International Business Machines Corporation

Airbnb, Inc.

Sailpoint Technologies Holdings, Inc.

David Louis Kaminsky

Ronald Patrick Doyle

David Mark Ogle

Richard Dean Telford

Xi Ning Wang

Mark N Wegman

John A Gunnels

John Michael Lake

Girish Sundaram

Neeraj Joshi

James Corvin Fletcher

Ying Liu

David Bruce Lindquist

Kathryn Heninger Britton

Richard Adam King

David Phillip Johnson

Jeffrey Scott Chase

Geoffrey Alexander Cohen

Bruce Dickson

Dinesh C Verma

Seraphin Bernard Calo

Xiping Wang

Rui Yin

Stephen C Baber

A Steven Krantz

Brian Blount

Ann Marie O'Meara

Marcia Lambert Peters Stockton

Patrick Joseph O'Sullivan

Al Chakra

Jay Michael Gambetta

Jun Zhang

John Alan Bivens

Si Bin Fan

Sandeep Kishan Singhal

Zheng Zhao

Timothy James Hahn

Marcia Lambert Peters

Jing Lu

David C Mckay

James P Gray

Zhe Yan

Ali Javadiabhari

Daniel A Gisolfi

Xiao Yan Tang

Bryan Eric Aupperle

Christina P Lau

Tian Zhang

Balachandar Rajaraman

Govindaraj Sampathkumar

David E Cox

Rodney A Smith

Xiao Long Chen

Ian Michael Holland

Thomas O Rowe

Zhiyong Li

Carl Shawn Kessler

Malcolm William Kilmer

Allen M Gilbert

Ramya H Prasad

Tao G Liu

Shao M Geng

Shuangtao Lv

Lori M Pilgrim

Lisa Seacat DeLuca

Steven Michael Miller

Sam Sampson Lightstone

Indrajit Poddar

Asit Dan

Paul Miller Bird

Stephen Glen Graham

John Joseph Rofrano

Diane Phylis Pozefsky

James M Mathewson, Ii

John William Sweitzer

Walid Rjaibi

Bala Rajaraman

Thai Quoc Tran

Kent Fillmore Hayes, Jr

Bruno Dos Santos Silva

Ronald Eugene Craig

Pratik Gupta

Vachaspathi Peter Kompella

Ron Williams

Yun Li Li

Lance D Bader

Jonathan Mayer Sobel

Na Dong

Angel Luis Diaz

Kyle M Smith

Jonathan Michael Seeber

Christina M Cruz

Carrie Weaver Searcey

Wendell Davis Jones

Eric Kirchstein

Keith Barber

Adam J Friedlander

Robert Hagan

Greg Kaszycki

Jonathan G Rossie

Systems, computer-implemented methods, and computer program products to facilitate quantum computing job scheduling 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 scheduler component that can determine a run order of quantum computing jobs based on one or more quantum based run constraints. The computer executable components can further comprise a run queue component that can store the quantum computing jobs based on the run order. In an embodiment, the scheduler component can determine the run order based on availability of one or more qubits comprising a defined level of fidelity.

Co-scheduling quantum computing jobs

An example operation may include one or more of generating an initial seed and allocating one or more authorized bits of the initial seed to a plurality of blocks in a distributed ledger, storing the initial seed and an identification of which authorized bits of the initial seed are allocated to each block of the distributed ledger, receiving a final seed value that is partially generated by each of a plurality of nodes configured to access the distributed ledger based on authorized bits of respective blocks updated by each respective node, and generating a random sequence value based on the final seed value and storing the random sequence value in a block of the distributed ledger.

Distributed ledger for generating and verifying random sequence

Techniques facilitating cached result use through quantum gate rewrite are provided. In one example, a computer-implemented method comprises converting, by a device operatively coupled to a processor, an input quantum circuit to a normalized form, resulting in a normalized quantum circuit; detecting, by the device, a match between the normalized quantum circuit and a cached quantum circuit among a set of cached quantum circuits; and providing, by the device, a cached run result of the cached quantum circuit based on the detecting.

