scholarly journals Option Pricing using Quantum Computers

Quantum ◽  
2020 ◽  
Vol 4 ◽  
pp. 291 ◽  
Author(s):  
Nikitas Stamatopoulos ◽  
Daniel J. Egger ◽  
Yue Sun ◽  
Christa Zoufal ◽  
Raban Iten ◽  
...  
Keyword(s):  
Option Pricing ◽  
Quantum Computer ◽  
Quantum Circuits ◽  
Quantum Computers ◽  
Barrier Options ◽  
Error Mitigation ◽  
Quantum Device ◽  
Amplitude Estimation ◽  
Simulation Results ◽  
Path Dependent

We present a methodology to price options and portfolios of options on a gate-based quantum computer using amplitude estimation, an algorithm which provides a quadratic speedup compared to classical Monte Carlo methods. The options that we cover include vanilla options, multi-asset options and path-dependent options such as barrier options. We put an emphasis on the implementation of the quantum circuits required to build the input states and operators needed by amplitude estimation to price the different option types. Additionally, we show simulation results to highlight how the circuits that we implement price the different option contracts. Finally, we examine the performance of option pricing circuits on quantum hardware using the IBM Q Tokyo quantum device. We employ a simple, yet effective, error mitigation scheme that allows us to significantly reduce the errors arising from noisy two-qubit gates.

scholarly journals Decoherence dynamics estimation for superconducting gate-model quantum computers

2020 ◽  
Vol 19 (10) ◽  
Author(s):  
Laszlo Gyongyosi
Keyword(s):  
Gaussian Noise ◽  
Quantum Computer ◽  
Computer Architectures ◽  
Quantum Circuits ◽  
Optimal Placement ◽  
Quantum Computers ◽  
Intermediate Scale ◽  
Layout Generation ◽  
Quantum Technology ◽  
Physical Layout

Abstract Superconducting gate-model quantum computer architectures provide an implementable model for practical quantum computations in the NISQ (noisy intermediate scale quantum) technology era. Due to hardware restrictions and decoherence, generating the physical layout of the quantum circuits of a gate-model quantum computer is a challenge. Here, we define a method for layout generation with a decoherence dynamics estimation in superconducting gate-model quantum computers. We propose an algorithm for the optimal placement of the quantum computational blocks of gate-model quantum circuits. We study the effects of capacitance interference on the distribution of the Gaussian noise in the Josephson energy.

scholarly journals Error mitigation with Clifford quantum-circuit data

Quantum ◽  
2021 ◽  
Vol 5 ◽  
pp. 592
Author(s):  
Piotr Czarnik ◽  
Andrew Arrasmith ◽  
Patrick J. Coles ◽  
Lukasz Cincio
Keyword(s):  
State Energy ◽  
Quantum Computer ◽  
Quantum Circuit ◽  
Training Data ◽  
Quantum Circuits ◽  
Accurate Estimation ◽  
Error Mitigation ◽  
Order Of Magnitude ◽  
Quantum Observables ◽  
Near Term

Achieving near-term quantum advantage will require accurate estimation of quantum observables despite significant hardware noise. For this purpose, we propose a novel, scalable error-mitigation method that applies to gate-based quantum computers. The method generates training data {Xinoisy,Xiexact} via quantum circuits composed largely of Clifford gates, which can be efficiently simulated classically, where Xinoisy and Xiexact are noisy and noiseless observables respectively. Fitting a linear ansatz to this data then allows for the prediction of noise-free observables for arbitrary circuits. We analyze the performance of our method versus the number of qubits, circuit depth, and number of non-Clifford gates. We obtain an order-of-magnitude error reduction for a ground-state energy problem on 16 qubits in an IBMQ quantum computer and on a 64-qubit noisy simulator.

