Bulletin of the American Physical Society
APS March Meeting 2023
Volume 68, Number 3
Las Vegas, Nevada (March 5-10)
Virtual (March 20-22); Time Zone: Pacific Time
Session W03: Quantum Computing and Other Frontiers in Chemical Physics |
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Sponsoring Units: DCP Chair: Steve Smith, South Dakota School of Mines & Technology Room: Room 126 |
Thursday, March 9, 2023 3:00PM - 3:12PM |
W03.00001: Characterizing the 1s:E state in the 28Si :77Se+ spin-photon system by the equation-of-motion variational quantum eigensolver method Cody S Fan, Adam D Cobb, Murat C Sarihan, Jiahui Huang, Jin Ho Kang, Khalifa M Azizur-Rahman, Susmit Jha, Chee Wei Wong Silicon based spin-photon interfaces are attractive candidates for quantum memory nodes in quantum networks. Silicon is the dominant host due to the vast silicon microelectronics industry and photonic integrated circuit infrastructure. One prominent spin-photon interface in the Si-platform is 28Si :77Se+ as it boasts a singlet-triplet T1 time of 4.6 hours at temperatures below 2 K and a T2 time of 2 seconds [1, 2]. However, the radiative efficiency of this spin-photon interface is only 0.8%, which is very low and makes spin-dependent luminescence readout schemes challenging, requiring additional steps such as Purcell enhancement or absorption spectroscopy [3-5]. It has been predicted that the energy of the 1s:E state in 28Si :77Se+ lies above the 1s:T2 state [6]. However, this has never been observed and it is entirely feasible that the 1s:E state lies below the 1s:T2 state, leading to the low radiative efficiency of the 1s:A-1s:T2:Γ7 transition. Traditionally, variational quantum eigensolvers only find the ground state of a Hamiltonian. Newer methods extend the algorithm to find the excited states of a Hamiltonian [7, 8]. This work utilizes the equation-of-motion variational quantum eigensolver method to find the energy level of the 1s:E state in the 28Si :77Se+ spin-photon system and examine the causes of low radiative efficiency to identify avenues for improvement. |
Thursday, March 9, 2023 3:12PM - 3:24PM |
W03.00002: Electronic Structure Simulations for Batteries and Fuel Cells Using a Quantum Computer Konstantin Lamp, Alejandro D Somoza, Felix Rupprecht, Marina Walt, Giorgio Silvi, Birger Horstmann One of the original and most promising applications of quantum computing is the simulation of a wide variety of processes in Physics and Chemistry with relevant industrial and scientific applications. Until now, all the classical algorithms that simulate the electronic and vibrational structure of atoms and molecules are severely restricted by the exponential growth in computational resources that are required to accommodate large chemical problems. In contrast, the quantum mechanical foundations of quantum processors provide a novel framework by which the correspondence between chemical orbitals and physical qubits can be exploited to develop quantum algorithms that may surpass their classical counterparts and tackle demanding problems that would be otherwise |
Thursday, March 9, 2023 3:24PM - 3:36PM |
W03.00003: Exploring Molecular Excited States with a Contracted Quantum Eigensolver Scott E Smart, Davis M Welakuh, Prineha Narang An important focus of quantum computing approaches for molecular systems is in accurately characterizing ground states. However, many interesting phenomena require access to higher energy states, which are more difficult to obtain in an accurate and efficient manner. In this work we introduce a contraction of a projected Schrödinger equation, which provides a necessary and sufficient condition for excited state solutions. From this, we introduce a contracted quantum eigensolver which can be used to find a solution of the contracted equation using a quantum computer. We then present applications to molecular systems demonstrating the approach. |
Thursday, March 9, 2023 3:36PM - 3:48PM |
W03.00004: Efficient Hamiltonian Encodings for Simulation of Interacting Fermions Jeffery Yu, Yuan Liu, Sina Zeytinoglu, Sho Sugiura In many scenarios for simulating interacting fermionic systems on quantum computers, such as finding the eigenstates or simulating the time evolutions, 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. We present a novel general framework to directly relate different fermion-to-qubit encoding schemes, and apply it to ab initio electronic structure Hamiltonians, which reduce the total number of gates for quantum chemistry simulations. |
Thursday, March 9, 2023 3:48PM - 4:00PM |
