Bullseye! New Method Accurately Centers Quantum Dots Within Photonic Chips
Researchers at JQI and the National Institute of Standards and Technology (NIST) have developed standards and calibrations for optical microscopes that allow quantum dots to be aligned with the center of a photonic component to within an error of 10 to 20 nanometers (about one-thousandth the thickness of a sheet of paper). Such alignment is critical for chip-scale devices that employ the radiation emitted by quantum dots to store and transmit quantum information.
Photon-Mediated Interactions in Lattices of Coplanar Waveguide Resonators
Dissertation Committee Chair: Professor Alicia Kollár
Committee:
Professor Mohammad Hafezi (Dean’s Representative)
Professor Steven Rolston
Professor Trey Porto
Professor Sarah Eno
Unifying non-Markovian characterisation with an efficient and self-consistent framework
Abstract: Noise on quantum devices is much more complex than it is commonly given credit. Far from usual models of decoherence, nearly all quantum devices are plagued both by a continuum of environments and temporal instabilities. These induce noisy quantum and classical correlations at the level of the circuit. The relevant spatiotemporal effects are difficult enough to understand, let alone combat. There is presently a lack of either scalable or complete methods to address the phenomena responsible for scrambling and loss of quantum information.
Carving Up Infinite Quantum Spaces into Simpler Surrogates
Researchers have constructed new mathematical tools for continuous variable (CV) quantum systems, which could lead to more efficient benchmarking for quantum devices and more efficient ways of representing quantum states on classical hardware.
Universal Sharpness Dynamics in Neural Network Training: Fixed Point Analysis, Edge of Stability, and Route to Chaos
Abstract: In gradient descent dynamics of neural networks, the top eigenvalue of the Hessian of the loss (sharpness) displays a variety of robust phenomena throughout training. This includes early time regimes where the sharpness may decrease during early periods of training (sharpness reduction), and later time behavior such as progressive sharpening and edge of stability. We demonstrate that a simple $2$-layer linear network (UV model) trained on a single training example exhibits all of the essential sharpness phenomenology observed in real-world scenarios.
How non-Hermitian superfluids are special
Committee: Steven Rolston (chair)
Ian Spielman (advisor)
Mohammad Hafezi (dean's rep)
William Phillips
Trey Porto
Generalized framework for fermion-to-qubit mappings through Clifford transformations
Abstract: In order to simulate interacting fermionic systems on quantum computers, the first step is to encode the physical Hamiltonian into qubit operators. Existing encoding procedures such as the Jordan-Wigner transformation and Bravyi-Kitaev transformation are not resource efficient because they encode each second-quantized fermionic operator into a Pauli string without incorporating the structure of the Hamiltonian in question.
Collective exciton properties in charge-ordered moire' transition metal dichalcogenide bilayers
Abstract: Light emitters within two-dimensional arrays have been demonstrated to exhibit various cooperative effects, including super- and sub-radiance, collective line-shift and linewidth, and topological features such as Chern bands and edge states. Motivated by these intriguing properties, the realization of emitter arrays has been attempted in cold atom experiments, which nevertheless cannot access the deep subwavelength regime.