Current graduate students

Learning in the Quantum Universe

Abstract: I will present recent progress in building a rigorous theory to understand how scientists, machines, and future quantum computers could learn models of our quantum universe. The talk will begin with an experimentally feasible procedure for converting a quantum many-body system into a succinct classical description of the system, its classical shadow. Classical shadows can be applied to efficiently predict many properties of interest, including expectation values of local observables and few-body correlation functions.

I will then build on the classical shadow formalism to answer two fundamental questions at the intersection of machine learning and quantum physics: Can classical machines learn to solve challenging problems in quantum physics? And can quantum machines learn exponentially faster than classical machines?

Bio: Hsin-Yuan (Robert) Huang is a Ph.D. student at Caltech, advised by John Preskill and Thomas Vidick. His research focuses on understanding how the theory of learning can provide new insights into physics, information, and quantum computing. His notable works include classical shadow tomography for learning large-scale quantum systems, provably efficient machine learning algorithms for solving quantum many-body problems, and quantum advantages in learning from experiments.

He has been awarded a Google Ph.D. fellowship, the Quantum Creator Prize, MediaTek research young scholarship, and the Kortschak scholarship.

Follow the link to attend this seminar on Zoom.

Please note: for the passcode, please email Joe Petrik no later than 10 a.m. day of.

Improved diagnostics and implementation for quantum error correction

IQC Special Seminar Featuring Gerardo Adesso, The University of Nottingham

What makes quantum technologies tick? Advantages in communication, computation, metrology and other applications can be traced back to distinct manifestations of quantum theory, such as coherence and entaglement.

IQC Special Seminar Featuring Makan Mohageg, NASA's Jet Propulsion Laboratory

JPL has been at the forefront of space-based quantum technologies. Cold Atom Lab is the first orbital experiment exploring the dynamics of Bose-Einstein condensates in micro-gravity. Deep Space Atomic Clock demonstrated that a trapped-Hg+ clock in space provides timing precision and accuracy required for improved spacecraft autonomous navigation.

IQC Colloquium, Alex Adronov McMaster University

Single-Walled Carbon Nanotubes (SWNTs) exhibit a number of unique mechanical, thermal, and electronic properties that render them useful for numerous applications, ranging from molecular electronics to nano-scale construction materials.  However, SWNTs are highly insoluble and are devoid of reactive functionality, posing major limitations to their modification, manipulation, and ...

CS/Math Seminar - Daochen Wang QuICS, UMD

The divide-and-conquer framework, used extensively in classical algorithm design, recursively breaks a problem into smaller subproblems, along with some auxiliary work, to give a recurrence relation for the classical complexity. We describe a quantum divide-and-conquer framework that, in certain cases, yields quantum speedup through an analogous recurrence relation for the quantum query complexity....

Roger Melko: Language models for quantum simulation

Abstract: As the frontiers of artificial intelligence advance more rapidly than ever before, generative language models like ChatGPT are poised to unleash vast economic and social transformation. In addition to their remarkable performance on typical language tasks (such as writing undergraduate research papers), language models are being rapidly adopted as powerful ansatze states for quantum many-body systems.  In this talk, I will discuss the use of language models for learning quantum states realized in experimental Rydberg atom arrays. By combining variational optimization with data-driven learning using qubit projective measurements, I will show how language models are poised to become one of the most powerful computational tools in our arsenal for the design and characterization of quantum simulators and computers.

CS/Math Seminar - Luowen Qian, Boston University in person and on ZOOM

Pseudorandom states (PRS) are efficiently constructible states that are effectively Haar random against efficient observers. Recently, this notion has found its influence in many fields like quantum information, quantum gravity, and quantum complexity. ...