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As the field of artificial intelligence is pushed forward, the question arises of how fast autonomous machines can learn. Within artificial intelligence, an important paradigm is reinforcement learning, where agents - learning entities capable of decision making - interact with the world they are placed in, called an environment. Thanks to these interactions, agents receive feedback from the environment and thus progressively adjust their behaviour to accomplish a given goal. An important question in reinforcement learning is how fast agents can learn to fulfill their tasks. To answer this question we consider a novel reinforcement learning framework where quantum mechanics is used. In particular, we quantize the agent and the environment and grant them the possibility to also interact quantum-mechanically, that is, by using a quantum channel for their communication. We demonstrate that this feature enables a speed-up in the agent's learning process, and we further show that combining this scenario with classical communication enables the evaluation of such an improvement. This learning protocol is implemented on an integrated re-programmable photonic platform interfaced with photons at telecommunication wavelengths. Thanks to the full tunability of the device, this platform proves the best candidate for the implementation of learning protocols, where a continuous update of the learning process is required.

Photonic system component counts are increasing rapidly, particularly in CMOS-compatible silicon photonics processes. Large numbers of cascaded active photonic devices are difficult to implement when accounting for constraints on area, power dissipation, and response time. Plasma dispersion and the thermo-optic effect, both available in CMOS-compatible silicon processes, address a subset of these criteria. With the addition of a few back-end-of-line etch processing steps, silicon photonics platforms can support nano-opto-electro-mechanical (NOEM) phase shifters. Realizing NOEM phase shifters that operate at CMOS-compatible voltages (≤ 1.2 V) and with low insertion loss remains a challenge. Here, we introduce a novel NOEM phase shifter fabricated alongside 90 nanometer transistors that imparts 5.63 radians phase shift at 1.08 volts bias over an actuation length of 25μm with an insertion loss of less than 0.04 dB and 3 dB bandwidth of 0.26 MHz.

Betalains are a family of natural pigments found exclusively in the plant order Caryophyllales. All members of this chemical family are biosynthesized through the common intermediate betalamic acid, which is capable of spontaneously condensing with various primary and secondary amines to produce betalains. Of particular interest is the red-violet betanin, most commonly obtained from Beta vulgaris (beet) as a natural food dye. We demonstrate the first complete microbial production of betanin in Saccharomyces cerevisiae from glucose, an early step towards a fermentation process enabling rapid, on-demand production of this natural dye. A titer of 17mg/L was achieved, corresponding to a color intensity obtained from 10g/L of beetroot extract. Further, we expanded the spectrum of betalain colors by condensing betalamic acid with various amines fed to an engineered strain of S. cerevisiae. Our work establishes a platform for microbial production of betalains of various colors as a potential alternative to land- and resource-intensive agricultural production.

A putative lipopeptide biosynthetic gene cluster is conserved in many species of Actinobacteria, including Mycobacterium tuberculosis and M. marinum, but the specific function of the encoding proteins has been elusive. Using both in vivo heterologous reconstitution and in vitro biochemical analyses, we have revealed that the five encoding biosynthetic enzymes are capable of synthesizing a family of isonitrile lipopeptides (INLPs) through a thio-template mechanism. The biosynthesis features the generation of isonitrile from a single precursor Gly promoted by a thioesterase and a nonheme iron(II)-dependent oxidase homolog and the acylation of both amino groups of Lys by the same isonitrile acyl chain facilitated by a single condensation domain of a nonribosomal peptide synthetase. In addition, the deletion of INLP biosynthetic genes in M. marinum has decreased the intracellular metal concentration, suggesting the role of this biosynthetic gene cluster in metal transport.

As Moore’s law and Dennard scaling come to an end, new devices and computing architectures are being explored. The development of computing hardware designed to address the rapidly growing need for computational power to accelerate artificial intelligence applications has prompted investigations into both. While silicon photonics is typically viewed as a communications platform, we discuss its application to artificial intelligence and some outstanding challenges to be addressed.

