Abstract: Systems and methods for hybrid classical-quantum optimization using random matrix theory-based subproblem identification on correlation matrices are disclosed. A method may include a classical computer program: receiving a problem to optimize and time series data comprising a plurality of parameters; computing an average and a correlation matrix for the time series data; determining an aspect ratio for the correlation matrix; filtering the correlation matrix based on the aspect ratio and using a denoising solution; redefining the problem into a plurality of subproblems; determining that one of the plurality of subproblems exceeds a limit of a quantum computer; repeatedly dividing the subproblem until the limit of the quantum computer is met; embedding the subproblems on the quantum computer, wherein the quantum computer is configured to execute a quantum optimization routine on each of the subproblems and output a plurality of solution vectors; and recombining the plurality of solution vectors.

Abstract: Embodiments use quantum conditional logic in the Quantum Phase Estimation Algorithm (QPEA) to compute eigenvalues prior to inversion. Embodiments estimate the eigenvalues of a unitary, U=eiÂt, generated by a N×N Hermitian matrix Â. The binary representations of the n-bit estimations of eigenvalues of  may be encoded in these states: |?i=|b1b2 . . . bn; ?i is an estimation of the i-th eigenvalue, excluding degeneracy, and .b1b2 . . . bn is its binary representation. To perform the eigenvalue inversion, an n-qubit controlled Ry rotation with angle ?i/2(n?1) conditioned on seeing |b1b2 . . . bn is applied for each possible n-bit binary string b1b2 . . . bn (2n values). The overall unitary is called a “uniformly controlled Ry rotation” in literature.

Abstract: In some aspects, the techniques described herein relate to a method including: executing a machine learning model; providing a data transformation module of the machine learning model that outputs a transformed dataset; providing a sensitive attribute suppression module of the machine learning model that outputs a sensitive attribute suppression loss; providing an annotated useful attribute preservation module of the machine learning model that outputs an annotated useful attribute preservation loss; providing an unannotated useful attribute preservation module of the machine learning model that outputs an unannotated useful attribute preservation loss; combining the sensitive attribute suppression loss, the annotated useful attribute preservation loss, and the unannotated useful attribute preservation loss into a total loss; and training a neural network of the data transformation module and a neural network of the unannotated useful attribute preservation module using the total loss.

Abstract: Systems and methods for decision tree construction and update using quantum algorithms are disclosed. A method may include: receiving, by a classical computer program, a dataset comprising a plurality of training examples, each of the plurality of training examples having a plurality of features; loading, by a classical computer program, the dataset into a quantum accessible data structure; providing, by the classical computer program, the quantum accessible data structure to a quantum computer, wherein the quantum computer is configured to perform quantum estimation of a Pearson correlation coefficient on the dataset in the quantum accessible data structure to create a weighted dataset; clustering, by the classical computer program and the quantum computer, each of the plurality of training examples in the weighted dataset into one of a plurality of clusters; and selecting, by the classical computer program, a label for each of the plurality of clusters.

Abstract: A method may include: receiving, by a webserver computer program, shared key material shared with a client application; receiving from a browser, a request for a secure connection; establishing a session with the browser over a first secure connection; establishing a shared secret key with the browser, wherein the browser creates a browser secret key encrypted with the shared secret key, encrypts the browser secret key with the shared secret key, and provides the browser secret key encrypted with the shared secret key and session information the client application over a second secure connection that is protected with the shared key material; decrypting the browser secret key encrypted with the shared secret key using the shared secret key; identifying the session with the browser from the session information; and establishing, end-to-end encryption on top of the second secure connection using the browser secret key or a derivation thereof.

Abstract: A method for dynamic detection and presentation of obscured real-world objects in augmented or mixed reality virtual content may include an object of interest computer program executed by an electronic device: (1) receiving data for a virtual or augmented reality object to display on an image of a physical environment on a display of the electronic device; (2) receiving data for a physical object in the physical environment; (3) determining that the physical object is obscured by the virtual or augmented reality object; (4) generating a representation of the physical object; and (5) providing the representation of the physical object to a virtual reality or augmented reality computer program executed by the electronic device, wherein the virtual reality or augmented reality computer program is configured to display the physical object over the virtual or augmented reality object.

Abstract: 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.

