Finite-key analysis of high-dimensional time-energy entanglement-based quantum key distribution. - Catherine Lee 001; Jacob Mower; Zheshen Zhang; Jeffrey H. Shapiro; Dirk R. Englund (Quantum Inf. Process., 2015)

WDM Weighted Sum in an 8x8 SOA-Based InP Cross-Connect for Photonic Deep Neural Networks. - Bin Shi; Nicola Calabretta; Darius Bunandar; Dirk R. Englund; Ripalta Stabile (PSC, 2018)

Room-Temperature Quantum Sensing in CMOS: On-Chip Detection of Electronic Spin States in Diamond Color Centers for Magnetometry. - Mohamed I. Ibrahim; Christopher Foy; Donggyu Kim; Dirk R. Englund; Ruonan Han 001 (VLSI Circuits, 2018)

Photonic Recurrent Ising Sampler. - Charles Roques-Carmes; Yichen Shen 001; Cristian Zanoci; Mihika Prabhu; Fadi Atieh; Li Jing 001; Tena Dubcek; Vladimir Ceperic; John D. Joannopoulos; Dirk R. Englund; Marin Soljacic (CoRR, 2018)

Large-Scale Optical Neural Networks based on Photoelectric Multiplication. - Ryan Hamerly; Alex Sludds; Liane Bernstein; Marin Soljacic; Dirk R. Englund (CoRR, 2018)

A Scalable Quantum Magnetometer in 65nm CMOS with Vector-Field Detection Capability. - Mohamed I. Ibrahim; Christopher Foy; Dirk R. Englund; Ruonan Han 001 (ISSCC, 2019)

Freely scalable and reconfigurable optical hardware for deep learning. - Liane Bernstein; Alexander Sludds; Ryan Hamerly; Vivienne Sze; Joel S. Emer; Dirk R. Englund (CoRR, 2020)

Quantum advantage for differential equation analysis. - Bobak Toussi Kiani; Giacomo De Palma; Dirk R. Englund; William M. Kaminsky; Milad Marvian; Seth Lloyd (CoRR, 2020)

Robust Zero-Change Self-Configuration of the Rectangular Mesh. - Ryan Hamerly; Saumil Bandyopadhyay; Dirk R. Englund (OFC, 2021)

IOI: In-network Optical Inference. - Zhizhen Zhong; Weiyang Wang; Manya Ghobadi; Alexander Sludds; Ryan Hamerly; Liane Bernstein; Dirk R. Englund (OptSys@SIGCOMM, 2021)

Hardware error correction for programmable photonics. - Saumil Bandyopadhyay; Ryan Hamerly; Dirk R. Englund (CoRR, 2021)

Accurate Self-Configuration of Rectangular Multiport Interferometers. - Ryan Hamerly; Saumil Bandyopadhyay; Dirk R. Englund (CoRR, 2021)

Stability of Self-Configuring Large Multiport Interferometers. - Ryan Hamerly; Saumil Bandyopadhyay; Dirk R. Englund (CoRR, 2021)

Infinitely Scalable Multiport Interferometers. - Ryan Hamerly; Saumil Bandyopadhyay; Dirk R. Englund (CoRR, 2021)

Quantum algorithms for group convolution, cross-correlation, and equivariant transformations. - Grecia Castelazo; Quynh The Nguyen; Giacomo De Palma; Dirk R. Englund; Seth Lloyd; Bobak Toussi Kiani (CoRR, 2021)

High-Scalability CMOS Quantum Magnetometer With Spin-State Excitation and Detection of Diamond Color Centers. - Mohamed I. Ibrahim; Christopher Foy; Dirk R. Englund; Ruonan Han 001 (IEEE J. Solid State Circuits, 2021)

Experimental quantum speed-up in reinforcement learning agents. - Valeria Saggio; Beate E. Asenbeck; Arne Hamann 002; Teodor Strömberg; Peter Schiansky; Vedran Dunjko; Nicolai Friis; Nicholas C. Harris; Michael Hochberg; Dirk R. Englund; Sabine Wölk; Hans J. Briegel; et al. (Nat., 2021)

Congestion-free Multiflow Quantum Tree Network with Logarithmic Overhead. - Hyeongrak Choi; Marc Grau Davis; Dirk R. Englund (SEC, 2022)

Design of Asymptotically Perfect Linear Feedforward Photonic Circuits. - Ryan Hamerly; Saumil Bandyopadhyay; Alexander Sludds; Dirk R. Englund (OFC, 2022)

