Internships

2023 Opportunities

The Physics & Informatics (PHI) Lab is eager to welcome our next class of interns. NTT Research was launched in 2019 for the sole purpose of fostering fundamental research. Our internship program allows every participant to actively contribute to that research while learning from leading minds.

Internships duration varies from 3 months to one year depending on the project nature and intern preference. Applicants should be physicists, computer scientists, brain scientists and electrical engineers enrolled in PhD programs and have an interest in exploring the interdisciplinary space between quantum information science and neuroscience using optical technologies.

Internship forms should be submitted by March 10, 2023 to assure full consideration. In addition to financial compensation, summer housing assistance and travel allowances are available to qualified candidates.

Examples of some potential projects:

Feasibility study for an experimental coherent Ising machine based on measurement feedback in a novel few-photon limit
The role of noise in diffusion model-based generative modeling
Physical neural networks with lithium niobite nanophotonics
Delocalized photonic training of DNNs using coherent Netcast
Dissecting the mechanistic basis of concept learning
Temporal Trapping for Ultrafast Optical Strong Coupling
Squeezed vacuum for quantum communication and control
Physical neural networks with CMOS electronics
TFLN vertical-cavity surface-emitting OPOs
Novel measurement schemes for 2D materials
Inverse design of nonlinear waveguides
Brain vs Machine: How do neural networks perform logical computation with language?
Physics of driven-dissipative non-linear networks in the presence of single-photon on-site non-linearity
Driving nonlinear topological photonics by structured non-Hermitian lattices
Benchmarking against other quantum machines and modern heuristics
Dynamics of topological and non-Hermitian photonic systems
Single photon quantum non-linearity from gate-defined dots
High-Speed Time-Multiplexed Optical Computing Systems
In-situ periodic poling of ferroelectric thin films
Advanced approaches to chip-to-fiber coupler
Hardware error correction in photonics
Monolithic sync pumped TFLN OPOs
Electronic-photonic integration for machine learning
Frequency-multiplexed combinatorial optimization solver utilizing optical frequency combs
Form for PHI Lab Internships

Internship Benefits

One-on-One Mentoring
Optical Laboratory
at Sunnyvale, CA
Journal Club on Quantum Information and Neural Networks
Quantum Researcher Certificate

The NTT Quantum Researcher Certificate

NTT Research offers an opportunity for motivated students from around the globe to explore the quantum world and earn this certification for engaging cutting-edge research in broadly defined quantum physics and information science.

The requirements for this certificate include completion of an internship, journal club presentation and attendance at all journal club presentations, and poster presentation of the research accomplishment at the intern reunion.

Intern Reunion

The past two years of internships were conducted in person or remotely, but in the fall we held the Intern Reunion at NTT Research One Campus in Sunnyvale, California, where everyone gathered to share the progress of each project and discuss it with interns, mentors, and PHI researchers. The reunion includes a poster session by all interns and the awarding of the NTT Quantum Researcher Certificate.

2022 Summer Internship Overview

A total of 26 graduate and undergraduate students from the United States, France, Italy and Japan participated in the PHI Lab internship program. Their project titles included:

Geometric Considerations for Normalization Layers in Equivariant Neural Networks
Learning representation of the brain activity via convex recurrent neural networks
Energy Landscape and Landau Theory of Self-Supervised Learning
A Mechanistic Lens on Mode-Connectivity in Neural Network Loss Landscapes
Image sensing with Optical Neural Networks
Towards scalable physical neural networks with thin-film lithium niobate
A Photonic Ising Machine using Ultra-Low Optical Energy
Hybrid Ising machines combining dissipative and conservative dynamics
Optimal Curriculum Learning Strategies for Sequential and Trail-Tracking Tasks
SCoherent SAT Solvers
Photonic Landau levels in an exciton-polariton microcavity
Scaling analysis of Grover’s algorithm for 3-SAT problems
Squeezed-Quantum-Noise-Assisted Optimization for Quadratic Binary Problems by CIM-CAC
Effects of quantum noise on the performance of optimization on OPO networks
Creating lateral quantum wells in monolayer semiconductors by an electrostatic confinement mechanism
Frequency-Multiplexed C-band Free-Space Optical Platform for Matrix-Vector Multiplication
Simulation of a Quantum Time-multiplexed Photonic Resonator Network
Algorithm and Error Analyses of the Simulation of Time-Dependent Hamiltonians
Measuring Geometry of Waveguide Using AFM
A Self-Similar Sine-Cosine Fractal Architecture for Multiport Interferometers
Hard mask development for next-generation lithium niobate processing
Efficient Hamiltonian Encodings for Simulation of Electronic Structure Hamiltonian
Modular Quantum Algorithms as Functional Transforms
Measurements' technique on 2D semiconductors
IR cavity caracterisationand outlook

