Papers

We investigate the combined effects of a brane intersecting the AdS boundary and background gravitational field on the local characteristics of the electromagnetic vacuum. Two types of boundary conditions on the brane are considered, which are higher-dimensional generalizations of the perfect electric (PEC) and perfect magnetic (PMC) boundary conditions in Maxwell's electrodynamics. The brane-induced contributions to the Wightman functions of the vector potential and field tensor are explicitly extracted. Simple expressions in terms of elementary functions are provided. The behavior of the vacuum expectation values (VEVs) is mimicked by a scalar field with a negative effective mass squared determined by the radius of the AdS spacetime. The expectation values of the electric and magnetic fields squares and of the energy-momentum tensor are investigated as local characteristics of the vacuum state. The brane-induced contributions to these VEVs have opposite signs for the PEC and PMC conditions. For the PMC condition, this contribution is negative for the electric field squared and positive for the magnetic field squared. The VEV of the energy-momentum tensor has a nonzero off-diagonal component. The brane-induced vacuum energy density is positive for PMC condition, whereas the normal and parallel stresses change sign as functions of the distance from the brane. Unlike the problem involving a planar boundary in the Minkowski bulk, the vacuum energy-momentum tensor does not vanish in (3+1)-dimensional AdS spacetime.

Conventional quantum thermometry assumes completely positive (CP) encoding maps, where the probe is initially uncorrelated with the environment. We consider realistic scenarios with initial probe-environment correlations leading to physically realizable non-completely positive (NCP) encoding, and show how such encodings can significantly impact temperature estimation of the environment. We first consider pure entangled probe-environment initial states (Type-I NCP encoding) and analytically show that for probes and environments of equal but arbitrary dimension, the maximum achievable precision matches the thermal-state bound, as in the CP case. However, upon relaxing the constraint of pure probe-environment states and considering general correlated initial states (Type-II NCP encoding), we demonstrate that the estimation precision can surpass the thermal-state limit. This establishes a clear advantage of NCP encoding in enhancing thermometric performance. We illustrate the results using qubit probes interacting with qubit environments via XY interactions.

Quantum batteries harness non-classical resources, such as quantum coherence and entanglement, to surpass the performance limits of classical energy-storage devices. Here we realize a room-temperature quantum battery based on a collective atomic spin ensemble in a thermal alkali-metal vapor, containing approximately $10^{12}$ $^{87}$Rb atoms with coherence times exceeding 110 ms. We operationally determine the battery capacity by directly measuring the extremal internal energies accessible under unitary evolution. This tomography-free protocol agrees closely with the conventional state-based definition and verifies the decomposition of capacity into coherent and incoherent contributions. We further show that quantum coherence can substantially enhance the storage capability independently of level populations, and experimentally establish quantitative relations linking battery capacity to von Neumann, Tsallis and linear entropies. By introducing a controlled dephasing channel with a magnetic-field gradient, we observe a monotonic reduction of capacity with coherence loss and track the corresponding evolution of the entropy-capacity relations. Our results identify thermal atomic spin ensembles as a scalable platform for quantum batteries and connect macroscopic quantum energy storage with operational quantum thermodynamics.

Quantum Neural Networks (QNNs) represent a promising direction within Quantum Machine Learning (QML), yet their realization on noisy intermediate-scale quantum (NISQ) devices remains constrained by decoherence, gate imperfections, crosstalk, and readout errors. This study provides a systematic evaluation of noise effects and mitigation strategies in hybrid quantum neural networks (HQNNs). Zero-Noise Extrapolation (ZNE), Digital Dynamical Decoupling (DDD), and Layerwise Richardson Extrapolation (LRE) are incorporated into end-to-end QNN training pipelines developed with PennyLane, simulated using Qiskit Aer noise models, and integrated with the Mitiq framework, while Probabilistic Error Cancellation (PEC) is evaluated separately under depolarizing noise due to its computational cost. Experiments conducted on the Iris dataset with five representative noise channels show that the impact of noise and the effect of mitigation are strongly dependent on the noise model and its strength. The model maintains comparatively strong performance under phase-flip and phase-damping noise, while substantial degradation is observed under high depolarizing and amplitude-damping noise. Across the evaluated mitigation methods, the observed benefits remain limited and noise-dependent: ZNE, DDD, and LRE generally follow the same degradation trends as the unmitigated baseline, while PEC shows limited gains only in the low-noise depolarizing regime. These findings highlight the need for context-specific mitigation strategies to improve the robustness of QNNs in practical NISQ settings.

