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How does the brain generate consciousness? The present paper is an attempt to answer this question from the perspective of the QBIT theory. In sum, the theory argues that the brain has a prior belief (P) about the stimulus that has caused a sensory representation (R) to be created in the brain. When the conditional entropy of P given R becomes less than zero, the brain becomes more than certain about (i.e. becomes conscious of) the stimulus. Conditional entropy can become negative (and thus the brain can become more than certain) only if the brain uses entangled quantum information in its computations. The QBIT theory suggests that, at the most fundamental level, consciousness is nothing but a special kind of entangled information. [ABSTRACT FROM AUTHOR]

Outlined is a proposal designed to culminate in the foundry fabrication of arrays of singly addressable quantum dot sources deterministically emitting single pairs of energy-time entangled photons at C-band wavelengths, each pair having negligible spin-orbit fine structure splitting, each pair being channeled into single mode pig-tail optical fibers. Entangled photons carry quantum state information among distributed quantum servers via I/O ports having two functions: the unconditionally secure distribution of decryption keys to decrypt publicly distributed, encrypted classical bit streams as input to generate corresponding qubit excitations and to convert a stream of quantum nondemolition measurements of qubit states into a classical bit stream. Outlined are key steps necessary to fabricate arrays of on-demand quantum dot sources of entangled photon pairs; the principles are (1) foundry fabrication of arrays of isolated quantum dots, (2) generation of localized sub-surface shear strain in a semiconductor stack, (3) a cryogenic anvil cell, (4) channeling entangled photons into single-mode optical fibers, (5) unconditionally secure decryption key distribution over the fiber network, (6) resonant excitation of a Josephson tunnel junction qubits from classical bits, and (7) conversion of quantum nondemolition measurements of qubit states into a classical bit. [ABSTRACT FROM AUTHOR]

In the field of cybersecurity, hackers often enter computer systems despite current security measures, owing to the huge amount of network traffic that makes intruder identification difficult. Differentiating between authorized traffic and abnormal data produced by Distributed Denial of Service (DDoS) attackers is still a major difficulty. This research provides a unique technique that uses Quantum Machine Learning (QML) to improve security protocols for secure communication between two parties. Our strategy enhances detection accuracy and speed by using the characteristics of quantum neural networks. The approach includes creating a dataset from network traffic patterns, preprocessing it, and then turning it into quantum bits via angle embedding. The research uses outlier analysis, min-entropy, and quantum state fidelity to distinguish between normal and abnormal data patterns. The dispersed randomness of network header data is measured using entropy, which aids in identifying security concerns. The suggested QML-based methodology outperforms conventional approaches and current models, including AMM-CNN and ANN models, with a detection accuracy of 99.87% for DDoS attacks. This advancement leads to more effective and secure communication networks. [ABSTRACT FROM AUTHOR]

Hexagonal boron nitride exhibits two types of defects with great potential for quantum information technologies: single-photon emitters (SPEs) and one-dimensional grain boundaries hosting topologically-protected phonons, termed as topologically-protected phonon lines (TPL). Here, by means of a simple effective model and density functional theory calculations, we show that it is possible to use these phonons for the transmission of information. Particularly, a single SPE can be used to induce single-, two- and qubit-phonon states in the one-dimensional channel, and (ii) two distant SPEs can be coupled by the TPL that acts as a waveguide, thus exhibiting strong quantum correlations. We highlight the possibilities offered by this material-built-in nano-architecture as a phononic device for quantum information technologies. [ABSTRACT FROM AUTHOR]

We introduce a new approach for describing nonstationary quantum systems with a discrete energy spectrum. The essence of this approach is that we describe the evolution of a quantum system in a time-dependent basis. In a sense, this approach is similar to the description of the system in the interaction representation. However, the time dependence of the basic states of the representation is determined not by the evolution operator with a time-independent Hamiltonian but by the eigenstates of the time-dependent Hamiltonian defined at the current time. The time dependence of the basic states of the representation leads to the appearance of an additional term in the Schrödinger equation, which in the case of slowly changing parameters of the Hamiltonian can be considered as a small perturbation. The adiabatic representation is suitable in cases where it is impossible to apply the standard interaction representation. The application of the adiabatic representation is illustrated by the example of two spins connected by a magnetic dipole–dipole interaction in a slowly varying external magnetic field. [ABSTRACT FROM AUTHOR]