Quantum algorithms for Noisy Intermediate-Scale Quantum (NISQ) machines have recently emerged as new promising routes towards demonstrating near-term quantum advantage (or supremacy) over classical systems. In these systems samples are typically drawn from probability distributions which --- under plausible complexity-theoretic conjectures --- cannot be efficiently generated classically. Rather than first define a physical system and then determine computational features of the output state, we ask the converse question: given direct access to the quantum state, what features of the generating system can we efficiently learn? In this work we introduce the Variational Quantum Unsampling (VQU) protocol, a nonlinear quantum neural network approach for verification and inference of near-term quantum circuits outputs. In our approach one can variationally train a quantum operation to unravel the action of an unknown unitary on a known input state; essentially learning the inverse of the black-box quantum dynamics. While the principle of our approach is platform independent, its implementation will depend on the unique architecture of a specific quantum processor. Here, we experimentally demonstrate the VQU protocol on a quantum photonic processor. Alongside quantum verification, our protocol has broad applications; including optimal quantum measurement and tomography, quantum sensing and imaging, and ansatz validation., Comment: Comments welcome. Updates references and acknowledgements

As Moore's law and Dennard scaling come to an end, new devices and computing architectures are being explored. The development of computing hardware designed specifically for machine learning has prompted explorations into both. While silicon photonics is typically viewed as a communications platform, it can serve as a particularly attractive computing platform for specific kinds of problems, including machine learning. Here, we will discuss our work towards realizing photonic matrix processors.

The electron-rich isonitrile is an important functionality in bioactive natural products, but its biosynthesis has been restricted to the IsnA family of isonitrile synthases. We herein provide the first structural and biochemical evidence of an alternative mechanism for isonitrile formation. ScoE, a putative non-heme iron(II)-dependent enzyme from Streptomyces coeruleorubidus, was shown to catalyze the conversion of (R)-3-((carboxymethyl)amino)butanoic acid to (R)-3-isocyanobutanoic acid through an oxidative decarboxylation mechanism. This work further provides a revised scheme for the biosynthesis of a unique class of isonitrile lipopeptides, of which several members are critical for the virulence of pathogenic mycobacteria., National Institutes of Health (U.S.). Molecular Biophysics Training Grant (T32 GM008313)

1-Alkenes are important platform chemicals that are almost exclusively produced from fossil hydrocarbons. Bioproduction of 1-alkenes can mitigate our dependence on declining petrochemical resources, thereby representing an important step in the field of green chemistry. Here, we report the discovery of a new family of membrane-bound desaturase-like enzymes that convert medium-chain fatty acids (10–16 carbons) into the corresponding 1-alkenes through oxidative decarboxylation. We further show that these desaturase-like enzymes could be efficient in transforming lauric acid to 1-undecene in E. coli compared to the existing 1-alkene biosynthetic enzymes. This work expands the enzyme inventory for the transformation of fatty acid precursors to hydrocarbons and promotes the industrial production of medium-chain 1-alkenes through microbial fermentation.

While “knowledge learning” about the outgroup has been regarded as one of the key mechanisms for the contact–prejudice relation since the contact hypothesis’ first inception (Pettigrew & Tropp, 2008), “learning,” more broadly, has rarely been used as an explanatory framework to investigate the consequences of intergroup contact. In this article, we lay the foundation of a learning model of anxiety and stress in ingroup–outgroup interactions. We distinguish between episodic and chronic anxiety responses to the outgroup and recommend investigations on the complexities of their dynamic interplay, as individuals accumulate and dynamically integrate their experiences with the outgroup over time. Through a review of established and emerging psychophysiological and behavioral research of anxiety during ingroup–outgroup interactions, we identify evidence consistent with this dynamic outlook of intergroup contact effects. In this context, we also advance novel and untested predictions for future investigations onto the temporal integration of contact effects during an individual’s lifespan.