Relativistic extensions of de Broglie-Bohm theory postulate a preferred foliation of space-time, an additional structure essential for defining simultaneous configurations on Minkowski space-time, but conventionally believed to be empirically undetectable at quantum equilibrium. In this paper, we outline an experimental protocol for empirically detecting the preferred foliation, which is assumed to be flat for simplicity. Building on the arrival-time distributions for spin-1/2 particles predicted by Das and Dürr, we show that in an EPRB-type experiment with spacelike-separated spin and arrival-time measurements, the observed arrival-time statistics will depend crucially on the temporal order of these measurements relative to the preferred foliation of space-time. This dependence offers a potential experimental signature of the preferred foliation postulated by relativistic Bohmian models. Moreover, it implies the possibility of superluminal signaling.

This work aims to address the bottleneck issues of hardware resource limitation and decoherence error in the Hamiltonian simulation of quantum fluids, which are caused by the standard quantum Fourier transform and the evolution of momentum operators, resulting in excessively deep circuits and excessive two-qubit gates. We propose an approximate operator optimization scheme aimed at reducing the circuit depth in Hamiltonian evolution. The proposed scheme successfully reduces the depth of analog circuits from $O(n^2)$ to $O(nlogn)$ or even $O(n)$ by eliminating $O(n^2)$ redundant two-qubit entangling gates. In this work, the numerical experiments are implemented on a supercomputing-oriented quantum simulator, simulating two-dimensional unsteady divergent flow. Experimental results demonstrate that although the truncation of high-frequency qubit coupling terms introduces deterministic theoretical errors, scaling at $O(n)$ for AQFT and $O(n^2)$ for momentum truncation, the optimized simulations successfully preserve the inherent macroscopic temporal evolution characteristics of the fluid in a 10-qubit simulation, achieving high correlation coefficients of $r$=0.933, $r$=0.941, and $r$=0.977 for density, X-momentum, and Y-momentum distributions respectively. Furthermore, we also analyzed the relationship between the algorithm truncation error and the hardware cumulative noise when the qubit number is extended to a higher level. This study proves that rationally adjusting truncation thresholds can establish an equilibrium point, preventing the hardware cumulative error from rapidly approaching 100% at the 20-30 qubit scale, providing a feasible engineering pathway for simulating complex fluid systems on real quantum devices in the future.

We present a quantum-dynamical framework for identifying structurally important residues in proteins based on continuous time quantum walks (CTQWs) on weighted residue interaction networks constructed from experimentally resolved structures. By mapping the weighted adjacency matrix to a Hamiltonian, residue importance emerges from the long-time averaged occupation probability, confirmed analytically through its spectral decomposition. Across a dataset of approximately 150 proteins spanning diverse structural and functional classes, CTQW centrality exhibits consistently strong agreement with classical eigenvector centrality in identifying central residues, while extending beyond it through incorporating signatures of quantum interference. Analyzing the time-averaged quantum transition matrix reveals consistently larger spectral gaps than the classical random-walk operator. Furthermore, biological relevance is confirmed through recovery of experimentally established functional residues in proteins kinase A and oxytocin. CTQW-derived centrality rankings are accessible on near-term intermediate-scale quantum hardware, as we demonstrate through a proof-of-principle implementation on IBM superconducting quantum hardware. These results establish continuous-time quantum walks as a computationally tractable framework for protein network analysis, that connects network theoretical treatments of protein structural biology to continuous-time quantum walk dynamics.

Small modular nuclear reactors (SMRs) are redefining the energy generation landscape by enabling the deployment of modular, scalable, and pre-built power units that can be used to build distributed autonomous microgrids for critical infrastructure and burgeoning AI factories. Often, these microgrids are linked together to provide a resilient, decentralized power generation infrastructure. Consequently, the cybersecurity of microgrids is of critical importance. In this work, we propose a quantum augmented network framework for resilient microgrids. We integrate the ideas of secure quantum networking, quantum anonymous notification, and quantum random number generation to strengthen the integrity, confidentiality, and privacy of microgrid networks. To substantiate the possible benefits of using quantum augmented microgrids, we simulate a practical high-impact classical attack: a traffic analysis and priority-action spoofing campaign that can (1) deanonymize the anonymous notification for a high-priority action, (2) force excessive key usage, and (3) induce harmful allow/block operations at the control level. We quantify how these attacks affect information leakage, spoof acceptance, key sufficiency, and operational outcomes such as latency, deadline misses, unserved energy, etc. This quantum augmented microgrid (QuAM) framework lets us evaluate trade-offs between privacy, availability, and the operational cost of mitigation (cover traffic, verification delays, and key-rotation policies), further paving the path for the study of more nuanced attacks that arise due to the use of quantum-classical integrated frameworks.

