Material informatics is a new initiative which has attracted a lot of attention in recent scientific research. The basic strategy is to construct comprehensive data sets and use machine learning to solve a wide variety of problems in material design and discovery. In pursuit of this goal, a key element is the quality and completeness of the databases used. Recent advance in the development of crystal structure prediction algorithms has made it a complementary and more efficient approach to explore the structure/phase space in materials using computers. In this talk, we discuss the importance of the structural motifs and motif-networks in crystal structure predictions. Correspondingly, powerful methods are developed to improve the sampling of the low-energy structure landscape.
The thermodynamic power conversion efficiency limit for silicon solar cells is close to 33%, while commercially available cells have efficiencies in the 17-20% range. The world record for silicon solar cells has inched upward from 25% to 26.7%, in the past twenty years, using cell thicknesses ranging from 450 microns to 165 microns. Photonic crystal architectures enable broadband light absorption beyond the longstanding Lambertian limit and allow silicon to absorb sunlight nearly as well as a direct-bandgap semiconductor. When combined with state-of-the-art electronics, a technological paradigm shift appears imminent. In this lecture, I describe how wave-interference-based solar light-trapping in realistic photonic crystals can break longstanding barriers, enabling flexible, thin-film, silicon to achieve an unprecedented, single-junction, power conversion of 31% [1, 2].
1. "Towards 30% Power Conversion Efficiency in Thin-Silicon Photonic-Crystal Solar Cells," S. Bhattacharya, I. Baydoun, Mi Lin and Sajeev John, Physical Review Applied, 11, 014005 (2019)
2. “Beyond 30% conversion efficiency in silicon solar cells” S. Bhattacharya and Sajeev John (to be published)
Studying nature directly from fundamental degrees of freedom is often computationally limited by physical characteristics of exponentially growing configuration (Hilbert) spaces with particle number and signal-to-noise problems. This leaves many systems of interest to nuclear and particle physics intractable for known algorithms with current and foreseeable classical computational resources. By leveraging their natural capacity to describe nature, the use of quantum systems themselves to form a computational framework leads to constructions of basic quantum field theories with resource requirements that are expected to scale only polynomially with the precision and size of the system. In this talk, I will present an overview of recent progress in, and the potential for, manipulating controllable quantum devices to pursue computational access to our microscopic descriptions of nature.
Since 2004 two-dimensional (2D) materials including graphene, transition metal dichalcogenides (TMDCs) and their heterostructures have continued to draw intense research world-side due to their fascinating new fundamental science and diverse potential applications. 2D systems contain a very small amount of material and scanning probe microscopy (atomic force microscopy and scanning tunneling microscopy) and transmission electron microscopy are commonly used to study their local structural quality. At Rensselaer we have developed a unique and simple method called azimuthal refection high-energy electron diffraction (ARHEED) to measure the wafer scale structural quality of 2D materials. In this talk, I will introduce the basic principle of ARHEED and its characterization of wafer-scale 2D materials. Several examples including graphene and MoS2 will be presented to illustrate the use of AHREED to probe the large scale integrity of the samples.
Pure carbon structures contain a wealth of information and potential properties, we focus on two, long linear carbon chains and Schwarzites. Long linear carbon chains, a one dimensional sp hybridized carbon chain,
have been observed to be encapsulated by a carbon nanotube. Together this system produces a resonant Raman signal from 1770-1860 cm-1, known as the C-mode. The origin of this signal is still under scrutiny. We explore the nature of Raman activity in long linear carbon chains through the use of first principles density functional theory and identify the effect of exact exchange in calculations using hybrid functionals. With exact exchange the most intense Raman active mode, the longitudinal optical mode, converges, with respect to length, to 1831
cm-1, within the range of reported measurements of the C-mode. Also the electronic gap converges, with respect to length, to 1.8 eV, near the known resonance energy.
Schwarzites are sp2, or hexagonal, triply periodic minimal carbon surfaces with negative Gaussian curvature from the introduction of 7-, 8-, 9-, and 10-membered rings. Recently theoretical impregnation of zeolites, simulating the templating processes, has produced Schwarzites.
We present first principles and classical dynamics calculations of electronic and vibronic density of states calculations to establish a connection between the theoretical structures proposed to the experimentally obtained materials. We identify the theoretical structures as energetically and dynamically stable, graphitic in nature, and semimetallic.
