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Entangling quantum memories via heralded photonic Bell measurement
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Qudits as Quantum Memory
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Quantum Memories, Processors and Transducers
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Hierarchical memories: Simulating quantum LDPC codes with local gates
Constant-rate low-density parity-check (LDPC) codes are promising candidates for constructing efficient fault-tolerant quantum memories. However, if physical gates are subject to geometric-locality constraints, it becomes challenging to realize these codes. In this paper, we construct a new family of [[N,K,D]] codes, referred to as hierarchical codes, that encode a number of logical qubits K=Ω(N/log(N) 2 ). The N th element of this code family is obtained by concatenating a constant-rate quantum LDPC code with a surface code; nearest-neighbor gates in two dimensions are sufficient to implement the corresponding syndrome-extraction circuit and achieve a threshold. Below threshold the logical failure rate vanishes superpolynomially as a function of the distance D(N). We present a bilayer architecture for implementing the syndrome-extraction circuit, and estimate the logical failure rate for this architecture. Under conservative assumptions, we find that the hierarchical code outperforms the basic encoding where all logical qubits are encoded in the surface code.
Roadmap for unconventional computing with nanotechnology
Abstract In the ‘Beyond Moore’s Law’ era, with increasing edge intelligence, domain-specific computing embracing unconventional approaches will become increasingly prevalent. At the same time, adopting a variety of nanotechnologies will offer benefits in energy cost, computational speed, reduced footprint, cyber resilience, and processing power. The time is ripe for a roadmap for unconventional computing with nanotechnologies to guide future research, and this collection aims to fill that need. The authors provide a comprehensive roadmap for neuromorphic computing using electron spins, memristive devices, two-dimensional nanomaterials, nanomagnets, and various dynamical systems. They also address other paradigms such as Ising machines, Bayesian inference engines, probabilistic computing with p-bits, processing in memory, quantum memories and algorithms, computing with skyrmions and spin waves, and brain-inspired computing for incremental learning and problem-solving in severely resource-constrained environments. These approaches have advantages over traditional Boolean computing based on von Neumann architecture. As the computational requirements for artificial intelligence grow 50 times faster than Moore’s Law for electronics, more unconventional approaches to computing and signal processing will appear on the horizon, and this roadmap will help identify future needs and challenges. In a very fertile field, experts in the field aim to present some of the dominant and most promising technologies for unconventional computing that will be around for some time to come. Within a holistic approach, the goal is to provide pathways for solidifying the field and guiding future impactful discoveries.
Phononic bus for coherent interfaces between a superconducting quantum processor, spin memory, and photonic quantum networks
A hybrid quantum system performs high-fidelity quantum state transduction between a superconducting (SC) microwave qubit and the ground state spin system of a solid-state artificial atom. This transduction is mediated via an acoustic bus connected by piezoelectric transducers to the SC microwave qubit. For SC circuit qubits and diamond silicon vacancy centers in an optimized phononic cavity, the system can achieve quantum state transduction with fidelity exceeding 99% at a MHz-scale bandwidth. By combining the complementary strengths of SC circuit quantum computing and artificial atoms, the hybrid quantum system provides high-fidelity qubit gates with long-lived quantum memory, high-fidelity measurement, large qubit number, reconfigurable qubit connectivity, and high-fidelity state and gate teleportation through optical quantum networks.
Quantum optical memory for entanglement distribution
Optical photons are powerful carriers of quantum information, which can be delivered in free space by satellites or in fibers on the ground over long distances. Entanglement of quantum states over long distances can empower quantum computing, quantum communications, and quantum sensing. Quantum optical memories are devices designed to store quantum information in the form of stationary excitations, such as atomic coherence, and are capable of coherently mapping these excitations to flying qubits. Quantum memories can effectively store and manipulate quantum states, making them indispensable elements in future long-distance quantum networks. Over the past two decades, quantum optical memories with high fidelities, high efficiencies, long storage times, and promising multiplexing capabilities have been developed, especially at the single-photon level. In this review, we introduce the working principles of commonly used quantum memory protocols and summarize the recent advances in quantum memory demonstrations. We also offer a vision for future quantum optical memory devices that may enable entanglement distribution over long distances.
