scholarly journals A Full Quantum Eigensolver for Quantum Chemistry Simulations

Research ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-11 ◽  
Author(s):  
Shijie Wei ◽  
Hang Li ◽  
GuiLu Long
Keyword(s):  
Quantum Computing ◽  
Quantum Chemistry ◽  
Gradient Descent ◽  
Materials Science ◽  
Hybrid Methods ◽  
Quantum Computer ◽  
Rapid Development ◽  
System Size ◽  
Near Term ◽  
Full Quantum

Quantum simulation of quantum chemistry is one of the most compelling applications of quantum computing. It is of particular importance in areas ranging from materials science, biochemistry, and condensed matter physics. Here, we propose a full quantum eigensolver (FQE) algorithm to calculate the molecular ground energies and electronic structures using quantum gradient descent. Compared to existing classical-quantum hybrid methods such as variational quantum eigensolver (VQE), our method removes the classical optimizer and performs all the calculations on a quantum computer with faster convergence. The gradient descent iteration depth has a favorable complexity that is logarithmically dependent on the system size and inverse of the precision. Moreover, the FQE can be further simplified by exploiting a perturbation theory for the calculations of intermediate matrix elements and obtaining results with a precision that satisfies the requirement of chemistry application. The full quantum eigensolver can be implemented on a near-term quantum computer. With the rapid development of quantum computing hardware, the FQE provides an efficient and powerful tool to solve quantum chemistry problems.

scholarly journals What is Quantum Computing and How it Works

2020 ◽  
pp. 1-5
Author(s):  
Bahman Zohuri ◽  
◽  
Farhang Mossavar Rahmani ◽  
Keyword(s):  
Artificial Intelligence ◽  
Quantum Computing ◽  
Quantum Computer ◽  
Time Frame ◽  
Basic Unit ◽  
Next Generation ◽  
Intel Corporation ◽  
Encrypt Data ◽  
Near Term ◽  
Incremental Step

Companies such as Intel as a pioneer in chip design for computing are pushing the edge of computing from its present Classical Computing generation to the next generation of Quantum Computing. Along the side of Intel corporation, companies such as IBM, Microsoft, and Google are also playing in this domain. The race is on to build the world’s first meaningful quantum computer—one that can deliver the technology’s long-promised ability to help scientists do things like develop miraculous new materials, encrypt data with near-perfect security and accurately predict how Earth’s climate will change. Such a machine is likely more than a decade away, but IBM, Microsoft, Google, Intel, and other tech heavyweights breathlessly tout each tiny, incremental step along the way. Most of these milestones involve packing more quantum bits, or qubits—the basic unit of information in a quantum computer—onto a processor chip ever. But the path to quantum computing involves far more than wrangling subatomic particles. Such computing capabilities are opening a new area into dealing with the massive sheer volume of structured and unstructured data in the form of Big Data, is an excellent augmentation to Artificial Intelligence (AI) and would allow it to thrive to its next generation of Super Artificial Intelligence (SAI) in the near-term time frame.

scholarly journals Application of Quantum Computing to Biochemical Systems: A Look to the Future

2020 ◽  
Vol 8 ◽  
Author(s):  
Hai-Ping Cheng ◽  
Erik Deumens ◽  
James K. Freericks ◽  
Chenglong Li ◽  
Beverly A. Sanders
Keyword(s):  
Quantum Computing ◽  
Physical System ◽  
Quantum Computer ◽  
Quantum Algorithms ◽  
Active Regions ◽  
Quantum Computers ◽  
The Future ◽  
Biochemical Systems ◽  
Near Term ◽  
Different Levels

Chemistry is considered as one of the more promising applications to science of near-term quantum computing. Recent work in transitioning classical algorithms to a quantum computer has led to great strides in improving quantum algorithms and illustrating their quantum advantage. Because of the limitations of near-term quantum computers, the most effective strategies split the work over classical and quantum computers. There is a proven set of methods in computational chemistry and materials physics that has used this same idea of splitting a complex physical system into parts that are treated at different levels of theory to obtain solutions for the complete physical system for which a brute force solution with a single method is not feasible. These methods are variously known as embedding, multi-scale, and fragment techniques and methods. We review these methods and then propose the embedding approach as a method for describing complex biochemical systems, with the parts not only treated with different levels of theory, but computed with hybrid classical and quantum algorithms. Such strategies are critical if one wants to expand the focus to biochemical molecules that contain active regions that cannot be properly explained with traditional algorithms on classical computers. While we do not solve this problem here, we provide an overview of where the field is going to enable such problems to be tackled in the future.

scholarly journals An Adaptive Optimizer for Measurement-Frugal Variational Algorithms

Quantum ◽  
2020 ◽  
Vol 4 ◽  
pp. 263 ◽  
Author(s):  
Jonas M. Kübler ◽  
Andrew Arrasmith ◽  
Lukasz Cincio ◽  
Patrick J. Coles
Keyword(s):  
Quantum Computing ◽  
Partial Derivative ◽  
Gradient Descent ◽  
State Of The Art ◽  
Stochastic Gradient ◽  
Stochastic Gradient Descent ◽  
Near Term ◽  
Variational Algorithms