Demonstration of WDM-Enabled Ultralow-Energy Photonic Edge Computing. - Alexander Sludds; Ryan Hamerly; Saumil Bandyopadhyay; Zhizhen Zhong; Zaijun Chen; Liane Bernstein; Manya Ghobadi; Dirk R. Englund (OFC, 2022)

Coherent VCSEL Network Computing. - Zaijun Chen; Alexander Sludds; Ronald Davis; Ian Christen; Lamia Ateshian; Liane Bernstein; Tobias Heuser; Niels Heermeier; James A. Lott; Stephan Reitzenstein; Ryan Hamerly; Dirk R. Englund (OECC/PSC, 2022)

WDM-Enabled Photonic Edge Computing. - Alexander Sludds; Ryan Hamerly; Saumil Bandyopadhyay; Zaijun Chen; Zhizhen Zhong; Liane Bernstein; Manya Ghobadi; Dirk R. Englund (OECC/PSC, 2022)

Delocalized Photonic Deep Learning on the Internet's Edge. - Alexander Sludds; Saumil Bandyopadhyay; Zaijun Chen; Zhizhen Zhong; Jared Cochrane; Liane Bernstein; Darius Bunandar; P. Ben Dixon; Scott A. Hamilton; Matthew Streshinsky; Ari Novack; Tom Baehr Jones; et al. (CoRR, 2022)

All-Photonic Artificial Neural Network Processor Via Non-linear Optics. - Jasvith Raj Basani; Mikkel Heuck; Dirk R. Englund; Stefan Krastanov (CoRR, 2022)

Single-Shot Optical Neural Network. - Liane Bernstein; Alexander Sludds; Christopher Panuski; Sivan Trajtenberg-Mills; Ryan Hamerly; Dirk R. Englund (CoRR, 2022)

Netcast: Low-Power Edge Computing with WDM-defined Optical Neural Networks. - Ryan Hamerly; Alexander Sludds; Saumil Bandyopadhyay; Zaijun Chen; Zhizhen Zhong; Liane Bernstein; Dirk R. Englund (CoRR, 2022)

Deep Learning with Coherent VCSEL Neural Networks. - Zaijun Chen; Alexander Sludds; Ronald Davis; Ian Christen; Liane Bernstein; Tobias Heuser; Niels Heermeier; James A. Lott; Stephan Reitzenstein; Ryan Hamerly; Dirk R. Englund (CoRR, 2022)

Frequency-Encoded Deep Learning with Speed-of-Light Dominated Latency. - Ronald Davis; Zaijun Chen; Ryan Hamerly; Dirk R. Englund (CoRR, 2022)

Single chip photonic deep neural network with accelerated training. - Saumil Bandyopadhyay; Alexander Sludds; Stefan Krastanov; Ryan Hamerly; Nicholas C. Harris; Darius Bunandar; Matthew Streshinsky; Michael Hochberg; Dirk R. Englund (CoRR, 2022)

A Self-Similar Sine-Cosine Fractal Architecture for Multiport Interferometers. - Jasvith Raj Basani; Sri Krishna Vadlamani; Saumil Bandyopadhyay; Dirk R. Englund; Ryan Hamerly (CoRR, 2022)

Transferable Learning on Analog Hardware. - Sri Krishna Vadlamani; Dirk R. Englund; Ryan Hamerly (CoRR, 2022)

THz Cryo-CMOS Backscatter Transceiver: A Contactless 4 Kelvin-300 Kelvin Data Interface. - Jinchen Wang; Mohamed I. Ibrahim; Isaac B. Harris; Nathan M. Monroe; Muhammad Ibrahim Wasiq Khan; Xiang Yi; Dirk R. Englund; Ruonan Han 001 (ISSCC, 2023)

A Phase-Optimal Linear Photonic Architecture. - Ryan Hamerly; Alexander Sludds; Dirk R. Englund (PSC, 2023)

Photonic Activation Function Using Sound Waves. - Grigorii Slinkov; Steven Becker; Dirk R. Englund; Birgit Stiller (PSC, 2023)

Towards Distributed Quantum Computing by Qubit and Gate Graph Partitioning Techniques. - Marc Grau Davis; Joaquin Chung 001; Dirk R. Englund; Rajkumar Kettimuthu (QCE, 2023)

Reinforcement Learning for Gate Synthesis in Noisy Quantum Systems. - Amara Katabarwa; Collin Farquhar; Hyeongrak Choi; Marc Grau Davis; Dirk R. Englund; Yudong Cao; Mekena Metcalf (QCE, 2023)