Robust Millisecond Coherence Times of Erbium Electron Spins
Erbium doped solids are prime candidates for quantum memories in optical quantum networks given their telecom-compatible photon emission. An electron spin of erbium with millisecond coherence time is desirable for generating remote entanglement between adjacent quantum network nodes. Here, in this study, we report GHz-range electron spin transitions of 167 Er 3+ in yttrium oxide (Y 2 O 3 ) matrix with coherence times that are consistently longer than a millisecond. By polarizing para magnetic impurity spins we achieve a spin T 2 up to 1.46 ms, and up to 7.1 ms after dynamical decoupling. These coherence lifetimes are among the longest found for erbium in crystalline matrices despite the presence of host nuclear spins. We further enhance the coherence time beyond conventional dynamical decoupling, using customized sequences to simultaneously mitigate spectral diffusion and dipolar interactions. Our study not only establishes 167 Er 3+ : Y 2 O 3 as a significant quantum memory platform but also provides a guideline for engineering long-lived erbium spins in a variety of host materials for quantum technologies.
Particle track classification using quantum associative memory
Pattern recognition algorithms are commonly employed to simplify the challenging and necessary step of track reconstruction in sub-atomic physics experiments. Aiding in the discrimination of relevant interactions, pattern recognition seeks to accelerate track reconstruction by isolating signals of interest. In high collision rate experiments, such algorithms can be particularly crucial for determining whether to retain or discard information from a given interaction even before the data is transferred to tape. As data rates, detector resolution, noise, and inefficiencies increase, pattern recognition becomes more computationally challenging, motivating the development of higher efficiency algorithms and techniques. Quantum associative memory is an approach that seeks to exploits quantum mechanical phenomena to gain advantage in learning capacity, or the number of patterns that can be stored and accurately recalled. Here, we study quantum associative memory based on quantum annealing and apply it to the particle track classification. We focus on discrimination models based on Ising formulations of quantum associative memory model (QAMM) recall and quantum content-addressable memory (QCAM) recall. We characterize classification performance of these approaches as a function detector resolution, pattern library size, and detector inefficiencies, using the D-Wave 2000Q processor as a testbed. Discrimination criteria is set using both solution-state energy and classification labels embedded in solution states. We find that energy-based QAMM classification performs well in regimes of small pattern density and low detector inefficiency. In contrast, state-based QCAM achieves reasonably high accuracy recall for large pattern density and the greatest recall accuracy robustness to a variety of detector noise sources.
Particle Track Classification Using Quantum Associative Memory (Final Technical Report)
This project explored the use of quantum-assisted algorithms for pattern matching in sub-atomic physics experiments. Pattern matching algorithms are commonly employed to prune data of random noise and to help discriminate between signals generated by particle tracks of interest and signals generated by background events. The quantum-assisted algorithms explored in this project were based on an Ising formulation of quantum associative model (QAMM) recall and quantum content-addressable memory (QCAM) recall. The recall is performed by comparing a probe pattern with those stored in a library of patterns encoded in the QAMM/QCAM model. The classification accuracy of QAMM and QCAM recall was determined as a function of detector resolution, noise, and efficiency and pattern density, where pattern density is defined as the ratio of the number of reference signal patterns encoded in the library to each pattern’s length. We found that QAMM achieved high classification accuracy when applied to datasets with low pattern density. QCAM achieved high classification accuracy for datasets with high pattern density and was found to be more robust to detector noise. The project methodology and results are described in detail in our arXiv preprint (arXiv:2011.11848) . This project was conducted by scientists at the Johns Hopkins University Applied Physics Laboratory and Oak Ridge National Laboratory from August 2018 to August 2020 and was supported by DOE grant DE-SC0019497.
Algorithmic optimization of quantum optical storage in solids
Quantum memory devices with high storage efficiency and bandwidth are essential elements for future quantum networks. Solid-state quantum memories can provide broadband storage, but they primarily suffer from low storage efficiency. We use passive optimization and algorithmic optimization techniques to demonstrate nearly a sixfold enhancement in quantum memory efficiency. In this regime, we demonstrate coherent and single-photon-level storage with a high signal-to-noise ratio. The optimization technique presented here can be applied to most solid-state quantum memories to significantly improve the storage efficiency without compromising the memory bandwidth. Published by the American Physical Society 2024
Er-doped anatase TiO 2 thin films on LaAlO 3 (001) for quantum interconnects (QuICs)
Rare-earth ions (REIs) doped into solid-state crystal hosts offer an attractive platform for realizing quantum interconnects that can function as quantum memories and quantum repeaters. The 4f valence electrons of REIs are shielded by 5s and 5p electrons and undergo highly coherent transitions even when embedded in host crystals. In particular, Er 3+ has an optical transition in the telecom band that is suitable for low-loss communication. Recently, REIs in thin film systems have gained interest due to potential advantages in providing a flexible host crystal environment, enabling scalable on-chip integration with other quantum devices. Here, we investigate the structural and optical properties of Er-doped anatase TiO 2 thin films on LaAlO 3 (001) substrates. By choosing a system with minimal lattice mismatch and adjusting Er-dopant concentration, we achieve optical inhomogeneous linewidths of 5 GHz at 4.5 K. Furthermore, we show that 9 nm-thick buffer and capping layers can reduce the linewidth by more than 40%, suggesting a pathway to further narrowing linewidths in this system. We also identify that Er 3+ ions mainly incorporate into substitutional Ti 4+ sites with non-polar D 2d symmetry, which makes Er dopants insensitive to the first order to local electric fields from impurities and is desirable for coherence properties of Er 3+ spins.
