Abstract: A user interface (UI), data structures and algorithms facilitate programming, analyzing, debugging, embedding, and/or modifying problems that are embedded or to be embedded on an analog processor (e.g., quantum processor), increasing computational efficiency and/or accuracy of problem solutions. The UI provides graph representations (e.g., source graph, target graph and correspondence therebetween) with nodes and edges which may map to hardware components (e.g., qubits, couplers) of the analog processor. Characteristics of solutions are advantageously represented spatially associated (e.g., overlaid or nested) with characteristics of a problem. Characteristics (e.g., bias state) may be represented by color, pattern, values, icons. Issues (e.g., broken chains) may be detected and alerts provided.

Abstract: A quantum processor comprises a plurality of tiles, the plurality of tiles arranged in a first grid, and where a first tile of the plurality of tiles comprises a number of qubits (e.g., superconducting qubits). The quantum processor further comprises a shift register comprising at least one shift register stage communicatively coupled to a frequency-multiplexed resonant (FMR) readout, a qubit readout device, a plurality of digital-to-analog converter (DAC) buffer stages, and a plurality of shift-register-loadable DACs arranged in a second grid. The quantum processor may further include a transmission line comprising at least one transmission line inductance, a superconducting resonator, and a coupling capacitance that communicatively couples the superconducting resonator to the transmission line. A digital processor may program at least one of the plurality of shift-register-loadable DACs. Programming the first tile may be performed in parallel with programming a second tile of the plurality of tiles.

Abstract: Computational systems implement problem solving using hybrid digital/quantum computing approaches. A problem may be represented as a problem graph which is larger and/or has higher connectivity than a working and/or hardware graph of a quantum processor. A quantum processor may be used determine approximate solutions, which solutions are provided as initial states to one or more digital processors which may implement classical post-processing to generate improved solutions. Techniques for solving problems on extended, more-connected, and/or “virtual full yield” variations of the processor's actual working and/or hardware graphs are provided. A method of operation in a computational system comprising a quantum processor includes partitioning a problem graph into sub-problem graphs, and embedding a sub-problem graph onto the working graph of the quantum processor. The quantum processor and a non-quantum processor-based device generate partial samples.

Abstract: The systems, devices, articles, and methods described herein generally relate to analog computers, for example quantum processors comprising qubits, couplers, and, or cavities. Analog computers, for example quantum processor based computers, are the subject of various sources of error which can hinder operation, potentially reducing computational accuracy and speed. Sources of error can be broadly characterized, for example as i) a background susceptibility do to inherently characteristics of the circuitry design, ii) as an h/J ratio imbalance, iii) bit flip errors, iv) fidelity, and v) Anderson localization, and various combinations of the aforesaid.

Abstract: Quantum annealers as analog or quantum processors can find paths in problem graphs embedded in a hardware graph of the processor, for example finding valid paths, shortest paths or longest paths. A set of input, for example nucleic acid reads, can be used to set up a graph with edges between nodes denoting overlap (i.e., common base pairs) between the reads with constraints applied to perform sequence alignment or sequencing of a nucleic acid (e.g., DNA) strand or sequence, finding a solution that has a ground state energy. At least a portion of the described approaches can be applied to other problems, for instance resource allocations problems, e.g., job scheduling problems, traveling salesperson problems, and other NP-complete problems.

Abstract: Approaches useful to operation of scalable processors with ever larger numbers of logic devices (e.g., qubits) advantageously take advantage of QFPs, for example to implement shift registers, multiplexers (i.e., MUXs), de-multiplexers (i.e., DEMUXs), and permanent magnetic memories (i.e., PMMs), and the like, and/or employ XY or XYZ addressing schemes, and/or employ control lines that extend in a “braided” pattern across an array of devices. Many of these described approaches are particularly suited for implementing input to and/or output from such processors. Superconducting quantum processors comprising superconducting digital-analog converters (DACs) are provided. The DACs may use kinetic inductance to store energy via thin-film superconducting materials and/or series of Josephson junctions, and may use single-loop or multi-loop designs. Particular constructions of energy storage elements are disclosed, including meandering structures.