Quantum computers promise to solve problems that are not practically feasible with classical computers, with applications ranging from drug development and quantum chemistry to artificial intelligence and cryptography. In this talk, I will give an overview of the current state of experimental quantum computing, specifically results with superconducting qubits. I will then highlight our work on improving the scalability of superconducting quantum devices by interfacing them with classical superconducting logic. Recent results as well as future experiments will be discussed.
Abstract 1: Adiabatic quantum computers like the D-Wave 2000Q can approximately solve the QUBO problem, which is an NP-Hard problem, and have been shown to outperform classical computers on several instances. Solving the QUBO problem literally means solving virtually any NP-Hard problem like the Traveling Salesman Problem (TSP), Airline Scheduling Problem, Protein Folding Problem, Genotype Imputation Problem etc., thereby enabling significant scientific progress, and potentially saving millions / billions of dollars in logistics, airlines, healthcare and many other industries. However, before QUBO problems are solved on quantum computers, they must be embedded (or compiled) onto the hardware of quantum computers, which in itself is a very hard problem. In this work, we propose an efficient embedding algorithm, that lets us embed QUBO problems fast, uses less qubits and gets the objective function value close to the global minimum value. We then compare the performance of our embedding algorithm to that of D-Wave's embedding algorithm, which is the current state of the art, and show that our embedding algorithm convincingly outperforms D-Wave's embedding algorithm. Our embedding approach works with perfect Chimera graphs, i.e. Chimera graphs with no missing qubits.
Abstract 2: For training unsupervised probabilistic machine learning models, matrix computation and sample generation are the two key steps. While GPUs excel at matrix computation, they use pseudo-random numbers to generate samples. Contrarily, Adiabatic Quantum Processors (AQP) use quantum mechanical systems to generate samples accurately and quickly, but are not suited for matrix computation. We present a Classical-Quantum Hybrid Approach for training unsupervised probabilistic machine learning models, leveraging GPUs for matrix computations and the D-Wave quantum sampling library for sample generation. We compare this approach to classical and quantum approaches across four performance metrics. Our results indicate that while the hybrid approach--which uses one AQP and one GPU--outperforms quantum and one of the classical approaches, it performs comparably to the GPU approach, and is outperformed by the CPU approach, which uses 56 high-end CPUs. Lastly, we compare sampling on AQP versus sampling library and show that AQP performs better.
Two-dimensional atomically-thin materials have received enormous interest as a result of their unique mechanical, electrical and optical properties. As a result of the enhanced light-matter interaction two-dimensional materials support they have been investigated for applications in opto-electronics although not much work has focused on these systems as a platform for quantum photonics and quantum optics. In this talk I will discuss approaches that leverage atomically thin two-dimensional materials, as well as their van der Waals heterostructures, for applications in quantum science. In the first part of the talk I will describe the unique photophysical properties of quantum emitters hosted by these atomically thin materials. I will describe our recent efforts to controllably charge the quantum emitters and realize a localized spin-valley-photon interface. I will also present results on realizing cavity polaritons that are a manifestation of many body physics arising when coupling the atomically thin semiconductor to a planar optical cavity.
Since the discovery of the proton and neutron physicists have been trying to image and understand the nucleon’s structure. Today the nucleon is described in terms of a mix of quarks and antiquarks interacting primarily via the strong nuclear force (quantum chromodynamics or QCD). This talk will briefly review the historical progress with electron accelerators leading to our present view of the nucleon’s structure and the recent experimental and theoretical physics progress, focusing on the exclusive reaction program at the Jefferson Lab electron accelerator facility in Virginia, where the structure of the nucleon is a primary subject of the recent and future experimental program.
Fundamental excitations (e.g., excitons, plasmons, phonons, and magnons) determine both the equilibrium and non-equilibrium properties of semiconductors, metals, and insulators. In this talk, I will give a few examples of our recent work in investigating fundamental excitations with various optical spectroscopy methods. I will focus on how excitons (bound electron-hole pairs) and their associated valley index influence light-emitting properties of semiconducting van der Waals monolayers and heterostructures. As a second example, I will discuss how coupling between excitons and surface plasmon polaritons can be used to sort and route valley polarized excitons using a metasurface. Finally, I will briefly discuss how coupling between magnons and phonons in magnetic insulators may lead to new thermoelectric devices.
