A drastic resurgence of interest in Neutral Atom Quantum Computing has ushered in a new era of fascinating demonstrations of key enabling technologies for Fault-Tolerant Quantum Computing. Here I will give an overview of recent demonstrations enabled by Atom Computing’s systems built around alkaline-earth(-like) elements including: long coherence times, high-fidelity-scalable-low-loss readout, individually driven 1Q gates, 2Q gates at high fidelity, mid-circuit measurement, and large array refilling.

Next-generation optical atomic clocks and quantum sensors are currently being investigated for positioning, navigation, and timing (PNT) applications such as navigation in GPS-denied environments and multi-static synthetic aperture radar (SAR) as well as commercial applications in 5G-and-beyond wireless communication, satellite synchronization, and geodetic sensing. These sensors have optical, electrical, and mechanical requirements for field deployability that are more challenging than those of prior industrial laser developments. These challenges can include broad optical spectral coverage and/or challenging narrow linewidth requirements of laser sources, low-noise laser driver and feedback electronics, high-bandwidth microwave detection and generation, thermal management and precision temperature control, and environmental ruggedness including passive and active vibration suppression. The laser systems used in current experiments require unacceptably large size, weight, and power designs and are sensitive to thermal and acoustic fluctuations. In this effort, we focus on an optical clockwork that will facilitate both civilian and military applications on a path to eventual deployment in GPS-denied environments. Two key optical subsystems necessary for next-generation field-deployed timekeepers include optical frequency combs (OFCs) and ultranarrow linewidth (UNL) lasers that are suitable for the interrogation of ultranarrow clock transitions. Vescent has developed a radiation-hardened-by-design optical frequency comb and is miniaturizing and ruggedizing these comb systems to eventually be deployed on satellites. The Technology Readiness Level of these OFCs has been tested at level 6 without any appreciable performance degradation and will be discussed. A summary of how OFC and UNL systems can be integrated into potential optical atomic clock systems will be presented.

Quantum sensing is broadly defined as the use of quantum materials, quantum coherence, and/or quantum entanglement to measure physical quantities and/or to enhance the sensitivity of classical analytical measurements. Certain materials exhibit interesting quantum properties that have the potential to be utilized in quantum sensing applications. One such quantum property is electronic spin, which is utilized in this work. Here, we built a custom apparatus capable of conducting both optically detected magnetic resonance (ODMR) and spin relaxometry. The quantum material investigated was an ensemble of nitrogen vacancies (NV) in nanodiamonds. We have characterized the system and measured ODMR spectra at different applied DC magnetic fields and observed the expected splitting of the resonances due the Zeeman effect. We also have measured the spin relaxation times for two different powers of the applied AC magnetic field. The lower power dataset exhibited expected exponential temporal dependence of the relaxation of a modified spin state, whereas the higher power dataset exhibited stretched exponential dependence of the evolution of the modified spin state, indicating the presence of high-power phenomena that emerge that retard the relaxation of the spin state.

Rare-earth ion defects in solid-state hosts have emerged as a promising candidate for emissive quantum memories owing to their inherent spin–photon interface and long optical and spin coherence times. Erbium (Er³⁺) in particular has optical transitions in the C-band making it well suited to the use of existing telecom technology infrastructure. In this work, we present a platform to integrate rare-earth ions into standard silicon photonic circuits. Erbium is co-deposited in CMOS-compatible TiO₂ host films onto SOI and patterned into high Purcell factor photonic crystal cavities. Purcell factors in excess of 500 are observed and transient spectral hole burning and photoluminescence excitation scans reveal homogeneous linewidths below 15 MHz. Additionally, we show that photonic wirebonding can provide a solution for low-loss and thermally stable fiber-to-chip coupling.

New results have been derived for wavefronts for single and multiple photons and combined with quantum hyperentanglement, multiphoton entanglement, and network properties. These new results arise from use of Lie algebra techniques for disentanglement of certain operators related to propagation. The new results include closed form exact expressions for functions related to the disentanglement process. These expressions permit many different solutions to the disentanglement process. These new expressions offer much higher order programmable self-accelerating curves to be created. This in turn facilitates more effective quantum-based sensing and communication around corners and other obstacles, with reduced loss. This approach significantly increases the information that can be communicated or stored when using a recently derived extension of superdense coding. The resulting wavefronts are shown to reduce diffraction and have the self-healing property, i.e. automatically reobtain their original form when initially damaged by turbulence. Each node of the network will transmit at least one signal and one ancilla photon in a hyper-entangled state. Parameters used for hyper-entanglement will include photon polarization, energy-time, orbital angular momentum, radial quantum number, etc. as well as up to 12 parameters characterizing the wavefront properties. Eigenfunctions of operators associated with each 2D paraxial wave equation will be determined each being a function of up to six parameters. The same wavefront or combinations of wavefronts can be applied to multiple photons to combine hyper-entanglement with multiphoton entanglement offering additional improvements. Measures of effectiveness such as the signal-to-noise ratio (SNR), measurement time, resolution measures, and Holevo bound are considered.