Abstract: A user interface (UI), data structures and algorithms facilitate programming, analyzing, debugging, embedding, and/or modifying problems that are embedded or to be embedded on an analog processor (e.g., quantum processor), increasing computational efficiency and/or accuracy of problem solutions. The UI provides graph representations (e.g., source graph, target graph and correspondence therebetween) with nodes and edges which may map to hardware components (e.g., qubits, couplers) of the analog processor. Characteristics of solutions are advantageously represented spatially associated (e.g., overlaid or nested) with characteristics of a problem. Characteristics (e.g., bias state) may be represented by color, pattern, values, icons. Issues (e.g., broken chains) may be detected and alerts provided.

Abstract: The systems, devices, articles, and methods described herein generally relate to analog computers, for example quantum processors comprising qubits, couplers, and, or cavities. Analog computers, for example quantum processor based computers, are the subject of various sources of error which can hinder operation, potentially reducing computational accuracy and speed. Sources of error can be broadly characterized, for example as i) a background susceptibility do to inherently characteristics of the circuitry design, ii) as an h/J ratio imbalance, iii) bit flip errors, iv) fidelity, and v) Anderson localization, and various combinations of the aforesaid.

Abstract: A system and method of operation embeds a three-dimensional structure in a topology of an analog processor, for example a quantum processor. The analog processor may include a plurality of qubits arranged in tiles or cells. A number of qubits and communicatively coupled as logical qubits, each logical qubit which span across a plurality of tiles or cells of the qubits. Communicatively coupling between qubits of any given logical qubit can be implemented via application or assignment of a first ferromagnetic coupling strength to each of a number of couplers that communicatively couple the respective qubits in the logical qubit. Other ferromagnetic coupling strengths can be applied or assigned to couplers that communicatively couple qubits that are not part of the logical qubit. The first ferromagnetic coupling strength may be substantially higher than the other ferromagnetic coupling strengths.

Abstract: This disclosure generally relates to processor systems comprising printed circuit boards, I/O chips and processor chips with mated contacts. Contacts are formed on an upper surface of a printed circuit board having a through-hole and on a processor chip inside the through-hole. The processor chip may be a superconducting quantum processor chip comprising qubits, couplers, Digital to Analog converters, QFP shift registers and analog lines. Contacts are formed on an upper surface on an I/O chip and mated with the contacts on the printed circuit board and the processor chip. Contacts may be Indium bump bonds or superconducting solder bonds. The processor chip and the I/O chip may include a shield layer, a substrate layer and a thermally conductive layer.

Abstract: Approaches useful to operation of scalable processors with ever larger numbers of logic devices (e.g., qubits) advantageously take advantage of QFPs, for example to implement shift registers, multiplexers (i.e., MUXs), de-multiplexers (i.e., DEMUXs), and permanent magnetic memories (i.e., PMMs), and the like, and/or employ XY or XYZ addressing schemes, and/or employ control lines that extend in a “braided” pattern across an array of devices. Many of these described approaches are particularly suited for implementing input to and/or output from such processors. Superconducting quantum processors comprising superconducting digital-analog converters (DACs) are provided. The DACs may use kinetic inductance to store energy via thin-film superconducting materials and/or series of Josephson junctions, and may use single-loop or multi-loop designs. Particular constructions of energy storage elements are disclosed, including meandering structures.

Abstract: A quantum processor performs input and output which may be performed synchronously. The quantum processor executes a problem to generate a classical output state, which is read out at least partially by an I/O system. The I/O system also transmits a classical input state to by the I/O system, which may include the same qubit-proximate devices used for read-out. The classical input state is written to the qubits, and the quantum processor executes based on the classical input state (e.g., by performing reverse annealing to transform the classical input state to quantum state).

Abstract: Josephson junctions (JJ) may replace primary inductance of transformers to realize galvanic coupling between qubits, advantageously reducing size. A long-range symmetric coupler may include a compound JJ (CJJ) positioned at least approximately at a half-way point along the coupler to advantageously provide a higher energy of a first excited state than that of an asymmetric long-range coupler. Quantum processors may include qubits and couplers with a non-stoquastic Hamiltonian to enhance multi-qubit tunneling during annealing. Qubits may include additional shunt capacitances, e.g., to increase overall quality of a total capacitance and improve quantum coherence. A sign and/or magnitude of an effective tunneling amplitude ?eff of a qubit characterized by a double-well potential energy may advantageously be tuned. Sign-tunable electrostatic coupling of qubits may be implemented, e.g., via resonators, and LC-circuits. YY couplings may be incorporated into a quantum anneaier (e.g., quantum processor).