Material discovery is a phenomenon practiced since the evolution of the world. The discovery of materials has led to significant development in varied fields such as Science, Engineering and Technology. Computationally simulating molecules has been an area of interest in the industry as well as academia. However, simulating large molecules can be computationally expensive in terms of computing power and complexity. Quantum computing is a recent development that can improve the efficiency in predicting properties of atoms and molecules which will be useful for material design. The Variational Quantum Eigensolver (VQE) is one such quantum algorithm used to calculate the ground state energy of molecules or ions. In this study, we have done a comparative analysis of the parameters that constitute the VQE algorithm. This includes components such as basis, qubit mapping, ansatz, and optimizers used. We have also developed a database consisting of 79 single atoms and their variations of oxidation states and 33 molecules with the data of their Hamiltonian and ground state energy and dipole moment. [ABSTRACT FROM AUTHOR]

Quantum phenomena, including entanglement, superposition, tunneling, and spin-orbit interactions, among others, are foundational to the development of recent innovations in quantum computing, teleportation, encryption, sensing, and new modalities of electronics, such as spintronics, spinorbitronics, caloritronics, magnonics, twistronics, and valleytronics. These emerging technologies provide disruptive influences to global commercial markets. These remarkable advances in quantum technologies are nearly always enabled by the discovery of materials and their quantum behaviors. Such advances are governed by quantum principles that are strongly influenced by environmental, physical, topological, and morphological conditions such as very small length scales, short time durations, ultrahigh pressures, ultralow temperatures, etc., which lead to quantum behaviors that manifest as quantum tunneling, entanglement, superpositioning, superfluidity, low-dimensional, high-temperature and high-pressure superconductivity, quantum fluctuations, Bose-Einstein condensates, topological effects, and other phenomena that are not yet fully understood nor adequately explored. Here, we provide a review of quantum materials developed up to 2023. Remarkable advances in quantum materials occur daily, and therefore, by the time of publication, new and exciting breakthroughs will have occurred that are regrettably not covered herein. [ABSTRACT FROM AUTHOR]

Shor's algorithm solves the elliptic curve discrete logarithm problem (ECDLP) in polynomial time. To optimize Shor's algorithm for binary elliptic curves, reducing the cost of binary field multiplication is essential because it is the most cost-critical arithmetic operation. In this paper, we propose Toffoli gate count-optimized, space-efficient (i.e., no ancilla qubits are used) quantum circuits for binary field ( (F 2 n) ) multiplication. To achieve this, we leverage the Karatsuba-like formulae and demonstrate that its application can be implemented without the need for ancillary qubits. We optimize these circuits in terms of CNOT gate count and depth. Building upon the Karatsuba-like formulae, we develop a space-efficient CRT-based multiplication technique utilizing two types of out-of-place multiplication algorithms to reduce the CNOT gate count. Our quantum circuits exhibit an extremely low Toffoli gate count of O (n 2 log 2 ∗ n) , where log 2 ∗ represents the iterative logarithmic function that grows very slowly. When compared to recent Karatsuba-based space-efficient quantum circuit, our approach requires only (10–25 %) of the Toffoli gate count and Toffoli depth for cryptographic field sizes in the range of n = 233–571. To the best of our knowledge, this represents the first successful utilization of the Karatsuba-like formulae and CRT-based multiplication in quantum circuits. [ABSTRACT FROM AUTHOR]

Measurement of a qubit (quantum bit) is a key element of quantum computation and is necessary for extracting information from a quantum processor. The physical implementation of a measurement protocol involves monitoring a physical quantity of a sensor, such as a current or a voltage, that is correlated with the state of the qubit to be measured. The monitoring of these sensors used to measure qubits in modern quantum computer architectures is typically divided between RF reflectometry and current/voltage monitoring. There are tradeoffs involved with both approaches for the reliable and accurate readout of qubits when it comes to scalable quantum computing architectures. In this article, we will review the working principles of a selection of sensors that are used to measure the state of qubits in semiconductors. The goal is to introduce electronic engineers with little or no background in quantum computing to the working principles of charge sensors in semiconductor quantum computers, their identification in various physical systems, and an overview of their design tradeoffs when measuring a qubit. This will allow electronic engineers to begin working with physics literature in the field of charge sensing. [ABSTRACT FROM AUTHOR]

