Юрий Кругляк_Квантовое моделирование в квантовой химии на квантовых компьютерах_399_стр

Квантовые вычислительные устройства

QC-1

A. D. Corcoles, A. Kandala, A. Javadi-Abhari et al

Challenges and Opportunities of Near-Term Quantum Computing Systems https://arxiv.org/pdf/1910.02894.pdf

07.10.2019

The concept of quantum computing has inspired a whole new generation of scientists, including physicists, engineers, and computer scientists, to fundamentally change the landscape of information technology. With experimental demonstrations stretching back more than two decades, the quantum computing community has achieved a major milestone over the past few years: the ability to build systems that are stretching the limits of what can be classically simulated, and which enable cloudbased research for a wide range of scientists, thus increasing the pool of talent exploring early quantum systems. While such noisy near-term quantum computing systems fall far short of the requirements for fault-tolerant systems, they provide unique testbeds for exploring the opportunities for quantum applications. Here we highlight the facets associated with these systems, including quantum software, cloud access, benchmarking quantum systems, error correction and mitigation in such systems, and understanding the complexity of quantum circuits and how early quantum applications can run on near term quantum computers.

QC-2

Frank Arute, Kunal Arya,..., John M. Martinis

Quantum supremacy using a programmable superconducting processor

Nature, 574, 505 – 510 (2019); 23.10.2019

The promise of quantum computers is that certain computational tasks might be executed exponentially faster on a quantum processor than on a classical processor. A fundamental challenge is to build a high-fidelity processor capable of running quantum algorithms in an exponentially large computational space. Here we report the use of a processor Sycamore with programmable superconducting qubits to create quantum states on 53 qubits, corresponding to a computational state-space of dimension 253 (about 1016). Measurements from repeated experiments sample the resulting probability distribution, which we verify using classical simulations. Our Sycamore processor takes about 200 seconds to sample one instance of a quantum circuit a million times—our benchmarks currently indicate that the equivalent task for a state-of-the-art classical supercomputer would take approximately 10,000 years. This dramatic increase in speed compared to all known classical algorithms is an experimental realization of quantum supremacy for this specific computational task, heralding a much-anticipated computing paradigm.

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QC-3

Zhihui Wang, Eleanor Rieffel

Dance with Noise in NISQ Era – A NASA Perspective on Quantum Computing https://ntrs.nasa.gov/archive/nasa/casi.ntrs.nasa.gov/20190032615.pdf

2019

The Noisy Intermediate-Scale Quantum (NISQ) Era: Google, Intel, IBM, Rigetti, Honeywell, IonQ.

QC-4

Salonik Resch, Ulya R. Karpuzcu

Benchmarking Quantum Computers and the Impact of Quantum Noise https://arxiv.org/abs/1912.00546

02.12.2019

Benchmarking is how the performance of a computing system is determined. Surprisingly, even for classical computers this is not a straightforward process. One must choose the appropriate benchmark and metrics to extract meaningful results. Different benchmarks test the system in different ways and each individual metric may or may not be of interest. Choosing the appropriate approach is tricky. The situation is even more open ended for quantum computers, where there is a wider range of hardware, fewer established guidelines, and additional complicating factors. Notably, quantum noise significantly impacts performance and is difficult to model accurately. Here, we discuss benchmarking of quantum computers from a computer architecture perspective and provide numerical simulations highlighting challenges which suggest caution.

QC-5

Thomas R. Bromley, Juan Miguel Arrazola, Soran Jahangiri at al

Applications of Near-Term Photonic Quantum Computers: Software and Algorithms

https://arxiv.org/abs/1912.07634 16.12.2019

Gaussian Boson Sampling (GBS) is a near-term platform for photonic quantum computing. Recent efforts have led to the discovery of GBS algorithms with applications to graph-based problems, point processes, and molecular vibronic

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spectra in chemistry. The development of dedicated quantum software is a key enabler in permitting users to program devices and implement algorithms. In this work, we introduce a new applications layer for the Strawberry Fields photonic quantum computing library. The applications layer provides users with the necessary tools to design and implement algorithms using GBS with only a few lines of code. This paper serves a dual role as an introduction to the software, supported with example code, and also a review of the current state of the art in GBS algorithms.

