67 citations · 355 across the 27 of their papers we have counts for
27 papers
Quantum algorithm for copula-based risk aggregation using orthogonal series density estimation
Hitomi Mori, Koichi Miyamoto
Quantum Monte Carlo integration (QMCI) provides a quadratic speed-up over its classical counterpart, and its applications have been investigated in various fields, including financ…
On the bias in iterative quantum amplitude estimation
Koichi Miyamoto
Quantum amplitude estimation (QAE) is a pivotal quantum algorithm to estimate the squared amplitude of the target basis state in a quantum state . Various improvemen…
A comprehensive survey on quantum computer usage: How many qubits are employed for what purposes?
Tsubasa Ichikawa, Hideaki Hakoshima, Koji Inui +18
Quantum computers (QCs), which work based on the law of quantum mechanics, are expected to be faster than classical computers in several computational tasks such as prime factoring…
The cross-sectional stock return predictions via quantum neural network and tensor network
Nozomu Kobayashi, Yoshiyuki Suimon, Koichi Miyamoto +1
In this paper, we investigate the application of quantum and quantum-inspired machine learning algorithms to stock return predictions. Specifically, we evaluate the performance of…
Quantum Metropolis-Hastings algorithm with the target distribution calculated by quantum Monte Carlo integration
Koichi Miyamoto
The Markov chain Monte Carlo method (MCMC), especially the Metropolis-Hastings (MH) algorithm, is a widely used technique for sampling from a target probability distribution on…
Quantum algorithm for position weight matrix matching
Koichi Miyamoto, Naoki Yamamoto, Yasubumi Sakakibara
We propose two quantum algorithms for a problem in bioinformatics, position weight matrix (PWM) matching, which aims to find segments (sequence motifs) in a biological sequence suc…
Extracting a function encoded in amplitudes of a quantum state by tensor network and orthogonal function expansion
Koichi Miyamoto, Hiroshi Ueda
There are quantum algorithms for finding a function satisfying a set of conditions, such as solving partial differential equations, and these achieve exponential quantum speedu…
Pricing multi-asset derivatives by variational quantum algorithms
Kenji Kubo, Koichi Miyamoto, Kosuke Mitarai +1
Pricing a multi-asset derivative is an important problem in financial engineering, both theoretically and practically. Although it is suitable to numerically solve partial differen…
Gravitational wave matched filtering by quantum Monte Carlo integration and quantum amplitude amplification
Koichi Miyamoto, Gonzalo Morrás, Takahiro S. Yamamoto +2
The speedup of heavy numerical tasks by quantum computing is now actively investigated in various fields including data analysis in physics and astronomy. In this paper, we propose…
Quantum algorithm for calculating risk contributions in a credit portfolio
Koichi Miyamoto
Finance is one of the promising field for industrial application of quantum computing. In particular, quantum algorithms for calculation of risk measures such as the value at risk…
Quantum algorithms for numerical differentiation of expected values with respect to parameters
Koichi Miyamoto
The quantum algorithms for Monte Carlo integration (QMCI), which are based on quantum amplitude estimation (QAE), speed up expected value calculation compared with classical counte…
Pricing multi-asset derivatives by finite difference method on a quantum computer
Koichi Miyamoto, Kenji Kubo
Following the recent great advance of quantum computing technology, there are growing interests in its applications to industries, including finance. In this paper, we focus on der…
Bermudan option pricing by quantum amplitude estimation and Chebyshev interpolation
Koichi Miyamoto
Pricing of financial derivatives, in particular early exercisable options such as Bermudan options, is an important but heavy numerical task in financial institutions, and its spee…
Linear Regression by Quantum Amplitude Estimation and its Extension to Convex Optimization
Kazuya Kaneko, Koichi Miyamoto, Naoyuki Takeda +1
Linear regression is a basic and widely-used methodology in data analysis. It is known that some quantum algorithms efficiently perform least squares linear regression of an expone…
Quantum Speedup of Monte Carlo Integration with respect to the Number of Dimensions and its Application to Finance
Kazuya Kaneko, Koichi Miyamoto, Naoyuki Takeda +1
Monte Carlo integration using quantum computers has been widely investigated, including applications to concrete problems. It is known that quantum algorithms based on quantum ampl…
Quantum Pricing with a Smile: Implementation of Local Volatility Model on Quantum Computer
Kazuya Kaneko, Koichi Miyamoto, Naoyuki Takeda +1
Applications of the quantum algorithm for Monte Carlo simulation to pricing of financial derivatives have been discussed in previous papers. However, up to now, the pricing model d…
Reduction of Qubits in Quantum Algorithm for Monte Carlo Simulation by Pseudo-random Number Generator
Koichi Miyamoto, Kenji Shiohara
It is known that quantum computers can speed up Monte Carlo simulation compared to classical counterparts. There are already some proposals of application of the quantum algorithm…
CMB distortion anisotropies due to the decay of primordial magnetic fields
Koichi Miyamoto, Toyokazu Sekiguchi, Hiroyuki Tashiro +1
We investigate the power spectrum of the distortion of Cosmic Microwave Background (CMB) due to the decay of the primordial magnetic fields. It is known that there are two-types of…
Cosmological and astrophysical constraints on superconducting cosmic strings
Koichi Miyamoto, Kazunori Nakayama
We investigate the cosmological and astrophysical constraints on superconducting cosmic strings (SCSs). SCS loops emit strong bursts of electromagnetic waves, which might affect va…
Forecast constraints on cosmic strings from future CMB, pulsar timing and gravitational wave direct detection experiments
Sachiko Kuroyanagi, Koichi Miyamoto, Toyokazu Sekiguchi +2
We study future observational constraints on cosmic string parameters from various types of next-generation experiments: direct detection of gravitational waves (GWs), pulsar timin…
Non-Gaussian isocurvature perturbations in dark radiation
Etsuko Kawakami, Masahiro Kawasaki, Koichi Miyamoto +2
We study non-Gaussian properties of the isocurvature perturbations in the dark radiation, which consists of the active neutrinos and extra light species, if exist. We first derive…
Forecast constraints on cosmic string parameters from gravitational wave direct detection experiments
Sachiko Kuroyanagi, Koichi Miyamoto, Toyokazu Sekiguchi +2
Gravitational waves (GWs) are one of the key signatures of cosmic strings. If GWs from cosmic strings are detected in future experiments, not only their existence can be confirmed…
Isocurvature perturbations in extra radiation
Masahiro Kawasaki, Koichi Miyamoto, Kazunori Nakayama +1
Recent cosmological observations, including measurements of the CMB anisotropy and the primordial helium abundance, indicate the existence of an extra radiation component in the Un…
Cosmological effects of decaying cosmic string loops with TeV scale width
Masahiro Kawasaki, Koichi Miyamoto, Kazunori Nakayama
In supersymmetric theories, cosmic strings produced in the early Universe often have a width of TeV scale, while the tension is much larger. In a scaling regime, an infinite cosmic…