Abstract In the field of cybersecurity, hackers often enter computer systems despite current security measures, owing to the huge amount of network traffic that makes intruder identification difficult. Differentiating between authorized traffic and abnormal data produced by Distributed Denial of Service (DDoS) attackers is still a major difficulty. This research provides a unique technique that uses Quantum Machine Learning (QML) to improve security protocols for secure communication between two parties. Our strategy enhances detection accuracy and speed by using the characteristics of quantum neural networks. The approach includes creating a dataset from network traffic patterns, preprocessing it, and then turning it into quantum bits via angle embedding. The research uses outlier analysis, min-entropy, and quantum state fidelity to distinguish between normal and abnormal data patterns. The dispersed randomness of network header data is measured using entropy, which aids in identifying security concerns. The suggested QML-based methodology outperforms conventional approaches and current models, including AMM-CNN and ANN models, with a detection accuracy of 99.87% for DDoS attacks. This advancement leads to more effective and secure communication networks.

Exploration of spin defects in semiconductors for possible qubits encourages the development of the quantum field. Silicon carbide (SiC) is a suitable platform to carry spin defects, due to its excellent electrical, mechanical and optical properties, together with its convenience for crystallographic growth and doping processes. In this study, a negatively charged phosphorus-vacancy (PCVSi−) defect, consisting of a silicon vacancy and nearby substitution of a phosphorus atom to a carbon atom in 4H–SiC, is investigated by first-principles calculations. This defect is demonstrated to possess a high spin (S = 1) with relatively low formation energy. Computed zero-phonon line energy and zero-field splitting parameters of this defect are close to those of neutral divacancy (VCVSi0), negatively charged nitrogen-vacancy center (NCVSi−) and some other color centers, which indicate a similarity of both optical and spin properties among them. Moreover, the electron spin coherence time of this defect turns out to be 1.15–1.40 ms. Such a long coherence time provides the defect with reliability for quantum information processing. Our results show that the PCVSi− defect can be a promising candidate for a qubit. [ABSTRACT FROM AUTHOR]

The paper presents a method for semantic data analysis by means of complex-valued matrix decomposition. The method is based on the quantum model of contextual decision-making, according to which observable probabilities are generated by qubit states, representing subjective meaning of the contexts relative to the basis decision. In the simplest three-context case, one of these qubits is decomposed to superposition of the remaining two, mathematically encoding semantic relations between the three contexts. For use in data analysis this model is translated to the matrix form, in which rows and columns correspond to the contexts and instances of experiment. The observable real-valued data then emerge from a complex-valued amplitude matrix, decomposed to a product of a real basis matrix and complex-valued matrix of superposition coefficients. This decomposition reveals stable process-semantic relations between the considered contexts, not captured by other methods of analysis. As a result, the data are approximated with higher precision and fewer parameters than singular and non-negative matrix decompositions, truncated to the same dimension. The model is experimentally approved in descriptive and prognostic regimes. The result opens prospects for development of nature-like computational architectures on novel logical grounds.

Superconducting niobium (Nb) thin films have recently attracted significant attention due to their utility for quantum information technologies. In the processing of Nb thin films, fluoride‐based chemical etchants are commonly used to remove surface oxides that are known to affect superconducting quantum devices adversely. However, these same etchants can also introduce hydrogen to form Nb hydrides, potentially negatively impacting microwave loss performance. Here, comprehensive materials characterization of Nb hydrides formed in Nb thin films as a function of fluoride chemical treatments is presented. In particular, secondary‐ion mass spectrometry, X‐ray scattering, and transmission electron microscopy reveal the spatial distribution and phase transformation of Nb hydrides. The rate of hydride formation is determined by the fluoride solution acidity and the etch rate of Nb2O5, which acts as a diffusion barrier for hydrogen into Nb. The resulting Nb hydrides are detrimental to Nb superconducting properties and lead to increased power‐independent microwave loss in coplanar waveguide resonators. However, Nb hydrides do not correlate with two‐level system loss or device aging mechanisms. Overall, this work provides insight into the formation of Nb hydrides and their role in microwave loss, thus guiding ongoing efforts to maximize coherence time in superconducting quantum devices. [ABSTRACT FROM AUTHOR]

