May 2024
·
62 Reads
·
1 Citation
Future Generation Computer Systems
This page lists the scientific contributions of an author, who either does not have a ResearchGate profile, or has not yet added these contributions to their profile.
It was automatically created by ResearchGate to create a record of this author's body of work. We create such pages to advance our goal of creating and maintaining the most comprehensive scientific repository possible. In doing so, we process publicly available (personal) data relating to the author as a member of the scientific community.
If you're a ResearchGate member, you can follow this page to keep up with this author's work.
If you are this author, and you don't want us to display this page anymore, please let us know.
May 2024
·
62 Reads
·
1 Citation
Future Generation Computer Systems
April 2024
·
10 Reads
Modeling chemical reactions with quantum chemical methods is challenging when the electronic structure varies significantly throughout the reaction, as well as when electronic excited states are involved. Multireference methods such as complete active space self-consistent field (CASSCF) can handle these multiconfigurational situations. However, even if the size of needed active space is affordable, in many cases the active space does not change consistently from reactant to product, causing discontinuities in the potential energy surface. The localized active space SCF (LASSCF) is a cheaper alternative to CASSCF for strongly correlated systems with weakly correlated fragments. The method is used for the first time to study a chemical reaction, namely the bond dissociation of a mono-, di-, and triphenylsulfonium cation. LASSCF calculations generate smooth potential energy scans more easily than the corresponding, more computationally expensive, CASSCF calculations, while predicting similar bond dissociation energies. Our calculations suggest a homolytic bond cleavage for di- and triphenylsulfonium, and a heterolytic pathway for monophenylsulfonium.
March 2024
·
43 Reads
·
1 Citation
Quantum subspace methods (QSMs) are a class of quantum computing algorithms where the time-independent Schrodinger equation for a quantum system is projected onto a subspace of the underlying Hilbert space. This projection transforms the Schrodinger equation into an eigenvalue problem determined by measurements carried out on a quantum device. The eigenvalue problem is then solved on a classical computer, yielding approximations to ground- and excited-state energies and wavefunctions. QSMs are examples of hybrid quantum-classical methods, where a quantum device supported by classical computational resources is employed to tackle a problem. QSMs are rapidly gaining traction as a strategy to simulate electronic wavefunctions on quantum computers, and thus their design, development, and application is a key research field at the interface between quantum computation and electronic structure. In this review, we provide a self-contained introduction to QSMs, with emphasis on their application to the electronic structure of molecules. We present the theoretical foundations and applications of QSMs, and we discuss their implementation on quantum hardware, illustrating the impact of noise on their performance.
March 2024
·
21 Reads
The simulation of chemical reactions is an anticipated application of quantum computers. Using a Diels-Alder reaction as a test case, in this study we explore the potential applications of quantum algorithms and hardware in investigating chemical reactions. Our specific goal is to calculate the activation barrier of a reaction between ethylene and cyclopentadiene forming a transition state. To achieve this goal, we use quantum algorithms for near-term quantum hardware (entanglement forging and quantum subspace expansion) and classical post-processing (many-body perturbation theory) in concert. We conduct simulations on IBM quantum hardware using up to 8 qubits, and compute accurate activation barriers in the reaction between cyclopentadiene and ethylene by accounting for both static and dynamic electronic correlation. This work illustrates a hybrid quantum-classical computational workflow to study chemical reactions on near-term quantum devices, showcasing the potential of quantum algorithms and hardware in accurately calculating activation barriers.
November 2023
·
27 Reads
·
2 Citations
Molecular Physics
September 2023
·
46 Reads
·
4 Citations
A prominent goal in quantum chemistry is to solve the molecular electronic structure problem for ground state energy with high accuracy. While classical quantum chemistry is a relatively mature field, the accurate and scalable prediction of strongly correlated states found, e.g., in bond breaking and polynuclear transition metal compounds remains an open problem. Within the context of a variational quantum eigensolver, we propose a new family of ansatzes which provides a more physically appropriate description of strongly correlated electrons than a unitary coupled cluster with single and double excitations (qUCCSD), with vastly reduced quantum resource requirements. Specifically, we present a set of local approximations to the unitary cluster Jastrow wavefunction motivated by Hubbard physics. As in the case of qUCCSD, exactly computing the energy scales factorially with system size on classical computers but polynomially on quantum devices. The local unitary cluster Jastrow ansatz removes the need for SWAP gates, can be tailored to arbitrary qubit topologies (e.g., square, hex, and heavy-hex), and is well-suited to take advantage of continuous sets of quantum gates recently realized on superconducting devices with tunable couplers. The proposed family of ansatzes demonstrates that hardware efficiency and physical transparency are not mutually exclusive; indeed, chemical and physical intuition regarding electron correlation can illuminate a useful path towards hardware-friendly quantum circuits.
