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## Publications

Publications (364)

Quantum subspace diagonalization (QSD) algorithms have emerged as a competitive family of algorithms that avoid many of the optimization pitfalls associated with parameterized quantum circuit algorithms. While the vast majority of the QSD algorithms have focused on solving the eigenpair problem for ground, excited-state, and thermal observable esti...

In coupled quantum systems pure dephasing mechanisms acting on one constituent of the hybrid system break symmetry and enable optical transitions which are forbidden in the non-coupled system, i.e., the pure dephasing bath opens a cascaded dissipation pathway. Here we show that this mechanism enables single-photon induced parametric down-conversion...

Quantum machine learning is a rapidly evolving area that could facilitate important applications for quantum computing and significantly impact data science. In our work, we argue that a single Kerr mode might provide some extra quantum enhancements when using quantum kernel methods based on various reasons from complexity theory and physics. Furth...

Simulating molecules using the Variational Quantum Eigensolver method is one of the promising applications for NISQ-era quantum computers. Designing an efficient ansatz to represent the electronic wave function is crucial in such simulations. Standard unitary coupled-cluster with singles and doubles (UCCSD) ansatz tends to have a large number of in...

Quantum chemistry calculations of large, strongly correlated systems are typically limited by the computation cost that scales exponentially with the size of the system. Quantum algorithms, designed specifically for quantum computers, can alleviate this, but the resources required are still too large for today’s quantum devices. Here we present a q...

Quantum Krylov subspace diagonalization (QKSD) algorithms provide a low-cost alternative to the conventional quantum phase estimation algorithm for estimating the ground- and excited-state energies of a quantum many-body system. While QKSD algorithms typically rely on using the Hadamard test for estimating Krylov subspace matrix elements of the for...

Reinforcement learning (RL) approaches that combine a tree search with deep learning have found remarkable success in searching exorbitantly large, albeit discrete action spaces, as in chess, Shogi and Go. Many real-world materials discovery and design applications, however, involve multi-dimensional search problems and learning domains that have c...

Optical tweezers are a powerful tool for exploring physical properties of particles in various environments through analysis of their dynamics in a trapping potential. Analysis of the trapped particle’s position is often done using interferometric back-focal-plane detection microscopy in which interference between the trapping laser and the light i...

Quantum chemistry calculations of large, strongly correlated systems are typically limited by the computation cost that scales exponentially with the size of the system. Quantum algorithms, designed specifically for quantum computers, can alleviate this, but the resources required are still too large for today’s quantum devices. Here we present a q...

Quantum chemistry calculations of large, strongly correlated systems are typically limited by the computation cost that scales exponentially with the size of the system. Quantum algorithms, designed specifically for quantum computers, can alleviate this, but the resources required are still too large for today’s quantum devices. Here we present a q...

Simulating molecules using the Variational Quantum Eigensolver method is one of the promising applications for NISQ-era quantum computers. Designing an efficient ansatz to represent the electronic wave function is crucial in such simulations. In this work we present a method that allows a significant reduction of the size of the unitary coupled clu...

Quantum Krylov subspace diagonalization (QKSD) algorithms provide a low-cost alternative to the conventional quantum phase estimation algorithm for estimating the ground and excited-state energies of a quantum many-body system. While QKSD algorithms have typically relied on using the Hadamard test for estimating Krylov subspace matrix elements of t...

Hybrids of graphene and metal plasmonic nanostructures are promising building blocks for applications in optoelectronics, surface-enhanced scattering, biosensing, and quantum information. An understanding of the coupling mechanism in these hybrid systems is of vital importance to its applications. Previous efforts in this field mainly focused on sp...

Indistinguishable photons are imperative for advanced quantum communication networks. Indistinguishability is difficult to obtain because of environment-induced photon transformations and loss imparted by communication channels, especially in noisy scenarios. Strategies to mitigate these transformations often require hardware or software overhead t...

We study the coupling of light and the structural order parameter in the charge density wave (CDW) state of the layered transition-metal dichalcogenide, Tantalum Disulfide ($1T-\mathrm{TaS_2}$). Using time-dependent density functional theory calculations of the dielectric properties along the distortions coordinates, we show that $1T-\mathrm{TaS_2}...

Two-dimensional (2D) semiconductors are attractive candidates for a variety of optoelectronic applications owing to the unique electronic properties that arise from quantum confinement along a single dimension. Incorporating nonradiative mechanisms that enable directed migration of bound charge carriers, such as Förster resonance energy transfer (F...