Cached result use through quantum gate rewrite

A method for automatically training a machine learning system to detect and identify a sensor triggering event associated with an internet of things (IoT) device is provided. The method may include capturing sensor data and capturing sound clips associated with the IoT device. The method may further include identifying the sensor triggering event associated with the IoT device. The method may further include sending an alert of the identified sensor triggering event. The method may also include correlating the captured sensor data, the captured sound clips, and the identified sensor triggering event. The method may further include identifying a second sensor triggering event by determining similarities between the correlated data associated with the identified sensor triggering event and additional sensor and sound data that is captured based on the second sensor triggering event.

Sensor triggered sound clip capturing for machine learning

A method for adaptive error correction in quantum computing includes executing a calibration operation on a set of qubits, the calibration operation determining an initial state of a quantum processor. In an embodiment, the method includes estimating, responsive to determining an initial state of the quantum processor, a runtime duration for a quantum circuit design corresponding to a quantum algorithm, the quantum processor configured to execute the quantum circuit design. In an embodiment, the method includes computing an error scenario for the quantum circuit design. In an embodiment, the method includes selecting, using the error scenario and the initial state of the quantum processor, a quantum error correction approach for the quantum circuit design. In an embodiment, the method includes transforming the quantum algorithm into the quantum circuit design, the quantum circuit design including a set of quantum logic gates.

Adaptive error correction in quantum computing

A security incident is detected at a first location; a risk of the security incident is evaluated. A first security scores is generated for the first location. A set of security scores are generated for a set of alternative locations; the set of security scores excludes the first security score. A second security score within the set of security scores is determined to be the best security score among a plurality of security scores; the plurality of security scores comprises the set of security scores and the first security score. A workload associated with the first location is migrated to a second location, where the second location is associated with the second security score.

Security evaluation for computing workload relocation

Application behavior is analyzed to determine relationships between data. Database objects accessed by an application are identified. Then, one or more relationships between the identified database objects are determined based on one or more from a group comprising statements of the application referring to the identified database objects and sets of the identified database objects accessed by different modules of the application.

Analyzing application behavior to determine relationships between data

Rendering a web element in a web page in an integrated development environment is provided. A reference address is extracted from code of a web page. The reference address references a web element. The web element is obtained based on the reference address and in response to the reference address indicating that the web element is an embedded web element. The web element is added to a resource pool. The web element of the resource pool is rendered in the web page.

Rendering a web element in a web page

A method, system and computer program product for identifying anomalous behavior (e.g., suspicious transactions). Information from at least one social media source (e.g., a posting) and from at least one non-social media source (e.g., a booking) are monitored. A transaction (e.g., credit card transaction) involving a user is identified. The monitored information is then analyzed to identify one or more characteristics (e.g., location of the user) of the user. A rating of invalidity of the transaction is generated based on the one or more characteristics, where the rating of invalidity refers to the likelihood that the transaction is likely to be anomaly, such as a suspicious transaction. If the rating exceeds a threshold, then an anomaly may be said to have occurred. By identifying anomalous behavior using both social media and non-social media sources, anomalous activities that truly occurred will be more accurately detected.

Using both social media and non-social media information to identify anomalous behavior

A request for a content document is sent by a client device to a content server through a first network connection. A current network characteristic of the first network connection differs from a configured download constraint to download a content portion of the content document. A root document that omits the content portion of the content document and that includes a content stub is downloaded from the content server. The content stub identifies the content portion using a content identifier and specifies the configured download constraint. A network connection change to the content server from the first network connection to a second network connection that satisfies the configured download constraint to download the content portion of the content document is detected, and the content portion is downloaded using the second network connection and the content identifier within the content stub.

Network-aware structured content downloads

A method normalizes a page flow into a portlet. One or more processors generates a portlet based on webpages in the page flow. The webpages are linked together through a navigation control in the portlet to execute a specific business logic. The webpages in the page flow include a first webpage and a second webpage, which are linked via a Uniform Resource Locator (URL). The processor(s) build an intra-portlet action based on a linking relationship between the first and second webpages by the portlet. The intra-portlet action is based on the URL that links the first webpage to the second webpage. The URL is located in a JavaScript file for the portlet and indicates a relative path for the portlet. The processor(s) convert the URL indicating the relative path for the portlet into a URL indicating an absolute path, which includes an attached root path for the portlet.

Normalizing a page flow

Growing community of inventors

Durham, NC, United States of America

David Louis Kaminsky