Cornerstones of the Cellular Automaton Interpretation of Quantum Mechanics are its ontological states that evolve by permutations, in this way never creating would-be quantum mechanical superposition states. We review and illustrate this with a classical Ising spin chain. It is shown that it can be related to the Weyl equation in the continuum limit. Yet, the model of discrete spins or bits unavoidably becomes a model of qubits by generating superpositions, if only slightly deformed. We study modifications of its signal velocity which, however, do not relate to mass terms. To incorporate the latter, we consider the Dirac equation in 1+1 dimensions and sketch an underlying discrete deterministic "necklace of necklaces" automaton that qualifies as ontological. [ABSTRACT FROM AUTHOR]

The resonant microwave pulses have been shown to be able to create magnetization of high-spin (S ≥ 1) metal ions even in the absence of an external magnetic field. This transformation of the ion spin states is similar to the "alignment–orientation" transition in atomic spectroscopy. These manipulations make it possible to translate the results of elementary quantum computing operations performed in zero magnetic fields into physically observable quantities. [ABSTRACT FROM AUTHOR]

Quantum field lens coding algorithm (QF-LCA) dataset is useful for simulating systems and predict system events with high probability. This is achieved by computing QF lens distance-based variables associated to event probabilities from the dataset produced by field lenses that encode system states on a quantum level. The probability of a state transition (ST), doubles in prediction values at the decoding step, e.g., ST probabilities of P≥1/3 into P≥2/3 based on a single field (SF) transform into a quantum double-field (QDF). This transformation doubles the ST probability space via the field's scalar κ, in a published QDF method article. A QDF, as a double-field computation (DFC) model, simulates thermodynamic systems in predicting events by producing datasets from a QF-LCA, using laser cooling methods relative to high energy systems. The dataset can be used to, e.g., train quantum algorithms via quantum artificial intelligence (QAI) for a QF-LCA user. The user then decides after the algorithm predicts and suggests an efficient energy path for the system to choose. For example, an N-particle system simulated as a heat engine, by QAI classifier(s), predicts and reroutes particle energy paths on a logarithmic input-output scale. To determine system's energy change, the QDF lens code (DFC) measures entanglement entropy (EE). The algorithm's classification of EE values distinguishes entangled states in the system. The QF-LCA program employs the dataset to achieve an automated prediction and classification method, rather than dataset's manual use and analysis by the user. As the system evolves in its distribution of states, those particles not reaching a desired energy state (a target state or TS), i.e., the probability of observing a ground or excited state (GS or ES) outcome at the decoding step, can be rerouted by the heat engine to satisfy a TS outcome. This establishes a GS or ES energy profile to access and classify states by a classifier. The data points (qubits) in this profile are inverse distance-based and labelled for a specific class. After learning the profile, the classifier decodes and predicts the next system state. A QDF AI game “Alice & Bob's Quantum Doubles,” is developed to validate the dataset as the P’s map for a classical/quantum prediction where the P’s of states and the user's P’s correlate in their value difference, ΔP. Dataset validation results are mapped to an intelligent decision simulator (IDS) as a QAI map. This maximizes system efficiency on a TS by EE of energy states (distributed in the system). Future additions to the dataset from the QAI map program can improve quantum algorithms to determine which particles of the system participate in a phase transition after state prediction. QF-LCA applications are in data science, security, forensics, particle physics, etc., such as retrieving or reconstructing information by distinguishing particle states from an evidence sample. Examples are, reconstruct damaged DNA strands of cells to predict a virus's TS, or cancer cell, its spread and growth against healthy cells, identify forged documents from genuine based on QDF's P values, and so on.