A putative lipopeptide biosynthetic gene cluster is conserved in many species of Actinobacteria, including Mycobacterium tuberculosis and M. marinum, but the specific function of the encoding proteins has been elusive. Using both in vivo heterologous reconstitution and in intro biochemical analyses, we have revealed that the five encoding biosynthetic enzymes are capable of synthesizing a new family of isonitrile lipopeptides (INLPs) through a thio-template mechanism. The biosynthesis features the generation of isonitrile from a single precursor Gly promoted by a thioesterase and a non-heme iron(II)-dependent oxidase homologue, and the acylation of both amino groups of Lys by the same isonitrile acyl chain facilitated by a single condensation domain of a non-ribosomal peptide synthetase (NRPS). In addition, the deletion of INLP biosynthetic genes in M. marinum has decreased the intracellular metal concentration, suggesting the role of this biosynthetic gene cluster in metal transport.Significance StatementMycobacterium tuberculosis is the leading causative agent of tuberculosis (TB), of which millions of deaths occur annually. A putative lipopeptide biosynthetic gene cluster has been shown to be essential for the survival of this pathogen in hosts, and homologous gene clusters have also been found in all pathogenic mycobacteria and other species of Actinobacteria. We have identified the function of these gene clusters in making a new family of isonitrile lipopeptides. The biosynthesis has several unique features, including an unprecedented mechanism for isonitrile synthesis. Our results have further suggested that these biosynthetic gene clusters play a role in metal transport, and thus have shed light on a new metal transport system that is crucial for virulence of pathogenic mycobacteria.

We demonstrate a large-scale tunable-coupling ring resonator array, suitable for high-dimensional classical and quantum transforms, in a CMOS-compatible silicon photonics platform. The device consists of a waveguide coupled to 15 ring-based dispersive elements with programmable linewidths and resonance frequencies. The ability to control both quality factor and frequency of each ring provides an unprecedented 30 degrees of freedom in dispersion control on a single spatial channel. This programmable dispersion control system has a range of applications, including mode-locked lasers, quantum key distribution, and photon-pair generation. We also propose a novel application enabled by this circuit – high-speed quantum communications using temporal-mode-based quantum data locking – and discuss the utility of the system for performing the high-dimensional unitary optical transformations necessary for a quantum data locking demonstration.

We present a network switch in the silicon-on-insulator platform capable of redistributing light to arbitrary outputs with continuously reconfigurable splitting ratios. We demonstrate software defined switching and physical-layer multicast of gigabit Ethernet.

Beyond communication, silicon photonics is becoming a promising platform for both quantum and classical information processing. Here, we discuss our recent results on using programmable nanophotonic systems to simulate quantum phenomena found in solid-state and biological systems as well as the implementation of optical neural networks for deep learning.

Something very surprising has been happening in photonics recently: the same foundries and processes that were developed to build transistors are being repurposed to build chips that can generate, detect, modulate, and otherwise manipulate light. This is pretty counterintuitive, since the electronics industry spends billions of dollars to develop tools, processes, and facilities that lend themselves to building the very best transistors without any thought about how to make these processes compatible with photonics (with the obvious exception of the processes designed to make CMOS and CCD camera chips).

In the field of silicon photonics, it has only recently become possible to build complex systems. As system power constraints and complexity increase, design margins will decrease - making understanding device noise performance and device-specific noise origins increasingly necessary. We demonstrate a waveguide-coupled germanium metal-semiconductor-metal photodetector exhibiting photoconductive gain with a responsivity of 1.76 A/W at 5 V bias and 10.6±0.96 fF capacitance. Our measurements indicate that a significant portion of the dark current is not associated with the generation of shot noise. The noise elbow at 5 V bias is measured to be approximately 150 MHz and the high-frequency detector noise reaches the Johnson noise floor.