2021 Summer Internship Overview

A total of 22 graduate and undergraduate students from the United States, Canada, United Kingdom, France, India, and Japan took part in the PHI Lab internship program. Their project titles included:

Neural Mechanics in Deep Learning Dynamics
Neural Network Pruning Algorithms
Deep Learning with CIM
Quantum Analog Computing for k-SAT Problems
Griffiths Phase in Residual Neural Networks
Weakly Quantum Physical Neural Networks
Max-Cut Quantum Algorithm Implementation on GPU
Max-Cut Quantum Algorithm Implementation on FPGA
Experimentally Demonstrating a CIM with an Optical Matrix-Vector Multiplier
Cyber CIM
Cyber CIM Architecture
Topological Physics in Optical Systems
Compressed Sensing Quantum Algorithm on GPU
Analog Feedback CIM experiment
Optical Simulation with NOPOs
Soliton Frequency Comb Experiment
Tensor Product Theory
Quantum and Classical Discrimination
Enhancement of Polariton-Polariton Interactions Via a Mediating Material

Publications Co-authored by 2022 Intern Students

"What shapes the loss landscape of self-supervised learning?"
NeurIPS 2022 Workshop: Self-Supervised Learning - Theory and Practice,
https://arxiv.org/abs/2210.00638
Liu Ziyin, Ekdeep Singh Lubana, Masahito Ueda, and Hidenori Tanaka
"Mechanistic Mode Connectivity"
NeurIPS 2022 Workshop: Distribution Shifts (DistShift) Connecting Methods and Applications
https://arxiv.org/abs/2211.08422
Ekdeep Singh Lubana, Eric J. Bigelow, Robert Dick, David Krueger, and Hidenori Tanaka
"Geometric Considerations for Normalization Layers in Equivariant Neural Networks"
NeurIPS 2022 Workshop: AI for Accelerated Materials Design
https://openreview.net/forum?id=p9fKD1sFog8
Max Aalto, Ekdeep Singh Lubana, and Hidenori Tanaka
"Image sensing with multilayer, nonlinear optical neural networks"
https://arxiv.org/abs/2207.14293
Tianyu Wang, Mandar M. Sohoni, Logan G. Wright, Martin M. Stein, Shi-Yuan Ma, Tatsuhiro Onodera, Maxwell G. Anderson, Peter L. McMahon
"A Self-Similar Sine-Cosine Fractal Architecture for Multiport Interferometers"
https://arxiv.org/abs/2209.03335
Jasvith Raj Basani, Sri Krishna Vadlamani, Saumil Bandyopadhyay, Dirk R. Englund, Ryan Hamerly
"Coherent SAT Solver"
Sam Reifenstein, Timothee Leleu, Tim McKenna, Marc Jankowski, Myoung-Gyun Suh, Edwin Ng, Farad Kyoyratee, Yoshitaka Inui, Zoltan Toroczkai, and Yoshihisa Yamamoto
"Benchmark study on quantum algorithms for combinatorial optimization problems"
https://arxiv.org/abs/2105.03528
Krishanu Sankar, Artur Scherer, Satoshi Kako, Sam Reifenstein, Navid Ghadermarzy, Willem B. Krayenhoff, Yoshitaka Inui, Edwin Ng, Tatsuhiro Onodera, Pooya Ronagh and Yoshihisa Yamamoto