A Single-Photon Detector (SPD) can detect extremely low intensity of electromagnetic wave - down to a single photon. Driven by the rapid developments in quantum information science and an increasing demand for ultra-low-light sensing across various domains, there is a need for transformative advancements in the design and development of SPDs. In this context, low-dimensional platforms, including quantum dots, superconducting nanowires and layered materials have emerged as crucial frontiers of research. This review explores the state-of-the-art of different low-dimensional SPD platforms, focusing on the engineering physics across their device architectures, performance parameters and application potential. By critically comparing the performance and addressing current challenges inherent to each low-dimensional platform, the review aims to outline future research directions to advance next-generation SPD technologies.

Quantum imaginary-time evolution (QITE) is a fundamental framework for preparing ground and thermal states, yet its computational cost scales significantly with the evolution duration $\tau$. Reducing this duration is critical for practical quantum advantage. Here, we establish a unified theoretical framework for the Mpemba effect in QITE – a counterintuitive phenomenon where a state initially farther from the ground state relaxes to it faster than one initially closer. We derive a remarkably simple necessary and sufficient condition for the occurrence of this effect, showing it is uniquely determined by the population ratios of excited states to the ground state. For practical state preparation, we introduce a rigorous sufficient condition for the finite-time Mpemba effect, ensuring the crossing occurs before reaching a prescribed proximity threshold. Furthermore, we unveil unique dynamical features, including a multiple-crossing phenomenon in multi-level systems and simultaneous intersections for collinear initial states. Our results provide criteria for identifying favorable initial states in QITE and offer deep insights into the speed limit of quantum state preparation.

How many black-box queries to a quantum channel are needed to learn its full classical description? This question lies at the heart of quantum channel tomography (also known as quantum process tomography), a fundamental task in the characterization and validation of quantum hardware. Despite extensive prior work, the optimal query complexity for quantum channel tomography is far from fully understood. In this paper, we study tomography of an unknown quantum channel with input dimension $d_1$, output dimension $d_2$, and Kraus rank at most $r$, to within error $\varepsilon$. We identify the dilation rate $\tau = r d_2 / d_1$ (which always satisfies $\tau\geq 1$ due to the trace preservation of quantum channels) as a key parameter, and establish that the optimal query complexity of channel tomography exhibits distinct scaling laws across three regimes of $\tau$. - In the boundary regime ($\tau = 1$): we show that the query complexity is $\Theta(r d_1 d_2/\varepsilon)$ for Choi trace norm error $\varepsilon$, and is upper bounded by $O(\min\{r d_1^{1.5} d_2/\varepsilon, r d_1 d_2/\varepsilon^2\})$ and lower bounded by $\Omega(r d_1 d_2/\varepsilon)$ for diamond norm error $\varepsilon$. - In the away-from-boundary regime ($\tau \geq 1+\Omega(1)$): we show that the query complexity is $\Theta(r d_1 d_2/\varepsilon^2)$ for both Choi trace norm and diamond norm errors $\varepsilon$. Our results uncover a sharp Heisenberg-to-classical phase transition in the query complexity of quantum channel tomography: at $\tau=1$, the optimal query complexity exhibits Heisenberg scaling $1/\varepsilon$, whereas for $\tau\geq 1+\Omega(1)$, it exhibits classical scaling $1/\varepsilon^2$. In addition, we show that in the near-boundary regime ($1< \tau < 1+o(1)$), the query complexity exhibits a mixture of Heisenberg and classical scaling behaviors.

Altermagnetism, known for its non-relativistic spin-split band structures with yet compensated moments, is being intensively investigated. Discovering new altermagnetic materials with characteristics suitable for practical use remains an important ongoing task. Recently a metallic room-temperature altermagnet candidate Rb1-xV2Te2O with a layered structure and d-wave spin symmetry has been reported based on experimental results from the spin-resolved photoemission spectroscopy and scanning tunnelling microscopy/spectroscopy (STM/STS) measurements. Here we report neutron powder diffraction (NPD) investigations on the magnetic structure of Rb1-xV2Te2O, which shows a G-type antiferromagnetic structure below the transition temperature of 337 K. The result is different from the original theoretical expectation, which might lead to new insights on the physics of this altermagnet candidate.

