Abstract: Systems and methods that facilitate quantum state preparation of a probability distribution and constructing a quantum operator for a stochastic process based on quantum state to facilitate quantum amplitude estimation. A loading component uses a context-aware distribution loading scheme to load arbitrary random distributions to facilitate preparing a quantum state of a probability distribution based on a structure of a quantum amplitude estimation algorithm, and an operating component constructs a quantum operator for arbitrary computable functions or stochastic processes based on the quantum state to perform quantum amplitude estimation.

Abstract: Systems and methods that address an optimized method to improve system and method for handling inequality constraints in mixed binary optimization problems on quantum computers and to solve local optima which significantly improves system performance. Embodiments employ an improved methodology that can optimize parameters, determine an optimal slack variable and optimize variational parameters for fixed slack variables. This procedure allows to move out of local minima, solve an optimization and improve th system performance by providing optimal results. These embodiments also extend to variational hybrid quantum/classical algorithms for gate-based quantum computers.

Abstract: Systems, computer-implemented methods, and computer program products to facilitate quantum state preparation of a probability distribution to perform amplitude estimation 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 data loader component that prepares a quantum state of a probability distribution based on structure of a quantum amplitude estimation algorithm. The computer executable components can further comprise an operator component that constructs a quantum operator based on the quantum state to perform quantum amplitude estimation.

Abstract: Systems and methods that address an optimized method to handle portfolio constraints such as integer budget constraints and solve portfolio optimization problems that map both to mixed binary and quadratic binary optimization problems. A digital processor is used to create a hierarchical clustering; this clustering is leveraged to allocate capital to sub-clusters of the hierarchy. Once the sub-clusters are sufficiently small, a quantum processor is used to solve the portfolio optimization problem. Thus, the innovation employs clustering to reduce an optimization problem to sub-problems that are sufficiently small enough to be solved using a quantum computer given available qubits.

Abstract: Techniques regarding determining a three-dimensional structure of a heteropolymer are provided. For example, one or more embodiments described herein can comprise a system, which can comprise a memory that can store computer executable components. The system can also comprise a processor, operably coupled to the memory, and that can execute the computer executable components stored in the memory. The computer executable components can comprise a polymer folding component that can generate a course-grained model to determine a three-dimensional structure of a heteropolymer based on a first qubit registry that encodes a conformation of the heteropolymer on a lattice and a second qubit registry that encodes an interaction distance between monomers comprised within the heteropolymer.

Abstract: Solving mixed integer problems using a hybrid classical-quantum computing system includes generating a plurality of decision variables for a function associated with a combinatorial optimization problem by a first processor using an optimizer, and deriving at least one quantum state parameter for a quantum processor based upon one or more of the decision variables. The quantum processor is initiated in a quantum state based upon the at least one quantum state parameter. A plurality of intermediate quantum states of the quantum processor are measured using a plurality of quantum measurements of the quantum state to obtain a plurality of samples. The plurality of samples are evaluated by the first processor to obtain a measure of a quality of the quantum state and of one or more solutions to the combinatorial optimization problem.

Abstract: Techniques and a system to facilitate simulation-based optimization on a quantum computer are provided. In one example, a system includes a quantum processor. The quantum processor performs a quantum amplitude estimation process based on a probabilistic distribution associated with a decision-making problem. Furthermore, the quantum processor includes a simulator that simulates the decision-making problem based on the quantum amplitude estimation process.

Abstract: A method of designing a molecule for an environment of interest using a quantum computer includes providing a linear superposition of a plurality of molecular species, the plurality of molecular species being initially weighted by equal initial coefficients; determining a lowest-energy quantum state for the superposition of the plurality of molecular species in a vacuum environment and in the environment of interest using a quantum optimization process; calculating a difference in lowest energy states between the vacuum environment and the environment of interest for each molecular species to provide a cost of the superposition of the plurality of molecular species; performing a quantum optimization process to determine a minimum cost for the superposition of the plurality of molecular species and to determine updated coefficients weighting the plurality of molecular species; and identifying the molecule for the environment of interest based on a comparison of the updated coefficients.

Abstract: The technology described herein is directed towards quantum circuits used to analyze risk, including expected value, variance, value at risk and conditional value at risk metrics. Aspects can comprise modeling uncertainty of one or more random variables to provide a first quantum sub-circuit by mapping the one or more variables to quantum states represented by a selected number of qubits using quantum gates, and encoding a risk metric into a second quantum sub-circuit, the second quantum sub-circuit comprising a first ancilla qubit and Y-rotations controlled by one or more other qubits. Further aspects can comprise performing amplitude estimation based on the first sub-circuit and the second sub-circuit to extract a probability value corresponding to the risk metric, wherein the probability value represents a probability of measuring a one state in the ancilla qubit.

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: Solving mixed integer problems using a hybrid classical-quantum computing system includes generating a plurality of decision variables for a function associated with a combinatorial optimization problem by a first processor using an optimizer, and deriving at least one quantum state parameter for a quantum processor based upon one or more of the decision variables. The quantum processor is initiated in a quantum state based upon the at least one quantum state parameter. A plurality of intermediate quantum states of the quantum processor are measured using a plurality of quantum measurements of the quantum state to obtain a plurality of samples. The plurality of samples are evaluated by the first processor to obtain a measure of a quality of the quantum state and of one or more solutions to the combinatorial optimization problem.