Publications Co-authored by 2021 Intern Students

"Noether’s Learning Dynamics: Role of Symmetry Breaking in Neural Networks"
Advances in Neural Information Processing Systems (NeurIPS), 2021
https://arxiv.org/abs/2105.02716
Hidenori Tanaka, Daniel Kunin
"Beyond BatchNorm: Towards a Unified Understanding of Normalization in Deep Learning"
Advances in Neural Information Processing Systems (NeurIPS), 2021
NeurIPS 2022 Workshop: Distribution Shifts (DistShift) Connecting Methods and Applications
https://proceedings.neurips.cc/paper/2021/file/2578eb9cdf020730f77793e8b58e165a-Paper.pdf
Ekdeep Singh Lubana, Robert P. Dick, Hidenori Tanaka
"Geometric Considerations for Normalization Layers in Equivariant Neural Networks"
NeurIPS 2022 Workshop: AI for Accelerated Materials Design
https://openreview.net/forum?id=p9fKD1sFog8
Max Aalto, Ekdeep Singh Lubana, and Hidenori Tanaka
"Image sensing with multilayer, nonlinear optical neural networks"
https://arxiv.org/abs/2207.14293
Tianyu Wang, Mandar M. Sohoni, Logan G. Wright, Martin M. Stein, Shi-Yuan Ma, Tatsuhiro Onodera, Maxwell G. Anderson, Peter L. McMahon
"A Self-Similar Sine-Cosine Fractal Architecture for Multiport Interferometers"
https://arxiv.org/abs/2209.03335
Jasvith Raj Basani, Sri Krishna Vadlamani, Saumil Bandyopadhyay, Dirk R. Englund, Ryan Hamerly
"Coherent SAT Solver"
Sam Reifenstein, Timothee Leleu, Tim McKenna, Marc Jankowski, Myoung-Gyun Suh, Edwin Ng, Farad Kyoyratee, Yoshitaka Inui, Zoltan Toroczkai, and Yoshihisa Yamamoto
"Benchmark study on quantum algorithms for combinatorial optimization problems"
https://arxiv.org/abs/2105.03528
Krishanu Sankar, Artur Scherer, Satoshi Kako, Sam Reifenstein, Navid Ghadermarzy, Willem B. Krayenhoff, Yoshitaka Inui, Edwin Ng, Tatsuhiro Onodera, Pooya Ronagh and Yoshihisa Yamamoto

Last Summer’s Lecture Schedule

The 2021 series consisted of eight lectures over eight weeks during July and August and covered multiple subjects pertaining to quantum information and neural networks.

Week 1 Yoshihisa Yamamoto Fundamental Postulates in Quantum Mechanics: Quantization, Projection, and Symmetrization Postulates
Week 2 Edwin Ng Digital Software for Simulating Closed/Open Quantum Systems, QuTiP and Beyond
Week 3 Adil Gangat Tensor Network Theory: How to Efficiently Simulate a Quantum Spin Chain on Digital Platform
Week 4 Jess Riedel Quantum Darwinism: When Classical Reality Surfaces from Quantum Substrate
Week 5 Tatsuhiro Onodera Introduction to Differential Programming
Week 6 Ryan Hamerly Design Principles for Machine Learning Hardware
Week 7 Logan Wright Open Questions and Challenges for the Physics of Intelligence
Week 8 Hidenori Tanaka Physical Principles of Learning Dynamics

Finally, on November 30th there was an Intern Reunion at NTT OneVision Center in Sunnyvale, CA that featured presentations by all the interns and the awarding of the NTT Quantum Researcher Certificates to each.

About PHI Lab

The Physics & Informatics (PHI) Lab uncovers fundamental principles and novel technologies that advance our information processing beyond the state of the art. We explore the interdisciplinary space between quantum information science and neuroscience using optical technologies. We foster an environment for physicists, computer scientists, brain scientists and electrical engineers to work together to build a new era of computation framework.

While we are relatively new to the United States, NTT (Nippon Telegraph and Telephone) has over 70 years of history in Japan supporting basic research and delivering breakthroughs to the real world.