ABSTRAK Pada artikel ini, teleportasi kuantum satu qubit dengan empat keadaan Bell sebagai kanal kuantum telah dikaji secara eksplisit. Empat keadaan Bell yang digunakan dinyatakan dalam bentuk kompak. Hasil kajian menunjukkan bahwa teleportasi kuantum satu qubit dengan empat keadaan Bell dapat dilakukan untuk mengirim informasi kuantum dari pengirim (Alice) ke penerima (Bob) setelah hasil pengukuran oleh Alice dikirim melalui kanal klasik. Untuk hasil pengukuran , dan dari setiap keadaan Bell , , pada persamaan 1, terdapat satu kemungkinan di mana Bob tidak perlu melakukan transformasi uniter untuk merekonstruksi qubitnya dan selebihnya Bob perlu melakukan transformasi uniter. Untuk keadaan Bell , Bob perlu melakukan transformasi uniter pada qubitnya dari setiap hasil pengukuran Alice. Kata kunci—Keadaan Bell, qubit, teleportasi kuantum. ABSTRACT In this article, one-qubit quantum teleportation with four Bell states as quantum channel has been studied explicitly. Four Bell states used are expressed in compact form. The result of study shown that one-qubit teleportation quantum with four Bell states can be carried out to send quantum information from the sender (Alice) to the receiver (Bob) after Alice’s measurement results are send via classical channel. For the measurement results are , dan from each Bell state , , in equation 1, there is one possibilty where Bob does not need to perform a unitary transformation to reconstruct his qubit and the rest Bob needs to perform a unitary transformation. For Bell state , Bob needs to perform a unitary transformation on his qubit from each of Alice’s measurements. Keywords—Bell state, qubit, quantum teleportation.

Quantum phenomena, including entanglement, superposition, tunneling, and spin–orbit interactions, among others, are foundational to the development of recent innovations in quantum computing, teleportation, encryption, sensing, and new modalities of electronics, such as spintronics, spin-orbitronics, caloritronics, magnonics, twistronics, and valleytronics. These emerging technologies provide disruptive influences to global commercial markets. These remarkable advances in quantum technologies are nearly always enabled by the discovery of materials and their quantum behaviors. Such advances are governed by quantum principles that are strongly influenced by environmental, physical, topological, and morphological conditions such as very small length scales, short time durations, ultrahigh pressures, ultralow temperatures, etc., which lead to quantum behaviors that manifest as quantum tunneling, entanglement, superpositioning, superfluidity, low-dimensional, high-temperature and high-pressure superconductivity, quantum fluctuations, Bose–Einstein condensates, topological effects, and other phenomena that are not yet fully understood nor adequately explored. Here, we provide a review of quantum materials developed up to 2023. Remarkable advances in quantum materials occur daily, and therefore, by the time of publication, new and exciting breakthroughs will have occurred that are regrettably not covered herein.

Advances in quantum information processing can open a way for numerous applications of the processing in various fields of science and technology: communication, precision measurement, computing, nano-scale detectors, and sensors. Classical and various quantum correlations have been studied in real spin 1/2 systems. The nonlocality measures provide a novel classification scheme for bipartite states, highlighting that nonlocality is a quantum resource distinct from other types of quantum correlations. We first studied the temperature and field dependencies of nonlocality measure in the three fictitious spin 1/2 system, which represents a nuclear spin-7/2 placed in magnetic and inhomogeneous electric fields. The relationship between nonlocality and other quantum correlations (entanglement and geometric discord) was studied. The Hamiltonian and spin operators for a spin 7/2 are represented in the basis formed by the Kronecker products of the Pauli matrices. This transformation allows us to represent a spin 7/2 as a system of three coupled fictitious spins 1/2 and, from the quantum information point of view, as an equivalent system of three coupling qubits. Well-developed methods were used to calculate measures of quantum correlations. For example, we consider 59Co (spin 7/2) in the compounds [Co(NH3)5Cl]Cl2 and Ca3Co2O6. The interaction between the fictitious spins of 59Co nuclei depends on the magnitude and direction of the external magnetic field. Other potential cases of quantum correlations can be realized based on nuclear spins 7/2 in solid-state systems, for instance, such as 51V, 165Ho, or 123Sb. [ABSTRACT FROM AUTHOR]

We analyze in detail a procedure of entangling of two singlet–triplet (S– T 0 ) qubits operated in a regime when energy associated with the magnetic field gradient, Δ B z , is an order of magnitude smaller than the exchange energy, J, between singlet and triplet states (Shulman et al. in Science 336:202, 2012). We have studied theoretically a single S– T 0 qubit in free induction decay and spin echo experiments. We have obtained analytical expressions for the time dependence of components of its Bloch vector for quasistatic fluctuations of Δ B z and quasistatic or dynamical 1 / f β -type fluctuations of J. We have then considered the impact of fluctuations of these parameters on the efficiency of the entangling procedure which uses an Ising-type coupling between two S– T 0 qubits. In particular, we have obtained an analytical expression for evolution of two qubits affected by 1 / f β -type fluctuations of J. This expression indicates the maximal level of entanglement that can be generated by performing the entangling procedure. Our results deliver also an evidence that in the above-mentioned experiment S– T 0 qubits were affected by uncorrelated 1 / f β charge noises. [ABSTRACT FROM AUTHOR]