September 2023
·
7 Reads
September 2023
·
148 Reads
·
6 Citations
npj Quantum Information
Modeling electronic systems is an important application for quantum computers. In the context of materials science, an important open problem is the computational description of chemical reactions on surfaces. In this work, we outline a workflow to model the adsorption and reaction of molecules on surfaces using quantum computing algorithms. We develop and compare two local embedding methods for the systematic determination of active spaces. These methods are automated and based on the physics of molecule-surface interactions and yield systematically improvable active spaces. Furthermore, to reduce the quantum resources required for the simulation of the selected active spaces using quantum algorithms, we introduce a technique for exact and automated circuit simplification. This technique is applicable to a broad class of quantum circuits and critical to enable demonstration on near-term quantum devices. We apply the proposed combination of active-space selection and circuit simplification to the dissociation of water on a magnesium surface using classical simulators and quantum hardware. Our study identifies reactions of molecules on surfaces, in conjunction with the proposed algorithmic workflow, as a promising research direction in the field of quantum computing applied to materials science.
August 2023
·
23 Reads
We introduce an adiabatic state preparation protocol which implements quantum imaginary time evolution under the Hamiltonian of the system. Unlike the original quantum imaginary time evolution algorithm, adiabatic quantum imaginary time evolution does not require quantum state tomography during its runtime, and unlike standard adiabatic state preparation, the final Hamiltonian is not the system Hamiltonian. Instead, the algorithm obtains the adiabatic Hamiltonian by integrating a classical differential equation that ensures that one follows the imaginary time evolution state trajectory. We introduce some heuristics that allow this protocol to be implemented on quantum architectures with limited resources. We explore the performance of this algorithm via classical simulations in a one-dimensional spin model and highlight essential features that determine its cost, performance, and implementability for longer times. We find competitive performance when compared to the original quantum imaginary time evolution, and argue that the rapid convergence of this protocol and its low resource requirements make it attractive for near-term state preparation applications.
July 2023
·
63 Reads
·
25 Citations
Nature
Quantum computers promise to solve certain computational problems much faster than classical computers. However, current quantum processors are limited by their modest size and appreciable error rates. Recent efforts to demonstrate quantum speedups have therefore focused on problems that are both classically hard and naturally suited to current quantum hardware, such as sampling from complicated—although not explicitly useful—probability distributions1–3. Here we introduce and experimentally demonstrate a quantum algorithm that is similarly well suited to current hardware, but which samples from complicated distributions arising in several applications. The algorithm performs Markov chain Monte Carlo (MCMC), a prominent iterative technique⁴, to sample from the Boltzmann distribution of classical Ising models. Unlike most near-term quantum algorithms, ours provably converges to the correct distribution, despite being hard to simulate classically. But like most MCMC algorithms, its convergence rate is difficult to establish theoretically, so we instead analysed it through both experiments and simulations. In experiments, our quantum algorithm converged in fewer iterations than common classical MCMC alternatives, suggesting unusual robustness to noise. In simulations, we observed a polynomial speedup between cubic and quartic over such alternatives. This empirical speedup, should it persist to larger scales, could ease computational bottlenecks posed by this sampling problem in machine learning⁵, statistical physics⁶ and optimization⁷. This algorithm therefore opens a new path for quantum computers to solve useful—not merely difficult—sampling problems.
