D-wave Systems Inc.

1372934 B.c. Ltd

Murray C Thom

Kelly T R Boothby

Aidan Patrick Roy

Sheir Yarkoni

William G Macready

Alexander M Tcaciuc

Sergey V Uchaykin

James King

Jacob Craig Petroff

Fabian Ariel Chudak

Zhengbing Bian

Dmytro Korenkevych

Yanbo Xue

Fiona L Hanington

Andrew Joseph Berkley

Paul I Bunyk

Trevor Michael Lanting

Mohammad H Amin

Andrew Douglas King

Gordon J Lamont

Richard David Neufeld

Anatoly Smirnov

William W Bernoudy

Robert B Israel

Edward D Dahl

Alexander Condello

Melody C Wong

David S Bruce

Thomas Mahon

Alexander Maassen Van Den Brink

Jason Rolfe

Jack R Raymond

Evgeny A Andriyash

Firas Hamze

Peter D Spear

Catherine McGeoch

David Pires

Aaron Lott

Mark W Johnson

J Craig Petroff

Kelly Tr Boothby

Jaspaul Chung

Florin Cioata

Jeffrey P Johnston

Skyler J Richter

Dominic Wong

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.

Error reduction and, or, correction in analog computing including quantum processor-based computing

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. Problem representations may be modified via the UI, and a computer system may autonomously generate new instances of the problem representation, update data structures, embed the new instance and cause the new instance to be executed by the analog processor.

User interface, programmer and/or debugger for embedding and/or modifying problems on quantum processors

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. A controller causes a processing operation on the partial samples to generate complete samples.

Systems and methods for analog processing of problem graphs having arbitrary size and/or connectivity

Display screen or portion thereof with graphical user interface

User in interface, programmer and/or debugger for embedding and/or modifying problems on quantum processors

The systems, devices, articles, and methods generally relate to sampling from an available probability distribution. The samples maybe used to create a desirable probability distribution, for instance for use in computing values used in computational techniques including: Importance Sampling and Markov chain Monte Carlo systems. An analog processor may operate as a sample generator, for example by: programming the analog processor with a configuration of the number of programmable parameters for the analog processor, which corresponds to a probability distribution over qubits of the analog processor, evolving the analog processor, and reading out states for the qubits. The states for the qubits in the plurality of qubits correspond to a sample from the probability distribution. Operation of the sampling device may be summarized as including updating a set of samples to include the sample from the probability distribution, and returning the set of samples.

Sampling from an analog processor

Systems and devices for providing differential input/output communication with a superconducting device are described. Each differential I/O communication is electrically filtered using a respective tubular filter structure incorporating superconducting lumped element devices and high frequency dissipation by metal powder epoxy. A plurality of such tubular filter structures is arranged in a cryogenic, multi-tiered assembly further including structural/thermalization supports and a device sample holder assembly for securing a device sample, for example a superconducting quantum processor. The interface between the cryogenic tubular filter assembly and room temperature electronics is achieved using hermetically sealed vacuum feed-through structures designed to receive flexible printed circuit board cable.

Input/output systems and devices for use with superconducting devices

Sampling from a set of spins with clamping

Growing community of inventors

Vancouver, Canada

Murray C Thom