Entanglement exhibits a unique property of quantum theory that is unseen in classical counterparts. The experimental confirmation of Bell's inequalities has surprised many people and revived interest and debate regarding the exact nature of quantum theory, including the wave-particle duality. On the other hand, rapid advancements in computing technology in recent years have provided a new tool for investigating the nature of quantum theory. In this paper, numerical simulation is used to visualize the nonlocality implied in quantum entanglement. In particular, a Gedanken experiment of a discrete approximation of a continuous quantum space is provided, similar to the case of the dual nature of particle/wave in the double-slit experiment. The results are expected to provide a different angle for a deeper understanding of the mysterious nature of quantum correlations. [ABSTRACT FROM AUTHOR]

The present publication considers implementing an online control proctoring system, with the possibility of using methods and models of pattern recognition using algorithmic quantum computing to conduct online exams. The study's object is the protection method within infrastructure proctoring systems in education. The study aims to create a security system for proctoring technology infrastructure in education. The article proposes an alternative approach to building protection systems with an effective recognition model using algorithmic quantum computing in proctoring platforms. This study addresses these issues and proposes a novel approach to generating a random cryptographic key using multimodal biometric technology. A presented quantum algorithm method for computer simulation of the data processing quantum principles allows studying and analysing how the created model for transforming a classical image into a quantum state works. This method also shows the possibilities of quantum information theory in interpreting classical problems or how to optimise the same, taking into account the development of methods for the functioning of models and algorithms for quantum computing, data protection and security of online video communications in a proctoring system in an educational environment. The novelty of this research is expressed primarily in the constant updating and addition of authentication systems using quantum computing in various aspects, including the proctoring system in the educational environment. The practical significance is due to the need in the current situation to attract attention to existing problems in structuring the infrastructure of a monitoring system within planning and coordinating the protection, thereby enhancing learning outcomes by eliminating security flaws using a quantum computing algorithm for pattern recognition. [ABSTRACT FROM AUTHOR]

Landauer's bound is applicable to irreversible quantum operations. In this study, we showcased that the Doppler temperature manifests the existence of Landauer's bound, which does not block a spin from (irreversibly) flipping with a tiny amount of energy via quantum tunneling. Verified by a spin–spin magnetic interaction experiment, this (energy) amount was determined to be only 1.25 times the theoretical value of Landauer's bound. Based on Heisenberg's principle, we defined information from a measuring perspective: one bit of information corresponds to the smallest error when quantifying the product of the measured energy uncertainty ( Δ E ) and the measured time duration ( Δ t ). We then illustrate an optically manipulated, spin-encoded, near-Landauer-bound, near-Heisenberg-limit quantum computer that encompasses this new definition of information. This study may represent the last piece of the puzzle in understanding both quantum Landauer erasure and Heisenberg's quantum limit since a single spin is the smallest information carrier. [ABSTRACT FROM AUTHOR]

Generalized 1 + 0-dimensional Liouvillean dynamics describing deformations of the Sachdev–Ye–Kitaev (SYK) model, as well as the various 1 + 1-dimensional dilaton and Horava–Lifshitz gravity theories, can all be mapped onto the single-particle quantum mechanics of a non-relativistic charge propagating in a (generally, curved) 2d space and subject to a (generally, non-uniform) magnetic field. The latter description sets a stage for the phenomenon of quantum Hall effect (QHE), thereby elucidating the intrinsically topological nature of the pertinent gravity theories and demystifying their (pseudo)holographic connection to a broad class of the SYK-like models. [ABSTRACT FROM AUTHOR]