Abstract: A computational method via a hybrid processor comprising an analog processor and a digital processor includes determining a first classical spin configuration via the digital processor, determining preparatory biases toward the first classical spin configuration, programming an Ising problem and the preparatory biases in the analog processor via the digital processor, evolving the analog processor in a first direction, latching the state of the analog processor for a first dwell time, programming the analog processor to remove the preparatory biases via the digital processor, determining a tunneling energy via the digital processor, determining a second dwell time via the digital processor, evolving the analog processor in a second direction until the analog processor reaches the tunneling energy, and evolving the analog processor in the first direction until the analog processor reaches a second classical spin configuration.

Abstract: A hybrid computing system for solving a computational problem includes a digital processor, a quantum processor having qubits and coupling devices that together define a working graph of the quantum processor, and at least one nontransitory processor-readable medium communicatively coupleable to the digital processor which stores at least one of processor-executable instructions or data. The digital processor receives a computational problem, and programs the quantum processor with a first set of bias fields and a first set of coupling strengths. The quantum processor generates samples as potential solutions to an approximation of the problem. The digital processor updates the approximation by determining a second set of bias fields based at least in part on the first set of bias fields and a first set of mean fields that are based at least in part on the first set of samples and coupling strengths of one or more virtual coupling devices.

Abstract: Generate an automorphism of the problem graph, determine an embedding of the automorphism to the hardware graph and modify the embedding of the problem graph into the hardware graph to correspond to the embedding of the automorphism to the hardware graph. Determine an upper-bound on the required chain strength. Calibrate and record properties of the component of a quantum processor with a digital processor, query the digital processor for a range of properties. Generate a bit mask and change the sign of the bias of individual qubits according to the bit mask before submitting a problem to a quantum processor, apply the same bit mask to the bit result. Generate a second set of parameters of a quantum processor from a first set of parameters via a genetic algorithm.

Abstract: Apparatus and methods advantageously provide parallel-plate capacitors in superconducting integrated circuits. A method may include forming a metal-oxide layer to overlie at least a portion of a first capacitor plate, the first capacitor plate comprising a superconductive material, and depositing a second capacitor plate to overlie at least a portion of the metal-oxide layer, the second capacitor plate comprising a superconductive material. The method may include depositing a base electrode of superconductive material to overlie at least a portion of a substrate, depositing the first capacitor plate to overlie at least a portion of the base electrode, and superconductingly electrically coupled to the base electrode, and depositing a counter electrode of superconductive material to overlie at least a portion of the second capacitor plate, the counter electrode superconductingly electrically coupled to the second capacitor plate.

Abstract: Approaches useful to operation of scalable processors with ever larger numbers of logic devices (e.g., qubits) advantageously take advantage of QFPs, for example to implement shift registers, multiplexers (i.e., MUXs), de-multiplexers (i.e., DEMUXs), and permanent magnetic memories (i.e., PMMs), and the like, and/or employ XY or XYZ addressing schemes, and/or employ control lines that extend in a “braided” pattern across an array of devices. Many of these described approaches are particularly suited for implementing input to and/or output from such processors. Superconducting quantum processors comprising superconducting digital-analog converters (DACs) are provided. The DACs may use kinetic inductance to store energy via thin-film superconducting materials and/or series of Josephson junctions, and may use single-loop or multi-loop designs. Particular constructions of energy storage elements are disclosed, including meandering structures.

Abstract: Systems and methods are described for operating a hybrid computing system using cluster contraction for converting large, dense input to reduced input that can be easily mapped into a quantum processor. The reduced input represents the global structure of the problem. Techniques involve partitioning the input variables into clusters and contracting each cluster. The input variables can be partitioned using an Unweighted Pair Group Method with Arithmetic Mean algorithm. The quantum processor returns samples based on the reduced input and the samples are expanded to correspond to the original input.

Abstract: A computational method via a hybrid processor comprising an analog processor and a digital processor includes determining a first classical spin configuration via the digital processor, determining preparatory biases toward the first classical spin configuration, programming an Ising problem and the preparatory biases in the analog processor via the digital processor, evolving the analog processor in a first direction, latching the state of the analog processor for a first dwell time, programming the analog processor to remove the preparatory biases via the digital processor, determining a tunneling energy via the digital processor, determining a second dwell time via the digital processor, evolving the analog processor in a second direction until the analog processor reaches the tunneling energy, and evolving the analog processor in the first direction until the analog processor reaches a second classical spin configuration.