Variational hybrid quantum-classical algorithms (VHQCAs) have the potential to be useful in the era of near-term quantum computing. However, recently there has been concern regarding the number of measurements needed for convergence of VHQCAs. Here, we address this concern by investigating the classical optimizer in VHQCAs. We introduce a novel optimizer called individual Coupled Adaptive Number of Shots (iCANS). This adaptive optimizer frugally selects the number of measurements (i.e., number of shots) both for a given iteration and for a given partial derivative in a stochastic gradient descent. We numerically simulate the performance of iCANS for the variational quantum eigensolver and for variational quantum compiling, with and without noise. In all cases, and especially in the noisy case, iCANS tends to out-perform state-of-the-art optimizers for VHQCAs. We therefore believe this adaptive optimizer will be useful for realistic VHQCA implementations, where the number of measurements is limited.

scholarly journals Accuracy and Resource Estimations for Quantum Chemistry on a Near-Term Quantum Computer

2019 ◽  
Vol 15 (9) ◽  
pp. 4764-4780 ◽  
Author(s):  
Michael Kühn ◽  
Sebastian Zanker ◽  
Peter Deglmann ◽  
Michael Marthaler ◽  
Horst Weiß
Keyword(s):  
Quantum Chemistry ◽  
Quantum Computer ◽  
Near Term

scholarly journals Application-Motivated, Holistic Benchmarking of a Full Quantum Computing Stack

Quantum ◽  
2021 ◽  
Vol 5 ◽  
pp. 415 ◽  
Author(s):  
Daniel Mills ◽  
Seyon Sivarajah ◽  
Travis L. Scholten ◽  
Ross Duncan
Keyword(s):  
Quantum Computing ◽  
Computing System ◽  
Noise Levels ◽  
Computing Systems ◽  
Figures Of Merit ◽  
Quantum Machine Learning ◽  
Near Term ◽  
Classical Computing ◽  
Quantum Volume ◽  
Full Quantum

Quantum computing systems need to be benchmarked in terms of practical tasks they would be expected to do. Here, we propose 3 "application-motivated" circuit classes for benchmarking: deep (relevant for state preparation in the variational quantum eigensolver algorithm), shallow (inspired by IQP-type circuits that might be useful for near-term quantum machine learning), and square (inspired by the quantum volume benchmark). We quantify the performance of a quantum computing system in running circuits from these classes using several figures of merit, all of which require exponential classical computing resources and a polynomial number of classical samples (bitstrings) from the system. We study how performance varies with the compilation strategy used and the device on which the circuit is run. Using systems made available by IBM Quantum, we examine their performance, showing that noise-aware compilation strategies may be beneficial, and that device connectivity and noise levels play a crucial role in the performance of the system according to our benchmarks.

scholarly journals What is Quantum Computing and How it Works

2020 ◽  
pp. 1-5
Author(s):  
Bahman Zohuri ◽  
◽  
Farhang Mossavar Rahmani ◽  
Keyword(s):  
Artificial Intelligence ◽  
Quantum Computing ◽  
Quantum Computer ◽  
Time Frame ◽  
Basic Unit ◽  
Next Generation ◽  
Intel Corporation ◽  
Encrypt Data ◽  
Near Term ◽  
Incremental Step

Companies such as Intel as a pioneer in chip design for computing are pushing the edge of computing from its present Classical Computing generation to the next generation of Quantum Computing. Along the side of Intel corporation, companies such as IBM, Microsoft, and Google are also playing in this domain. The race is on to build the world’s first meaningful quantum computer—one that can deliver the technology’s long-promised ability to help scientists do things like develop miraculous new materials, encrypt data with near-perfect security and accurately predict how Earth’s climate will change. Such a machine is likely more than a decade away, but IBM, Microsoft, Google, Intel, and other tech heavyweights breathlessly tout each tiny, incremental step along the way. Most of these milestones involve packing more quantum bits, or qubits—the basic unit of information in a quantum computer—onto a processor chip ever. But the path to quantum computing involves far more than wrangling subatomic particles. Such computing capabilities are opening a new area into dealing with the massive sheer volume of structured and unstructured data in the form of Big Data, is an excellent augmentation to Artificial Intelligence (AI) and would allow it to thrive to its next generation of Super Artificial Intelligence (SAI) in the near-term time frame

scholarly journals Magnetic and Electronic Properties of Heavy Lanthanides (Gd, Tb, Dy, Er, Ho, Tm)

Crystals ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 82
Author(s):  
Radel R. Gimaev ◽  
Aleksei S. Komlev ◽  
Andrei S. Davydov ◽  
Boris B. Kovalev ◽  
Vladimir I. Zverev
Keyword(s):  
Rare Earth ◽  
Electronic Properties ◽  
High Purity ◽  
Materials Science ◽  
Rapid Development ◽  
Rare Earth Metals ◽  
State University ◽  
Important Place ◽  
Heavy Lanthanides ◽  
Baikov Institute