Fast settling phase locked loops (PLLs) play a pivotal role in many applications requiring rapid attainment of a stable frequency and phase. In modern communication standards, these PLLs are extensively utilized to guarantee precise compliance with dynamic resource allocation requirements. In processors, these PLLs manage dynamic voltage frequency scaling. Moreover, the fast-settling PLLs expedite the scanning of frequency spectra in sophisticated electronic radar set-ups, proving particularly advantageous for imaging and scanning radar applications. The rapid response exhibited by these PLLs is also harnessed in quantum technologies, catering to the urgent need for precise frequency adjustments to manipulate qubit states effectively. The strategies employed to attain fast-settling PLLs are primarily classified into five broad techniques in this article: enhanced phase frequency detection, hybrid multiple subsystems, VCO start-up, gear shift, and look-up table or finite state machine. This article explores the fundamental operational principles encompassing these techniques and presents optimal settling times for each method reported in the literature. Finally, the architectures utilizing these techniques will be evaluated based on their figure of merit (FoM), settling time, and tuning range. [ABSTRACT FROM AUTHOR]

This article will review recent progress in cryogenic CMOS designs for future scaled quantum computing applications. After introducing the scaling challenges associated with qubit control and readout electronics operating at room temperature, approaches taken to date to cryogenic control electronics design will be discussed, focusing on the most recent relevant publications. Elements of ultra-low power circuit and system design approaches for cryogenic controllers in scaled CMOS nodes (40nm to 14nm) will be reviewed, including a discussion of current state-of-the art cryogenic controller performance and power efficiency. Note that leading designs, when operated as transmon qubit state controllers, have achieved gate error rates in the range of 10-4 to 10-3 achieving spurious free dynamic range (SFDR) of ~40dB while consuming 4-23mW of power per qubit under active control, with power efficiency strongly driven by the complexity of the digital processor integrated in the controller design. These demonstrations, while significant, are just the first steps toward achieving the performance, efficiency, and scalability that will be required for future systems. This review article will discuss fundamental tradeoffs in CMOS cryogenic designs in order to address the needs of future scaled quantum computing systems. [ABSTRACT FROM AUTHOR]

Quantum information processing leverages the principles of quantum mechanics, utilizing qubits, to improve computational and communicative tasks. In this realm, the quantum channel’s capacity is pivotal in determining the efficiency and accuracy of quantum information handling, with its performance being significantly influenced by channel noise. Our study aims to establish a holistic hybrid quantum noise model to determine the quantum channel capacity. In this paper, we formulated a mathematical expression for this capacity and conducted simulations for both Gaussian and non-Gaussian inputs. A hybrid noise model is constructed by convolution of Poisson-distributed quantum noise with classical additive white Gaussian noise. We characterized the quantum-classical noise and the received signal using Gaussian Mixture Models. The maximum amount of quantum information that can be reliably transmitted over a quantum channel (per use of the channel) is determined by its capacity, and entropy and related quantities like mutual information play a role in calculating this capacity. Our formulation of quantum channel capacity is derived from the mutual information shared between the transmitter and receiver, encompassing the entropies of the signals. The quantum channel presents a higher capacity-to-signal-to-noise ratio for Gaussian inputs than non-Gaussian ones.

A limited number of qubits, high error rates, and limited qubit connectivity are major challenges for effective near-term quantum computations. Quantum circuit partitioning divides a quantum computation into classical postprocessing steps and a set of smaller scale quantum computations that individually require fewer qubits, lower qubit connectivity, and typically incur less error. However, as partitioning generally increases the duration of a quantum computation exponentially in the required partitioning effort, it is crucial to select optimal partitioning points, so-called cuts, and to use optimal cut realizations. In this work, we develop the first optimal partitioning method relying on quantum circuit knitting for optimal cut realizations and an optimal selection of wire cuts and gate cuts that trades off ancilla qubit insertions for a decrease in quantum computing time. Using this combination, the developed method demonstrates a reduction in quantum computing runtime by 41% on average compared to previous quantum circuit partitioning methods. Furthermore, the qubit requirement of the evaluated quantum circuits was reduced by 40% on average for a runtime budget of one hour and a sampling frequency of 1 kHz. These results highlight the optimality gap of previous quantum circuit partitioning methods and the possible extension in the computational reach of near-term quantum computers.

