Abstract: A method for calculating excited state properties of a molecular system using a hybrid classical-quantum computing system includes determining, using a quantum processor and memory, a ground state wavefunction of a combination of quantum logic gates. In an embodiment, the method includes forming a set of excitation operators. In an embodiment, the method includes forming a set of commutators from the set of excitation operators and a Hamiltonian operator. In an embodiment, the method includes mapping the set of commutators onto a set of qubit states, the set of qubit states corresponding to a set of qubits of the quantum processor. In an embodiment, the method includes evaluating, using the quantum processor and memory, the set of commutators. In an embodiment, the method includes causing a quantum readout circuit to measure an excited state energy from the set of computed commutators.

Abstract: Configuring a quantum computing system to determine a solution to an optimization problem includes encoding the optimization problem in an encoding language to produce an encoded optimization model. The encoded optimization model is transformed into a unconstrained model. The encoded optimization model includes an objective function having one or more terms. The one or more terms are converted to one or more Pauli terms. An Ising Hamiltonian is generated using the one or more terms. The Ising Hamiltonian corresponds to the optimization problem. An instruction indicative of the Ising Hamiltonian is provided to the quantum computing system.

Abstract: 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 extrapolation component that extrapolates a system parameter of a parameter set to determine a starting parameter value of a variational circuit. The computer executable components can further comprise a variational component that determines a system parameter value of the parameter set based on the starting parameter value.

Abstract: A mobile application design search method, system, and computer program product include detecting a feature in an uploaded design source files, generating keywords that describe each feature for design screens in the design source files, and creating a database including the feature and the keywords associated with the feature to enable a keyword search for a type of the feature that can be reused in a new application design source file.

Abstract: A workflow extraction method, system, and computer program product include analyzing, for each of the design screens, a relatability of one design screen to a previously analyzed design screen in the database and generating a tag that represents a workflow and creating a database linking the tag to a sequence of design screens from a transition graph that details how to move from one of the design screens to another.

Abstract: A method, including identifying over a set of classified applications a set of discriminating features, determining via code analysis, when a first application is subjected to classification, positions of the first application's code that correspond to discriminating features, and forwarding to a classification algorithm, such that according to its output the code fragments corresponding to the discriminating features are reported beyond a determination itself of the discriminating features.

Abstract: A system and method for static detection and categorization of information-flow downgraders includes transforming a program stored in a memory device by statically analyzing program variables to yield a single assignment to each variable in an instruction set. The instruction set is translated to production rules with string operations. A context-free grammar is generated from the production rules to identify a finite set of strings. An information-flow downgrader function is identified by checking the finite set of strings against one or more function specifications.

Abstract: Techniques facilitating generation of a fused kernel that can approximate a full kernel of a convolutional neural network are provided. In one example, a computer-implemented method comprises determining a first pattern of samples of a first sample matrix and a second pattern of samples of a second sample matrix. The first sample matrix can be representative of a sparse kernel, and the second sample matrix can be representative of a complementary kernel. The first pattern and second pattern can be complementary to one another. The computer-implemented method also comprises generating a fused kernel based on a combination of features of the sparse kernel and features of the complementary kernel that are combined according to a fusing approach and training the fused kernel.

Abstract: A program is executed that includes multiple script functions. For a selected script function, the following are performed during program execution. It is determined whether the selected script function should or should not be executed based on a utility corresponding to the selected script function. The utility was determined prior to determining whether the selected script function should be executed. The selected script function is executed in response to a determination the selected script function should be executed. Execution of the selected script function is skipped in response to a determination the selected script function should not be executed. These techniques may be applied in real-time to crawl a program such as a webpage or may be applied using offline learning followed by a real-time crawling of the program. Apparatus, methods, and program products are disclosed.

Abstract: A method for performing program analysis includes receiving programs of a first platform that have been assigned a first label and programs of the first platform that have been assigned a second label. Each of the programs of the first platform is expressed as platform-independent logical features. A discriminatory model or classifier is trained, using machine learning, based on the expression of the programs of the first platform as platform-independent logical features, to distinguish between programs of the first label and programs of the second label. An unlabeled program of a second platform is received and is expressed as platform-independent logical features. The trained discriminatory model or classifier is used to determine if the unlabeled program warrants the first label or the second label, based on the expression of the unlabeled program as platform-independent logical features.