QC-6

Arighna Deb, Gerhard W. Dueck, Robert Wille

Towards Exploring the Potential of Alternative Quantum Computing Architectures http://iic.jku.at/files/eda/2020_date_potential_of_alternative_quantum_computing_ar chitectures.pdf

11.01.2020

The recent advances in the physical realization of Noisy Intermediate Scale Quantum (NISQ) computers have motivated research on design automation that allows users to execute quantum algorithms on them. Certain physical constraints in the architectures restrict how logical qubits used to describe the algorithm can be mapped to physical qubits used to realize the corresponding functionality. Thus far, this has been addressed by inserting additional operations in order to overcome the physical constrains. However, all these approaches have taken the existing architectures as invariant and did not explore the potential of changing the quantum architecture itself—a valid option as long as the underlying physical constrains remain satisfied. In this work, we propose initial ideas to explore this potential. More precisely, we introduce several schemes for the generation of alternative coupling graphs (and, by this, quantum computing architectures) that still might be able to satisfy physical constraints but, at the same time, allow for a more efficient realization of the desired quantum functionality.

Программирование квантовых компьютеров

P-1

Guang Hao Low, Nicholas P. Bauman, Christopher E. Granade et al

Q# and NWChem: Tools for Scalable Quantum Chemistry on Quantum Computers

https://arxiv.org/abs/1904.01131v1 : LiH, H10, C20 01.04.2019

Fault-tolerant quantum computation promises to solve outstanding problems in quantum chemistry within the next decade. Realizing this promise requires scalable tools that allow users to translate descriptions of electronic structure problems to optimized quantum gate sequences executed on physical hardware, without requiring

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specialized quantum computing knowledge. To this end, we present a quantumchemistry library, under the open-source MIT license, that implements and enables straightforward use of state-of-art quantum simulation algorithms. The library is implemented in Q#, a language designed to express quantum algorithms at scale, and interfaces with NWChem, a leading electronic structure package. We define a standardized schema for this interface, Broombridge, that describes secondquantized Hamiltonians, along with metadata required for effective quantum simulation, such as trial wavefunction ansatzes. This schema is generated for arbitrary molecules by NWChem, conveniently accessible, for instance, through Docker containers and a recently developed web interface EMSL Arrows. We illustrate use of the library with various examples, including groundand excitedstate calculations for LiH, H10, and C20 with an active-space simplification, and automatically obtain resource estimates for classically intractable examples.

P-2

Jarrod R. McClean, Kevin J. Sung, Ian D. Kivlichan et al

OpenFermion: The Electronic Structure Package for Quantum Computers https://arxiv.org/pdf/1710.07629v5.pdf

27.02.2019

Quantum simulation of chemistry and materials is predicted to be an important application for both near-term and fault-tolerant quantum devices. However, at present, developing and studying algorithms for these problems can be difficult due to the prohibitive amount of domain knowledge required in both the area of chemistry and quantum algorithms. To help bridge this gap and open the field to more researchers, we have developed the OpenFermion software package (www.openfermion.org). OpenFermion is an open-source software library written largely in Python under an Apache 2.0 license, aimed at enabling the simulation of fermionic and bosonic models and quantum chemistry problems on quantum hardware. Beginning with an interface to common electronic structure packages, it simplies the translation between a molecular specification and a quantum circuit for solving or studying the electronic structure problem on a quantum computer, minimizing the amount of domain expertise required to enter the field. The package is designed to be extensible and robust, maintaining high software standards in documentation and testing. This release paper outlines the key motivations behind design choices in OpenFermion and discusses some basic OpenFermion functionality which we believe will aid the community in the development of better quantum algorithms and tools for this exciting area of research.