We introduce a new approach for describing nonstationary quantum systems with a discrete energy spectrum. The essence of this approach is that we describe the evolution of a quantum system in a time-dependent basis. In a sense, this approach is similar to the description of the system in the interaction representation. However, the time dependence of the basic states of the representation is determined not by the evolution operator with a time-independent Hamiltonian but by the eigenstates of the time-dependent Hamiltonian defined at the current time. The time dependence of the basic states of the representation leads to the appearance of an additional term in the Schrödinger equation, which in the case of slowly changing parameters of the Hamiltonian can be considered as a small perturbation. The adiabatic representation is suitable in cases where it is impossible to apply the standard interaction representation. The application of the adiabatic representation is illustrated by the example of two spins connected by a magnetic dipole–dipole interaction in a slowly varying external magnetic field.

We analyze the results of the test of π/2 qubit rotations on a public quantum computer provided by IBM. We measure a single qubit rotated by π/2 about a random axis, and we accumulate vast statistics of the results. The test performed on different devices shows systematic deviations from the theoretical predictions, which appear at level 10-3. Some of the differences, beyond 5 standard deviations, cannot be explained by simple corrections due to nonlinearities of pulse generations. The magnitude of the deviation is comparable with the randomized benchmarking of the gate, but we additionally observe a pronounced parametric dependence. We discuss other possible reasons for the deviations, including states beyond the single-qubit space. The deviations have a similar structure for various devices used at different times, so they can also serve as a diagnostic tool to eliminate imperfect gate implementations and a faithful description of the involved physical systems. [ABSTRACT FROM AUTHOR]

Qutrit is a three-level quantum system with a higher level than qubits, which can process quantum information in a more complex state space. Therefore, in some information processing tasks, qutrits are more efficient than qubits. In this paper, we first briefly review the basic knowledge of qubit and extend it to the qutrit scenario. Then, the noiseless qutrit channel is given by simple extension, and the transmission characteristics between it and the noiseless qubit channel are discussed. Subsequently, we provided a three-dimensional version of the amplitude damping channel based on its construction method. In this paper we will refer to it as the noisy qutrit channel N (ρ) . Finally, we discuss the transmission characteristics of N (ρ) and the amplitude damping channel, as well as the expected fidelity and entanglement fidelity of N (ρ) . What's interesting is that we find whether it is a noisy channel or a noiseless channel, the qutrit channel can send qubit information, but the qubit channel cannot send qutrit information completely. The special case in which the qubit channel can send qutrit information completely is when the input qutrit state is | 0 ⟩ or | 1 ⟩ or a linear combination of | 0 ⟩ and | 1 ⟩ . [ABSTRACT FROM AUTHOR]

The quantum mechanical transition probability is symmetric. A probabilistically motivated and more general quantum logical definition of the transition probability was introduced in two preceding papers without postulating its symmetry, but in all the examples considered there it remains symmetric. Here we present a class of binary models where the transition probability is not symmetric, using the extreme points of the unit interval in an order unit space as quantum logic. We show that their state spaces are strictly convex smooth compact convex sets and that each such set K gives rise to a quantum logic of this class with the state space K. The transition probabilities are symmetric iff K is the unit ball in a Hilbert space. In this case, the quantum logic becomes identical with the projection lattice in a spin factor which is a special type of formally real Jordan algebra. [ABSTRACT FROM AUTHOR]

Since the mention of the Fourth Industrial Revolution in 2016, quantum computers and quantum computing (QC) have emerged as key technologies. Many researchers are trying to realize quantum computers and quantum computing. In particular, most of the development and application of metaheuristics algorithms using quantum computing is focused on computer engineering fields. Cases in which the developed algorithm is applied to the optimal design of a building or the optimal design results presented by expanding the algorithm in various directions are very insufficient. Therefore, in this paper, we proposed four methods of adopting qubits to perform pitch adjusting in the optimization process of the QbHS (quantum-based harmony search) algorithm and applied it to TTO (truss topology optimization) using four methods to compare the results. The four methods of adopting qubits have the same or decreased number of qubits adopted as the number of iterations changes. As a result of applying TTO using four methods, convergence performance differed depending on the adoption method, and convergence performance was superior to conventional HS (harmony search) algorithms in all methods. The optimal design of structural engineering using such QC is expected to contribute to the revitalization of future technologies in the architectural field and the field of computer information systems. [ABSTRACT FROM AUTHOR]