Abstract: Described herein are quantum gradient algorithms that result in a quantum advantage over conventional methods. In an example, a quantum circuit is configured to implement a quantum gradient algorithm when executed on qubits of a quantum computing system. The quantum gradient algorithm includes a phase oracle OSƒm defined by a finite difference approximation with an order greater than zero, and a complexity of the quantum gradient algorithm scales as (?{square root over (k)}/?). The quantum circuit is repeatedly executed on qubits of a quantum computing system to determine a k-dimensional gradient of a function ƒ(x) within an error ? at point x0.

Abstract: Techniques of facilitating improved computational efficiency in Variational Quantum Eigensolver calculations by quantum computing devices. In one example, a system can comprise a processor that executes computer executable components stored in memory. The computer executable components can comprise: a distribution component; and a feedback component. The distribution component can set a Pauli-dependent sample budget for a Pauli term of an operator to unevenly distribute a total sample budget for evaluating an expected value of the operator among a plurality of Pauli terms composing the operator. The plurality of Pauli terms can comprise the Pauli term. The feedback component can evaluate compatibility between a prescreening variance for the Pauli term and a production variance of the Pauli term generated using the Pauli-dependent sample budget.

Abstract: One or more systems, computer-implemented methods and/or computer program products provided that can facilitate performing Boltzmann probability distribution sampling and determining a thermalization rate using quantum computing operations. A system can comprise a memory that stores computer-executable component, and a processor, operatively coupled to the memory, that executes computer-executable components. The computer-executable components can comprise a mapping component that maps a Fokker-Planck equation to a quantum problem comprising a first quantum operator, and a quantum computation component that, based on the mapping, second quantum operator as a function of a lowest eigenvalue of the first quantum operator, and wherein the quantum computation component further determines a thermalization rate as a function of the second quantum operator.

Abstract: Systems, computer-implemented methods, and computer program products to facilitate multireference parallelization of variational quantum computing to achieve high accuracy with short circuit depths. According to an embodiment, a system can comprise a processor that executes computer executable components stored in memory. The computer executable components comprise a trial component that prepares a multireference trial state based on a qubit operator, by applying a unitary circuit operator to a sum of selected initial configurations.

Abstract: Systems, computer-implemented methods, and computer program products to facilitate estimation of quantum resources to calculate an expectation value of a stochastic process using a re-parameterization method are provided. According to an embodiment, a system can comprise a processor that executes computer executable components stored in memory. The computer executable components can comprise a re-parameterization component that applies a quantum fault-tolerant operation to a variationally prepared quantum state corresponding to a probability distribution to produce a quantum state corresponding to a target probability distribution. The computer executable components can further comprise an estimation component that estimates at least one defined criterion of a quantum computer to be used to compute an expectation value of a stochastic process associated with the target probability distribution.

Abstract: Techniques of facilitating improved computational efficiency in Variational Quantum Eigensolver calculations by quantum computing devices. In one example, a system can comprise a processor that executes computer executable components stored in memory. The computer executable components can comprise: a distribution component; and a feedback component. The distribution component can set a Pauli-dependent sample budget for a Pauli term of an operator to unevenly distribute a total sample budget for evaluating an expected value of the operator among a plurality of Pauli terms composing the operator. The plurality of Pauli terms can comprise the Pauli term. The feedback component can evaluate compatibility between a prescreening variance for the Pauli term and a production variance of the Pauli term generated using the Pauli-dependent sample budget.