Abstract: The present disclosure provides methods and systems for using a hybrid architecture of classical and non-classical (e.g., quantum) computing to compute the quantum mechanical energy and/or electronic structure of a chemical system, as well as to identify stable conformations of a chemical system (e.g., a molecule) and/or to perform an ab initio molecular dynamics calculation or simulation on the chemical system.

Abstract: A method and system are disclosed for performing real-time analytics on a plurality of data streams, the method comprising obtaining a plurality of data streams; accumulating real-time changes of the obtained plurality of data streams in a buffer unit to provide a buffered data portion; monitoring the buffered data portion for determining a calculation event, wherein the calculation event is based on a strategy based on observing given features in the buffered data portion; upon detection of the calculation event, generating an optimization problem indicative of the real-time analytics to be performed on one of given data portions of the plurality of data streams and a data structure generated using given data portions of the plurality of data streams; transforming the generated optimization problem into an optimization problem suitable for an optimization oracle; providing the transformed generated optimization problem to the optimization oracle; obtaining at least one solution from the optimization oracle;

Abstract: The present disclosure provides methods and systems for solving an optimization problem using a computing platform comprising at least one non-classical computer and at least one digital computer. The at least one non-classical computer may be configured to perform an adiabatic quantum computation with a first Hamiltonian and second Hamiltonian.

Abstract: The present disclosure provides methods and systems for using a hybrid architecture of quantum and classical computing to compute the quantum mechanical energy and/or electronic structure of a chemical system, as well as to identify stable conformations of a chemical system (e.g., a molecule) and/or to perform an ab initio molecular dynamics calculation or simulation on the chemical system.

Abstract: The present disclosure provides methods, systems, and media for quantum computing, including allowing access to quantum ready and/or quantum enabled computers in a distributed computing environment (e.g., the cloud). Such methods and systems may provide optimization and computational services. Methods and systems of the present disclosure may enable quantum computing to be relatively and readily scaled across various types of quantum computers and users at various locations, in some cases without the need for users to have a deep understanding of the resources, implementation or the knowledge that may be required for solving optimization problems using a quantum computer. Systems provided herein may include user interfaces that enable users to perform data analysis in a distributed computing environment while taking advantage of quantum technology in the backend.

Abstract: The present disclosure provides methods, systems, and media for allowing access to quantum ready and/or quantum enabled computers in a distributed computing environment (e.g., the cloud). Such methods and systems may provide optimization and computational services on the cloud. Methods and systems of the present disclosure may enable quantum computing to be relatively and readily scaled across various types of quantum computers and users at various locations, in some cases without the need for users to have a deep understanding of the resources, implementation or the knowledge that may be required for solving optimization problems using a quantum computer. Systems provided herein may include user interfaces that enable users to perform data analysis in a distributed computing environment while taking advantage of quantum technology in the backend.

Abstract: A method and system are disclosed for performing real-time analytics on a plurality of data streams, the method comprising obtaining a plurality of data streams; accumulating real-time changes of the obtained plurality of data streams in a buffer unit to provide a buffered data portion; monitoring the buffered data portion for determining a calculation event, wherein the calculation event is based on a strategy based on observing given features in the buffered data portion; upon detection of the calculation event, generating an optimization problem indicative of the real-time analytics to be performed on one of given data portions of the plurality of data streams and a data structure generated using given data portions of the plurality of data streams; transforming the generated optimization problem into an optimization problem suitable for an optimization oracle; providing the transformed generated optimization problem to the optimization oracle; obtaining at least one solution from the optimization oracle;

Abstract: The present disclosure provides methods, systems, and media for allowing access to quantum ready and/or quantum enabled computers in a distributed computing environment (e.g., the cloud). Such methods and systems may provide optimization and computational services on the cloud. Methods and systems of the present disclosure may enable quantum computing to be relatively and readily scaled across various types of quantum computers and users at various locations, in some cases without the need for users to have a deep understanding of the resources, implementation or the knowledge that may be required for solving optimization problems using a quantum computer. Systems provided herein may include user interfaces that enable users to perform data analysis in a distributed computing environment while taking advantage of quantum technology in the backend.

Abstract: The present disclosure provides methods, systems, and media for quantum computing, including allowing access to quantum ready and/or quantum enabled computers in a distributed computing environment (e.g., the cloud). Such methods and systems may provide optimization and computational services. Methods and systems of the present disclosure may enable quantum computing to be relatively and readily scaled across various types of quantum computers and users at various locations, in some cases without the need for users to have a deep understanding of the resources, implementation or the knowledge that may be required for solving optimization problems using a quantum computer. Systems provided herein may include user interfaces that enable users to perform data analysis in a distributed computing environment while taking advantage of quantum technology in the backend.

Abstract: The present disclosure provides methods, systems, and media for allowing access to quantum ready and/or quantum enabled computers in a distributed computing environment (e.g., the cloud). Such methods and systems may provide optimization and computational services on the cloud. Methods and systems of the present disclosure may enable quantum computing to be relatively and readily scaled across various types of quantum computers and users at various locations, in some cases without the need for users to have a deep understanding of the resources, implementation or the knowledge that may be required for solving optimization problems using a quantum computer. Systems provided herein may include user interfaces that enable users to perform data analysis in a distributed computing environment while taking advantage of quantum technology in the backend.

