scholarly journals A systematic variational approach to band theory in a quantum computer

RSC Advances ◽  
2021 ◽  
Vol 11 (62) ◽  
pp. 39438-39449
Author(s):  
Kyle Sherbert ◽  
Frank Cerasoli ◽  
Marco Buongiorno Nardelli
Keyword(s):  
Band Structure ◽  
Variational Approach ◽  
Quantum Computer ◽  
Quantum Algorithm ◽  
Band Theory ◽  
Classical Algorithm

A quantum algorithm to calculate the band structure of any crystal, with efficiency comparable to the classical algorithm.

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.

scholarly journals Practical Quantum Computing

2021 ◽  
Vol 2 (1) ◽  
pp. 1-35
Author(s):  
Adrien Suau ◽  
Gabriel Staffelbach ◽  
Henri Calandra
Keyword(s):  
Wave Equation ◽  
Quantum Computer ◽  
Quantum Algorithms ◽  
Quantum Algorithm ◽  
Quantum Circuit ◽  
Equation Solving ◽  
Small Quantum ◽  
Quantum Wave ◽  
Variational Algorithms ◽  
The One

In the last few years, several quantum algorithms that try to address the problem of partial differential equation solving have been devised: on the one hand, “direct” quantum algorithms that aim at encoding the solution of the PDE by executing one large quantum circuit; on the other hand, variational algorithms that approximate the solution of the PDE by executing several small quantum circuits and making profit of classical optimisers. In this work, we propose an experimental study of the costs (in terms of gate number and execution time on a idealised hardware created from realistic gate data) associated with one of the “direct” quantum algorithm: the wave equation solver devised in [32]. We show that our implementation of the quantum wave equation solver agrees with the theoretical big-O complexity of the algorithm. We also explain in great detail the implementation steps and discuss some possibilities of improvements. Finally, our implementation proves experimentally that some PDE can be solved on a quantum computer, even if the direct quantum algorithm chosen will require error-corrected quantum chips, which are not believed to be available in the short-term.

Quantum lower bound for recursive Fourier sampling

2003 ◽  
Vol 3 (2) ◽  
pp. 165-174
Author(s):  
S. Aaronson
Keyword(s):  
Lower Bound ◽  
Quantum Algorithm ◽  
Independent Interest ◽  
Classical Algorithm ◽  
Fourier Sampling ◽  
Adversary Method

We revisit the oft-neglected `recursive Fourier sampling' (RFS) problem, introduced by Bernstein and Vazirani to prove an oracle separation between BPP and BQP. We show that the known quantum algorithm for RFS is essentially optimal, despite its seemingly wasteful need to uncompute information. This implies that, to place \mathsf{BQP} outside of PH[\log] relative to an oracle, one would need to go outside the RFS framework. Our proof argues that, given any variant of RFS, either the adversary method of Ambainis yields a good quantum lower bound, or else there is an efficient classical algorithm. This technique may be of independent interest.

Quantum algorithm for measuring the energy of n qubits with unknown pair-interactions

2002 ◽  
Vol 2 (3) ◽  
pp. 198-207
Author(s):  
D. Janzing
Keyword(s):  
Quantum State ◽  
Quantum Computer ◽  
Quantum Algorithm ◽  
Pair Interaction ◽  
Phase Estimation ◽  
Solid States ◽  
Energy Gaps ◽  
Large N ◽  
Conditional Transformation ◽  
Essential Assumption

The well-known algorithm for quantum phase estimation requires that the considered unitary is available as a conditional transformation depending on the quantum state of an ancilla register. We present an algorithm converting an unknown n-qubit pair-interaction Hamiltonian into a conditional one such that standard phase estimation can be applied to measure the energy. Our essential assumption is that the considered system can be brought into interaction with a quantum computer. For large n the algorithm could still be applicable for estimating the density of energy states and might therefore be useful for finding energy gaps in solid states.

TOWARDS A QUANTUM ALGORITHM FOR THE PERMANENT

2007 ◽  
Vol 05 (01n02) ◽  
pp. 223-228 ◽  
Author(s):  
ANNALISA MARZUOLI ◽  
MARIO RASETTI
Keyword(s):  
Field Theory ◽  
Quantum Field Theory ◽  
Quantum Computation ◽  
Quantum Computer ◽  
Quantum Algorithm ◽  
Topological Quantum Field Theory ◽  
Quantum Field ◽  
Topological Quantum

We resort to considerations based on topological quantum field theory to outline the development of a possible quantum algorithm for the evaluation of the permanent of a 0 - 1 matrix. Such an algorithm might represent a breakthrough for quantum computation, since computing the permanent is considered a "universal problem", namely, one among the hardest problems that a quantum computer can efficiently handle.

The Dawn of Quantum Information

2020 ◽  
pp. 258-270
Author(s):  
Gershon Kurizki ◽  
Goren Gordon
Keyword(s):  
Quantum Information ◽  
Large Scale ◽  
Quantum Computer ◽  
Quantum Algorithm ◽  
Single Step ◽  
Weather Forecasts ◽  
State Of Mind ◽  
Process Simulations ◽  
Superposition States ◽  
Quantum Revolution

Henry and Eve have finally tested their quantum computer (QC) with resounding success! It may enable much faster and better modelling of complex pharmaceutical designs, long-term weather forecasts or brain process simulations than classical computers. A 1,000-qubit QC can process in a single step 21000 possible superposition states: its speedup is exponential in the number of qubits. Yet this wondrous promise requires overcoming the enormous hurdle of decoherence, which is why progress towards a large-scale QC has been painstakingly slow. To their dismay, their QC is “expropriated for the quantum revolution” in order to share quantum information among all mankind and thus impose a collective entangled state of mind. They set out to foil this totalitarian plan and restore individuality by decohering the quantum information channel. The appendix to this chapter provide a flavor of QC capabilities through a quantum algorithm that can solve problems exponentially faster than classical computers.

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