Abstract: A quantum computing device comprises a surface code lattice that includes l logical qubits, where l is a positive integer. The surface code lattice is partitioned into two or more regions based on lattice geometry. A compression engine is coupled to each logical qubit of the l logical qubits. Each compression engine is configured to compress syndrome data generated by the surface code lattice using a geometry-based compression scheme. A decompression engine is coupled to each compression engine. Each decompression engine is configured to receive compressed syndrome data, decompress the received compressed syndrome data, and route the decompressed syndrome data to a decoder block.

Abstract: A quantum prediction AI system includes a quantum prediction circuit adapted to receive an input vector representing a subset of a time-sequential sequence; encode the input vector as a corresponding qubit register; apply a trained quantum circuit to the qubit register; and measure one or more qubits output from the quantum prediction circuit to infer a next data point in the series following the subset represented by the input vector.

Abstract: A quantum computing device comprises a surface code lattice that includes l logical qubits, where l is a positive integer. The surface code lattice is partitioned into two or more regions based on lattice geometry. A compression engine is coupled to each logical qubit of the l logical qubits. Each compression engine is configured to compress syndrome data generated by the surface code lattice using a geometry-based compression scheme. A decompression engine is coupled to each compression engine. Each decompression engine is configured to receive compressed syndrome data, decompress the received compressed syndrome data, and route the decompressed syndrome data to a decoder block.

Abstract: A quantum computing device comprises a surface code lattice that includes/logical qubits, where/is a positive integer. The surface code lattice is partitioned into two or more regions based on lattice geometry. A compression engine is coupled to each logical qubit of the/logical qubits. Each compression engine is configured to compress syndrome data generated by the surface code lattice using a geometry-based compression scheme. A decompression engine is coupled to each compression engine. Each decompression engine is configured to receive compressed syndrome data, decompress the received compressed syndrome data, and route the decompressed syndrome data to a decoder block.

Abstract: A quantum computing system is adapted to prepare a cat state in a quantum circuit with fault tolerance t and circuit depth less than or equal to 4+4t by performing a series of operations that includes: performing a sequence of joint parity measurements on individual pairs of neighboring qubits in a series of qubits entangled to form an initial cat state; repeating the sequence of measurements over at least t-rounds; and disentangling a first set of alternating qubits from the initial cat state, the prepared cat state being formed by a remaining second set of alternating qubits, the second set of alternating qubits being interlaced with the first set of alternating qubits along a line of one-dimensional connectivity, the series of operations being sufficient to guarantee that a prepared cat state is has less than or equal to t number of faults.

Abstract: A quantum computing device comprises at least one quantum register including a plurality of logical qubits. A compression engine is coupled to each logical qubit of the plurality of logical qubits. Each compression engine is configured to compress syndrome data. A decompression engine is coupled to each compression engine. Each decompression engine is configured to receive compressed syndrome data, decompress the received compressed syndrome data, and route the decompressed syndrome data to a decoder block.

Abstract: A quantum computing system is adapted to prepare a cat state in a quantum circuit with fault tolerance t and circuit depth less than or equal to 4+4t by performing a series of operations that includes: performing a sequence of joint parity measurements on individual pairs of neighboring qubits in a series of qubits entangled to form an initial cat state; repeating the sequence of measurements over at least t-rounds; and disentangling a first set of alternating qubits from the initial cat state, the prepared cat state being formed by a remaining second set of alternating qubits, the second set of alternating qubits being interlaced with the first set of alternating qubits along a line of one-dimensional connectivity, the series of operations being sufficient to guarantee that a prepared cat state is has less than or equal to t number of faults.

