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公开(公告)号：US10768659B2
公开(公告)日：2020-09-08
申请号：US16273257
申请日：2019-02-12
发明人： Jacques Johannes Carolan , Mihika Prabhu , Scott A. Skirlo , Yichen Shen , Marin Soljacic , Nicholas Christopher Harris , Dirk Englund
IPC分类号： G06E3/00 , G06N3/04 , G06N3/08 , G02F1/225 , G02F1/35 , G02F1/365 , G02F3/02 , G06N3/067 , G02F1/21
摘要： An optical neural network is constructed based on photonic integrated circuits to perform neuromorphic computing. In the optical neural network, matrix multiplication is implemented using one or more optical interference units, which can apply an arbitrary weighting matrix multiplication to an array of input optical signals. Nonlinear activation is realized by an optical nonlinearity unit, which can be based on nonlinear optical effects, such as saturable absorption. These calculations are implemented optically, thereby resulting in high calculation speeds and low power consumption in the optical neural network.
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公开(公告)号：US11914415B2
公开(公告)日：2024-02-27
申请号：US17736667
申请日：2022-05-04
发明人： Jacques Johannes Carolan , Mihika Prabhu , Scott A. Skirlo , Yichen Shen , Marin Soljacic , Dirk Englund , Nicholas C. Harris
IPC分类号： G06E3/00 , G06N3/04 , G06N3/084 , G02F1/225 , G02F1/35 , G02F1/365 , G02F3/02 , G06N3/067 , G06N3/08 , G02F1/21
CPC分类号： G06E3/005 , G02F1/225 , G02F1/3526 , G02F1/365 , G02F3/024 , G06E3/006 , G06E3/008 , G06N3/04 , G06N3/0675 , G06N3/08 , G06N3/084 , G02F1/212 , G02F2202/32 , G02F2203/15
摘要： An optical neural network is constructed based on photonic integrated circuits to perform neuromorphic computing. In the optical neural network, matrix multiplication is implemented using one or more optical interference units, which can apply an arbitrary weighting matrix multiplication to an array of input optical signals. Nonlinear activation is realized by an optical nonlinearity unit, which can be based on nonlinear optical effects, such as saturable absorption. These calculations are implemented optically, thereby resulting in high calculation speeds and low power consumption in the optical neural network.
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3.发明授权公开(公告)号：US11054590B1
公开(公告)日：2021-07-06
申请号：US16734727
申请日：2020-01-06
IPC分类号： G02B6/42
摘要： A process is provided for the high-yield heterogeneous integration of ‘quantum micro-chiplets’ (QMCs, diamond waveguide arrays containing highly coherent color centers) with an aluminum nitride (AlN) photonic integrated circuit (PIC). As an example, the process is useful for the development of a 72-channel defect-free array of germanium-vacancy (GeV) and silicon-vacancy (SiV) color centers in a PIC. Photoluminescence spectroscopy reveals long-term stable and narrow average optical linewidths of 54 MHz (146 MHz) for GeV (SiV) emitters, close to the lifetime-limited linewidth of 32 MHz (93 MHz). Additionally, inhomogeneities in the individual qubits can be compensated in situ with integrated tuning of the optical frequencies over 100 GHz. The ability to assemble large numbers of nearly indistinguishable artificial atoms into phase-stable PICs is useful for development of multiplexed quantum repeaters and general-purpose quantum computers.