The optical properties of erbium-doped yttrium iron garnet (Er:YIG) thin films have been studied at temperatures between 1.6 K and 260 K. Single crystal YIG thin films on GGG (Gd₃Ga₅O₁₂) have been implanted with 20 keV Er⁺ ions to the fluences of (0.5 or 1.0) × 10¹⁶ ion/cm². Erbium concentration has been kept on a level preventing a detrimental effect on the magnetic properties of the YIG garnet while providing the ion ratio enough for intense photoluminescence. Raman spectra for the YIG films on GGG substrate which are similar to the literature data have been observed. No effect of the erbium implantation on Raman peaks has been revealed and explained by the small thickness of the implanted layer. Photoluminescence signals appearing with temperature cooling between 680nm and 720nm have been observed and attributed to the emission from the erbium ions. Our result reveals that doping YIG by Er can be useful for tailoring the magneto-optical properties of YIG.

Integrated optical phased arrays (OPAs), fabricated in advanced silicon-photonics platforms, enable manipulation and dynamic control of free-space light in a compact form factor, at low costs, and in a non-mechanical way. This talk will highlight our work on developing OPA-based platforms, devices, and systems that enable chip-based solutions to high-impact problems in areas including augmented-reality displays, LiDAR sensing for autonomous vehicles, optical trapping for biophotonics, 3D printing, and trapped-ion quantum engineering.

A quantum autoencoder functions as a type of quantum artificial neural network designed to compress sequences of quantum states through a training process. In this work, we analyze the compression performance of quantum autoencoders and obtain an asymptotic upper bound on the encoder’s compression rate.

The development of quantum artificial intelligence (QAI) may lead a new computing revolution. This paper studies a model of quantum inference engine (QIE), which is a novel architecture designed to enhance quantum artificial intelligence by leveraging quantum principles. It discusses a role of the quantum superposition and entanglement in the transition from classical to quantum computational models, which surpasses the classical inference engines. The details of QIE’s structure is provided, from the quantum knowledge base to the inference mechanisms, demonstrating the capacity in the parallel processing and complex probabilistic reasoning. This research outlines the significant advancements in computational inference with the quantum technologies, especially in the era of the Noisy Intermediate-Scale Quantum (NISQ). The QIE shows its improved efficiency, scalability, and accuracy in handling intricate data and probabilistic models. The quantum inference engine will be useful for the research and applications in quantum artificial intelligence.

Physically unclonable functions (PUFs) are designed to act as device ‘fingerprints.’ Given an input challenge, the PUF circuit should produce an unpredictable response for use in situations such as root-of-trust applications and other hardware-level cybersecurity applications. PUFs are typically subcircuits present within integrated circuits (ICs), and while conventional IC PUFs are well-understood, several implementations have proven vulnerable to malicious exploits, including those perpetrated by machine learning (ML)-based attacks. Such attacks can be difficult to prevent because they are often designed to work even when relatively few challenge-response pairs are known in advance. Hence the need for both more resilient PUF designs and analysis of ML-attack susceptibility. Previous work has developed a PUF for photonic integrated circuits (PICs). A PIC PUF not only produces unpredictable responses given manufacturing-introduced tolerances, but is also less prone to electromagnetic radiation eavesdropping attacks than a purely electronic IC PUF. In this work, we analyze the resilience of the proposed photonic PUF when subjected to ML-based attacks. Specifically, we describe a computational PUF model for producing the large datasets required for training ML attacks; we analyze the quality of the model; and we discuss the modeled PUF’s susceptibility to ML-based attacks. We find that the modeled PUF generates distributions that resemble uniform white noise, explaining the exhibited resilience to neural-network-based attacks designed to exploit latent relationships between challenges and responses. Preliminary analysis suggests that the PUF exhibits similar resilience to generative adversarial networks, and continued development will show whether more-sophisticated ML approaches better compromise the PUF and—if so—how design modifications might improve resilience.

Feature selection is a critical step in the machine learning (ML) model development workflow, aimed at identifying the most relevant subset of features from a dataset to improve ML model performance. In this paper, we investigate the use of quantum annealing to enhance the efficiency and effectiveness of feature selection, as compared to classical algorithmic methods for feature selection, prior to constructing a ML model for Internet of Things network intrusion detection. We aim to determine the optimal selection of network traffic features that contribute most to the detection of network intrusions. Leveraging a quantum annealing algorithm, which exploits quantum mechanics principles to find optimal solutions, along with D-Wave’s hybrid quantum computing service, enables us to successfully tackle this combinatorial optimization problem. Our quantum machine learning approach leverages the strengths of both classical and quantum computing, offering a “one-shot” solution to feature selection without the need for iterative ML model training or incremental construction of the solution.