Demo: First Demonstration of Real-Time Photonic-Electronic DNN Acceleration on SmartNICs. - Zhizhen Zhong; Mingran Yang; Jay Lang; Dirk R. Englund; Manya Ghobadi (SIGCOMM, 2023)

Lightning: A Reconfigurable Photonic-Electronic SmartNIC for Fast and Energy-Efficient Inference. - Zhizhen Zhong; Mingran Yang; Jay Lang; Christian Williams; Liam Kronman; Alexander Sludds; Homa Esfahanizadeh; Dirk R. Englund; Manya Ghobadi (SIGCOMM, 2023)

Development of a Boston-area 50-km fiber quantum network testbed. - Eric Bersin; Matthew Grein; Madison Sutula; Ryan Murphy; Yan Qi Huan; Mark Stevens; Aziza Suleymanzade; Catherine Lee 001; Ralf Riedinger; David J. Starling; Pieter-Jan Stas; Can M. Knaut; et al. (CoRR, 2023)

A CMOS-Integrated Color Center Pulse-Sequence Control and Detection System. - Jinchen Wang; Isaac B. Harris; Xibi Chen; Dirk R. Englund; Ruonan Han 001 (CICC, 2024)

Quantum Networks: Exploring Scalability, Topology, and Error Correction. - Hyeongrak Choi; Marc Grau Davis; Álvaro G. Iñesta; Dirk R. Englund (OFC, 2024)

Quantum Circuit Switching with One-Way Repeaters in Star Networks. - Álvaro G. Iñesta; Hyeongrak Choi; Dirk R. Englund; Stephanie Wehner (QCE, 2024)

Hypermultiplexed Integrated Tensor Optical Processor. - Shaoyuan Ou; Alexander Sludds; Ryan Hamerly; Ke Zhang; Hanke Feng; Eric Zhong; Cheng Wang; Dirk R. Englund; Mengjie Yu; Zaijun Chen (CoRR, 2024)

Dynamic Inhomogeneous Quantum Resource Scheduling with Reinforcement Learning. - Linsen Li; Pratyush Anand; Kaiming He; Dirk R. Englund (CoRR, 2024)

Quantum-secure multiparty deep learning. - Kfir Sulimany; Sri Krishna Vadlamani; Ryan Hamerly; Prahlad Iyengar; Dirk R. Englund (CoRR, 2024)

Towards the Information-Theoretic Limit of Programmable Photonics. - Ryan Hamerly; Jasvith Raj Basani; Alexander Sludds; Sri Krishna Vadlamani; Dirk R. Englund (CoRR, 2024)

QAMNet: Fast and Efficient Optical QAM Neural Networks. - Marc Gong Bacvanski; Sri Krishna Vadlamani; Kfir Sulimany; Dirk Robert Englund (CoRR, 2024)

Optical QAM Neural Networks for Efficient AI Accelerators. - Marc Gong Bacvanski; Sri Krishna Vadlamani; Kfir Sulimany; Dirk Robert Englund (OFC, 2025)

A Three-Terminal Nanophotonic Integrator for Deep Neural Networks. - Saumil Bandyopadhyay; Kfir Sulimany; Alexander Sludds; Ryan Hamerly; Keren Bergman; Dirk R. Englund (OFC, 2025)

Single-Shot Matrix-Matrix Multiplication Optical Processor for Deep Learning. - Chao Luan; Ronald Davis; Dirk R. Englund; Ryan Hamerly (OFC, 2025)

Quantum-Secure Deep Learning in Optical Networks. - Kfir Sulimany; Sri Krishna Vadlamani; Ryan Hamerly; Prahlad Iyengar; Dirk R. Englund (OFC, 2025)

WaveguideQED.jl: An Efficient Framework for Simulating Non-Markovian Waveguide Quantum Electrodynamics. - Matias Bundgaard-Nielsen; Dirk R. Englund; Mikkel Heuck; Stefan Krastanov (Quantum, 2025)

Disaggregated Deep Learning via In-Physics Computing at Radio Frequency. - Zhihui Gao; Sri Krishna Vadlamani; Kfir Sulimany; Dirk R. Englund; Tingjun Chen (CoRR, 2025)

AI-Driven Robotics for Free-Space Optics. - Shiekh Zia Uddin; Sachin Vaidya; Shrish Choudhary; Zhuo Chen; Raafat K. Salib; Luke Huang; Dirk R. Englund; Marin Soljacic (CoRR, 2025)

Machine Intelligence on Wireless Edge Networks. - Sri Krishna Vadlamani; Kfir Sulimany; Zhihui Gao; Tingjun Chen; Dirk R. Englund (CoRR, 2025)