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A variable behaving as a quantum in economic system is studied on the basis of quantum mechanics. The several formulas of relevant variable are derived along with this speculation. Thus a possible value for the common constant which may be understood as Planck constant in economic system is calculated. There, a concerned variable seems to exhibit a quantum behavior.
Recently it has been pointed out that there might be a similarity between the rational expectation hypothesis in economics and quantum mechanics, where their observers are both in respective systems. Nevertheless, on the other hand, the principle of uncertainty in economics has not yet been discovered so far. Therefore we will study on this problem by starting to formulate the basic equations respective which correspond to quantum mechanics. Here we pursue solely a behavior of certain representative variable with which an important econophysical quantity is newly introduced, and then discuss about Planck constant in economic system.


Quantum 2020

A variable behaving as a quantum in economic system

quantum behavior

principle of uncertainty

planck constant in economic system

The Institute of Physics and IOP Publishing, in partnership with the Chinese Physical Society (CPS) and the University of Science and Technology of China (USTC) are proud to have brought together the international quantum science community online for this inaugural conference.


Early career and leading researchers from universities, industry and government worldwide came together to share, learn and collaborate on the latest research and emerging areas of high interest across quantum science and technology. The broad themes covered by Quantum 2020 included:

Quantum communication;
Quantum computing and quantum simulation;
Quantum sensing, metrology and imaging;
Quantum information theory, software and algorithms;
Quantum foundations;
Quantum technology in industry.
The four-day event featured talks from world-renowned scientists, interactive poster sessions and two exciting panel discussions on the themes of Quantum Technology in Industry and Quantum Technology Programmes Around the World.


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poster

Relative quantum complexity is the measure of state distance between two quantum states. In quantum circuits, it could be argued as the number of fundamental quantum logic gates required to change the initial state of a quantum system to another state. From the Penrose diagrams of Ads/CFT black holes, it has been analyzed that the volume of black holes increases with time. The astounding similarity between the growth of quantum complexity and the volume of black holes is believed to be the fundamental postulate to quantize gravity. Here, we implement a simulation model to demonstrate the power of one clean qubit. We explicate how addition of one clean qubit could increase the uncomplexity of a maximally complex state. We explore the clean qubit computation in IBM quantum experience platform by designing the circuits and running them on IBM QASM simulator. This one clean qubit computation is realized for maximally complex five states made of single-, two-, three-, four-, and five-qubit systems and the results are discussed by comparing the power of one thermal photon on the accessible spacetime of an observer near the black hole horizon.

Simulation Model for complexity in Blackholes and demonstration of power of clean qubit using IBM QX

At present, the surface-electrode ion trap is an important device to realize large-scale and integrated quantum information processing. However, there are still a series of problems in the fabrication process of the surface-electrode ion trap, the biggest disadvantage is that the surface topography is difficult to control during the fabrication. The rougher the surface, the worse the electrical and trapping ability of the surface-electrode ion trap. Therefore, we propose a micro-nano technology to control topography of surface-electrode ion trap, which is suitable for the fabrication of most surface electrode ion traps. In addition, based on the proposed micro-nano technology of controlling surface topography, we give a method to fabricate surface electrode ion trap with specific surface roughness, and successfully fabricated surface electrode ion traps with roughness of 6.2 nm to 45 nm. Experiments have proved that the technology of controlling surface roughness is feasible and repeatable. By fabricating surface-electrode ion traps with different topogrphy, we may have a deeper understanding of the influence of surface roughness on the trap performance, especially in electrical performance, heating rate, ion trapping ability and other aspects.

Micro-nano technology for controlling the surface topography of thick film surface-electrode ion trap

A silicon wafer based platform consisting of quantum nano pillars is presented in terms of quantum sensing and imaging. The pillars can be fabricated on silicon wafers using plasma processing under chlorine atmosphere. The pillars so produced on silicon wafers are still crystalline and their surfaces can be smoothed under control. The density of the pillars is very high, that is ⁓1010 cm-2. They have a tapered like structure with tip ends of few atomic sizes, where quantum size effects are dominating optical properties, such as ultrafast radiative recombination down to femtosecond regime at blue spectral region, offering interesting applications of quantum information processing involving ultrafast optical switching. 
Quantum pillars form an interesting application platform for identifying of chemical and biological species. The ensemble of quantum pillars can accommodate related species for subsequent measurements using quantum qubit systems such as diamond NV centers. 


Silicon quantum pillars for quantum sensing and imaging

We estimate the influence of passive source side channels on the BB84 decoy-state protocol. We use additional degrees of freedom as a model of side channels to calculate secret key rates for the intercept-resend attack, the unitary individual attack, and the unitary collective attack. We use a connection between this model and the Hong-Ou-Mandel (HOM) visibility to show that for state-of-the-art sources, used in quantum key distribution (QKD), the presence of passive source side channels does not reduce the security of the protocol significantly.