Fundamentals of Quantum Computing, Quantum Supremacy, and Quantum Machine Learning

2021 ◽  
pp. 21-46
Author(s):  
Kamaljit I. Lakhtaria ◽  
Vrunda Gadesha
Keyword(s):  
Machine Learning ◽  
Quantum Computing ◽  
Quantum Computer ◽  
Error Mitigation ◽  
Fundamental Goal ◽  
Quantum Device ◽  
Quantum Machine Learning ◽  
Simulation Error ◽  
The Difference ◽  
Quantum Optimization

When we aim to demonstrate that a programmable quantum device can solve complex problems which cannot be addressed by classic computers, this fundamental goal is known as quantum supremacy. This concept has changed every fundamental rule of computation. In this chapter, the detailed concept of quantum computing and quantum supremacy is explained along with various open source tools and real-time applications of this technology. The major base concepts, quantum computing, the difference between classical and quantum computer on physical level, programing quantum device, and the experiment-quantum supremacy are explained conceptually. This chapter also includes an introduction of the tools Cirq and OpenFermion plus the applications like quantum simulation, error mitigation technique, quantum machine learning, and quantum optimization, which are explained with illustrations.

scholarly journals Automated Quantum Hardware Selection for Quantum Workflows

Electronics ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 984
Author(s):  
Benjamin Weder ◽  
Johanna Barzen ◽  
Frank Leymann ◽  
Marie Salm
Keyword(s):  
Quantum Computer ◽  
Quantum Algorithm ◽  
Software Tool ◽  
Quantum Circuit ◽  
Quantum Circuits ◽  
Quantum Computers ◽  
Workflow Model ◽  
Selection For ◽  
Selection Of

The execution of a quantum algorithm typically requires various classical pre- and post-processing tasks. Hence, workflows are a promising means to orchestrate these tasks, benefiting from their reliability, robustness, and features, such as transactional processing. However, the implementations of the tasks may be very heterogeneous and they depend on the quantum hardware used to execute the quantum circuits of the algorithm. Additionally, today’s quantum computers are still restricted, which limits the size of the quantum circuits that can be executed. As the circuit size often depends on the input data of the algorithm, the selection of quantum hardware to execute a quantum circuit must be done at workflow runtime. However, modeling all possible alternative tasks would clutter the workflow model and require its adaptation whenever a new quantum computer or software tool is released. To overcome this problem, we introduce an approach to automatically select suitable quantum hardware for the execution of quantum circuits in workflows. Furthermore, it enables the dynamic adaptation of the workflows, depending on the selection at runtime based on reusable workflow fragments. We validate our approach with a prototypical implementation and a case study demonstrating the hardware selection for Simon’s algorithm.

scholarly journals Structure optimization for parameterized quantum circuits

Quantum ◽  
2021 ◽  
Vol 5 ◽  
pp. 391
Author(s):  
Mateusz Ostaszewski ◽  
Edward Grant ◽  
Marcello Benedetti
Keyword(s):  
Ground State ◽  
Heisenberg Model ◽  
Quantum Computer ◽  
Structure Optimization ◽  
Hydrogen Gas ◽  
Quantum Circuits ◽  
Quantum Computers ◽  
Computational Overhead ◽  
Parameter Values ◽  
Better Than

We propose an efficient method for simultaneously optimizing both the structure and parameter values of quantum circuits with only a small computational overhead. Shallow circuits that use structure optimization perform significantly better than circuits that use parameter updates alone, making this method particularly suitable for noisy intermediate-scale quantum computers. We demonstrate the method for optimizing a variational quantum eigensolver for finding the ground states of Lithium Hydride and the Heisenberg model in simulation, and for finding the ground state of Hydrogen gas on the IBM Melbourne quantum computer.

scholarly journals Quantum Computing in the NISQ era and beyond

Quantum ◽  
2018 ◽  
Vol 2 ◽  
pp. 79 ◽  
Author(s):  
John Preskill
Keyword(s):  
Quantum Computing ◽  
Quantum Physics ◽  
Quantum Computer ◽  
Fault Tolerant ◽  
Quantum Circuits ◽  
Quantum Gates ◽  
Quantum Computers ◽  
Many Body ◽  
Significant Step ◽  
Near Future

