International Business Machines Corporation

Jsr Corporation

Stephen Peter Wood

Marco Pistoia

Shaohan Hu

Jay Michael Gambetta

Joseph W Ligman

Jennifer Ceil Lai

Rudy Raymond Harry Putra

Shimei Pan

Mercan Topkara

Jeffrey Scott Boston

Anni Rosa Coden

Zhen Wen

Peng Liu

Jie Lu

Kyungmin Lee

Richard Chen

Gegi Thomas

Antonio Mezzacapo

Omer Tripp

David M Lubensky

Leon Lumelsky

Ivano Tavernelli

Panagiotis Barkoutsos

Nelson R Manohar

Arthur Giuseppe Rattew

Gregory Louis Truty

John J Ponzo

Peter Hans Westerink

Nikolaj Moll

Gavin O Jones

Julia Elizabeth Rice

William Louis Luken

Joseph Latone

Pauline Ollitrault

Rajesh Balasubramanian

Edward Oliver Pyzer-Knapp

Mario Motta

Joe Ligman

Yuya Onishi

Systems, computer-implemented methods, and computer program products that can facilitate applying a reinforcement learning policy to available actions are described. According to an embodiment, a system can comprise a memory that stores computer executable components and a processor that executes the computer executable components stored in the memory. The computer executable components can comprise a state encoder that maps, based on one or more encoding parameters, a state of an environment on to one or more qubits of a quantum device. The system can further comprise a variational component that combines a reinforcement learning policy with a sampling of the one or more qubits, resulting, based on one or more variational parameters, in a probability distribution of a plurality of available actions at the state of the environment.

Quantum reinforcement learning agent

A method includes measuring an amplitude of a state of a quantum circuit, the amplitude corresponding to a first location in an object database. In the embodiment, the method includes executing, using a classical processor and a first memory, a verification operation, responsive to measuring the amplitude, to verify a target object in the first location. In the embodiment, the method includes re-measuring a second amplitude of a second state of the quantum circuit, the second amplitude having undergone a first plurality of amplitude amplifications, the second amplitude corresponding to a second location in the object database, the second location being verified as the target object, and wherein a total number of the first plurality of amplitude amplifications being less than a square root of a set of objects in the object database.

Automatic quantum searching of object databases

In an embodiment, a method includes measuring a first number of control qubits in a quantum algorithm, wherein a quantum circuit representation of the quantum algorithm includes a multiple-controlled-NOT gate. In an embodiment, a method includes measuring a second number of ancilla qubits in a quantum computer. In an embodiment, a method includes comparing the first number and the second number to determine an optimum compilation method for a quantum circuit. In an embodiment, a method includes compiling, in response to the comparison determining the second number is greater than one and less than the difference of the first number and 2, a quantum circuit from the quantum algorithm using a hybrid method.

Adaptive quantum circuit construction for multiple-controlled-not gates

Adaptive quantum circuit construction for multiple-controlled-NOT gates

A method for tracking user interactions with an application includes: storing the application in a memory of a mobile device, the application being associated with an instrumented widget and a library, the widget including an event logger; executing the application and the widget; receiving, through a user interface of the mobile device, an input corresponding to the event logger of the widget; logging, by the library, the input corresponding to the event logger of the widget in the memory of the mobile device; filtering a plurality of events, including the input corresponding to the event logger of the widget, to manage what data is reported to a monitor; and transmitting the input corresponding to the event logger of the widget to a server as monitored data.

Widget provisioning of user experience analytics and user interface / application management

Systems and methods that facilitate motion formalism utilizing quantum computing, to compute matrix operators in terms of commutators between qubit operators and measurements on the quantum hardware, wherein the commutators are computed utilizing symbolic calculus. Embodiments reduce computational cost of generalized eigenvalue synthesis relying on symbolic calculus and parallelization. Embodiments disclosed herein can also develop estimators of excited-states properties, considering constants of motion (e.g. spin) and non-constants of motions (e.g. dipoles, density matrices).