Abstract: The present disclosure provides methods, systems, and non-transitory computer-readable media for hybrid computing integrating resources of classical computing and non-classical computing. A hybrid computing system may comprise an interface that receives a quadratic unconstrained binary optimization (QUBO) problem from a user, and a solver operatively coupled to the interface. The solver may solve the QUBO problem by a hybrid computer comprising a classical computer and a non-classical computer. The classical computer may comprise a digital processor and memory.

Abstract: The present disclosure provides methods, systems, and media for quantum computing, including allowing access to quantum ready and/or quantum enabled computers in a distributed computing environment (e.g., the cloud). Such methods and systems may provide optimization and computational services. Methods and systems of the present disclosure may enable quantum computing to be relatively and readily scaled across various types of quantum computers and users at various locations, in some cases without the need for users to have a deep understanding of the resources, implementation or the knowledge that may be required for solving optimization problems using a quantum computer. Systems provided herein may include user interfaces that enable users to perform data analysis in a distributed computing environment while taking advantage of quantum technology in the backend.

Abstract: A method and a system are disclosed for determining a hierarchical clustering for a group comprising a plurality of items.

Abstract: The present disclosure provides methods, systems, and media for allowing access to quantum ready and/or quantum enabled computers in a distributed computing environment (e.g., the cloud). Such methods and systems may provide optimization and computational services on the cloud. Methods and systems of the present disclosure may enable quantum computing to be relatively and readily scaled across various types of quantum computers and users at various locations, in some cases without the need for users to have a deep understanding of the resources, implementation or the knowledge that may be required for solving optimization problems using a quantum computer. Systems provided herein may include user interfaces that enable users to perform data analysis in a distributed computing environment while taking advantage of quantum technology in the backend.

Abstract: The present disclosure provides methods, systems, and media for quantum computing, including allowing access to quantum ready and/or quantum enabled computers in a distributed computing environment (e.g., the cloud). Such methods and systems may provide optimization and computational services. Methods and systems of the present disclosure may enable quantum computing to be relatively and readily scaled across various types of quantum computers and users at various locations, in some cases without the need for users to have a deep understanding of the resources, implementation or the knowledge that may be required for solving optimization problems using a quantum computer. Systems provided herein may include user interfaces that enable users to perform data analysis in a distributed computing environment while taking advantage of quantum technology in the backend.

Abstract: A method for solving a problem involving a hypergraph partitioning is disclosed, the method comprising receiving an indication of a problem involving a hypergraph partitioning; obtaining at least one property associated with a quadratic unconstrained binary optimization solver operatively coupled with the digital computer; formulating a partitioning problem of the hypergraph as an unconstrained binary optimization problem; reducing the unconstrained binary optimization problem into a quadratic unconstrained binary optimization problem; mapping the quadratic unconstrained binary optimization problem into the quadratic unconstrained binary optimization solver; obtaining from the quadratic unconstrained binary optimization solver at least one solution to the quadratic unconstrained binary optimization problem; applying a refinement procedure and translating the refined at least one solution to provide an indication of the partitioning and providing a solution to the problem.

Abstract: The present disclosure provides methods, systems, and media for allowing access to quantum ready and/or quantum enabled computers in a distributed computing environment (e.g., the cloud). Such methods and systems may provide optimization and computational services on the cloud. Methods and systems of the present disclosure may enable quantum computing to be relatively and readily scaled across various types of quantum computers and users at various locations, in some cases without the need for users to have a deep understanding of the resources, implementation or the knowledge that may be required for solving optimization problems using a quantum computer. Systems provided herein may include user interfaces that enable users to perform data analysis in a distributed computing environment while taking advantage of quantum technology in the backend.

Abstract: The present disclosure provides methods, systems, and media for allowing access to quantum ready and/or quantum enabled computers in a distributed computing environment (e.g., the cloud). Such methods and systems may provide optimization and computational services on the cloud. Methods and systems of the present disclosure may enable quantum computing to be relatively and readily scaled across various types of quantum computers and users at various locations, in some cases without the need for users to have a deep understanding of the resources, implementation or the knowledge that may be required for solving optimization problems using a quantum computer. Systems provided herein may include user interfaces that enable users to perform data analysis in a distributed computing environment while taking advantage of quantum technology in the backend.

Abstract: A method and a system are disclosed for determining a weight allocation in a group comprising a large plurality of items using an optimization oracle, the method comprising obtaining an indication of a plurality of data for each item of a large plurality of items; generating a covariance matrix for the plurality of data; generating a hierarchical tree structure having a plurality of clusters, each cluster having a corresponding item associated therewith, the generating comprising until there is one item associated per cluster of the hierarchical tree structure, recursively formulating an optimization problem to divide a given set of items into two different clusters, translating the formulated optimization problem into an unconstrained binary optimization problem, providing an indication of the unconstrained binary optimization problem to an optimization oracle, receiving an indication of at least one solution from the optimization oracle, assigning a cluster to each item of the given set of items using the a

Abstract: A method for solving a problem involving a hypergraph partitioning is disclosed, the method comprising receiving an indication of a problem involving a hypergraph partitioning; obtaining at least one property associated with a quadratic unconstrained binary optimization solver operatively coupled with the digital computer; formulating a partitioning problem of the hypergraph as an unconstrained binary optimization problem; reducing the unconstrained binary optimization problem into a quadratic unconstrained binary optimization problem; mapping the quadratic unconstrained binary optimization problem into the quadratic unconstrained binary optimization solver; obtaining from the quadratic unconstrained binary optimization solver at least one solution to the quadratic unconstrained binary optimization problem; applying a refinement procedure and translating the refined at least one solution to provide an indication of the partitioning and providing a solution to the problem.