Reliable quantum computation requires fault-tolerant protocols to prevent errors from propagating during syndrome extraction in quantum error correction. We present a novel fault-tolerant syndrome extraction technique for CSS codes, which we refer to as the cut-cat state scheme. While each ancilla qubit interacts non-fault-tolerantly with a pair of data qubits, we introduce additional cat stabilizer measurements to identify and correct the resulting hook errors. Our approach maintains the key benefit of cat-based extraction, i.e., parallelized data qubit interactions, while reducing the number of simultaneous qubits required by more than half. Compared to flag-based state-of-the-art protocols, the cut-cat scheme offers a notable advantage in terms of two-qubit gate count as the code distance increases.

Quantum Noise Characterization (QNC) is indispensable for benchmarking and mitigating errors in Noisy Intermediate-Scale Quantum (NISQ) devices. However, traditional Quantum Process Tomography (QPT) suffers from an exponential parameter explosion, severely hindering its scalability. In this paper, we propose a Hierarchical Progressive Optimization (HPO) framework to efficiently extract high-order spatial crosstalk in multi-qubit systems. The complexity analysis shows that the combinatorial projection mask reduces the required number of Pauli transfer matrix (PTM) elements from O($16^N$) to O($N^2 3^N$). Numerical simulations on a 10-qubit HHL circuit achieve a fidelity of 0.9381 with the HPO method, compared to 0.7431 obtained using global depolarizing-noise mitigation.

Within the present noisy intermediate-scale quantum-computing era, hybrid quantum-classical-processor algorithms have emerged as promising avenues for tackling electronic-structure eigenproblems. Among them, the so-called ensemble-variational quantum eigensolver has been designed to treat ground and excited states on an equal footing and proven effective in capturing features such as conical intersections and avoided crossings between two electronic states, as we recently demonstrated for formaldimine. We also showed on that example how the underlying ensemble-variational principle was prone to provide a quasi-diabatic representation "for free". To date, this method has been limited to computing only two eigenstates of a Hamiltonian. The aim of the present paper is to show how and under what conditions this can be generalized to models that involve three coupled electronic states or more. Our approach relies on designing a parameterized basis transformation that can directly be implemented on a quantum computer for further post-treatment. This nontrivial step is accompanied by the development of quantum circuits specifically adapted to the several states of interest. An algebraic optimization strategy for the parameters of the basis transformation is formulated to obtain the target eigenstates as well as the optimally diabatic states under various objective flavors of the ensemble-variational principle. Our approach was tested for addressing the first three coupled electronic states of the H$_4^+$ molecular ion as a proof of principle, with three electrons in four spatial orbitals, along various geometries.

Practical utilization of Gottesman-Kitaev-Preskill (GKP) qubits requires not only the preparation of logical basis states, but also the ability to prepare and evaluate arbitrary logical qubit superpositions. Currently, this is typically done via quantum state tomography, which is resource-intensive. We introduce a family of positive semidefinite Hermitian operators, one for each point on the logical Bloch sphere, whose unique zero-eigenvalue ground states are the corresponding ideal GKP qubit states. We show that the expectation value of each operator serves as a witness of non-Gaussianity, and corresponds to twice the logical infidelity for states in the ideal logical GKP subspace. Furthermore, the truncated finite-dimensional counterparts of these operators yield physical approximations of arbitrary logical GKP states as their ground states. The evaluation of the proposed operators requires only three quadrature measurements, making this framework practical for both the experimental characterization and numerical optimization of GKP state preparation circuits.

Stark-localized quantum probes have recently been shown to enable quantum-enhanced weak-field sensing with polynomial or super-polynomial scaling. In this paper, we show that the spatial geography of the encoded field can elevate this advantage to a genuine exponential scaling. We study a one-dimensional Stark probe subject to an exponential gradient profile, \(V_j=e^{aj}\), and analyze its metrological performance in both equilibrium and non-equilibrium regimes, for single-particle and interacting many-body settings. In the equilibrium single-particle case, we derive an analytical lower bound showing that the quantum Fisher information grows exponentially with system size, and confirm numerically that this enhancement persists throughout the extended phase and at the localization transition. We further show that the same exponential scaling survives for mid-spectrum eigenstates and in the interacting many-body regime. This advantage remains intact under a fair resource analysis because the relevant preparation gap closes only algebraically, so the polynomial preparation overhead cannot offset the exponential gain in sensitivity. In the non-equilibrium regime, a simple product-state initialization followed by free evolution already retains exponential enhancement, eliminating the need for cooling, adiabatic preparation, or operation within a narrowly tuned sensing window. Finally, we outline a superconducting implementation based on flux-tunable transmon qubits with graded mutual inductive coupling to a common sensing bus. Our results identify exponentially graded Stark potentials as a distinct and experimentally plausible route to weak-field sensing with exponentially improving precision.