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公开(公告)号：US11237454B2
公开(公告)日：2022-02-01
申请号：US16680908
申请日：2019-11-12
发明人： Jacques Johannes Carolan , Uttara Chakraborty , Nicholas C. Harris , Mihir Pant , Dirk Robert Englund
IPC分类号： H01S3/094 , G02F1/35 , H01S3/08 , H01S3/13 , H01S3/067 , H01S3/23 , G02F1/355 , G02F1/365 , H01S3/083 , H01S3/16
摘要： Typically, quantum systems are very sensitive to environmental fluctuations, and diagnosing errors via measurements causes unavoidable perturbations. Here, an in situ frequency-locking technique monitors and corrects frequency variations in single-photon sources based on resonators. By using the classical laser fields used for photon generation as probes to diagnose variations in the resonator frequency, the system applies feedback control to correct photon frequency errors in parallel to the optical quantum computation without disturbing the physical qubit. Our technique can be implemented on a silicon photonic device and with sub 1 pm frequency stabilization in the presence of applied environmental noise, corresponding to a fractional frequency drift of
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公开(公告)号：US10268232B2
公开(公告)日：2019-04-23
申请号：US15612043
申请日：2017-06-02
发明人： Nicholas Christopher Harris , Jacques Johannes Carolan , Mihika Prabhu , Dirk Robert Englund , Scott A. Skirlo , Yichen Shen , Marin Soljacic
摘要： An optical neural network is constructed based on photonic integrated circuits to perform neuromorphic computing. In the optical neural network, matrix multiplication is implemented using one or more optical interference units, which can apply an arbitrary weighting matrix multiplication to an array of input optical signals. Nonlinear activation is realized by an optical nonlinearity unit, which can be based on nonlinear optical effects, such as saturable absorption. These calculations are implemented optically, thereby resulting in high calculation speeds and low power consumption in the optical neural network.
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公开(公告)号：US11790221B2
公开(公告)日：2023-10-17
申请号：US16826364
申请日：2020-03-23
CPC分类号： G06N3/067 , G02F1/35 , G06N3/04 , G06N10/00 , G02F2203/50
摘要： Many of the features of neural networks for machine learning can naturally be mapped into the quantum optical domain by introducing the quantum optical neural network (QONN). A QONN can be performed to perform a range of quantum information processing tasks, including newly developed protocols for quantum optical state compression, reinforcement learning, black-box quantum simulation and one way quantum repeaters. A QONN can generalize from only a small set of training data onto previously unseen inputs. Simulations indicate that QONNs are a powerful design tool for quantum optical systems and, leveraging advances in integrated quantum photonics, a promising architecture for next generation quantum processors.
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公开(公告)号：US11334107B2
公开(公告)日：2022-05-17
申请号：US16986383
申请日：2020-08-06
发明人： Jacques Johannes Carolan , Mihika Prabhu , Scott A. Skirlo , Yichen Shen , Marin Soljacic , Dirk Englund , Nicholas Christopher Harris
IPC分类号： G06E3/00 , G06N3/04 , G06N3/08 , G02F1/225 , G02F1/35 , G02F1/365 , G02F3/02 , G06N3/067 , G02F1/21
摘要： An optical neural network is constructed based on photonic integrated circuits to perform neuromorphic computing. In the optical neural network, matrix multiplication is implemented using one or more optical interference units, which can apply an arbitrary weighting matrix multiplication to an array of input optical signals. Nonlinear activation is realized by an optical nonlinearity unit, which can be based on nonlinear optical effects, such as saturable absorption. These calculations are implemented optically, thereby resulting in high calculation speeds and low power consumption in the optical neural network.
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公开(公告)号：US20190294199A1
公开(公告)日：2019-09-26
申请号：US16273257
申请日：2019-02-12
发明人： Jacques Johannes Carolan , Mihika Prabhu , Scott A. Skirlo , Yichen Shen , Marin Soljacic , Nicholas Christopher Harris , Dirk Englund
摘要： An optical neural network is constructed based on photonic integrated circuits to perform neuromorphic computing. In the optical neural network, matrix multiplication is implemented using one or more optical interference units, which can apply an arbitrary weighting matrix multiplication to an array of input optical signals. Nonlinear activation is realized by an optical nonlinearity unit, which can be based on nonlinear optical effects, such as saturable absorption. These calculations are implemented optically, thereby resulting in high calculation speeds and low power consumption in the optical neural network.
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