International Business Machines Corporation

Prakash Murali

Shivkumar Kalyanaraman

Dilip Krishnaswamy

David C Mckay

Ali Javadiabhari

Ranjini Bangalore Guruprasad

Ranjini Bangalore

Nitisha Jain

Systems, computer-implemented methods, and computer program products to facilitate characterizing crosstalk of a quantum computing system based on sparse data collection are provided. 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 package component that packs subsets of quantum gates in a quantum device into one or more bins. The computer executable components can further comprise an assessment component that characterizes crosstalk of the quantum device based on a number of the one or more bins into which the subsets of quantum gates are packed.

Characterizing crosstalk of a quantum computing system based on sparse data collection

Systems, computer-implemented methods, and computer program products that facilitate instruction scheduling to mitigate quantum gate crosstalk errors and/or qubit decoherence errors in a quantum device based on device characterization data are provided. 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 an assessment component that obtains device characterization data of a quantum device. The computer executable components can further comprise a scheduler component that generates a quantum gate execution schedule comprising parallel execution and serial execution of quantum gates in the quantum device based on the device characterization data.

Instruction scheduling facilitating mitigation of crosstalk in a quantum computing system

Methods, systems, and computer program products for providing energy elasticity services via distributed virtual batteries are provided herein. A computer-implemented method includes grouping virtual energy storage resources from a distributed collection of virtual energy storage systems; partitioning the virtual energy storage resources of each virtual energy storage system into (i) a sub-set of the virtual energy storage resources allocated for participation in one or more local energy markets and (ii) a sub-set of the virtual energy storage resources allocated for participation in one or more geographically-distributed energy markets; scheduling, based at least in part on the grouping and the partitioning, an allocation of at least a portion of the virtual energy storage resources from the distributed collection of virtual energy storage systems to one or more geographically-distributed energy markets; and outputting the scheduled allocation to the distributed collection of multiple virtual energy storage systems.

Providing energy elasticity services via distributed virtual batteries

One embodiment provides a method, including: executing, using at least one processor, computer readable program code to: identify a plurality of possibilities at the disposal of a data center for changing its energy demand in its role as a consumer of energy, wherein each of the possibilities is associated with: a time interval during which change in energy consumption of the data center is to take place; and an amount of energy to be drawn, during the time interval, by the data center from an electric provider through a connection to a power grid; wherein the plurality of possibilities are different from each other; proactively determine, based on the identified plurality of possibilities, the ability of the data center to change its energy consumption, thereby changing the amount of energy drawn by the data center from the energy provider; and communicate, to a remote device that is in direct communication with an energy supplier, data indicating the ability of the data center to change its energy consumption.

System and method for a data center to provide energy elasticity services at different time scales

One embodiment provides a method, including: identifying an application executing across a plurality of processors, wherein the application generates communication messages between the plurality of processors; collecting, using a profiler, a plurality of samples of the messages, wherein the plurality of samples are collected at a predetermined sampling rate and wherein the collecting comprises interrupting the execution of the application to collect a sample; determining, using an adaptive sampling technique, if the sampling rate comprises a sampling rate that is sufficiently low while meeting a predetermined quality threshold; adjusting, based upon the sampling rate not comprising a sampling rate that is sufficiently low, the sampling rate, and then collecting samples until the sampling rate comprises the sampling rate that is sufficiently low while meeting a predetermined quality threshold; and building, using the collected samples, an output performance profile of the application.

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Princeton, NJ, United States of America

Prakash Murali