Several cryptographic systems depend upon the computational difficulty of reversing cryptographic hash functions. Robust hash functions transform inputs to outputs in such a way that the inputs cannot be later retrieved in a reasonable amount of time even if the outputs and the function that created them are known. Consequently, hash functions can be cryptographically secure, and they are employed in encryption, authentication, and other security methods. It has been suggested that such cryptographically-secure hash functions will play a critical role in the era of post-quantum cryptography (PQC), as they do in conventional systems. In this work, we introduce a procedure that leverages the principle of reversibility to generate circuits that invert hash functions. We provide a proof-of-concept implementation and describe methods that allow for scaling the hash function inversion approach. Specifically, we implement one manifestation of the algorithm as part of a more general automated quantum circuit synthesis, compilation, and optimization toolkit. We illustrate production of reversible circuits for crypto-hash functions that inherently provide the inverse of the function, and we describe data structures that increase the scalability of the hash function inversion approach.

While photonic quantum circuits may be implemented using polarization-encoded qubits, their photonic integrated circuit (PIC) realization has been limited by on-chip impairments such as mode dispersion and polarization state stability that do not hinder bulk-optic, table-top setups. In this paper, we will present an interpretation of on-chip polarization and provide the beginning of a portfolio of components that may be used for polarization-encoded qubits. Central to our work is the use of waveguides of square cross-section, which symmetrically support orthogonal TE and TM modes with perpendicular electric fields. Preliminary designs for components to manipulate these modes are presented, along with measurements relevant to polarization in PICs. The research has relevance, as well, to sensing and security.

It has been shown that the optoelectronic properties of WSe₂, such as strong light absorption, high carrier mobility, and direct bandgap, make it a desirable material for a range of devices, including photodetectors, photovoltaics, and light-emitting diodes. At the same time, the physical characteristics of materials, including their electrical and optical properties, are greatly influenced by defects. The structural defects in WSe₂ have a distinctive effect on their light-matter interactions, and the ensuing performance of the devices. The prospect of utilizing these effects in cutting-edge technologies, such as quantum information and quantum optoelectronics, comes when the nature of such defects in WSe₂ is better understood and regulated through various defect generation schemes. Here, we discuss how surface modifications in mechanically-exfoliated WSe₂ crystallites through a plasma process effects the light emission properties of the crystallites, where such studies are conducted through Raman and photoluminescence spectroscopy.

We report a fully-packaged, on-chip multi-photon-pair source using spontaneous-four-wave-mixing (SFWM) in silicon waveguide spirals. Our source consists of four, two-centimeter long spiral waveguides that are pumped in parallel using a pulsed laser source. We detected a four-fold coincidence rate of 180±20Hz, corresponding to an on-chip coincidence rate of 908±42Hz.

Frequency-bin encoding is massively parallelizable and robust for optical fiber transmission. When coupled with an additional degree of freedom (DoF), the expansion of the Hilbert space allows for deterministic controlled operations between two DoFs within a single photon. Such capabilities, when combined with photonic hyperentanglement, are of great value for quantum communication protocols, including dense coding and single-copy entanglement distillation. In this talk, we present an all-fiber-coupled, ultrabroadband polarization–frequency hyperentangled source and conduct comprehensive quantum state tomography across multiple dense wavelength division multiplexing channels spanning the optical C+L-band (1530–1625 nm). In addition, we design and implement a high-fidelity controlled-NOT (cnot) operation between polarization and frequency DoFs by exploiting electro-optic phase modulation within a fiber Sagnac loop. Collectively, our hyperentangled source and two-qubit gate should unlock new opportunities for harnessing polarization–frequency resources in established telecommunication fiber networks for future quantum applications.

The star coupler is an integrated diffractive element which realizes an imperfect discrete Fourier transform in the optical path basis. We simulate star couplers of many different sizes / dimensions and calculate their mixing entropy and their transmission. Based on these results, we discuss the suitability of star coupler devices for enabling multi-plane light conversion in the path basis using photonic integrated circuits.

Photonic integrated circuits provide a scalable platform for photonics-based quantum technologies. However, integrating quantum emitters and electro-optic cavities within this platform remains an open challenge proving to be a major hurdle from implementing key functionalities for quantum photonics, such as single photon sources and nonlinearities. Here, we address this shortcoming with the hybrid integration of InAs/InP quantum dot emitters on foundry silicon photonics and the implementation of photonic crystal cavities in thin-film lithium niobate. Co-integrated on-chip electronics allow us to tune the emission properties of the quantum dots while enabling GHz-rate coherent modulation over photons trapped in the cavities, thus providing a new level of programmability over interactions between optical fields and atom-like systems in integrated circuits. Our results open the door to a new generation of quantum information processors that can be manufactured in leading semiconductor foundries.

This study presents a comprehensive bibliometric analysis of the fusion between quantum tomography and the Extended Kalman Filter (EKF), emphasizing its superiority in refining quantum tomographic reconstructions compared to conventional methodologies. By intersecting quantum mechanical principles with sophisticated filtering technologies, our analysis uncovers emergent research trajectories within the domain of quantum information science. It underscores the significant potential that this integration holds for the evolution of quantum technology applications. Furthermore, this paper delineates the expansive impact of improved quantum state information across a spectrum of scientific fields, thereby enriching the discourse on quantum state estimation and its applications. Through this investigation, we contribute to a deeper understanding of the pivotal role that advanced filtering techniques, specifically the EKF, play in advancing quantum tomography, paving the way for future innovations in quantum computing and beyond.