Abstract: A method for enhancing hybrid-classical algorithms for combinatorial optimization includes executing, on a quantum processor, a variational algorithm, the execution producing a subset of a set of solutions (solution space) of the variational algorithm within a predefined period, the variational algorithm computing a quantum state of a quantum system corresponding to a combinatorial optimization problem, each solution in the subset having a corresponding value; sorting, according to a sorting criterion, the subset of solutions; isolating, based on the sorting, a portion of the subset of solutions wherein a value corresponding to each solution in the portion is within a boundary defined by a threshold value; computing an average value of the solutions from the portion of the subset of solutions; and altering the variational algorithm to produce a second subset of solutions such that the second subset of solutions comprises solutions having values within the boundary.

Abstract: A method for enhancing hybrid-classical algorithms for combinatorial optimization includes executing, on a quantum processor, a variational algorithm, the execution producing a subset of a set of solutions (solution space) of the variational algorithm within a predefined period, the variational algorithm computing a quantum state of a quantum system corresponding to a combinatorial optimization problem, each solution in the subset having a corresponding value; sorting, according to a sorting criterion, the subset of solutions; isolating, based on the sorting, a portion of the subset of solutions wherein a value corresponding to each solution in the portion is within a boundary defined by a threshold value; computing an average value of the solutions from the portion of the subset of solutions; and altering the variational algorithm to produce a second subset of solutions such that the second subset of solutions comprises solutions having values within the boundary.

Abstract: Techniques for facilitating utilizing a quantum computing circuit in conjunction with a stochastic control problem are provided. In one embodiment, a system is provided that comprises a quantum computing circuit that prepares a quantum state that represents a stochastic control problem. The system can further comprise a classical computing device that determines parameters for the quantum computing circuit.

Abstract: The technology described herein is directed towards quantum circuits used to analyze risk, including expected value, variance, value at risk and conditional value at risk metrics. Aspects can comprise modeling uncertainty of one or more random variables to provide a first quantum sub-circuit by mapping the one or more variables to quantum states represented by a selected number of qubits using quantum gates, and encoding a risk metric into a second quantum sub-circuit, the second quantum sub-circuit comprising a first ancilla qubit and Y-rotations controlled by one or more other qubits. Further aspects can comprise performing amplitude estimation based on the first sub-circuit and the second sub-circuit to extract a probability value corresponding to the risk metric, wherein the probability value represents a probability of measuring a one state in the ancilla qubit.

Abstract: The present invention relates to compounds and methods useful for the detection and treatment of disorders associated with frameshift mutations in coding microsatellite regions. The compounds and methods are applicable in cancers, especially of DNA mismatch repair deficient (MMR) sporadic tumors and HNPCC associated tumors. The compounds are useful for detection of disorders and in therapy such as immuno-therapy. The diagnostic methods relate to diagnosis and prognostic assessment of disorders associated with frameshift polypeptides originating from frameshift mutations in coding microsatellite regions of genes based on the detection of immunological entities directed against said frameshift polypeptides in body fluids.

Abstract: A piston pump, in particular high-pressure fuel pump, has a cylinder liner and at least one coupling element. The at least one coupling element is fastened to the cylinder liner for the retention of a valve device. The at least one coupling element is a tubular sleeve.

Abstract: The invention relates to a clamping device (1), for example swing tensioners (1), bracing elements, machine vises or block cylinders, with a movable clamping element (2) for clamping a workpiece with a defined clamping force, and with an electric motor (10) for mechanically driving the clamping element (2), also with a control unit that controls the electric motor (10). The invention provides that the control unit detects an electrical operating parameter of the electric motor (10) as a measure of the clamping force. The contact of the clamping element with the workpiece is detected in this manner. Subsequently, the electric motor (10) is then driven further by a defined number of revolutions, the number of revolutions after contact with the workpiece defining the clamping force. The invention further comprises a corresponding control method.

Abstract: The present invention relates to compounds and methods useful for the detection and treatment of disorders associated with frameshift mutations in coding microsatellite regions. The compounds and methods are applicable in cancers, especially of DNA mismatch repair deficient (MMR) sporadic tumors and HNPCC associated tumors. The compounds are useful for detection of disorders and in therapy such as immuno-therapy. The diagnostic methods relate to diagnosis and prognostic assessment of disorders associated with frameshift polypeptides originating from frameshift mutations in coding microsatellite regions of genes based on the detection of immunological entities directed against said frameshift polypeptides in body fluids.

Abstract: According to an exemplary embodiment, a computer-implemented method for attempting to optimize a supply chain network (SCN) includes forecasting demand in the SCN based on a set of demand data. One or more time-dependent reorder points (ROPs) deemed to optimize the SCN are generated by a computer processor, based on the demand forecast, where each time-dependent ROP represents an ROP that changes over time. A simulation of operations of the SCN is performed, using the time-dependent ROPs.