Noisy Intermediate-Scale Quantum (NISQ) technology will be available in the near future. Quantum computers with 50-100 qubits may be able to perform tasks which surpass the capabilities of today's classical digital computers, but noise in quantum gates will limit the size of quantum circuits that can be executed reliably. NISQ devices will be useful tools for exploring many-body quantum physics, and may have other useful applications, but the 100-qubit quantum computer will not change the world right away - we should regard it as a significant step toward the more powerful quantum technologies of the future. Quantum technologists should continue to strive for more accurate quantum gates and, eventually, fully fault-tolerant quantum computing.

scholarly journals An Extensible Computing Platform for Heavy Quantum Simulation Workloads

2021 ◽  
Author(s):  
Andrés García ◽  
José Ranilla ◽  
Raul Alonso Alvarez ◽  
Luis Meijueiro
Keyword(s):  
Quantum Computing ◽  
High Performance ◽  
Quantum Computer ◽  
General Purpose ◽  
Quantum Circuits ◽  
Quantum Computers ◽  
Computing Platform ◽  
Current State ◽  
Classical Computing ◽  
Computing Simulation

The shortage of quantum computers, and their current state of development, constraints research in many fields that could benefit from quantum computing. Although the work of a quantum computer can be simulated with classical computing, personal computers take so long to run quantum experiments that they are not very useful for the progress of research. This manuscript presents an open quantum computing simulation platform that enables quantum computing researchers to have access to high performance simulations. This platform, called QUTE, relies on a supercomputer powerful enough to simulate general purpose quantum circuits of up to 38 qubits, and even more under particular simulations. This manuscript describes in-depth the characteristics of the QUTE platform and the results achieved in certain classical experiments in this field, which would give readers an accurate idea of the system capabilities.

Replication of Quantum Computing towards an Unconventional Environment using QuIDE

2019 ◽  
Vol 8 (4) ◽  
pp. 9461-9464
Keyword(s):  
Quantum Computer ◽  
Source Code ◽  
Circuit Diagram ◽  
Quantum Computers ◽  
Coordinated Development ◽  
Development Environment ◽  
Integrated Development ◽  
Complexity Of Algorithms ◽  
Performance Results ◽  
Exponential Complexity

Current quantum computer simulation strategies are inefficient in simulation and their realizations are also failed to minimize those impacts of the exponential complexity for simulated quantum computations. We proposed a Quantum computer simulator model in this paper which is a coordinated Development Environment – QuIDE (Quantum Integrated Development Environment) to support the improvement of algorithm for future quantum computers. The development environment provides the circuit diagram of graphical building and flexibility of source code. Analyze the complexity of algorithms shows the performance results of the simulator and used for simulation as well as result of its deployment during simulation

scholarly journals Asset–liability modelling in the quantum era

2021 ◽  
Vol 26 ◽  
Author(s):  
T. Berry ◽  
J. Sharpe
Keyword(s):  
Quantum Mechanics ◽  
Quantum Computer ◽  
Quantum Algorithm ◽  
Capital Requirements ◽  
Quantum Computers ◽  
Investment Management ◽  
Asset Liability Management ◽  
Liability Management ◽  
Insight Into ◽  
Current Practices

Abstract This paper introduces and demonstrates the use of quantum computers for asset–liability management (ALM). A summary of historical and current practices in ALM used by actuaries is given showing how the challenges have previously been met. We give an insight into what ALM may be like in the immediate future demonstrating how quantum computers can be used for ALM. A quantum algorithm for optimising ALM calculations is presented and tested using a quantum computer. We conclude that the discovery of the strange world of quantum mechanics has the potential to create investment management efficiencies. This in turn may lead to lower capital requirements for shareholders and lower premiums and higher insured retirement incomes for policyholders.

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