Artificial Neural Networks are computational network models inspired by signal processing in the brain. These models have dramatically improved the performance of many learning tasks, including speech and object recognition. However, today's computing hardware is inefficient at implementing neural networks, in large part because much of it was designed for von Neumann computing schemes. Significant effort has been made to develop electronic architectures tuned to implement artificial neural networks that improve upon both computational speed and energy efficiency. Here, we propose a new architecture for a fully-optical neural network that, using unique advantages of optics, promises a computational speed enhancement of at least two orders of magnitude over the state-of-the-art and three orders of magnitude in power efficiency for conventional learning tasks. We experimentally demonstrate essential parts of our architecture using a programmable nanophotonic processor., 8 pages, 3 figures

Large-scale quantum technologies require exquisite control over many individual quantum systems. Typically, such systems are very sensitive to environmental fluctuations, and diagnosing errors via measurements causes unavoidable perturbations. In this work we present an in situ frequency locking technique that monitors and corrects frequency variations in single photon sources based on microring resonators. By using the same classical laser fields required for photon generation as a probe to diagnose variations in the resonator frequency, our protocol applies feedback control to correct photon frequency errors in parallel to the optical quantum computation without disturbing the physical qubit. We implement our technique on a silicon photonic device and demonstrate sub 1 pm frequency stabilization in the presence of applied environmental noise, corresponding to a fractional frequency drift of, Comments welcome

Advances in photonic integrated circuits have recently enabled electrically reconfigurable optical systems that can implement universal linear optics transformations on spatial mode sets. This review paper covers progress in such “programmable nanophotonic processors” as well as emerging applications of the technology to problems including classical and quantum information processing and machine learning.

A large-scale tunable-coupling ring resonator array is demonstrated in a CMOS-compatible silicon photonics platform to achieve tunable frequency-dependent group delay. The system is proposed for a phase-encoded quantum data locking protocol.

We propose an on-chip nanophotonic system that do the neural network computing all in optical domain. Our system is able to give equivalent learning performance, while potentially achieve 3 orders of magnitude faster speed than conventional electronic neural nets.

Quantum information science offers inherently more powerful methods for communication, computation, and precision measurement that take advantage of quantum superposition and entanglement. In recent years, theoretical and experimental advances in quantum computing and simulation with photons have spurred great interest in developing large photonic entangled states that challenge today’s classical computers. As experiments have increased in complexity, there has been an increasing need to transition bulk optics experiments to integrated photonics platforms to control more spatial modes with higher fidelity and phase stability. The silicon-on-insulator (SOI) nanophotonics platform offers new possibilities for quantum optics, including the integration of bright, nonclassical light sources, based on the large third-order nonlinearity (χ(3)) of silicon, alongside quantum state manipulation circuits with thousands of optical elements, all on a single phase-stable chip. How large do these photonic systems need to be? Recent theoretical work on Boson Sampling suggests that even the problem of sampling from e30 identical photons, having passed through an interferometer of hundreds of modes, becomes challenging for classical computers. While experiments of this size are still challenging, the SOI platform has the required component density to enable low-loss and programmable interferometers for manipulating hundreds of spatial modes. Here, we discuss the SOI nanophotonics platform for quantum photonic circuits with hundreds-to-thousands of optical elements and the associated challenges. We compare SOI to competing technologies in terms of requirements for quantum optical systems. We review recent results on large-scale quantum state evolution circuits and strategies for realizing high-fidelity heralded gates with imperfect, practical systems. Next, we review recent results on silicon photonics-based photon-pair sources and device architectures, and we discuss a path towards large-scale source integration. Finally, we review monolithic integration strategies for single-photon detectors and their essential role in on-chip feed forward operations., United States. Air Force Office of Scientific Research (FA9550-14-1-0052), United States. Air Force Research Laboratory. RITA Program (FA8750-14-2-0120), American Society for Engineering Education. National Defense Science and Engineering Graduate Fellowship, National Science Foundation (U.S.). Graduate Research Fellowship Program (Grant 1122374).