... The rapidly evolving field of quantum computing could offer crucial breakthroughs in addressing these issues and exceed the capabilities of conventional methods [4][5][6][7][8][9]. As this technology continues to mature, the potential benefits it offers to complex engineering problems are becoming more apparent [10][11][12][13][14][15][16][17][18][19][20][21][22]. However, the challenge lies in accurately identifying those scenarios where quantum computing holds an advantage and in crafting algorithms to harness this potential. ...
May 2024
Future Generation Computer Systems
... Algorytmy korzystające z podprzestrzeni kwantowych zyskują coraz większą popularność ze względu na to, że przy obwodach kwantowych o umiarkowanie większej głębokości niż VQE, możliwe jest uzyskanie zbieżności zbliżonej do QPE [19]. Głównym założeniem tego typu metod jest skonstruowanie -wymiarowej wariacyjnej podprzestrzeni wielowymiarowej przestrzeni Hilberta za pomocą zbioru stanów bazowych , a następnie zrzutowanie na tę podprzestrzeń równania Schrödingera niezależnego od czasu. ...
March 2024
... Previous methods for employing the Jastrow ansatz for QC include adding auxiliary qubits, 37,38 approximating the operator, 37,39 and unitarization of the operator. 32,35,40 CVQE allows us to employ the Jastrow operator without auxiliary qubits, approximations, or unitarization. ...
September 2023
... This configuration was favored due to its minimal total value energy compared to other configurations. 63,64 The Supporting Information (Figures S1−S60) contains models of molecular complexes, electron density distributions, electron density distribution gradients, and visualizations of the highest occupied molecular orbital (HOMO) and lowest occupied molecular orbital (LUMO) of AsA-Fe-AmA triple chelate complexes. ...
September 2023
npj Quantum Information
... Eventually, as shown in Fig. 1g, due to the annealing process the dwell-time of dynamics in the neighborhood of the optima increases with time. Note that state-space exploration in the low-temperature regime is a significant problem in SA algorithms and literature hybrid quantum-classical methods [58] have been proposed to accelerate this process. In NeuroSA, the Fowler-Nordheim dynamical process allows for a finite probability of escape even in the low-temperature regime; however, this probability diminishes over time. ...
July 2023
Nature
... However, direct experimental approaches to entanglement phase transitions face two fundamental obstacles. First, a direct measurement of entanglement entropy requires quantum state tomography, the cost of which scales exponentially with system size, an issue already faced in some recent experiments [13][14][15]. The second, and more serious, bottleneck is posed by the exponential postselection problem [3]: to extract the prop- * Email: agorbanz@iasbs.ac.ir † Email: teemu.ojanen@tuni.fi ...
June 2023
Nature Physics
... tion within the research community [26,[34][35][36]. ...
May 2023
Journal of Chemical Theory and Computation
... Additionally, our experimental implementation of QLanczos for the spin system expands on prior theoretical work by Kirby, Motta, and Mezzacapo [26] by combining it with Variational Fast-Forwarding (VFF) [8]. The method allows us to implement the theoretical method experimentally on a 4-spin site instance. ...
May 2023
Quantum
... This can be achieved by computing approximate wavefunctions through classical heuristics, such as Hartree-Fock, configuration interaction, [7] or density matrix renormalization group (DMRG) approaches, [8] and loading such states on quantum hardware. [9] On fault-tolerant quantum hardware, quantum heuristicssuch as the variational quantum eigensolver (VQE), [10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27] adiabatic state preparation (ASP), [28][29][30][31][32][33][34][35] and quantum subspace diagonalization (QSD) [14,[36][37][38][39][40][41][42][43][44][45][46][47][48] -could be used to prepare initial states for quantum phase estimation, a method for which the runtime rigorously depends on the overlap between the initial state and the target eigenstate. [49][50][51] The challenge is that for systems where such heuristics are accurate, the problem can often be solved entirely using classical algorithms (to sufficient accuracy). ...
April 2023
The Journal of Physical Chemistry A
... Another thread of research in ground-state energy estimation has drawn on methods from numerical linear algebra to classically postprocess quantum measurementoutcome data in a more efficient and robust manner [53,56,61,111,113,127]. These methods employ techniques such as filter diagonalization [53,56], Lanczos methods [61], and dynamic mode decomposition [111]. ...
Reference:
Early Fault-Tolerant Quantum Computing
March 2023
Physical Review A