Upper-bounding source side-channel attack on the BB84 decoy-state protocol

From academia to industry, the field of quantum technologies is highly collaborative as we enter the second quantum revolution. 
QURECA (Quantum Resources and Careers) aims to create a link between the different stakeholders in the quantum community through a common language, and to generate global opportunities with quantum technologies. QURECA provides a range of professional services, and the solution to the quantum workforce skills bottleneck: the first online platform for quantum training and resourcing.
One of the main reasons QURECA was created was to tackle the “quantum bottleneck” that our society is experiencing. A reason for this being that many PhD students and graduates in the field struggle to apply their skillset and understand how it can assist in their career development.
Whether you are looking for your ideal job, to enhance your skillset or to find out more about opportunities in quantum, discover how your expertise can be useful and how to start your quantum career path!

Careers in quantum technologies

A nonlinear phase shift is introduced to a Mach‐Zehnder interferometer (MZI), and we present a scheme for enhancing the phase sensitivity. In our scheme, one input port of a standard MZI is injected with a coherent state and the other input port is injected with one mode of a two‐mode squeezed‐vacuum state. The final interference output of the MZI is detected with the method of active correlation output readout. Based on the optimal splitting ratio of beam splitters, the phase sensitivity can beat the standard quantum limit and approach the quantum Cramér‐Rao bound (QCRB). The effects of photon loss on phase sensitivity are discussed. Our scheme can also provide some estimates for units of χ(3), due to the relation between the nonlinear phase shift and the susceptibility χ(3) of the Kerr medium.

Nonlinear phase estimation enhanced by an actively correlated Mach‐Zehnder interferometer

The problem of dynamical charge carriers in a nanowire double quantum dots system under the influence of Dresshaul, Rashba spin-orbit coupling and Zeeman energy is introduced for comprehensive quantum theory and semiquantum approximation. The energy eigenvalues via shifted 1/N expansion is calculated as a function of the roots corresponding to quantum states and the semiconductor nanowire double quantum dots parameters. We find out that the Coulomb energy decreases while the magneto-confining energy increases whilst the quantum state changes. The gallium arsenide nanowire double quantum dots is in good agreement with representation of the true ground state at all values of the resulting Dresselhaus and Rashba spin-orbit coupling parameters.

The understanding of spin-orbit effects in a nanowire double quantum dots system

Encoding discrete variables into qubits is an important task for applying quantum computing to combinatorial optimisation problems, both under the context of quantum annealing and gate model algorithms such as QAOA. Traditionally discrete variables are encoded by implementing a 'one hot' constraint on a set of qubits. I demonstrate that a superior method to encode such variables is to encode them as a domain wall on an Ising chain as discussed in [1]. I discuss how this method works and present numerical evidence for it's superior performance. As an extreme example, in some cases for quantum annealing using a domain wall encoding instead of one hot can have as much impact as completely re-engineering the hardware. I also discuss the cases in which unary encodings (one hot or domain wall) may be preferable to binary encodings or vice-versa. I further discuss how this encoding can be used in quantum simulation of field theories as discussed in [2]

[1] Chancellor N 2019 Quantum Sci. Technol. 4 045004 https://doi.org/10.1088/2058-9565/ab33c2

[2] Abel S, Chancellor N, Spannowsky M https://arxiv.org/abs/2003.07374 (see also: arXiv:2006.06003)

A domain wall encoding for quantum annealing and QAOA

Well-developed theoretical tools exist to analyse how quantum dynamics can solve computational problems by varying Hamiltonians slowly (adiabatically). However, relatively few tools exist for the opposite limit of rapid quenches, used in quantum annealing and quantum walks. We develop a theoretical understanding and several practical tools for this regime. By analysing various energy expectation values, we show that monotonic quenches will yield a better result on average than random guessing. By characterising local dynamics, we identify cases where rapid quenches will lead to a substantially improved numerical scaling. We then use these tools to develop heuristics for choosing control parameters.

The poster is based on the work in Callison et al, NJP 21 123022 (2019) and Callison et al, arXiv:2007.11599(2020). It offers an introduction to the framework of continuous-time quantum computing, and an explanation of where rapid quenches sit within it. Along with some useful examples, an outline of the theoretical understanding and tools we have developed are presented. Finally, some examples are shown to illustrate how to use the heuristic methods these tools provide; in particular, we show how to choose quantum walk hopping rates and rapid quench schedules.

An energetic perspective on rapid quenches in quantum annealing

The past few years have seen numerous attempts to leverage the power of deep networks to solve the quantum many-body problem, and neural representations of many body wavefunctions have proliferated. These prior applications of neural networks to quantum mechanics have sought representations of the wavefunction. However, there are several mathematically equivalent formulations of quantum mechanics, and hence alternative routes for the application of machine learning. 


We demonstrate how reinforcement learning may be used to solve problems in quantum mechanics via the path integral representation. In our work we provide a novel neural approach to many-body quantum mechanics that leverages optimal control to approximate the Feynman–Kac path measure. The drift of the quantum stochastic control process is chosen to match the distribution of paths in the Feynman–Kac (FK) representation of the solution of the imaginary time Schrodinger equation. This provides a variational principle that can be used for reinforcement learning of a neural representation and a new alternative to earlier deep learning approaches that start from the Schrodinger picture. Further, our approach learns an optimal importance sampler for the FK trajectories, providing a drop-in replacement for path integral Monte Carlo.


A variable behaving as a quantum in economic system

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