We propose and analyze the design of a programmable photonic integrated circuit for high-fidelity quantum computation and simulation. We demonstrate that the reconfigurability of our design allows us to overcome two major impediments to quantum optics on a chip: it removes the need for a full fabrication cycle for each experiment and allows for compensation of fabrication errors using numerical optimization techniques. Under a pessimistic fabrication model for the silicon-on-insulator process, we demonstrate a dramatic fidelity improvement for the linear optics controlled-not and controlled-phase gates and, showing the scalability of this approach, the iterative phase estimation algorithm built from individually optimized gates. We also propose and simulate an experiment that the programmability of our system would enable: a statistically robust study of the evolution of entangled photons in disordered quantum walks. Overall, our results suggest that existing fabrication processes are sufficient to build a quantum photonic processor capable of high-fidelity operation.

Silicon micro-ring resonators have been demonstrated to be potential “on- chip” efficient sources of time-energy entangled photons. In these devices, photon pairs are generated by spontaneous four-wave-mixing (SFWM), an elastic scattering event involving two pump photons that results in the generation of an idler and a signal photon. The mass production of such integrated devices for quantum optic experiment requires the implementation of fast and reliable techniques to monitor the emitted two-photon state as well as the device performances. In this work we show that the joint spectral density of photon pairs that would be generated by SFWM in a silicon ring resonator can be measured with unprecedented resolution and speed, improving of several orders of magnitudes the results of traditional approaches based on coincidence measurements.

Quantum random walks (QRWs) implemented in photonic media have seen significant recent attention for their applicability to problems in quantum simulation and quantum transport. However, performing statistically robust and high-fidelity studies of these problems has required either manual tuning of optical elements or the fabrication of multiple integrated photonic chips. Here, we present our recent theoretical and preliminary experimental results on the role of disorder and decoherence in QRWs implemented in a large-scale, programmable nanophotonic processor (PNP).

Single nitrogen vacancy centers in nanostructured diamond form high quality nodes integrated into low-loss photonic circuitry, enabling on-chip detection and signal manipulation. Pre-selection provides near-unity yield. Long coherence times are demonstrated in integrated nodes.

We present an architecture for programmable nanophotonic processors capable of arbitrary discrete transformations for quantum and classical applications. A method to combat fabrication imperfections with high fidelity is discussed along with initial experimental results.

Environmental noise and disorder play critical roles in quantum particle and wave transport in complex media, including solid-state and biological systems. Recent work has predicted that coupling between noisy environments and disordered systems, in which coherent transport has been arrested due to localization effects, could actually enhance transport. Photonic integrated circuits are promising platforms for studying such effects, with a central goal being the development of large systems providing low-loss, high-fidelity control over all parameters of the transport problem. Here, we fully map the role of disorder in quantum transport using a nanophotonic processor consisting of a mesh of 88 generalized beamsplitters programmable on microsecond timescales. Over 64,400 transport experiments, we observe several distinct transport regimes, including environment-assisted quantum transport and the ''quantum Goldilocks'' regime in strong, statically disordered discrete-time systems. Low loss and high-fidelity programmable transformations make this nanophotonic processor a promising platform for many-boson quantum simulation experiments., Comment: 4 figures, 8 pages

We design a resistive heater optimized for efficient and low-loss optical phase modulation in a silicon-on-insulator (SOI) waveguide and characterize the fabricated devices. Modulation is achieved by flowing current perpendicular to a new ridge waveguide geometry. The resistance profile is engineered using different dopant concentrations to obtain localized heat generation and maximize the overlap between the optical mode and the high temperature regions, while simultaneously minimizing optical loss due to free-carrier absorption. A 61.6 micrometer-long phase shifter was fabricated in a CMOS process with oxide cladding and two metal layers. The device features a phase-shifting efficiency of 24.77 +/- 0.43 mW/pi and a -3 dB modulation bandwidth of 130.0 +/- 5.59 kHz. The insertion loss measured for 21 devices across an 8-inch wafer was only 0.23 +/- 0.13 dB. Considering the prospect of densely integrated photonic circuits, we also quantify the separation necessary to isolate thermo-optic devices in the standard 220 nm SOI platform., This paper was published in Optics Express and is made available as an electronic reprint with the permission of OSA. The paper can be found at the following URL on the OSA website: http://dx.doi.org/10.1364/OE.22.010487. Systematic or multiple reproduction or distribution to multiple locations via electronic or other means is prohibited and is subject to penalties under law

