bosonic degrees of freedom, i.e. problems composed of or approximated by dd-level particles (qudits). Recently, several methods for encoding these systems into a set of qubits have been introduced, where each encoding's efficiency was studied in terms of qubit and gate counts. Here, we build on previous results by including effects of hardware connectivity. To study the number of SWAP gates required to Trotterize commonly used quantum operators, we use both analytical arguments and automatic tools that optimize the schedule in multiple stages. We study the unary (or one-hot), Gray, standard binary, and block unary encodings, with three connectivities: linear array, ladder array, and square grid. Among other trends, we find that while the ladder array leads to substantial efficiencies over the linear array, the advantage of the square over the ladder array is less pronounced. These results are applicable in hardware co-design and in choosing efficient qudit encodings for a given set of near-term quantum hardware. Additionally, this work may be relevant to the scheduling of other quantum algorithms for which matrix exponentiation is a subroutine.Comment: Accepted to QCE20 (IEEE Quantum Week). Corrected erroneous circuits in Figure

    3D VIEWS AND VISIBILITY ANALISYS USING OPEN DATA AND OPEN SOFTWARE TO SUPPORT POLICIES FOR LANDSCAPE AND CULTURAL HERITAGE ENHANCEMENT

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    Il paper illustra alcune metodologie per produrre visualizzazioni GIS a supporto delle politiche di valorizzazione paesaggistica, dei beni culturali e dei connessi processi decisionali. Si tratta di viste 3D navigabili, analisi di visibilità e analisi per il riconoscimento delle unità sceniche di paesaggio: sono state elaborate a partire da dati open avvalendosi di un software GIS open, in una sperimentazione didattica universitaria presso il Politecnico di Torino.The paper presents some methods to produce GIS views to support policies for enhancing landscape and cultural heritage, and their related decision-making processes. They are navigable 3D views, visibility analyses, and analyses for the recognition of scenic units: they were developed using open data and open GIS software in a university course at the Politecnico di Torino
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