Abstract: A quantum computer prepares system qubits into respective selected states by obtaining an initial steering circuit. The initial steering circuit is a quantum circuit comprising one or more quantum interactions between at least one detector qubit and the system qubits that is performable by the quantum computer. The quantum computer performs one or more iterations of causing the at least one detector qubit to be initialized into an initial detector state, causing performance of the steering circuit, and causing measurement of the at least one detector qubit. The quantum computer determines that the one or more system qubits are in the respective selected states. The quantum computer may then use the system qubits in performance of a quantum program. The initial steering circuit may be determined using a machine learning algorithm to determine parameters of a parameterized unitary operator enacted thereby. The steering circuit may be updated on each iteration.

Abstract: A system includes a plurality of qubits; a qubit manipulation system for controlling evolution of respective quantum states of the qubits; a measurement system for performing measurement of qubit quantum states; and a controller for controlling operation of the qubit manipulation system and receiving measurement results from the measurement system. The controller is configured to cause the qubit manipulation system to execute a first portion of a program circuit and an assertion circuit; and receive measurement results that indicate a quantum state of an ancilla qubit used in performing a comparison test between an assertion qubit on which an assertion channel of the assertion circuit was performed and system qubits on which the first portion of the program circuit was performed. The controller is further configured to process the measurement results to determine a noise status of the system; and provide an indication of the noise status.

Abstract: A quantum computer prepares a logical qubit in a selected state by obtaining a steering circuit. The steering circuit is a quantum circuit comprising one or more quantum interactions between at least one detector qubit and at least one system qubit that is performable by the quantum computer. The quantum computer comprises a plurality of physical qubits that includes the at least one detector qubit and the at least one system qubit. The quantum computer performs one or more iterations of causing one or more detector qubits of the plurality of physical qubits to be initialized into an initial state, causing performance of the steering circuit, and causing measurement of the one or more detector qubits. The quantum computer determines that the logical qubit is in the selected state. The quantum computer may then use the logical qubit in performance of a quantum program.

Abstract: A quantum computer prepares system qubits into respective selected states by obtaining an initial steering circuit. The initial steering circuit is a quantum circuit comprising one or more quantum interactions between at least one detector qubit and the system qubits that is performable by the quantum computer. The quantum computer performs one or more iterations of causing the at least one detector qubit to be initialized into an initial detector state, causing performance of the steering circuit, and causing measurement of the at least one detector qubit. The quantum computer determines that the one or more system qubits are in the respective selected states. The quantum computer may then use the system qubits in performance of a quantum program. The initial steering circuit may be determined using a machine learning algorithm to determine parameters of a parameterized unitary operator enacted thereby. The steering circuit may be updated on each iteration.

Abstract: An example embodiment may involve persistent storage containing definitions of (i) assignments of bots to endpoints, (ii) software packages for execution by the bots, (iii) schedules for the bots to execute the software packages, and (iv) processes that associate the bots with the software packages and the schedules. This embodiment may also involve processors configured to: receive, from a computing device, a request for bot deployment, wherein the computing device includes a bot runtime; identify, in the processes, a bot assigned to an endpoint that is associated with the computing device, wherein the bot is associated with a software package and a schedule; and transmit, to the computing device, data including a representation of the bot, a copy of the software package, and a copy of the schedule, wherein reception of the data causes the bot to execute, using the bot runtime, the software package in accordance with the schedule.

Abstract: Example embodiments relate to parallelized exception handling for large datasets. One example embodiment includes a method. The method includes retrieving one or more sets of entries to be analyzed. The method also includes selecting an available computing resource. In addition, the method includes causing the available computing resource to perform an analysis of each entry within the respective set of entries to identify previously defined exceptions. Further, the method includes causing, for each entry within the respective set of entries, a list of exceptions associated with the respective entry to be created or updated based on the analysis. Additionally, the method includes causing, for each entry within the respective set of entries, metadata associated with the respective entry to be updated when the list of exceptions associated with the respective entry indicates that no exceptions are associated with the respective entry.

Abstract: Example embodiments relate to parallelized exception handling for large datasets. One example embodiment includes a method. The method includes retrieving one or more sets of entries to be analyzed. The method also includes selecting an available computing resource. In addition, the method includes causing the available computing resource to perform an analysis of each entry within the respective set of entries to identify previously defined exceptions. Further, the method includes causing, for each entry within the respective set of entries, a list of exceptions associated with the respective entry to be created or updated based on the analysis. Additionally, the method includes causing, for each entry within the respective set of entries, metadata associated with the respective entry to be updated when the list of exceptions associated with the respective entry indicates that no exceptions are associated with the respective entry.

Abstract: Embodiments provide for side-channel leakage evaluation of asymmetric key cryptography algorithms. An example method includes identifying inputs, constraints, and a sequence of steps involved in an algorithm of a design specification; generating input test vectors, wherein the input test vectors are associated with a secrecy guarantee of the algorithm; generating a testbench for simulation of the design specification; generating power traces by simulating the design specification; performing a leakage assessment on generated power profiles; generating a divergence factor; and determining whether the design specification has a side-channel vulnerability.

