Graduate

DNA has emerged as a compelling data storage medium due to its density, longevity, and eternal relevance compared to current memory technologies. However, the high price of synthesizing DNA (list price $3,500 per megabyte) remains a major bottleneck for adoption of this promising storage solution. In this talk, I will present our work towards breaking down this barrier using enzymatic DNA synthesize and a tailored codec for robust data retrieval. I will also touch upon some fundamental considerations when designing DNA information storage systems.

Combining photography and spectroscopy, spectral imaging enables us to see what no traditional color camera has seen before. The current trend is to miniaturize the technology and bring it towards industry. In this talk, I will first give a general introduction to the most common pitfalls of spectral imaging and the challenges that come with miniaturization. Major pitfalls include balancing cross-talk, quantum efficiency, illumination and the optics. Miniaturization has become possible thanks to the monolithic per-pixel integration of thin-film Fabry-Pérot filters on CMOS imaging sensors. I will explain the difficulty of using these cameras with non- telecentric lenses. This is a major concern because of the angular dependency of the thin-film filters. I will demonstrate how this important issue can be solved using a model-based approach.

As part of the Japan – U.S. Innovation Awards Symposium we will be honoring the following companies with the 2019 Sunbridge Emerging Leader Award: Zoom Video Communications of the U.S. and WHILL of Japan. These Awards, one to a U.S. firm and one to a Japanese firm, recognize later-stage dynamically growing companies that have begun to transform an industry or value chain. They will be presented at the ninth annual Japan-US Innovation Awards Symposium.

WHILL - Since its founding in 2012, WHILL's mission is to transform today's antiquated power wheelchair and scooter experiences into a new kind of empowering devices, intelligent personal electric vehicles (EVs). WHILL is reinventing the personal mobility industry with personal EVs that focus on an approachable and aesthetically pleasing powered vehicles that boosts confidence and pushes the boundaries of personal transportation. Headquartered in Yokohama with offices in the San Francisco Bay Area, Taiwan and EU, WHILL is focused on enabling everyone to explore the world in comfort and style.

Zoom Video Communications, Inc. - Zoom helps businesses and organizations bring their teams together in a frictionless environment to get more done. Their easy, reliable cloud platform for video, voice, content sharing, and chat runs across mobile devices, desktops, telephones, and room systems. Founded in 2011, Zoom is publicly traded on Nasdaq (ticker: ZM) and is based in San Jose, California.

TBA

A quantum annealer with fully programmable all-to-all coupling via Floquet engineering
Peter McMahon

Quantum annealing is a promising approach to heuristically solving difficult combinatorial optimization problems. However, the connectivity limitations in current devices lead to an exponential degradation of performance on general problems. We propose an architecture for a quantum annealer that achieves full connectivity and full programmability while using a number of physical resources only linear in the number of spins. We do so by application of carefully engineered periodic modulations of oscillator-based qubits, resulting in a Floquet Hamiltonian in which all the interactions are tunable; this flexibility comes at a cost of the coupling strengths between spins being smaller than they would be had the spins been directly coupled. Our proposal is well-suited to implementation with superconducting circuits, and we give analytical and numerical evidence that fully-connected, fully-programmable quantum annealers with 1000 qubits could be constructed with Josephson parametric oscillators having coherence times of 500 microseconds, and other system-parameter values that are routinely achieved with current technology. Our approach could also have impact beyond quantum annealing, since it readily extends to bosonic quantum simulators and would allow the study of models with arbitrary connectivity between lattice sites. Describes work performed jointly with Tatsuhiro Onodera and Edwin Ng.

Spin squeezing in free-space atomic sensors
Zheng Cui

The compatibility of cavity-generated spin-squeezed atomic states with atom-interferometric sensors that require freely falling atoms is demonstrated. An ensemble of hundreds of thousands of spin-squeezed atoms in a high-finesse optical cavity with near-uniform atom-cavity coupling is prepared, released into free space, and measured using one of two different methods. The first method consists of recapturing the atoms in the cavity and probing them with the same QND measurement used to generate the initial entanglement among the atoms. Up to 9.8^{+0.5}_{-0.4} dB of metrologically-relevant squeezing is retrieved for few-hundred microseconds free-fall times, and decaying levels of squeezing are mapped out up to 3 milliseconds free-fall times. This protocol suffers of atom loss and atom-cavity coupling inhomogeneity after recapture. Fluorescence population spectroscopy is an alternative method when longer free-falls times are required. This method allows for the atom ensemble to free fall for up to 4 milliseconds without significant loss of squeezing nor quantum coherence. When operating as a microwave atomic clock with a 3.6 millisecond Ramsey time, a single-shot fractional frequency stability of 8.4(0.2)x10^{-12} is reported, 4.1(0.2) decibels below the quantum projection limit. The ability of the clock to utilize the maximum squeezing available is limited by microwave amplitude and phase noise, and external magnetic field fluctuations in the system. Free fall times of up to 8 milliseconds are also achieved, but at a loss of state coherence.