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P-3

Patrick J. Coles, Stephan Eidenbenz, Scott Pakin et al

Quantum Algorithm Implementations for Beginners https://arxiv.org/abs/1804.03719

10.04.2018

As quantum computers have become available to the general public, the need has arisen to train a cohort of quantum programmers, many of whom have been developing classic computer programs for most of their career. While currently available quantum computers have less than 100 qubits, quantum computer hardware is widely expected to grow in terms of qubit counts, quality, and connectivity. Our article aims to explain the principles of quantum programming, which are quite different from classical programming, with straight-forward algebra that makes understanding the underlying quantum mechanics optional (but still fascinating). We give an introduction to quantum computing algorithms and their implementation on real quantum hardware. We survey 20 different quantum algorithms, attempting to describe each in a succintc and self-contained fashion; we show how they are implemented on IBM's quantum computer; and in each case we discuss the results of the implementation with respect to differences of the simulator and the actual hardware runs. This article introduces computer scientists and engineers to quantum algorithms and provides a blueprint for their implementations.

P-4

Y. I. Ozhigov

About quantum computer software

https://arxiv.org/abs/1910.11428: Rb85 hν →, He6 → He5 + n → He4 + 2n 11.10.2019

Quantum computer is the key to controlling complex processes. If its hardware, in general is successfully created on the basis of the physical baggage of the 20th century, the mathematical software is fundamentally lagging behind. Feynman's user interface in the form of quantum gate arrays, cannot be used for the control because it gives the solution of Schrödinger equation with quadratic slowdown compared to the real process. The software must then imitate the real process using appropriate program primitives written as the programs for classical supercomputer. The decoherence will be reflected by some constant – the number of basic states that can fit into the limited of memory available to software. The real value of this constant can be found in the experimental realization of Grover search algorithm. Rough estimates of this constant are given based on the simplest processes of quantum electrodynamics and nuclear decay.

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P-5

Devon Rojas

The Modern State of Quantum Proframming Language http://www.devonrojas.com/assets/The%20Modern%20State%20of%20Quantum%2 0Programming.pdf

15.11.2019

Work remains in all of these languages as developers fine-tune the intricacies and abilities of them. There is much more time to be spent focusing on handling quantum error correction within quantum programs and designing a robust software framework that can accommodate the various physical constraints of quantum devices. With so many QPLs out there to choose from and build off of, it is hard to pick a single language that has the optimal design format for developers and quantum computers. Does it make more sense to continue in the path of imperative languages because of the amount of global developers it has, or is it more beneficial to take advantage of the error-free runtime execution of declarative languages? Or, like Quil, is there a mix between the two, or another paradigm altogether, that is best-suited for the quantum environment? The answers to these questions are all unclear – for now. As quantum computer accessibility grows, it is likely that a better understanding of the efficiencies of each language will come about, from developer ease-of-use to optimizations of quantum algorithms to faulttolerant quantum program execution by quantum error-correcting protocols. At the time being, the current languages serve as a gateway to the future, providing us with the ability to innovate next-generation of quantum algorithms and learn much more about the quantum world than we ever thought possible.

Перспективные исследования

PR-1

Scott E. Smart, David I. Schuster, David A. Mazziotti

Experimental data from a quantum computer verifies the generalized Pauli exclusion principle

https://www.nature.com/articles/s42005-019-0110-3; https://static-content.springer.com/esm/art%3A10.1038%2Fs42005-019-0110- 3/MediaObjects/42005_2019_110_MOESM1_ESM.pdf: H3, C3H3 31.01.2019

“What are the consequences… that Fermi particles cannot get into the same state…” R. P. Feynman wrote of the Pauli exclusion principle, “In fact, almost all the peculiarities of the material world hinge on this wonderful fact.” In 1972 Borland and Dennis showed that there exist powerful constraints beyond the Pauli exclusion principle on the orbital occupations of Fermi particles, providing important restrictions on quantum correlation and entanglement. Here we use computations on

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quantum computers to experimentally verify the existence of these additional constraints. Quantum many-fermion states are randomly prepared on the quantum computer and tested for constraint violations. Measurements show no violation and confirm the generalized Pauli exclusion principle with an error of one part in one quintillion.