Abstract: An example embodiment may involve persistent storage containing definitions of (i) assignments of bots to endpoints, (ii) software packages for execution by the bots, (iii) schedules for the bots to execute the software packages, and (iv) processes that associate the bots with the software packages and the schedules. This embodiment may also involve processors configured to: receive, from a computing device, a request for bot deployment, wherein the computing device includes a bot runtime; identify, in the processes, a bot assigned to an endpoint that is associated with the computing device, wherein the bot is associated with a software package and a schedule; and transmit, to the computing device, data including a representation of the bot, a copy of the software package, and a copy of the schedule, wherein reception of the data causes the bot to execute, using the bot runtime, the software package in accordance with the schedule.

Abstract: Embodiments herein provide a method for providing personalized response suggestions to a user for a notification event using an electronic device. The method includes detecting the notification event associated with a user. The method includes authenticating presence of the user for the notification event based on Ultra-Wide Band (UWB) signal data obtained from the electronic device and/or one or more IoT devices. The method includes determining current activity of the user based on the UWB signal data in response to a successful authentication. The method includes correlating the current activity with a plurality of activities performed by the user in past, and a past interaction pattern of the user in connection with events substantially similar to nature of the notification event. The method includes generating one or more auto response suggestions for the notification event as a result of correlation.

Abstract: An example embodiment may involve persistent storage containing definitions of (i) assignments of bots to endpoints, (ii) software packages for execution by the bots, (iii) schedules for the bots to execute the software packages, and (iv) processes that associate the bots with the software packages and the schedules. This embodiment may also involve processors configured to: receive, from a computing device, a request for bot deployment, wherein the computing device includes a bot runtime; identify, in the processes, a bot assigned to an endpoint that is associated with the computing device, wherein the bot is associated with a software package and a schedule; and transmit, to the computing device, data including a representation of the bot, a copy of the software package, and a copy of the schedule, wherein reception of the data causes the bot to execute, using the bot runtime, the software package in accordance with the schedule.

Abstract: An example embodiment may involve persistent storage containing definitions of (i) assignments of bots to endpoints, (ii) software packages for execution by the bots, (iii) schedules for the bots to execute the software packages, and (iv) processes that associate the bots with the software packages and the schedules. This embodiment may also involve processors configured to: receive, from a computing device, a request for bot deployment, wherein the computing device includes a bot runtime; identify, in the processes, a bot assigned to an endpoint that is associated with the computing device, wherein the bot is associated with a software package and a schedule; and transmit, to the computing device, data including a representation of the bot, a copy of the software package, and a copy of the schedule, wherein reception of the data causes the bot to execute, using the bot runtime, the software package in accordance with the schedule.

Abstract: Embodiments herein provide a method for providing personalized response suggestions to a user for a notification event using an electronic device. The method includes detecting the notification event associated with a user. The method includes authenticating presence of the user for the notification event based on Ultra-Wide Band (UWB) signal data obtained from the electronic device and/or one or more IoT devices. The method includes determining current activity of the user based on the UWB signal data in response to a successful authentication. The method includes correlating the current activity with a plurality of activities performed by the user in past, and a past interaction pattern of the user in connection with events substantially similar to nature of the notification event. The method includes generating one or more auto response suggestions for the notification event as a result of correlation.

Abstract: A computing system includes a server. The server is communicatively coupled to a data repository and is configured to store a data in the data repository. The server is further configured to create a server instance, wherein the server instance is associated with a user. The server is additionally configured to create a session based on an external entity requesting a resource from the server instance, and to execute a bot detection logic to determine if the external entity is a bot. If the external entity is a bot then the server is configured to perform a bot-based action, wherein the server is configured to provide for multi-instance support to a plurality of users.

Abstract: A computing system includes a server. The server is communicatively coupled to a data repository and is configured to store a data in the data repository. The server is further configured to create a server instance, wherein the server instance is associated with a user. The server is additionally configured to create a session based on an external entity requesting a resource from the server instance, and to execute a bot detection logic to determine if the external entity is a bot. If the external entity is a bot then the server is configured to perform a bot-based action, wherein the server is configured to provide for multi-instance support to a plurality of users.

Abstract: A system implements user permissions and user subscriptions with regard to content posted on one or more peer-to-peer knowledge sharing platforms (e.g., Community pages). Permissions are assigned to groups of users, rather than individual users. Permissions are determined by the groups of which the user in question is a member.

Abstract: The present approach relates to updating a customer-extended application in such a manner that customer extensions of certain widgets in the application are preserved thorough the update. A cloud-computing system may facilitate customer extension of a widget of an initial version of the application by providing a first subset of script associated with one or more extension point hooks, such that the first subset of the script may receive customer script to extend the widget. In this manner, customers may extend aspects of the widget by modifying the script via the one or more extension point hooks to cater those extensible widgets to specific customer needs in a manner that can be maintained as updates occur over time, which may allow the customer to save time and resources that would otherwise be consumed by modifying the application after the enterprise upgrades the application.

Abstract: A system implements user permissions and user subscriptions with regard to content posted on one or more peer-to-peer knowledge sharing platforms (e.g., Community pages). Permissions are assigned to groups of users, rather than individual users. Permissions are determined by the groups of which the user in question is a member.

Abstract: A system implements user permissions and user subscriptions with regard to content posted on one or more peer-to-peer knowledge sharing platforms (e.g., Community pages). Permissions are assigned to groups of users, rather than individual users. Permissions are determined by the groups of which the user in question is a member.

Abstract: A system implements user permissions and user subscriptions with regard to content posted on one or more peer-to-peer knowledge sharing platforms (e.g., Community pages). Permissions are assigned to groups of users, rather than individual users. Permissions are determined by the groups of which the user in question is a member.