Incompatibility as a Resource for Programmable Quantum Instruments
Quantum instruments represent the most general type of quantum measurement, as they incorporate processes with both classical and quantum outputs. In many scenarios, it may be desirable to have some “on-demand” device that is capable of implementing one of many possible instruments whenever the experimenter desires. We refer to such objects as programmable instrument devices (PIDs), and this paper studies PIDs from a resource-theoretic perspective. A physically important class of PIDs are those that do not require quantum memories to implement, and these are naturally “free” in this resource theory. Additionally, these free objects correspond precisely to the class of unsteerable channel assemblages in the study of channel steering. The traditional notion of measurement incompatibility emerges as a resource in this theory since any PID controlling an incompatible family of instruments requires a quantum memory to build. We identify an incompatibility preorder between PIDs based on whether one can be transformed into another using processes that do not require additional quantum memories. Necessary and sufficient conditions are derived for when such transformations are possible based on how well certain guessing games can be played using a given PID. Ultimately our results provide an operational characterization of incompatibility, and they offer semi-device-independent tests for incompatibility in the most general types of quantum instruments. Published by the American Physical Society 2024
Spin-optomechanical cavity interfaces by deep subwavelength phonon-photon confinement
A central goal of quantum information science is transferring qubits between space, time, and modality. Spin-based systems in solids are promising quantum memories, but high-fidelity transfer of their quantum states to telecom optical fields remains challenging. Here, we introduce a phonon-mediated interface between spins in a diamond nanobeam optomechanical crystal and telecom optical fields by a simultaneous deep-subwavelength confinement of optical and acoustic fields with mode volumes $V_{\textrm{mech}}$$/Λ^3_\textrm{p} ~ 10^{-5}$ and $V_{\textrm{opt}}$$/λ^3 ~ 10^{−3}$, respectively. This confinement boosts the spin-mechanical coupling rate of Group-IV silicon vacancy (SiV − ) centers by an order of magnitude to ~ 32 MHz while retaining high acousto-optical couplings. The optical cavity couples to the spin irrespective of the emitter’s native excited states, avoiding spectral diffusion. Using Quantum Monte Carlo simulations, we estimate heralded entanglement fidelities exceeding 0.96 between two such interfaces. We anticipate broad utility beyond diamond emitter-telecom systems to most solid-state quantum memories.
Er : Li Nb O 3 with High Optical Coherence Enabling Optical Thickness Control
Integrated photonics capable of incorporating rare-earth ions with high optical coherence is desirable for realizing efficient quantum transducers, compact quantum memories, and hybrid quantum systems. Here we describe a photonic platform based on the SmartCut erbium-doped lithium niobate thin film, and explore its stable optical transitions at telecom wavelength in a dilution refrigerator. Optical coherence time of up to 180μs, rivaling the value of bulk crystals, is achieved in optical ridge waveguides and ring resonators. With this integrated platform, we demonstrate tunable light-ion interaction and flexible control of optical thickness by exploiting long waveguides, whose lengths are in principle variable. This unique ability to obtain high optical density using low-concentration ions further leads to the observation of multiecho pulse trains in centimeter-long waveguides. Our results establish a promising photonic platform for quantum information processing with rare-earth ions.
SRF Levitation and Trapping of Nanoparticles
A proposal has been conceived to levitate and trap mesoscopic particles using radio frequency (RF) fields in a superconducting RF(SRF) cavity. Exploiting the intrinsic characteristics of an SRF cavity, this proposal aims at overcoming a major limit faced by state-of-the-art laser trapping techniques. The goal of the proposal is to establish a foundation to enable observation of quantum phenomena of an isolated mechanical oscillator interacting with microwave fields. An experiment supported by LDRD funding at JLab has started to address R&D issues relevant to these new research directions using existing SRF facilities at JLab. The success of this experiment would establish its groundbreaking relevance to quantum information science and technology, which may lead to applications in precision force measurement sensors, quantum memories, and alternative quantum computing implementations with promises for superior coherence characteristics and scalability well beyond the start-of-the-art. In this contribution, we will introduce the proposal and basic consideration of the experiment.