PR-2

Gabrielle Diemma, Shane Kalette, Emanuele Curotto

Quantum Simulations of Lithium Ion Solvation Dynamics in Mixed Stockmayer Clusters

Chem. Phys. Lett., 725: 16, 80 – 86 (2019) https://acswebcontent.acs.org/prfar/2017/Paper14824.html 06.2019

The structure, classical thermodynamics, and ground state properties of a cluster comprised of a lithium ion surrounded by 106 points dipoles, are determined. Two types of Stockmayer particles, D(N) and D(T), with disparate polarities are chosen to reproduce the empirical room temperature properties of six molecules of a highly polar substance, namely nitromethane, and one hundred of a relatively less polar substance, tetrahydrofuran, to study the effects of additives in electrolyte mixtures typically used in lithium batteries. The global minimum features a pentacoordinated charge on the surface, while the ion is found between two solvation layers around room temperature.

PR-3

Saad M.Darwish, Tamer A.Shendi, Ahmed Younes

Chemometrics approach for the prediction of chemical compounds' toxicity degree based on quantum inspired optimization with applications in drug discovery

Chemometrics Intelligent Lab. Systems, 193: 15, 103826 (2019) 10.2019

Chemometrics, the application of mathematical and statistical methods to the analysis of chemical data, is finding ever widening applications in the chemical process environment. The reliable prediction of toxic effects of chemicals in living systems is highly desirable in domains such as cosmetics, drug discovery, food safety, and the manufacturing of chemical compounds. Toxicity prediction requires several new approaches for knowledge discovery from data to paradigm composite associations between the modules of the chemical compound; the computational demands of such techniques increase greatly with the number of chemical compounds involved. State- of-the-art prediction methods such as neural networks and multi-layer regression require either tuning parameters or complex transformations of predictor or outcome variables and do not achieve highly accurate results. This paper proposes a Quantum

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Inspired Genetic Programming “QIGP” model to improve prediction accuracy. Genetic Programming is utilized to give a linear equation for calculating the degree of toxicity more accurately. Quantum computing is employed to improve the selection of the best-of-run individuals and handles parsimony pressure to reduce the complexity of solutions. The results of the internal validation analysis indicated that the QIGP model has better goodness of fit statistics then, and significantly outperforms, the Neural Network model.

PR-4

Anton Robert, Panagiotis Kl. Barkoutsos, Stefan Woerner, Ivano Tavernelli

Resource-E cient Quantum Algorithm for Protein Folding https://arxiv.org/abs/1908.02163

06.08.2019

Predicting the three-dimensional (3D) structure of a protein from its primary sequence of amino acids is known as the protein folding (PF) problem. Due to the central role of proteins' 3D structures in chemistry, biology and medicine applications (e.g., in drug discovery) this subject has been intensively studied for over half a century. Although classical algorithms provide practical solutions, sampling the conformation space of small proteins, they cannot tackle the intrinsic NP-hard complexity of the problem, even reduced to its simplest Hydrophobic-Polar model. While fault-tolerant quantum computers are still beyond reach for state-of-the-art quantum technologies, there is evidence that quantum algorithms can be successfully used on Noisy Intermediate-Scale Quantum (NISQ) computers to accelerate energy optimization in frustrated systems. In this work, we present a model Hamiltonian with O(N4) scaling and a corresponding quantum variational algorithm for the folding of a polymer chain with N monomers on a tetrahedral lattice. The model reflects many physico-chemical properties of the protein, reducing the gap between coarsegrained representations and mere lattice models. We use a robust and versatile optimisation scheme, bringing together variational quantum algorithms specifically adapted to classical cost functions and evolutionary strategies (genetic algorithms), to simulate the folding of the 10 amino acid Angiotensin peptide on 22 qubits. The same method is also successfully applied to the study of the folding of a 7 amino acid neuropeptide using 9 qubits on an IBM Q 20-qubit quantum computer. Bringing together recent advances in building gate-based quantum computers with noisetolerant hybrid quantum-classical algorithms, this work paves the way towards accessible and relevant scientific experiments on real quantum processors.