Abstract: A method for parallelization of a numeric optimizer includes detecting an initialization of a numeric optimization process of a given function. The method computes a vector-distance between an input vector and a first neighbor vector of a set of neighbor vectors. The method predicts, using the computed vector-distance, a subset of the set of neighbor vectors. The method pre-computes, in a parallel processing system, a set of evaluation values in parallel, each evaluation value corresponding to one of the subset of the set of neighbor vectors. The method detects a computation request from the numeric optimization process, the computation request involving at least one of the set of evaluation values. The method supplies, in response to receiving the computation request, and without performing a computation of the computation request, a parallelly pre-computed evaluation value from the set of evaluation values to the numeric optimization process.

Abstract: A method for correcting perspective distortion includes acquiring a plurality of images of a given subject by at least one camera of a mobile device, wherein each of the images is taken using respective actual settings for the camera captured by at least one sensor of the mobile device. The method further includes processing the images and the respective actual settings for each of the images to synthesize a single image of the given subject, wherein the single image emulates using specified virtual settings for the camera. The method further comprises displaying the synthesized single image of the given subject to a user of the mobile device.

Abstract: A method for parallelization of a numeric optimizer includes detecting an initialization of a numeric optimization process of a given function. The method computes a vector-distance between an input vector and a first neighbor vector of a set of neighbor vectors. The method predicts, using the computed vector-distance, a subset of the set of neighbor vectors. The method pre-computes, in a parallel processing system, a set of evaluation values in parallel, each evaluation value corresponding to one of the subset of the set of neighbor vectors. The method detects a computation request from the numeric optimization process, the computation request involving at least one of the set of evaluation values. The method supplies, in response to receiving the computation request, and without performing a computation of the computation request, a parallelly pre-computed evaluation value from the set of evaluation values to the numeric optimization process.

Abstract: A method for quantum circuit compilation with quantum libraries includes receiving a set of quantum assembly language from a user, the quantum assembly language comprising reference to a quantum algorithm. In an embodiment, the method includes selecting a quantum device to execute the set of quantum assembly language. In an embodiment, the method includes selecting, responsive to the selected quantum device, an implementation of the quantum algorithm from a remote repository, the remote repository comprising a set of implementations of a set of quantum algorithms. In an embodiment, the method includes, compiling the quantum algorithm from the set of quantum assembly language. In an embodiment, the method includes executing, using the selected quantum device, the selected implementation of the quantum algorithm.

Abstract: Synthesizing sanitization code for applications based upon a probabilistic prediction model includes receiving a set of applications. The set of applications is partitioned into a first subset of applications and a second subset of applications. The first subset has one or more malicious payloads associated therewith, and the second subset has one or more non-malicious payloads associated therewith. A probabilistic prediction model is computed based upon the malicious payloads associated with the first subset of applications. One or more predicted malicious payloads are predicted from the probabilistic prediction model.

Abstract: In one or more embodiments described herein, device, computer-implemented methods, and/or computer program products that facilitate automated survey results generation from an image 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 image capturing component that captures a first sample image. The computer executable components can further comprise an image processing component that processes the first sample image to determine a survey count, wherein the survey count indicates a number of times a survey image was identified in the first sample image. The computer executable components can further comprise an authentication component that adjusts the survey count based on detection of a discrepancy.

Abstract: A method for performing program analysis includes receiving programs of a first platform that have been assigned a first label and programs of the first platform that have been assigned a second label. Each of the programs of the first platform is expressed as platform-independent logical features. A discriminatory model or classifier is trained, using machine learning, based on the expression of the programs of the first platform as platform-independent logical features, to distinguish between programs of the first label and programs of the second label. An unlabeled program of a second platform is received and is expressed as platform-independent logical features. The trained discriminatory model or classifier is used to determine if the unlabeled program warrants the first label or the second label, based on the expression of the unlabeled program as platform-independent logical features.

Abstract: An improved information tracking procedure is provided. A precise information tracking procedure is performed for a sensitive value when an application is predicted to modify the sensitive value prior to the sensitive value reaching a data sink. The sensitive value comprises an attribute that may be linked to external knowledge to reveal sensitive information about an individual. In response to the application not being predicted to modify the sensitive value prior to the sensitive value reaching the data sink, a value-based information tracking procedure is performed. The value-based information tracking procedure comprises storing one or more values that are observed at a data source, and then determining whether or not each of these one or more values are observed at the data sink.

Abstract: The subject disclosure relates generally to an automated testing tool for quantum software development kits (SDKs). A system in accordance with an embodiment comprises a memory that stores computer-executable components. A processor is operably coupled to the memory and executes the computer-executable components stored in the memory. The computer-executed components comprises: a transformation component that receives a qasm program and transforms the qasm program; a testing component that tests the transformed qasm program on the SDK; and a reporting component that reports whether a quantum SDK has functioned properly or failed for the transformed qasm program.

Abstract: 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.