Reinforcement learning (RL) approaches that combine a tree search with deep learning have found remarkable success in searching exorbitantly large, albeit discrete action spaces, as demonstrated recently in board games like chess, Shogi, and Go. Many real-world materials discovery and design applications, however, involve multi-dimensional search p...

Ultrafast spectroscopy is an important tool for studying photoinduced dynamical processes in atoms, molecules, and nanostructures. Typically, the time to perform these experiments ranges from several minutes to hours depending on the choice of spectroscopic method. It is desirable to reduce this time overhead not only to shorten time and laboratory...

Nonequilibrium photon correlations of coherently excited single quantum systems can reveal their internal quantum dynamics and provide spectroscopic access. Here we propose and discuss the fundamentals of a coherent photon coincidence spectroscopy based on the application of laser pulses with variable delay and the detection of a time-averaged two-...

Herein we report experimental evidence of directional SERS from molecules situated inside a single nanowire-nanoparticle junction cavity. The emission was confined to a narrow range of wavevectors perpendicular to the axis of the cavity. In addition to this, the molecules excite multiple guided modes of the nanowire which were imaged using leakage...

Ultrafast spectroscopy is an important tool for studying photoinduced dynamical processes in atoms, molecules, and nanostructures. Typically, the time to perform these experiments ranges from several minutes to hours depending on the choice of spectroscopic method. It is desirable to reduce this time overhead to not only to shorten time and laborat...

Achieving propagation lengths in hybrid systems involving plasmonic components beyond typical values of tens of m is important for advancing quantum plasmonics applications. Here we report long-range optical energy propagation in hybrid photonicdevices due to excitons in semiconductor quantum dots (SQDs) strongly coupled to surface lattice resonanc...

Second harmonic generation (SHG) microscopy is useful for visualizing interfaces and sub-structures within a wide range of materials due to the propensity for SHG to occur in non-centrosymmetric environments. However, since SHG is a nonlinear process generally necessitating small focal sizes for higher peak powers, a raster scanning approach is usu...

Quantum optics experiments, involving the measurement of low-probability photon events, are known to be extremely time-consuming. We present a methodology for accelerating such experiments using physically motivated ansatzes together with simple statistical learning techniques such as Bayesian maximum a posteriori estimation based on few-shot data....

Although the study of nonradiating anapoles has long been part of fundamental physics, the dynamic anapole at optical frequencies was only recently experimentally demonstrated in a specialized silicon nanodisk structure. We report excitation of the electrodynamic anapole state in isotropic silicon nanospheres using radially polarized beam illuminat...

We examine the limits of applicability of a simple non-Hermitian model for exciton/plasmon interactions in the presence of dissipation and dephasing. The model can be used as an alternative to the more complete Lindblad density matrix approach and is computationally and conceptually simpler. We find that optical spectra in the linear regime can be...

We analyze the cooling of a mechanical resonator coupled to an ensemble of interacting two-level systems via an open quantum systems approach. Using an exact analytical result, we find optimal cooling occurs when the phonon mode is critically coupled ($\gamma \sim g$) to the two-level system ensemble. Typical systems operate in sub-optimal cooling...

Quantum optics experiments, involving the measurement of low-probability photon events, are known to be extremely time-consuming. We present a new methodology for accelerating such experiments using simple statistical learning techniques such as Bayesian maximum a posteriori estimation based on few-shot data. We show that it is possible to reconstr...

Non-equilibrium photon correlations of coherently excited single quantum systems can reveal their internal quantum dynamics and provide spectroscopic access. Here we propose and discuss the fundamentals of a coherent photon coincidence spectroscopy based on the application of laser pulses with variable delay and the detection of an time-averaged tw...

The efficiency of a thermophotovoltaic (TPV) system depends critically upon the spectral selectivity and stability of an emitter, which may operate most effectively at temperatures in excess of 1000 °C. We computationally design and experimentally demonstrate a novel selective emitter design based on multilayer nanostructures, robust to off-normal...

We examine the limits of applicability of a simple non-Hermitian model for exciton/plasmon interactions in the presence of dissipation and dephasing. The model can be used as an alternative to the more complete Lindblad density matrix approach and is computationally and conceptually simpler. We find that optical spectra in the linear regime can be...

We describe and demonstrate a method for the computation of quantum dynamics on small, noisy universal quantum computers. This method relies on the idea of `restarting' the dynamics; at least one approximate time step is taken on the quantum computer and then a parameterized quantum circuit ansatz is optimized to produce a state that well approxima...

This Perspective discusses the electronic structure of plasmonic resonances in metal nanostructures, clarifying existing misconceptions on the topic. Here we underscore the key property of the plasmonic response in metal nanocrystals: the plasmon and its wave function are mostly composed of a large number of low-energy excitations, which involve el...