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PR-5

Anurag Mishra, Alireza Shabani

High-Quality Protein Force Fields with Noisy Quantum Processors https://arxiv.org/abs/1907.07128

16.07.2019

A central problem in biophysics and computational drug design is accurate modeling of biomolecules. The current molecular dynamics simulation methods can answer how a molecule inhibits a cancerous cell signaling pathway, or the role of protein misfolding in neurodegenerative diseases. However, the accuracy of current force fields (interaction potential) limits the reliability of computer simulations. Fundamentally a quantum chemistry problem, here we discuss developing new force fields using scalable ab initio quantum chemistry calculations on quantum computers. For a list of dipeptides for local parameterizations, we estimate the required number of qubits to be 1576 to 3808 with cc-pVTZ(-f) orbital basis and 88 to 276 with activespace reductions. We use Q# quantum computing chemistry package for our analysis. The estimated number of 100s of qubits put pharmaceutical application of near-term quantum processors in a realistic perspective.

PR-6

Jason P. Terry, Prosper D. Akrobotu, Christian F. A. Negre, Susan M. Mniszewski

Quantum Isomer Search https://arxiv.org/abs/1908.00542 01.08.2019

Isomer search or molecule enumeration refers to the problem of finding all the isomers for a given molecule. Many classical search methods have been developed in order to tackle this problem. However, the availability of quantum computing architectures has given us the opportunity to address this problem with new (quantum) techniques. This paper describes a quantum isomer search procedure for determining all the structural isomers of alkanes. We first formulate the structural isomer search problem as a quadratic unconstrained binary optimization (QUBO) problem. The QUBO formulation is for general use on either annealing or gate-based quantum computers. We use the D-Wave quantum annealer to enumerate all structural isomers of all alkanes with fewer carbon atoms (n < 10) than Decane (C10H22). The number of isomer solutions increases with the number of carbon atoms. We find that the sampling time needed to identify all solutions scales linearly with the number of carbon atoms in the alkane. We probe the problem further by employing reverse annealing as well as a perturbed QUBO Hamiltonian and find that the combination of these two methods significantly reduces the number of samples required to find all isomers.

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PR-7

Libor Veis, Jakub Visnak, Hiroaki Nishizawa, Hiromi Nakai, Jiri Pittner

Quantum Chemistry beyond Born–Oppenheimer Approximation on a Quantum Computer: A Simulated Phase Estimation Study

Intern. J. Quant. Chem. (2016); DOI: 10.1002/qua.25176: H2, HT

We present an efficient quantum algorithm for beyond-Born – Oppenheimer molecular energy computations. Our approach combines the quantum full configuration interaction method with the nuclear orbital plus molecular orbital method. We give the details of the algorithm and demonstrate its performance by classical simulations. Two isotopomers of the hydrogen molecule (H2, HT) were chosen as representative examples and calculations of the lowest rotationless vibrational transition energies were simulated.

PR-8

Maria A. Castellanos, Amro Dodin, Adam P. Willard

On the design of molecular excitonic circuits for quantum computing: the universal quantum gates

https://europepmc.org/abstract/ppr/ppr99610; DOI: 10.26434/chemrxiv.9991976.v1 16.10.2019

This manuscript presents a strategy for controlling the transformation of excitonic states through the design of circuits made up of coupled organic dye molecules. Specifically, we show how unitary transformation matrices can be mapped to the Hamiltonians of physical systems of dye molecules with specified geometric and chemical properties. The evolution of these systems over specific times encode the action of the unitary transformation. We identify the bounds on complexity of the transformations that can be represented by these circuits. We formalize this strategy and apply it to identify the excitonic circuits of the four universal quantum logic gates: NOT, Hadamard, π/8 and CNOT. We discuss the properties of these circuits and how their performance is expected to be influenced by the presence of environmental noise. We quantify the bounds on the spectroscopic properties of organic dye circuits under which single-qubit unitary transformations are possible.

PR-9

Dries Sels, Hesam Dashti, Samia Mora, Olga Demler, Eugene Demler

Quantum approximate Bayesian computation for NMR model inference https://arxiv.org/abs/1910.14221

31.10.2019

Recent technological advances may lead to the development of small scale quantum computers capable of solving problems that cannot be tackled with classical computers. A limited number of algorithms has been proposed and their relevance to 389