Tensor networks can often accurately approximate various systems that are of interest to physicists, but the computational cost of contracting the network is often prohibitively demanding. Quantum computer can resolve this bottleneck, but because the size of the computation scales with the size of the network, the existing quantum computers may appear to be far too noisy for this task. We prove a nontrivial error bound on the outcome of the computation that does not scale with the size of the network. This is possible because certain tensor networks are secretly implementing a quantum analogue of a (classical) Markovian dynamics. The long-time stability of the Markovian dynamics gives rise to a nontrivial error bound on the outcome of the computation. This suggests that there may be practical problems of interest that are amenable to relatively noisy quantum computers.

Congratulations to the graduating class of 2019!

Go to EE Department Commencement information page.

Stanford University Commencement Weekend.

Buildings account for the largest share of U.S. greenhouse gas emissions at 32% of the total, followed by industry at 30%, transportation at 29%, and agriculture at 9%. Clearly, any program to greatly reduce greenhouse gas emissions must include buildings. This talk will explore the opportunities and challenges to greatly reducing greenhouse gas emissions in the building sector, using as a case study a recent solar retrofit of an existing house that rendered it "zero-carbon." Implications for the future of the utility system will be discussed.

Jesse Gibson
Title: Information Theory in Next-Generation DNA Sequencing Technologies
The completion of the first human genome sequence in the early 2000's represented a major success for the scientific community. It also represented the return on a significant investment - billions of dollars and a little over a decade's worth of work. DNA sequencing costs have since fallen at a rate even faster than the exponential improvements predicted by Moore's Law in computing. Today, a complete human genome can be sequenced for closer to a few thousand dollars in about a week. A major factor in this improvement was the shift from the serial reads used in the human genome project to massively parallel sequencing technologies. These new technologies however present new problems - how can we understand a genome given millions of short reads drawn randomly from the underlying sequence and potentially degraded by noise in the process? Bioinformatics boasts a plethora of algorithms that meet this challenge in practice but it's not immediately obvious what 'optimal' analyses might look like. This talk will focus on the work of David Tse and others that have used the perspective of information theory to establish fundamental bounds on our ability to interpret next generation sequencing output. In particular, I will focus on the problems of assembling an unknown sequence de novo and of variant calling when the population of molecules being sequenced is not homogenous.

Tony Ginart
Title: Towards a Compression Theory for Metric Embeddings
Embedding matrices are widely used in diverse domains such as NLP, recommendation systems, information retrieval, and computer vision. For large-scale datasets, embedding matrices can consume large amounts of memory, and compression for these objects is desirable. However, the relevant distortion metrics applicable to embeddings make them significantly more compressible than classical sources considered in information theory. Furthermore, related results such as the Johnson-Lindenstrauss theorem are formulated in terms of reduction in dimension rather than codelength. Additionally, embeddings come with certain query-time constraints, such as in the sense of a succinct data structure. In this talk, we formulate the problem of metric embedding compression from the information theoretic lense and review related literature in information theory, signal processing, and dimensionality reduction. We adapt pre-existing results to establish some lower and upper bound in some regimes. Finally, we cover some of the state-of-the-art compression algorithms used to compress embeddings in practice.

The Stanford LASERs are part of a national program of gatherings that brings artists and scientists together for informal presentations and conversation with the audience. Each evening event, free of charge and open to the public, will present four artists, scientists, thinkers, inventors, and scholars who are working on paradigm shifts. Each evening also allows the audience to socialize and encourages people in the audience to briefly introduce their own work. Chaired by Piero Scaruffi.

Location: Li Ka Shing Building, Room LK 130
Admission: Free
Parking: There should be ample parking in the structure on corner of Campus Drive West and Roth Way.
The Stanford LASERs are sponsored by the Stanford Deans of Research; Engineering; Humanities & Sciences; Medicine; and Earth, Energy & Environmental Sciences; Continuing Studies; and the Office of Science Outreach.