Water is ubiquitous, yet displays a rich variety of thermodynamic properties and anomalies. An understanding of liquid-vapor phenomena in water is of broad impor- tance to everyday processes such as evaporation, condensation and cavitation, as well as energy technologies such as steam turbines. An accurate description of the vapor- liquid phenomena...

Herein experimental evidence of directional surface enhanced Raman scattering from molecules situated inside a single nanowire–nanoparticle junction cavity is reported. The emission is confined to a narrow range of wavevectors perpendicular to the axis of the cavity. In addition to this, the molecules excite multiple guided modes of the nanowire wh...

Crystal structure prediction has been a grand challenge in material science owing to the large configurational space that one must explore. Evolutionary (genetic) algorithms coupled with first principles calculations are commonly used in crystal structure prediction to sample the ground state and metastable states of materials based on configuratio...

In this letter, we consider the question of designing insulator/metal thermovoltaic structures with periodically corrugated interfaces that give optimal performance based on the metric of useful power density. Using a Monte Carlo approach in a robust, rapid, and high-accuracy numerical simulation strategy, we have identified such interface shapes....

An accurate and computationally efficient molecular level description of mesoscopic behavior of ice-water systems remains a major challenge. Here, we introduce a set of machine-learned coarse-grained (CG) models (ML-BOP, ML-BOPdih, and ML-mW) that accurately describe the structure and thermodynamic anomalies of both water and ice at mesoscopic scal...

We introduce a technique for recovering noise-free observables in noisy quantum systems by combining the results of many slightly different experiments. Our approach is applicable to a variety of quantum systems, but we illustrate it with applications to quantum information and quantum sensing. The approach corresponds to repeating the same quantum...

We analyze the cooling of a mechanical resonator coupled to an ensemble of interacting two-level systems via an open quantum systems approach. Using an exact analytical result, we find optimal cooling occurs when the phonon mode is critically coupled (γ∼g) to the two-level system ensemble. Typical systems operate in suboptimal cooling regimes due t...

Solution-processed perovskite quantum wells have been used to fabricate increasingly efficient and stable optoelectronic devices. Little is known about the dynamics of photogenerated excitons in perovskite quantum wells within the first few hundred femtoseconds – a crucial timescale on which energy and charge transfer processes may compete. Here we...

The ever-increasing power of modern supercomputers, along with the availability of highly scalable atomistic simulation codes, has begun to revolutionize predictive modeling of materials. In particular, molecular dynamics (MD) has led to breakthrough advances in diverse fields, including tribology, catalysis, sensing, and nanoparticle self-assembly...

Classical molecular dynamics (MD) simulations enable modeling of materials and examination of microscopic details that are not accessible experimentally. The predictive capability of MD relies on the force field (FF) used to describe interatomic interactions. FF parameters are typically determined to reproduce selected material properties computed...

The photons in circularly polarized light can transfer their quantized spin angular momentum to micro- and nanostructures via absorption and scattering. This normally exerts positive torque on the objects wher the sign (i.e., handedness or angular direction) follows that of the spin angular momentum. Here we show that the sign of the optical torque...

From Newtons third law, the principle of actio et reactio, we expect the forces between interacting particles to be equal and opposite. However, non-reciprocal forces can arise. Specifically, this has recently been shown theoretically in the interaction between dissimilar optically trapped particles mediated by an external field. As a result, despi...

Tailoring the emission spectra of a thermophotovoltaic (TPV) emitter away from that of a blackbody has the potential to minimize transmission and thermalization loss in a photovoltaic receiver. Selective TPV emitters can lead to solar energy conversion with efficiency greater than the Shockley–Queisser limit and can facilitate the generation of use...

Coarse-grained molecular dynamics (MD) simulations represent a powerful approach to simulate longer time scale and larger length scale phenomena than those accessible to all-atom models. The gain in efficiency, however, comes at the cost of atomistic details. The reverse transformation, also known as back-mapping, of coarse grained beads into their...

Developing a fundamental understanding of ultrafast non-thermal processes in metallic nanosystems will lead to applications in photodetection, photochemistry and photonic circuitry. Typically, non-thermal and thermal carrier populations in plasmonic systems are inferred either by making assumptions about the functional form of the initial energy di...

We report on the experimental observation of differential wavevector distribution of surface enhanced Raman scattering (SERS) and fluorescence from dye molecules confined to a gap between plasmonic silver nanowire and a thin, gold mirror. The fluorescence was mainly confined to higher values of in-plane wavevectors, whereas SERS signal was uniforml...