System-based extension of qEOM algorithm for quantum computation of excited-state properties

A method for bootstrapping a variational algorithm for quantum computing includes performing, using a quantum processor, a first iteration of a variational algorithm on a first wavefunction to compute a first expectation value of a first quantum system corresponding to a solution of the first iteration, the first wavefunction corresponding to a first quantum state of the first quantum system, the first expectation value comprising an energy of the first quantum state. The embodiment includes generating, based on the solution of the first iteration a second wavefunction as output of the first iteration of the variational algorithm, the second wavefunction corresponding to a second quantum state of the first quantum system. The embodiment includes performing, using the quantum processor, a second iteration of the variational algorithm on the second wavefunction to compute a second expectation value of a second quantum system, the second expectation value comprising an energy of a first quantum state of the second quantum system.

Bootstrapping a variational algorithm for quantum computing

A method of operating a mobile device includes displaying a user interface as an image, the user interface being composed of a plurality of widgets, storing a privacy policy identifying at least one of the widgets, capturing a screenshot image corresponding to the screenshot image, excluding the at least one of the widgets from the screenshot image to create a modified screenshot image, and transmitting the modified screenshot image over a network to a monitoring server.

Privacy-preserving user-experience monitoring

A method includes generating, as executed by a processor on a computer, a plurality of topic-specific user knowledge models for each user of a plurality of users, each topic-specific user knowledge model representing a level of knowledge possessed by a respective user on a single topic from a set of globally defined topics shared among the plurality of users, generating a plurality of topic-specific expert knowledge models, each topic-specific expert knowledge model representing an aggregate level of knowledge possessed by a plurality of expert users on a single topic from a set of globally defined topics shared among the plurality of users, comparing the topic-specific user knowledge model of the first user with the topic-specific expert knowledge model for a respective topic to determine a distance between a user knowledge level and an aggregate expert knowledge level for the topic.

Systems, methods, and computer program products for expediting expertise

A system includes a user model module that generates a plurality of topic-specific user knowledge models for each user of a plurality of users, each topic-specific user knowledge model representing a level of knowledge possessed by a respective user on a single topic from a set of globally defined topics shared among the plurality of users, a expertise model building module that generates a plurality of topic-specific expert knowledge models, each topic-specific expert knowledge model representing an aggregate level of knowledge possessed by a plurality of expert users on a single topic from a set of globally defined topics shared among the plurality of users, and a processor of a computer that executes instructions for comparing the topic-specific user knowledge model of the first user with the topic-specific expert knowledge model for a respective topic to determine a distance between a user knowledge level and an aggregate expert knowledge level for the topic.

Techniques regarding quantum algorithm concatenation are provided. For example, one or more embodiments described herein can comprise a system, which can comprise a memory that can store computer executable components. The system can also comprise a processor, operably coupled to the memory, and that can execute the computer executable components stored in the memory. The computer executable components can comprise a concatenation component, operatively coupled to the processor, that can concatenate a first quantum algorithm and a second quantum algorithm by using an output of the first quantum algorithm as an initial parameter in the second quantum algorithm.

Quantum algorithm concatenation

Facilitating code re-use includes receiving a first design document. The first user design document specifies a graphical layout of a first set of user interface elements of a user interface of a first application. First source code associated with the design document is received. The first source code is configured to implement the first set of user interface elements of the user interface. A processor extracts the first set of user interface elements from the first user interface design document. A first portion of the first source code corresponding to a first user interface element of the first set of user interface elements is identified. The first portion of the first source code is encapsulated into a module to enable re-use of the portion of the source code in a second application.

User interface code re-use based upon machine learning of design documents

In an embodiment, a method of estimating the cost of a software project comprising receiving natural language software descriptions and electronic source code files for respective completed software projects; storing, in a computer memory, an input set of functional labels and size data extracted from each of the source code files, the functional labels corresponding to labels in a software development library; training a natural language processing model to output a project set of functional labels for one of the source code files; training a regression analysis model to output a project size for the one of the source code files; predicting, using the natural language understanding model, a proposal set of functional labels; predicting, using the regression analysis model, a proposal size; and using the proposal size to calculate a proposal cost; and preparing a software development proposal that includes a natural language proposed-software description and the proposal cost.

Cognitive software development

Growing community of inventors

Thornwood, NY, United States of America

Stephen Peter Wood