A major challenge in nanofabrication is to pattern unconventional substrates that cannot be processed for a variety of reasons, such as incompatibility with spin coating, electron beam lithography, optical lithography, or wet chemical steps. Here, we present a versatile nanofabrication method based on re-usable silicon membrane hard masks, patterned using standard lithography and mature silicon processing technology. These masks, transferred precisely onto targeted regions, can be in the millimetre scale. They allow for fabrication on a wide range of substrates, including rough, soft, and non-conductive materials, enabling feature linewidths down to 10 nm. Plasma etching, lift-off, and ion implantation are realized without the need for scanning electron/ion beam processing, UV exposure, or wet etching on target substrates., United States. Dept. of Energy. Office of Basic Energy Sciences (Brookhaven National Laboratory. Contract DE-AC02-98CH10886), Alexander von Humboldt-Stiftung

Photonic-integrated circuits have emerged as a scalable platform for complex quantum systems. A central goal is to integrate single-photon detectors to reduce optical losses, latency and wiring complexity associated with off-chip detectors. Superconducting nanowire single-photon detectors (SNSPDs) are particularly attractive because of high detection efficiency, sub-50-ps jitter and nanosecond-scale reset time. However, while single detectors have been incorporated into individual waveguides, the system detection efficiency of multiple SNSPDs in one photonic circuit—required for scalable quantum photonic circuits—has been limited to, United States. Army Research Office (Defense Advanced Research Projects Agency. Information in a Photon (InPho) Program Grant W911NF-10-1-0416), National Science Foundation (U.S.) (Grant ECCS-1128222), United States. Air Force Office of Scientific Research. Multidisciplinary University Research Initiative (Grant FA9550-14-1-0052), Claude E. Shannon Fellowship, iQuISE Fellowship, National Science Foundation (U.S.). Integrative Graduate Education and Research Traineeship (Grant DGE-1069420), International Business Machines Corporation (Faculty Award)

With unprecedented resolution we measure the joint spectral density of photon pairs that would be generated by spontaneous four wave mixing in a silicon ring resonator and show how the quantum correlations can be tailored. © 2015 OSA.

Shared shuttle runs are an important factor in the microelectronics business ecosystem — allowing fables semiconductor companies to access advanced processes and supporting the development of new tools and processes. We report on the creation and progress of a shared shuttle program for access to advanced silicon photonics optoelectronic platforms. We present an 18 GHz integrated traveling-wave Mach-Zehnder modulator, with small-signal Vπ of 6V, and discuss sources of nonlinearity in our platform. A ring modulator is shown to have an SFDR IMD of 84 dB.Hz2/3. We present the first measurements of the nonlinear distortions of silicon-based traveling-wave modulators, and demonstrate an SFDR IMD of 103 dB.Hz2/3.

We present a traveling-wave Mach-Zehnder modulator operates at 25 Gb/s with 1 V pp . The 400 fJ/bit energy consumption is a 10× improvement over the best reported values in silicon Mach-Zehnders, becoming competitive with ring modulators.

Shared shuttle runs are an important factor of the microelectronics business ecosystem, allowing fabless semiconductor companies to access advanced processes and supporting the development of new tools and processes. We report on the creation and progress of a shared shuttle program for access to advanced silicon photonics optoelectronic platforms that we expect will create a similar environment for the field of integrated photonics.