Rare earth metals (REM) occupy a special and important place in our lives. This became especially noticeable during the rapid development of industry in the industrial era of the twentieth century. The tendency of development of the rare-earth metals market certainly remains in the XXI century. According to experts estimates the industry demand for chemical compounds based on them will tend to grow during the nearest years until it reaches the market balance. At the same time, the practical use of high-purity rare-earth metals requires the most accurate understanding of the physical properties of metals, especially magnetic ones. Despite a certain decline in interest in the study of high-purity REM single crystals during the last decade, a number of scientific groups (Ames Lab, Lomonosov Moscow State University (MSU), Baikov Institute of Metallurgy and Materials Science Russian Academy of Science (RAS)) are still conducting high-purity studies on high-purity metal samples. The present article is a combination of a review work covering the analysis of the main works devoted to the study of heavy REMs from gadolinium to thulium, as well as original results obtained at MSU. The paper considers the electronic properties of metals in terms of calculating the density of states, analyzes the regularities of the magnetic phase diagrams of metals, gives the original dependences of the Neel temperature and tricritical temperatures for Gd, Tb, Dy, Er, Ho, Tm, and also introduces a phenomenological parameter that would serve as an indicator of the phase transformation in heavy REMs.

scholarly journals Evasion guidance for air-breathing hypersonic vehicles against unknown pursuer dynamics

2021 ◽  
Author(s):  
Tian Yan ◽  
Yuanli Cai ◽  
Bin Xu
Keyword(s):  
Parameter Estimation ◽  
Gradient Descent ◽  
Rapid Development ◽  
Energy Optimization ◽  
Hypersonic Vehicles ◽  
Air Breathing ◽  
Related Research ◽  
Practical Guidance ◽  
Simulation Results ◽  
Guidance Algorithm

AbstractThe rapid development of hypersonic vehicles has motivated the related research dramatically while the evasion of the hypersonic vehicles becomes one of the challenging issues. Different from the work based on the premise that the pursuers’ information is fully known, in this paper the evasion guidance for air-breathing hypersonic vehicles (AHVs) against unknown pursuer dynamics is studied. The gradient descent is employed for parameter estimation of the unknown dynamics of the pursuer. The energy-optimized evasion guidance algorithm is further developed by taking the acceleration constraint and energy optimization into consideration. Under the proposed algorithm, the system can deal with the unknown pursuer dynamics effectively and provide more practical guidance for the evasion process. The simulation results show that the proposed method can enable the AHV to achieve successful evasion.

scholarly journals Optimal teleportation via noisy quantum channels without additional qubit resources

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Dong-Gil Im ◽  
Chung-Hyun Lee ◽  
Yosep Kim ◽  
Hyunchul Nha ◽  
M. S. Kim ◽  
...  
Keyword(s):  
Quantum Computing ◽  
Quantum Teleportation ◽  
Quantum Communication ◽  
Quantum Noise ◽  
Single Copy ◽  
Entangled State ◽  
Quantum Network ◽  
Quantum Channels ◽  
Maximally Entangled State ◽  
Near Term

AbstractQuantum teleportation exemplifies how the transmission of quantum information starkly differs from that of classical information and serves as a key protocol for quantum communication and quantum computing. While an ideal teleportation protocol requires noiseless quantum channels to share a pure maximally entangled state, the reality is that shared entanglement is often severely degraded due to various decoherence mechanisms. Although the quantum noise induced by the decoherence is indeed a major obstacle to realizing a near-term quantum network or processor with a limited number of qubits, the methodologies considered thus far to address this issue are resource-intensive. Here, we demonstrate a protocol that allows optimal quantum teleportation via noisy quantum channels without additional qubit resources. By analyzing teleportation in the framework of generalized quantum measurement, we optimize the teleportation protocol for noisy quantum channels. In particular, we experimentally demonstrate that our protocol enables to teleport an unknown qubit even via a single copy of an entangled state under strong decoherence that would otherwise preclude any quantum operation. Our work provides a useful methodology for practically coping with decoherence with a limited number of qubits and paves the way for realizing noisy intermediate-scale quantum computing and quantum communication.

scholarly journals An Identity-Based Blind Signature Scheme Using Lattice with Provable Security

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Quanrun Li ◽  
Chingfang Hsu ◽  
Debiao He ◽  
Kim-Kwang Raymond Choo ◽  
Peng Gong
Keyword(s):  
Quantum Computer ◽  
Rapid Development ◽  
Random Oracle Model ◽  
Random Oracle ◽  
Mean Value ◽  
Blind Signature ◽  
Signature Scheme ◽  
Practical Applications ◽  
Universal Quantum ◽  
Identity Based

With the rapid development of quantum computing and quantum information technology, the universal quantum computer will emerge in the near decades with a very high probability and it could break most of the current public key cryptosystems totally. Due to the ability of withstanding the universal quantum computer’s attack, the lattice-based cryptosystems have received lots of attention from both industry and academia. In this paper, we propose an identity-based blind signature scheme using lattice. We also prove that the proposed scheme is provably secure in the random oracle model. The performance analysis shows that the proposed scheme has less mean value of sampling times and smaller signature size than previous schemes. Thus, the proposed scheme is more suitable for practical applications.

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