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On noise in swap ASAP repeater chains: exact analytics, distributions and tight approximations
– 11/07 – 12:00pm – HBL Instruction 1102 –
Abstract: Losses are one of the main bottlenecks for the distribution of entanglement in quantum networks, which can be overcome by the implementation of quantum repeaters. The most basic form of a quantum repeater chain is the swap ASAP repeater chain. In such a repeater chain, elementary links are generated and swapped as soon as two adjacent links have been generated. As each entangled state is waiting to be swapped, decoherence is experienced, lowering the fidelity of the state. The aim of this project is to understand the total amount of decoherence experienced. We find analytical expressions for the average noise and its distribution for a small number of links. Furthermore, by exploiting tools from analytic combinatorics we find exponentially tight approximations on the average noise. Finally, we also use methods from statistical physics to numerically calculate quantities of interest for the inhomogeneous case. Our tools can be used to understand and optimize the performance of near-term quantum communication systems.
Bio:Dr. Kenneth Goodenough is a postdoctoral researcher under Don Towsley at the University of Massachusetts, Amherst. During his PhD with David Elkouss at QuTech he has worked on near-term repeater schemes, and afterwards focused on distillation and error correction. Currently he is interested in understanding the mathematical structures behind noisy quantum systems.
UCONN TODAY — Quantum Initiative professor Baikun Li has recently published a paper on applying groundbreaking techniques to convert carbon dioxide emissions into renewable energy sources.
The researchers’ findings were recently published the Royal Society of Chemistry’s esteemed Energy and Environmental Science Journal.
Environmental engineering professor Baikun Li led a 12-person interdisciplinary team exploring the process of electrochemical CO2 reduction. In addition to supporting UConn’s priority research goal of climate change mitigation, it also achieved an interdisciplinary collaboration comprised of several schools and colleges. The effort featured faculty and grad students from environmental engineering, materials science and engineering, electrical and computer engineering, chemistry, and more.
“Climate change is one of the world’s most pressing challenges,” says Pamir Alpay, UConn’s Vice President for Research, Innovation, and Entrepreneurship and a co-author on the manuscript whose group worked on the atomistic modeling of the surface reactions of catalytic processes. “This study works to reduce our carbon footprint through carefully designed experimental work with sophisticated multi-scale modeling. “The resulting reduction in carbon dioxide benefits our planet and exemplifies UConn’s research priorities.”
The interdisciplinary team of 12 UConn researchers explored the process of electrochemical carbon dioxide reduction.
Each year, the extraction and burning of fossil fuels like coal, oil, and natural gas releases more carbon dioxide into the atmosphere than natural processes can remove. The carbon dioxide can remain for thousands of years, trapping heat and warming the Earth’s surface.
In 2019, Li and the team set out to understand the fundamental mechanisms of CO2 reduction. Electrochemical CO2 reduction is the conversion of carbon dioxide into a hydrocarbon fuel through a chemical reaction. It represents a future possibility where humans could generate gasoline, aviation fuel, and other useful substances using carbon dioxide captured from the air — reducing greenhouse gas emissions while providing a sustainable energy source.
“What we really want to achieve in the future is the complete cycle of carbon,” says Xingyu Wang, an environmental engineering Ph.D. student who worked on the team. “One of the biggest questions we aim to explore is, ‘How can we utilize the carbon dioxide that already exists in the atmosphere without exploiting existing resources here on Earth?’”
It’s a question that many research studies aim to answer. But few break down electrochemical CO2 reduction to the most fundamental level: the reaction.
The chemical reaction that converts CO2 gas into other chemical feedstocks happens under the action of a metal catalyst. Polymers bonded to the surface of the catalyst help stabilize and promote the reaction by keeping metal nanoparticles in place.
For example, Li says that copper is a well-known catalyst for CO2 reduction, but it does not absorb CO2 easily. By coating the surface of the copper with a polymer called polytetrafluoroethylene (PTFE), the team was able to change the polarity of the surface and improve CO2 gas absorption.
“In our study, we laid the foundation for the exploration of other polymers,” says Li. “Later on, other researchers can use the fundamental modeling in our work to study other molecule polymers based on what we have discovered so far.”
Another value of this study is its cost effectiveness. CO2 reduction can be achieved through expensive manufacturing pathways or relatively simple methods like this one, says Wang.
“Our study shows that we do not need to rely on the most expensive methods. We can achieve the same goal through this mixture of organic and inorganic material,” Wang says.
The team is one of many interdisciplinary collaborations across UConn that addess climate change mitigation and seek sustainable fuel sources. Li and her team have won a Convergence Award for Research in Interdisciplinary Centers (CARIC) for their work across quantum technology and climate change. The team is working with the Physics Department to develop an animation of the process for educational purposes within the industry.
“The broad impact of this methodology doesn’t only apply to CO2 reduction,” Li says. “It has countless applications, but we used CO2 reduction as an example of how we can use quantum level modeling for potential future research.”
Quenched random-mass disorder in the critical Gross-Neveu-Yukawa Models
– 11/03 – 1:00pm – S213K –
Abstract: In the clean limit, continuous symmetry-breaking quantum phase transitions in 2D Dirac materials such as graphene and surfaces of 3D topological insulators are described by (2+1)D critical Gross-Neveu-Yukawa (GNY) models. In this talk, I will present our results of the study of the effects of quenched random-mass disorder, both short- and long-range correlated, on the universal critical properties of the Ising, XY, and Heisenberg GNY models. The problem was studied via the application of the replica renormalization group combined with a controlled triple epsilon expansion below four dimensions. Among interesting results, we find new finite-disorder quantum critical and multicritical points and an instance of the supercritical Hopf bifurcation in the renormalization-group flow, which is accompanied by the birth of a stable limit cycle corresponding to discrete scale invariance.
Time permitting, I will lay out a picture of possible percolation of the topological phase in the ferroelectric superconductors subjected to magnetic field.