Abstract: A method for performing a quantum-logic operation on a quantum computer. The method includes enacting classical pebbling on an initial computation graph G defining the quantum-logic operation; extracting a quantum circuit B based on a sequence of steps obtained from the classical pebbling, that sequence including at least one computation step and at least one measurement-based uncomputation step; executing the quantum circuit B on a qubit register of the quantum computer; recording at least one measurement result of the at least one measurement-based uncomputation step of the quantum circuit B as executed on the qubit register; constructing a clean-up computation graph G? based on the at least one measurement result; enacting reversible pebbling on the clean-up computation graph G?; extracting a quantum circuit B? based on a sequence of steps obtained from the reversible pebbling, that sequence including computation and uncomputation steps; and executing the quantum circuit B? on the qubit register.

Abstract: A quantum prediction AI system includes a quantum prediction circuit adapted to receive an input vector representing a subset of a time-sequential sequence; encode the input vector as a corresponding qubit register; apply a trained quantum circuit to the qubit register; and measure one or more qubits output from the quantum prediction circuit to infer a next data point in the series following the subset represented by the input vector.

Abstract: A quantum computing device comprises at least one quantum register including a plurality of logical qubits. A compression engine is coupled to each logical qubit of the plurality of logical qubits. Each compression engine is configured to compress syndrome data. A decompression engine is coupled to each compression engine. Each decompression engine is configured to receive compressed syndrome data, decompress the received compressed syndrome data, and route the decompressed syndrome data to a decoder block.

Abstract: A quantum computing device comprises at least one quantum register including a plurality of qubits, and a hardware decoder. The hardware decoder is configured to: receive syndrome data from one or more of the plurality of qubits; and decode the received syndrome data by implementing a Union-Find decoding algorithm via a hardware microarchitecture including two or more pipeline stages.

Abstract: A quantum computing device comprises at least one quantum register including l logical qubits, where l is a positive integer. The quantum computing device further includes a set of d decoder blocks coupled to the at least one quantum register, where d<2*l. In this way, the decoder blocks may share decoding requests generated by the logical qubits.

Abstract: A system that facilitates ranking search results returned by a search engine in response to receipt of a query is described herein. The system includes a receiver component that receives categorical metadata pertaining to an item and categorical metadata pertaining to the query and a computation component that computes at least one of a document feature pertaining to the item, a query feature pertaining to the query, or a document-query feature pertaining to the item and the query based at least in part upon one or more of the categorical metadata pertaining to the item or the categorical metadata pertaining to the query. The system also includes a ranker component that selectively places the item in a particular location in a sequence of items based at least in part upon the at least one of the document feature, the query feature, or the document-query feature.

Abstract: Methods and computer-readable media are provided for summarizing the content of a plurality of documents and presenting the results of such multiple-document summarization to a user in such a way that the user is able to quickly and easily discern what, if any, unique information each document contains. Each sentence of each document is assigned a score based upon the perceived importance of the information contained therein. The sentences receiving the highest scores are then compared with one another to identify and remove any duplicate sentences. The remaining high-scoring sentences are extracted from the corresponding documents and presented to the user, for instance, in a bulleted list format. The user can then simply scan the list and can quickly and easily discern the unique information contained in each document.

Abstract: A system that facilitates ranking search results returned by a search engine in response to receipt of a query is described herein. The system includes a receiver component that receives categorical metadata pertaining to an item and categorical metadata pertaining to the query and a computation component that computes at least one of a document feature pertaining to the item, a query feature pertaining to the query, or a document-query feature pertaining to the item and the query based at least in part upon one or more of the categorical metadata pertaining to the item or the categorical metadata pertaining to the query. The system also includes a ranker component that selectively places the item in a particular location in a sequence of items based at least in part upon the at least one of the document feature, the query feature, or the document-query feature.

Abstract: Methods and computer-readable media are provided for summarizing the content of a plurality of documents and presenting the results of such multiple-document summarization to a user in such a way that the user is able to quickly and easily discern what, if any, unique information each document contains. Each sentence of each document is assigned a score based upon the perceived importance of the information contained therein. The sentences receiving the highest scores are then compared with one another to identify and remove any duplicate sentences. The remaining high-scoring sentences are extracted from the corresponding documents and presented to the user, for instance, in a bulleted list format. The user can then simply scan the list and can quickly and easily discern the unique information contained in each document.