Abstract: A method for removing uninterested attributes from multi-modality data may include: receiving, by a multi-modality attribute removal computer program executed by an electronic device, multi-modality data comprising a plurality of modalities from a data source, wherein data in each modality are related; receiving, by the multi-modality attribute removal computer program, an uninterested attribute in the multi-modality data to remove; training, by the multi-modality attribute removal computer program, a modality-focused encoder for each modality of the multi-modality data to remove the uninterested attribute using a removal loss and a retention loss for the respective modality; receiving, by the multi-modality attribute removal computer program, a multi-modality data set for processing; and processing, by the multi-modality attribute removal computer program, the multi-modality data set using the modality-focused encoders, wherein the processing results in a processed multi-modality data set with the uninterest

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: Systems and methods for bridging gaps in cryptographic secret distribution using line-of-sight-secured networks are disclosed. In one embodiment, a system may include: a first physical location providing a cryptographic secret; a second physical location comprising a space-based vehicle transceiver that receives the cryptographic secret from the first physical location over a secure communication channel; a space-based vehicle that receives the cryptographic secret from the second physical location over a first line-of-sight communication channel; and a third physical location that receives the cryptographic secret from the space-based vehicle over a second line-of-sight communication channel, encrypts data with the cryptographic secret, and communicates the encrypted data to the first physical location over a communication network; wherein the first physical location receives the encrypted data and decrypts the encrypted data using the cryptographic secret.

Abstract: Systems and methods for secure cryptographic secret distribution are disclosed. In one embodiment, a method for secure cryptographic secret distribution may include: (1) receiving, at a key relay station, a cryptographic secret from a webserver over a first communication network; (2) storing, by the key relay station, the cryptographic secret; (3) authenticating, by the key relay station, an end user via an end user electronic device; and (4) securely communicating, by the key relay station, the cryptographic secret to the end user electronic device. The end user electronic device is configured to store the cryptographic secret in secure storage on the end user electronic device, to encrypt data with the cryptographic secret, and to communicate the encrypted data to the webserver over a second communication network.

Abstract: Systems and methods for low-cost simulation of quantum algorithms are disclosed. A method may include a quantum computer simulator computer program: (1) receiving a compact description of a problem and an objective to evaluate, a first circuit parameter, and a second circuit parameter; (2) precomputing a diagonal vector comprising diagonal elements of a phase Hamiltonian; (3) initializing a state vector; (4) applying a phase operator to the state vector with the first circuit parameter; (5) applying a mixing operator to the state vector with the second circuit parameter; (6) reading the state vector; (7) computing a quality of the state vector based on the objective; and (8) updating the first circuit parameter and the second circuit parameter based on the quality.

Abstract: Systems and methods for efficient error mitigation in quantum circuit execution using parity checks and classical feedback are disclosed.

Abstract: Systems and methods for quantum key distribution (QKD) secured vault-based application-to-application communication are disclosed. A method may include: receiving, at a vault application at a first facility, a request for a shared quantum key for communication of a secret in a vault at the first facility to an application at a second facility; distilling, by quantum devices at the first and the second facility and over a quantum communication channel, a shared quantum key using a QKD protocol; receiving, by an encryptor at the first facility, the secret; encrypting, by the encryptor at the first facility, the secret with the shared quantum key, communicating, the encrypted secret to the second facility over a communication network; decrypting, by an encryptor at the second facility, the encrypted secret with the shared quantum key; and receiving, by the application at the second facility, the secret from the encryptor at the second facility.

Abstract: Systems and methods for wayfinding in hazardous environments are disclosed. In one embodiment, a method for wayfinding in a hazardous environment may include: (1) receiving, at an emergency response computer program executed by an electronic device, a plurality of real time streams of data, each real time stream of data from a sensing device in an area; (2) detecting, by the emergency response computer program, an alarm condition in the area based on the real-time streams of data; (3) determining, by the emergency response computer program, that the alarm condition satisfies an alarm condition rule; (4) calculating, by the emergency response computer program, a plurality of routes to an egress point from the area; and (5) controlling, by the emergency response computer program, a digital signage in the area to display one of the plurality of routes the egress point.

Abstract: A method and method for testing an application includes performing a static analysis of metadata of coding of an application, using a test application program executed by a processor on a computer. Available user interface states are simulated based on the static analysis. A configuration file of the application is accessed and parsed to enumerate states possible for the application. A coverage metric is calculated for the application based on a number of states reached by the simulating and a number of states possible.

Abstract: A hybrid classical-quantum computing device to execute a quantum circuit corresponding to a variational problem, is configured. The configuring further comprises causing the hybrid classical-quantum computing device to execute the quantum circuit by performing an adiabatic progression operation, wherein the adiabatic progression operation comprises increasing the difficulty of the variational problem from a simplified version of the problem to the variational problem.

Abstract: A hybrid classical-quantum computing device to execute a quantum circuit corresponding to a variational problem, is configured. The configuring further comprises causing the hybrid classical-quantum computing device to execute the quantum circuit by performing an adiabatic progression operation, wherein the adiabatic progression operation comprises increasing the difficulty of the variational problem from a simplified version of the problem to the variational problem.

Abstract: Systems and methods for efficient error mitigation in quantum circuit execution using parity checks and classical feedback are disclosed.

Abstract: 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.