A semiconductor device of an embodiment includes first and second couplers, an encoding circuit, and a demodulating circuit. The encoding circuit executes differential Manchester encoding on digital data based on a clock inputted thereto via the first coupler and outputs an encoded data. The demodulating circuit includes a first sampling circuit which samples the encoded data inputted via the second coupler based on a sampling frequency set to be two times higher than that of the encoded data and which outputs first sample data, a second sampling circuit which samples the encoded data at a timing earlier than that in the first sampling circuit and which outputs second sample data, a determination circuit which determines whether or not the first and the second sample data match each other, and a selection circuit which selects first phase data or second phase data from the first sample data.

Examples are disclosed that relate to encoding data on a data-storage medium. The method comprises obtaining a representation of a measurement performed on the data-storage medium, the representation being based on a previously recorded pattern of data encoded in the data-storage medium in a layout that defines a plurality of data locations. The method further comprises inputting the representation into a data decoder comprising a trained machine-learning function, and obtaining from the data decoder, for each data location of the layout, a plurality of probability values, wherein each probability value is associated with a corresponding data value and represents the probability that the corresponding data value matches the actual data value in the previously recorded pattern of data at a same location in the layout.

Examples are disclosed that relate to encoding data on a data-storage medium. The method comprises obtaining a representation of a measurement performed on the data-storage medium, the representation being based on a previously recorded pattern of data encoded in the data-storage medium in a layout that defines a plurality of data locations. The method further comprises inputting the representation into a data decoder comprising a trained machine-learning function, and obtaining from the data decoder, for each data location of the layout, a plurality of probability values, wherein each probability value is associated with a corresponding data value and represents the probability that the corresponding data value matches the actual data value in the previously recorded pattern of data at a same location in the layout.

A semiconductor device of an embodiment includes first and second couplers, an encoding circuit, and a demodulating circuit. The encoding circuit executes differential Manchester encoding on digital data based on a clock inputted thereto via the first coupler and outputs an encoded data. The demodulating circuit includes a first sampling circuit which samples the encoded data inputted via the second coupler based on a sampling frequency set to be two times higher than that of the encoded data and which outputs first sample data, a second sampling circuit which samples the encoded data at a timing earlier than that in the first sampling circuit and which outputs second sample data, a determination circuit which determines whether or not the first and the second sample data match each other, and a selection circuit which selects first phase data or second phase data from the first sample data.

A semiconductor device of an embodiment includes first and second couplers, an encoding circuit, and a demodulating circuit. The encoding circuit executes differential Manchester encoding on digital data based on a clock inputted thereto via the first coupler and outputs an encoded data. The demodulating circuit includes a first sampling circuit which samples the encoded data inputted via the second coupler based on a sampling frequency set to be two times higher than that of the encoded data and which outputs first sample data, a second sampling circuit which samples the encoded data at a timing earlier than that in the first sampling circuit and which outputs second sample data, a determination circuit which determines whether or not the first and the second sample data match each other, and a selection circuit which selects first phase data or second phase data from the first sample data.

Examples are disclosed that relate to reading stored data. The method comprises obtaining a representation of a measurement performed on a data-storage medium, the representation being based on a previously recorded pattern of data encoded in the data-storage medium in a layout that defines a plurality of data locations. The method further comprises inputting the representation into a data decoder comprising a trained machine-learning function, and obtaining from the data decoder, for each data location of the layout, a plurality of probability values, wherein each probability value is associated with a corresponding data value and represents the probability that the corresponding data value matches the actual data value in the previously recorded pattern of data at a same location in the layout.

Examples are disclosed that relate to reading stored data. The method comprises obtaining a representation of a measurement performed on a data-storage medium, the representation being based on a previously recorded pattern of data encoded in the data-storage medium in a layout that defines a plurality of data locations. The method further comprises inputting the representation into a data decoder comprising a trained machine-learning function, and obtaining from the data decoder, for each data location of the layout, a plurality of probability values, wherein each probability value is associated with a corresponding data value and represents the probability that the corresponding data value matches the actual data value in the previously recorded pattern of data at a same location in the layout.

Superconducting interface circuits and methods convert between non-return-to-zero (NRZ) encoded voltage signals and reciprocal quantum logic (RQL) compliant signals of opposite-polarity single flux quantum (SFQ) pulse pairs, and vice-versa, so as to provide high-speed NRZ input to, and output from, RQL computing circuitry.

A semiconductor device of an embodiment includes first and second couplers, an encoding circuit, and a demodulating circuit. The encoding circuit executes differential Manchester encoding on digital data based on a clock inputted thereto via the first coupler and outputs an encoded data. The demodulating circuit includes a first sampling circuit which samples the encoded data inputted via the second coupler based on a sampling frequency set to be two times higher than that of the encoded data and which outputs first sample data, a second sampling circuit which samples the encoded data at a timing earlier than that in the first sampling circuit and which outputs second sample data, a determination circuit which determines whether or not the first and the second sample data match each other, and a selection circuit which selects first phase data or second phase data from the first sample data.

A semiconductor device of an embodiment includes first and second couplers, an encoding circuit, and a demodulating circuit. The encoding circuit executes differential Manchester encoding on digital data based on a clock inputted thereto via the first coupler and outputs an encoded data. The demodulating circuit includes a first sampling circuit which samples the encoded data inputted via the second coupler based on a sampling frequency set to be two times higher than that of the encoded data and which outputs first sample data, a second sampling circuit which samples the encoded data at a timing earlier than that in the first sampling circuit and which outputs second sample data, a determination circuit which determines whether or not the first and the second sample data match each other, and a selection circuit which selects first phase data or second phase data from the first sample data.