A single Integrated Computational Element (ICE) predictive of multiple sample characteristics.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for receiving, by a computational graph system, a request to process a computational graph; obtaining data representing a subgraph of the computational graph, the computational graph comprising a plurality of nodes and directed edges, wherein each node represents a respective operation, wherein each directed edge connects a respective first node to a respective second node, the subgraph assigned to a first device by a placer in the computational graph system; determining that the first device comprises a hardware accelerator having a plurality of streams; in response to determining, generating instructions that when executed by the first device cause the first device to: assign the operation represented by each node in the subgraph to a respective stream; and perform the operations represented by the nodes in the subgraph in accordance with the assignment.

Systems, methods, and apparatus, including computer programs encoded on a computer storage medium for processing a network input through a neural network having one or more initial neural network layers followed by a softmax output layer. In one aspect, the methods include obtaining a layer output generated by the one or more initial neural network layers and processing the layer output through the softmax output layer to generate a neural network output. Processing the layer output through the softmax output layer includes determining, for each possible output value, a number of occurrences in the layer output values; for each possible output value occurring in the layer output values, determining a respective exponentiation measure; determining a normalization factor for the layer output by combining the exponentiation measures in accordance with the number of occurrences of the possible output values; and determining, for each of layer output values, a softmax probability value.

Examples described herein relate to concurrently performing operations on optical signals. In an example, a method includes providing, to an optical circuit, a first plurality of signals having a first optical property and encoding a first vector. A second plurality of signals is provided to the circuit that encodes a second vector and has a second optical property that is different from the first optical property. A first attribute-dependent operation is performed on the first plurality of signals via the circuit to perform a first matrix multiplication operation on the first vector, and concurrently, a second attribute-dependent operation is performed on the second plurality of signals to perform a second matrix multiplication operation on the second vector. The first matrix multiplication operation and the second matrix multiplication operation are different based on the first optical property being different from the second optical property.

In one embodiment, a computer program product for optimizing core utilization in a neurosynaptic network includes a computer readable storage medium having program instructions embodied therewith, where the computer readable storage medium is not a transitory signal per se, and where the program instructions are executable by a processor to cause the processor to perform a method including identifying, by the processor, one or more unused portions of a neurosynaptic network, and for each of the one or more unused portions of the neurosynaptic network, disconnecting, by the processor, the unused portion from the neurosynaptic network.

Novel tools and techniques are provided for implementing computing, and, more particularly, to methods, systems, and apparatuses for implementing transient state computing with optics. In various embodiments, a chromatic transient state computing system might receive one or more input values and might assign a chromabit value to each of the one or more input values. The chromatic transient state computing system might include a plurality of sets of colored light emitting diodes (LEDs) and a corresponding set of photoreceptors. Each distinguishable color as detected by one of the photoreceptors might correspond to a combination of colors emitted by a set of colored LEDs, each distinguishable color representing a chromabit value. The chromatic transient state computing system might perform a computing operation using the assigned chromabit values each corresponding to each of the one or more input values, and might output one or more output values resulting from the computing operation.

Novel tools and techniques are provided for implementing computing, and, more particularly, to methods, systems, and apparatuses for implementing transient state computing with optics. In various embodiments, a chromatic transient state computing system might receive one or more input values and might assign a chromabit value to each of the one or more input values. The chromatic transient state computing system might include a plurality of sets of colored light emitting diodes (LEDs) and a corresponding set of photoreceptors. Each distinguishable color as detected by one of the photoreceptors might correspond to a combination of colors emitted by a set of colored LEDs, each distinguishable color representing a chromabit value. The chromatic transient state computing system might perform a computing operation using the assigned chromabit values each corresponding to each of the one or more input values, and might output one or more output values resulting from the computing operation.

Novel tools and techniques are provided for implementing data transmission, and, more particularly, to methods, systems, and apparatuses for implementing data transmission utilizing techniques used for transient state computing with optics. In various embodiments, a photo-transmitter system of a chromatic transient state data transmission system might send, over optical transmission media, a data signal comprising a series of chromabit values, by emitting, using a set of colored light emitters, a combination of colors representing each chromabit value. A photo-receiver system of the chromatic transient state data transmission system that is communicatively coupled to the photo-transmitter system via the optical transmission media might receive the data signal, each distinguishable color as detected by each photoreceptor corresponding to a combination of emitted colors. A computing system might autonomously convert the data signal comprising the series of chromabit values into a converted data signal that is compatible with a receiving device.

Novel tools and techniques are provided for implementing data transmission, and, more particularly, to methods, systems, and apparatuses for implementing data transmission utilizing techniques used for transient state computing with optics. In various embodiments, a photo-transmitter system of a chromatic transient state data transmission system might send, over optical transmission media, a data signal comprising a series of chromabit values, by emitting, using a set of colored light emitters, a combination of colors representing each chromabit value. A photo-receiver system of the chromatic transient state data transmission system that is communicatively coupled to the photo-transmitter system via the optical transmission media might receive the data signal, each distinguishable color as detected by each photoreceptor corresponding to a combination of emitted colors. A computing system might autonomously convert the data signal comprising the series of chromabit values into a converted data signal that is compatible with a receiving device.

The disclosure describes an adaptive and optimal imaging of individual quantum emitters within a lattice or optical field of view for quantum computing. Advanced image processing techniques are described to identify individual optically active quantum bits (qubits) with an imager. Images of individual and optically-resolved quantum emitters fluorescing as a lattice are decomposed and recognized based on fluorescence. Expected spatial distributions of the quantum emitters guides the processing, which uses adaptive fitting of peak distribution functions to determine the number of quantum emitters in real time. These techniques can be used for the loading process, where atoms or ions enter the trap one-by-one, for the identification of solid-state emitters, and for internal state-detection of the quantum emitters, where each emitter can be fluorescent or dark depending on its internal state. This latter application is relevant to efficient and fast detection of optically active qubits in quantum simulations and quantum computing.