W03.00005: Two-temperature model in plasmonic nanocrystals with complex shapes Oscar R Avalos-Ovando, Lucas V Besteiro, Artur Movsesyan, Alexandre O Govorov The field of plasmonics has emerged as a novel way of manipulating the optical properties of nanomaterials upon illumination. Firstly, plasmonic nanocrystals (NCs) have shown promising uses, as their optical response can be manipulated through the careful design of their geometry; and secondly, plasmonic NCs generate heat efficiently in the presence of electromagnetic radiation. So, it is natural to wonder what opto-thermal effects occur in plasmonics NCs but with complex shapes. Here we tackle that question by studying the temporal dynamics of several complex-shape gold NCs. We use a two-temperature model to study the ultrafast photothermal responses, and we solve for the lattice and the electronic temperatures. We observe the creation of local modifications of the dielectric function via the temperature, which leads to the thermal imprint of plasmonic hotspots. Also, absorption signals are largely enhanced at the ultrafast timescales, showing that this is a general effect on all plasmonic NCs. Our results can lead to the design of ultrafast and optically reconfigurable nanophotonic devices. |
Thursday, March 9, 2023 4:00PM - 4:12PM |
W03.00006: Design of molecular excitonic circuits for quantum computing: Theory and application to simple quantum algorithms. Maria A Castellanos, Adam P Willard Excitonic circuits made of organic dye molecules are known to be highly sensitive to environmental noise, however, they can also be strongly coupled so as to enable rapid transfer and evolution of phase information. Designing potential quantum computing platforms based on these systems requires a detailed description of their strengths and limitations. |
Thursday, March 9, 2023 4:12PM - 4:24PM |
W03.00007: Crystal structure and proton conductivity behavior of CsH2PO4 sealed in small gas-filled volumes Cristian Botez We have used x-ray diffraction and ac-impedance spectroscopy to investigate the crystal structure and proton conductivity of CsH2PO4 (CDP) sealed in small volumes (15 ml and 50 ml) of air or inert gasses at T=250°C. Our data shows that CDP’s proton conductivity stays constant under these conditions at superprotonic values of ~2.5×10-2 S·cm-1 for at least 10 hours. Removing the gas from the chamber leads to a sharp drop in the proton conductivity of two orders of magnitude in ~ 2 hours. The gas pressure is several orders of magnitude below what was previously used to stabilize CDP’s superprotonic phase (~1GPa), and we found no evidence of a self-generated water vapor atmosphere in the chambers. Therefore, hermetically sealing CDP in small gas-filled volumes represents a new method to stabilize its superprotonic phase, which opens new paths for large scale applications of phosphate-based solid acids as intermediate-temperature fuel cell electrolytes. |
Thursday, March 9, 2023 4:24PM - 4:36PM |
W03.00008: Calculation of ionization potential of semiconductor nanoparticles using machine-learning accelerated construction of the self-energy operator Arindam Chakraborty, Chengpeng Gao, Chilukuri K Mohan, Nishant R Rodrigues The self-energy operator in many-electron system contains information about ionization potentials (IPs) and electron-affinities (EAs). In this work, we construct the self-energy operator using ensemble learner and apply ML-driver self-energy operator for determination of ionization energies for a series of PbS, CdS, PbSe and CdSe quantum dots. One of the principle challenges in the construction of self-energy operator is the unfavorable scaling of computational cost with respect to the increasing size of the chemical system. Specifically, the conventional method of constructing requires AO-to-MO transformation of integral (N5 scaling), followed by the construction of 2-particle 1-hole and 1-particle 2-hole components of self-energy (N3 scaling). Consequently, the conventional approach becomes computationally prohibitive for nanoparticles with 300+ heavy atoms with an excess of 5000 basis functions. In this work, we address this computational bottleneck by machine-learning the self-energy operator using a stack of ensemble learner comprising of neural networks and random forests. Specifically, we start with the frequency-domain representation of the self-energy operator and transform it into a real-space 13-dimensional kernel. We then show that the kernel can be factorized into tensor products of low-dimensional irreducible tensors the ensemble learners are used to learn these low-dimensional tensors and which are then used in tandem to construct to full self-energy operator. |
Thursday, March 9, 2023 4:36PM - 4:48PM |
W03.00009: Quantum informed machine-learning potentials for modeling CO2 adsorption in metal organic frameworks Binquan Luan, Bowen Zheng, Felipe L Oliveira, Rodrigo N Ferreira, Mathias B Steiner, Grace X Gu, Hendrik F Hamann Global warming caused by excessive emission of greenhouse gases (mainly CO2) into atmosphere imposes profound changes in environment. For curbing the global temperature increase, effective approaches for carbon capture are needed. As porous sorbents, metal organic frameworks (MOFs) are promising candidate-materials that potentially combine high CO2 uptake and CO2/N2 selectivity. However, it is still challenging to computationally identify the best suited species within the hundreds of thousands of MOF structures known today. First-principles-based simulations of CO2 adsorption in MOFs would provide the necessary accuracy, however, they are impractical for screening purpose due to the high computational cost. Classical-force-field based simulations would be computationally feasible, however, they do not provide sufficient accuracy. Here, we report the quantum-informed machine-learning force fields (QMLFF) for atomistic simulations of CO2 in MOFs. We demonstrate that the method has a much higher computational efficiency (~1000 times) than first-principles one while maintaining quantum-level accuracy. As a proof of principle, we show that the QMLFF-based atomistic simulations can yield various physical quantities comparable to experimental results. The combination of machine learning and atomistic simulation paves the way for modeling CO2 capture by MOFs both accurately and efficiently. |
