The disclosure describes various aspects of techniques for using global interactions in efficient quantum circuit constructions. More specifically, this disclosure describes ways to use a global entangling operator to efficiently implement circuitry common to a selection of important quantum algorithms. The circuits may be constructed with global Ising entangling gates (e.g., global Mølmer-Sørenson gates or GMS gates) and arbitrary addressable single-qubit gates. Examples of the types of circuits that can be implemented include stabilizer circuits, Toffoli-4 gates, Toffoli-n gates, quantum Fourier transformation (QTF) circuits, and quantum Fourier adder (QFA) circuits. In certain instances, the use of global operations can substantially improve the entangling gate count.

The disclosure describes various aspects of techniques for using global interactions in efficient quantum circuit constructions. More specifically, this disclosure describes ways to use a global entangling operator to efficiently implement circuitry common to a selection of important quantum algorithms. The circuits may be constructed with global Ising entangling gates (e.g., global Mølmer-Sørenson gates or GMS gates) and arbitrary addressable single-qubit gates. Examples of the types of circuits that can be implemented include stabilizer circuits, Toffoli-4 gates, Toffoli-n gates, quantum Fourier transformation (QTF) circuits, and quantum Fourier adder (QFA) circuits. In certain instances, the use of global operations can substantially improve the entangling gate count.

A method for searching data includes storing a probe data and a target data expressed in a first orthogonal domain. The target data includes potential probe match data each characterized by the length of the target data. The probe data representation and the target data are transformed into an orthogonal domain. In the orthogonal domain, the target data is encoded with modulation functions to produce a plurality of encoded target data, each of the modulation functions having a position index corresponding to one of the potential probe match data. The plurality of encoded target data is interfered with the probe data in the orthogonal domain and an inverse transform result is obtained. If the inverse transform result exceeds a threshold, information is output indicating a match between the probe data and a corresponding one of the potential probe match data.

Embodiments described herein include systems and techniques for converting (i.e., transducing) a quantum-level (e.g., single photon) signal between the three wave forms (i.e., optical, acoustic, and microwave). A suspended crystalline structure is used at the nanometer scale to accomplish the desired behavior of the system as described in detail herein. Transducers that use a common acoustic intermediary transform optical signals to acoustic signals and vice versa as well as microwave signals to acoustic signals and vice versa. Other embodiments described herein include systems and techniques for storing a qubit in phonon memory having an extended coherence time. A suspended crystalline structure with specific geometric design is used at the nanometer scale to accomplish the desired behavior of the system.

A quantum circuit that is a quantum random access memory that can write basis states of a weighted superposition in real time into a memory cell or a superposition of memory cells. The quantum circuit is a quantum random access memory that can write a prepared superposition. The quantum circuit is a quantum random access memory that can write classical data.

A quantum circuit that is a quantum random access memory that can write basis states of a weighted superposition in real time into a memory cell or a superposition of memory cells. The quantum circuit is a quantum random access memory that can write a prepared superposition. The quantum circuit is a quantum random access memory that can write classical data.

A Heisenberg scaler reduces noise in quantum metrology and includes: a stimulus source that provides physical stimuli; a physical system including quantum sensors that receive a first and second physical stimuli; produces a measured action parameter; receives an perturbation pulse; and produces modal amplitude; an estimation machine that: receives the measured action parameter and produces a zeroth-order value from the measured action parameter; a gradient analyzer that: receives the measured action parameter and produces the measured action parameter and a gradient; the sensor interrogation unit that: receives the modal amplitude; receives the gradient and the measured action parameter; produces the perturbation pulse; and produces a first-order value from the modal amplitude, the gradient, and the measured action parameter; a Heisenberg determination machine that: receives the zeroth-order value; receives the first-order value; and produces a physical scalar from the zeroth-order value and the first-order value.

A Heisenberg scaler reduces noise in quantum metrology and includes: a stimulus source that provides physical stimuli; a physical system including quantum sensors that receive a first and second physical stimuli; produces a measured action parameter; receives an perturbation pulse; and produces modal amplitude; an estimation machine that: receives the measured action parameter and produces a zeroth-order value from the measured action parameter; a gradient analyzer that: receives the measured action parameter and produces the measured action parameter and a gradient; the sensor interrogation unit that: receives the modal amplitude; receives the gradient and the measured action parameter; produces the perturbation pulse; and produces a first-order value from the modal amplitude, the gradient, and the measured action parameter; a Heisenberg determination machine that: receives the zeroth-order value; receives the first-order value; and produces a physical scalar from the zeroth-order value and the first-order value.

A method of performing an inference task on a knowledge graph comprising semantic triples of entities, wherein entity types are subject, object and predicate, and wherein each semantic triple comprises one of each entity type, using a quantum computing device, wherein a first entity of a first type and a second entity of a second type are given and the inference task is to infer a third entity of the third type. By performing specific steps and choosing values according to specific prescriptions, an efficient and resource-saving method is developed that utilizes the power of quantum computing systems for inference tasks on large knowledge graphs. An advantageous value for a cutoff threshold for a cutoff based on singular values of a singular value tensor decomposition is prescribed, and a sequence of steps is developed in which only the squares of the singular values are of consequence and their signs are not.

A method of performing an inference task on a knowledge graph comprising semantic triples of entities, wherein entity types are subject, object and predicate, and wherein each semantic triple comprises one of each entity type, using a quantum computing device, wherein a first entity of a first type and a second entity of a second type are given and the inference task is to infer a third entity of the third type. By performing specific steps and choosing values according to specific prescriptions, an efficient and resource-saving method is developed that utilizes the power of quantum computing systems for inference tasks on large knowledge graphs. An advantageous value for a cutoff threshold for a cutoff based on singular values of a singular value tensor decomposition is prescribed, and a sequence of steps is developed in which only the squares of the singular values are of consequence and their signs are not.