Related papers: Nontrapping Tunable Topological Photonic Memory
Phase-change memory (PCM) is a scalable and low latency non-volatile memory (NVM) technology that has been proposed to serve as storage class memory (SCM), providing low access latency similar to DRAM and often approaching or exceeding the…
Photonic neuromorphic computing offers a promising route to overcoming the limitations of conventional von Neumann architectures by exploiting the high bandwidth, low latency, and massive parallelism of optical systems. However, most…
Reconfigurable photonic mesh networks of tunable beamsplitter nodes can linearly transform $N$-dimensional vectors representing input modal amplitudes of light for applications such as energy-efficient machine learning hardware, quantum…
A hallmark of biological intelligence is neural reuse,the ability to preserve past learning and repurpose it for new tasks and changing environments. Photonic neural hardware offers high-bandwidth, low-latency computation, but current…
The rapid rise of artificial intelligence, and in-memory computing has reinvigorated research on scalable, energy-efficient, and reconfigurable photonic hardware. Non-volatile phase-change materials (PCMs) are attractive, as they offer…
Particles hopping on a two-dimensional hyperbolic lattice feature unconventional energy spectra and wave functions that provide a largely uncharted platform for topological phases of matter beyond the Euclidean paradigm. Using real-space…
As computing resource demands continue to escalate in the face of big data, cloud-connectivity and the internet of things, it has become imperative to develop new low-power, scalable architectures. Neuromorphic photonics, or photonic neural…
After more than 70 years of development, holography has become an essential tool of modern optics in many applications. In fact, for various applications of different kinds of holographic techniques, stability and antijamming ability are…
Motivated by new capabilities to realise artificial gauge fields in ultracold atomic systems, and by their potential to access correlated topological phases in lattice systems, we present a new strategy for designing topologically…
We demonstrate tunable Schottky barrier height and record photo-responsivity in a new-concept device made of a single-layer CVD graphene transferred onto a matrix of nanotips patterned on n-type Si wafer. The original layout, where…
Photonic computing offers a low-power, high-bandwidth paradigm for information processing; however, the analogue nature of conventional architectures means that intrinsic noise and fabrication imperfections greatly impact performance,…
Photonic computing promises ultrafast and energy-efficient artificial intelligence. However, existing photonic neural networks (PNNs) remain functionally shallow and difficult to scale. Here we establish a theory-guided framework showing…
Efficient storage of solar thermal energy is still one of the major bottlenecks in realizing dispatchable solar thermal systems. Present work is a significant step in this direction, wherein, we propose, thermochromism assisted photon…
We present an integrated magneto-photonic device for all-optical switching of non-volatile multi-bit spintronic memory. The bits are based on stand-alone magneto-tunnel junctions which are perpendicularly magnetized with all-optically…
Development of memory devices with ultimate performance has played a key role in innovation of modern electronics. As a mainstream technology nonvolatile memory devices have manifested high capacity and mechanical reliability, however…
Quantum networks will enable a variety of applications, from secure communication and precision measurements to distributed quantum computing. Storing photonic qubits and controlling their frequency, bandwidth and retrieval time are…
Emergent collective modes in lattices give birth to many intriguing physical phenomena in condensed matter physics. Among these collective modes, large-area modes typically feature small-level spacings, while a mode with stable frequency…
Reservoir computing is a brain inspired approach for information processing, well suited to analogue implementations. We report a photonic implementation of a reservoir computer that exploits frequency domain multiplexing to encode neuron…
The computing speeds in modern multi-core processors and big data servers are no longer limited by the on-chip transistor density that doubles every two years following the Moores law, but are limited by the on-chip data communication…
Deploying state-of-the-art CNNs requires power-hungry processors and off-chip memory. This precludes the implementation of CNNs in low-power embedded systems. Recent research shows CNNs sustain extreme quantization, binarizing their weights…