Thursday, March 9, 2023 4:48PM - 5:00PM |
W03.00010: Comprehensive exploration of graphically defined reaction spaces Qiyuan Zhao, Michael Woulfe, Lawal Ogunfowora, Sanjay Garimella, Sai Mahit Vaddadi, Dylan Anstine, Olexandr Isayev, Brett M Savoie Thermodynamic and kinetic properties of reactions are essential to elucidate detailed reaction mechanisms and predict reaction yields. However, limited amount of reaction databases have been built to include these quantitative chemical reaction data, especially activation energies. In this study, we utilized the concept of model reaction to comprehensively explore the reaction space and generated 177k organic reactions involving C, H, O and N atoms. These reactions are calculated at GFN2-xTB and B3LYP-D3/TZVP levels of theory and show a great coverage of the entire reaction space. A delta-learning model was then trained on this dataset, which can approach the chemical accuracy in reproducing DFT level activation energies and can even outperform DFT calculations with the introduction of a small number of G4-level computations. We believe this large quantitative chemical reaction database can accelerate progress in the development of novel machine learning models for predicting reactions properties and general machine learning force field. |
Thursday, March 9, 2023 5:00PM - 5:12PM |
W03.00011: TUNING THE IMMISCIBILITY AND DEGREE OF REACTIVITY OF TERTIARY AMINES BY CHANGING THEIR FUNCTIONAL GROUPS: A DFT BASED COMPUTATIONAL STUDY Juan M Lopez-Encarnacion, Eduardo Nicolau, Perla E Cruz-Tato, Aleshka W Arce-Garcia The reclamation of water is a very important topic in our current society and critical for human manned space travel such as the International Space Station. Currently, tertiary amines have been used as a switchable polarizable solvent to increase the osmotic potential and reuse carbon dioxide for separation of water by forward osmosis. Both, immiscibility and the degree of reactiviy are identified as requirements to use tertiary amines in the water filtration systems. In this work, we conducted Density Functional Theory (DFT) computations for octanol-water partition coefficient (LogP), HOMO-LUMO gap (ΔE), and study the proton transfer process based on Gibbs free-energy and molecular dynamics simulations on 108 tertiary amines with different functional groups: 36 linear, 36 cyclic and 36 aromatic. |
Thursday, March 9, 2023 5:12PM - 5:24PM |
W03.00012: Polariton Enhanced Free Charge Carrier Generation in Donor-Acceptor Cavity Systems by a Second-Hybridization Mechanism Weijun Wu, Andrew E Sifain, Courtney A DelPo, Gregory D Scholes Cavity quantum electrodynamics has been studied as a potential approach to modify free charge carrier generation in donor-acceptor heterojunctions because of the delocalization and controllable energy level properties of hybridized light–matter states known as polaritons. However, in many experimental systems, cavity coupling decreases charge separation. Here, we theoretically study the quantum dynamics of a coherent and dissipative donor–acceptor cavity system, to investigate the dynamical mechanism and further discover the conditions under which polaritons may enhance free charge carrier generation. We use open quantum system methods based on single-pulse pumping to find that polaritons have the potential to connect excitonic states and charge separated states, further enhancing free charge generation on an ultrafast timescale of several hundred femtoseconds. The mechanism involves that polaritons with proper energy level allow the exciton to overcome the high Coulomb barrier induced by electron-hole attraction. Moreover, we propose that a second-hybridization between a polariton state and dark states with similar energy enables the formation of the hybrid charge separated states that are optically active. These two mechanisms lead to a maximum of 50\% enhancement of free charge carrier generation on a short timescale. However, our simulation reveals that on the longer timescale of picoseconds, internal conversion and cavity loss dominate and suppress free charge carrier generation, reproducing the experimental results. Thus, our work shows that polaritons can affect the charge separation mechanism and promote free charge carrier generation efficiency, but predominantly on a short timescale after photoexcitation. |
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