Neutrinos, the most ghostly of Standard Model particles, were first detected by Clyde Cowan and Frederick Reines in 1956. Although these particles are included in the Standard Model, their properties such as mass and mixing parameters are not predicted and must be measured. Ever since their discovery, physicists have been trying to piece together a comprehensive understanding of the neutrino and over the past 6 decades a nearly complete picture has emerged. However, there are still some undetermined parameters as well as phenomena that have resisted explanation. One of these unexplained phenomena that has arisen rather recently termed the "reactor antineutrino anomaly" is the deficit in the measured flux of antineutrinos from nuclear reactors relative to the expected flux from calculation. Furthermore, the energy spectrum of reactor antineutrinos from recent experiments deviates from the calculated shape in the region of 5-7 MeV antineutrino energy. PROSPECT, the Precision Reactor Oscillation and Spectrum experiment, currently taking data at Oak Ridge National Lab, aims to shed some light on these anomalies by measuring the flux a few meters from the core of a highly enriched uranium (HEU) research reactor. In so doing, many obstacles had to be overcome, not the least of which was designing a detector that could isolate antineutrino events from huge backgrounds inherent in the environment at the surface of the Earth and next to a reactor. In this talk, I will give a brief history of neutrinos and how their properties were determined highlighting some key experiments. Special emphasis will be given to the PROSPECT experiment with recent data and analysis shown.
This year, the Nobel Prize in Physics was awarded to Arthur Ashkin, Gérard Mourou and Donna Strickland for their groundbreaking research leading to optical tweezers and chirped laser pulse amplification. These inventions have revolutionized laser physics. Extremely small objects and incredibly rapid processes are now being seen in a new light. Advanced precision instruments are opening up unexplored areas of research and a multitude of industrial and medical applications.
In this talk, the physical principles behind optical tweezers and chirped laser pulse amplification are explained. The high impact of the inventions and their broad applications today will be discussed.
Recently, experiments with ultracold gases have made it possible to study dynamics of (nearly) isolated many-body quantum systems. This has revived theoretical interest on this topic. In generic isolated systems, one expects nonequilibrium dynamics to result in thermalization: a relaxation to states where the values of macroscopic quantities are stationary, universal with respect to widely differing initial conditions, and predictable through the time-tested recipe of statistical mechanics. However, it is not obvious what feature of a many-body system makes quantum thermalization possible, in a sense analogous to that in which dynamical chaos makes classical thermalization possible. Underscoring that new rules could apply in the quantum case, experimental studies in one-dimensional systems have shown that traditional statistical mechanics can provide wrong predictions for the outcomes of relaxation dynamics. We argue that generic isolated quantum systems do in fact relax to states in which observables are well-described by statistical mechanics. Moreover, we show that time evolution itself plays a merely auxiliary role as thermalization happens at the level of individual eigenstates. We also discuss what happens at integrable points, in which a different set of rules apply.
Significant research and development in the field of Si Photonics have been done in the past two decades leading to the worldwide establishment of Si Photonics foundry services. The technology advancement includes hybrid integration of III-V laser diodes on Si platform, micro-ring or disk resonators, integrated PN junction based Mach-Zehnder (MZ) light modulators, SiGe on Si photodetectors, SiN low-loss waveguides, integrated optical delay line, array waveguide gratings etc. In my group, the current focus of research is slow-light Bragg grating rib waveguides and slot waveguides on Si substrate. Slow-light waveguide has enhanced light-matter interaction so allowing significant size reduction in active photonic devices such as MZ light modulators. The MZ modulator is a basic building block for a large array of tunable optical interference units for the on-chip optical neuromorphic computing application in which the MZ interferometer serves as an arbitrary unitary matrix. The passive slow-light waveguide is also a key element for chip scale photonic system integration in many application areas. For example, the slow-light Bragg grating waveguide has been used to construct tunable optical delay lines for beamforming in phased array antennas. For on-chip optical reservoir computing, a dispersive Bragg grating is a critical element in obtaining nanoseconds of true-time delay for storage of memories.
In this talk, I will start from a general picture of excited states, such as quasiparticles and excitons, in solids and how to calculate them by first-principles approaches. Then I will focus on light-matter interactions of nanoscale materials, in which the reduced dimensionality substantially enhances many-electron interactions by one to two orders of magnitude and results in unique excited-state properties, such as strongly polarized excitons and exciton liquids. By clarifying and calculating electron-electron, electron-hole, and electron-plasmon interactions, respectively, we can accurately explain many important measurements and provide new routes to engineer light-matter interactions for device and energy applications of nanostructures. Finally, taking a new family of two-dimensional materials, black phosphorus and its isoelectronic materials as examples, I will broaden the study by combining different levels of first-principles tools and models to reliably predict a wide range of electronic, optical, thermal, and polarization properties of solids.