A Phase Transition in Minesweeper

We study the average-case complexity of the classic Minesweeper game in which players deduce the locations of mines on a two-dimensional lattice. Playing Minesweeper is known to be co-NP-complete. We show empirically that Minesweeper exhibits a phase transition analogous to the well-studied SAT phase transition. Above the critical mine density it becomes almost impossible to play Minesweeper by logical inference. We use a reduction to Boolean unsatisfiability to characterize the hardness of Minesweeper instances, and show that the hardness peaks at the phase transition. Furthermore, we demonstrate algorithmic barriers at the phase transition for polynomial-time approaches to Minesweeper inference. Finally, we comment on expectations for the asymptotic behavior of the phase transition

Multi-mode Cavity Centric Architectures for Quantum Simulation

Near-term quantum computing technologies grapple with huge complexity overheads, hindering their ability to induce algorithms, necessitating engineering and scientific innovations. One class of problems of interest is Quantum Simulation, whereby quantum systems are simulated using a quantum computer. However, current devices are yet to surpass classical tensor network techniques. For problems of interest, where classical simulation techniques fail, large degrees of entanglement are required. Another challenge of implementing quantum simulation problems is that qubits sit idle whilst alternating simulation terms are implemented, exposing the system to decoherence. In the near term, 2D planar superconducting lattices of circuit-QED elements such as the transmon continue to draw substantial attention, but they are hindered by their nearest neighbor topology and relatively short lifespan, two problems that are problematic for quantum simulation. One technology of particular interest is the multi-mode superconducting resonator capable of storing multiple qubits in one device. We observe that these cavities have a natural virtual topology that aligns particularly well with quantum simulation problems, and exhibit much longer lifespans in comparison to other planar superconducting hardware. In this paper we present MUCIC, we discuss the simple integration of these devices into the current landscape and their implications to quantum simulation, motivated by their alignment to the quantum simulation problem, and potential as a quantum memory candidate. We report the development of MUCICs transpiler, leading to reductions of up to 82% in quantum simulation circuit depths. Additionally, our investigation demonstrates improvements of up to 19.4% in converged results from Variational Quantum Algorithms

Tunable inductive coupler for high fidelity gates between fluxonium qubits

The fluxonium qubit is a promising candidate for quantum computation due to its long coherence times and large anharmonicity. We present a tunable coupler that realizes strong inductive coupling between two heavy-fluxonium qubits, each with $\sim50$MHz frequencies and $\sim5$ GHz anharmonicities. The coupler enables the qubits to have a large tuning range of $\textit{XX}$ coupling strengths ($-35$ to $75$ MHz). The $\textit{ZZ}$ coupling strength is $<3$kHz across the entire coupler bias range, and $<100$Hz at the coupler off-position. These qualities lead to fast, high-fidelity single- and two-qubit gates. By driving at the difference frequency of the two qubits, we realize a $\sqrt{i\mathrm{SWAP}}$ gate in $258$ns with fidelity $99.72\%$, and by driving at the sum frequency of the two qubits, we achieve a $\sqrt{b\mathrm{SWAP}}$ gate in $102$ns with fidelity $99.91\%$. This latter gate is only 5 qubit Larmor periods in length. We run cross-entropy benchmarking for over $20$ consecutive hours and measure stable gate fidelities, with $\sqrt{b\mathrm{SWAP}}$ drift ($2 \sigma$) $< 0.02\%$ and $\sqrt{i\mathrm{SWAP}}$ drift $< 0.08\%$.Comment: 16 pages, 14 figure

It's all about the children: a participant-driven photo-elicitation study of Mexican-origin mothers' food choices

Abstract Background There is a desperate need to address diet-related chronic diseases in Mexican-origin women, particularly for those in border region colonias (Mexican settlements) and other new destination communities in rural and non-rural areas of the U.S. Understanding the food choices of mothers, who lead food and health activities in their families, provides one way to improve health outcomes in Mexican-origin women and their children. This study used a visual method, participant-driven photo-elicitation, and grounded theory in a contextual study of food choices from the perspectives of Mexican-origin mothers. Methods Teams of trained promotoras (female community health workers from the area) collected all data in Spanish. Ten Mexican-origin mothers living in colonias in Hidalgo County, TX completed a creative photography assignment and an in-depth interview using their photographs as visual prompts and examples. English transcripts were coded inductively by hand, and initial observations emphasized the salience of mothers' food practices in their routine care-giving. This was explored further by coding transcripts in the qualitative data analysis software Atlas.ti. Results An inductive conceptual framework was created to provide context for understanding mothers' daily practices and their food practices in particular. Three themes emerged from the data: 1) a mother's primary orientation was toward her children; 2) leveraging resources to provide the best for her children; and 3) a mother's daily food practices kept her children happy, healthy, and well-fed. Results offer insight into the intricate meanings embedded in Mexican-origin mothers' routine food choices. Conclusions This paper provides a new perspective for understanding food choice through the eyes of mothers living in the colonias of South Texas -- one that emphasizes the importance of children in their routine food practices and the resilience of the mothers themselves. Additional research is needed to better understand mothers' perspectives and food practices with larger samples of women and among other socioeconomic groups

Heterogeneous Architectures for Superconducting Quantum Computing

Since their advent more than two decades ago, superconducting quantum devices have been a leading platform for quantum computation. Year by year, coherence times increase, gate errors decrease, and new records are set for the number of qubits in a system. As the challenges of scaling continue to accumulate, there is more room than ever for innovation at all levels of the quantum computing stack. This thesis explores the concept of heterogeneity in superconducting quantum computer design at two different levels. At the level of the two-qubit entangling gate, this thesis investigates two novel tunable coupler architectures for parametric gates. Devices are designed to optimize the trade-off between gate speed and fidelity while providing a platform to study leakage outside the computational subspace. At the quantum computer architecture level, we design and simulate a heterogeneous architecture for lattice surgery of surface codes based on ideas from quantum networking. A co-design approach leads to a hardware-aware error-correcting architecture that aims to improve the efficiency of Pauli-based computation

Composting for Sustainable Waste Management

This report, prepared for McNeil Consumer Healthcare of Las Piedras, Puerto Rico, explored options to reduce their landfill waste volume and raise community awareness of waste-related environmental concerns through composting. The following document addresses the necessary background, research methods, findings, and recommendations. Through classroom presentations, physical composting, and investigation of composting systems, we initiated community interaction and established the best future options for McNeil. Through education and setting a positive example, this project aims to promote sustainable waste management

Automate [sic] image analysis routines for recording microstructural features of IN100

Quantitative microscopy is used to evaluate mechanical properties through measurement of components such as: grain, gamma prime, carbide and porosity size distribution. These properties of high temperature metals, such as the Nickel-based Superalloy IN100 used by Pratt & Whitney, are essential to the performance of the material. In the past, measurement of these features was predominately done manually, requiring many hours for a large number of micrographs in order to achieve the accuracy needed. This project examined the automation and validation of the enhancement and measurement of IN100's material properties using Adobe Photoshop