Advancement in quantum information and quantum technologies has ushered in a new era of technological revolution in large scale atomistic simulation and efficient system on a chip device fabrication. This has led to innovative ways of harnessing rigorous search algorithms for functional quantum materials and steered scientists to dig deeper into the world of quantum phenomenon and applications. In this work, we delineate the advanced electronic structure and vibrational properties utilizing the popular meta-GGA functionals, spectral signatures of the Raman active phonon modes, explored their average mean free paths, and whether they conserve helicity, by leveraging first principles density functional theory and density functional perturbation theory. A systematic analysis of the role of phonon lifetimes, consequences of phonon-phonon and three phonon scattering rates and phonon linewidths have been presented. Further, a study of the the frequency and temperature dependent Gruneisen parameter has been employed in conjecture with the temperature dependent thermal expansion and thermal conductivity to portray the effect of anharmonicity in the phonon spectra of these two materials. Finally, we provide strategies for tuning the properties of these materials in an effort to improve their efficacy for advanced thermoelectric, photovoltaic and optoelectronic device applications.

Various classical machine learning models, including linear regression, kernel methods, and deep neural networks, exhibit double descent, in which the test risk peaks near the interpolation threshold and then decreases in the overparameterized regime. However, this phenomenon has received less attention in the quantum setting. In this work, we investigate the double descent phenomenon in quantum kernel ridge regression (QKRR). By applying deterministic equivalents from random matrix theory (RMT), we derive an asymptotic expression for the test risk of QKRR in the high-dimensional limit. Our analysis rigorously characterizes the interpolation peak and reveals how explicit regularization can effectively suppress it. We corroborate our theoretical results with numerical simulations, demonstrating close agreement even for finite-size quantum systems.

Detecting coherence transfer in complex quantum networks can be challenging due to uncharacterized experimental conditions and limited system access. Here, we use static and dynamic coherence features to introduce a nonlinear criterion for identifying coherence transfer. The criterion requires only two measurement settings for network-state populations in an experimental state basis, regardless of the network's size. It remains valid even when the verification capabilities of checkpoint nodes are uncharacterized. The principle and method are general, encompassing networks with different access levels and scenarios, from those requiring no input changes to those involving coherence dynamics in the time domain. Experimentally, using remote state preparation and entanglement swapping, we transfer single polarization qubits and polarization-entangled pairs in four- and six-photon entanglement networks. The criterion provides experimental evidence of coherence transfer in multi-photon entanglement networks. Our findings offer a practical tool for coherence transfer in quantum information and open quantum systems in networks.

We introduce map-dependent quantum characteristic functions constructed from the normalized Choi operator of quantum dynamical maps. We prove a Bochner–Choi positivity theorem establishing that the positive-type condition of the associated Gram matrix is equivalent to complete positivity of the underlying quantum channel. Applying the construction to intermediate dynamical maps, we obtain a characterization of CP-divisibility in terms of positivity of two-time characteristic functions. Numerical examples for amplitude damping and pure dephasing models demonstrate that negativity of the Gram matrix coincides with the breakdown of CP-divisibility and the emergence of information backflow. The proposed framework provides a new bridge between characteristic-function methods in quantum statistics and structural properties of quantum dynamical maps.

Quantum dots are nanometer-scale semiconductor particles that exhibit size-dependent quantum mechanical properties. In this work, we investigate the dynamics of quantum correlations, quantified by the concurrence and the quantum coherence, in a bipartite system of coupled double quantum dots. The analysis is carried out within both Markovian and non-Markovian regimes, and further extended to different noisy quantum channels, including amplitude damping, phase flip, and phase damping. Our results show that environmental memory plays a crucial role in the preservation of quantum correlations, leading to oscillatory behavior and partial revivals in the non-Markovian regime, in contrast to the monotonic decay observed under Markovian dynamics. Moreover, distinct decoherence mechanisms induce qualitatively different effects: dissipative channels rapidly suppress correlations, while phase-based channels lead to either redistribution or gradual degradation. A key finding is that quantum coherence exhibits a higher robustness compared to entanglement under all considered conditions, highlighting its relevance as a reliable quantum resource in noisy environments. These results provide valuable insights into the control and protection of quantum correlations in realistic solid-state systems.

Periodic driving plays a central role in quantum control, but its application in interacting spin systems is often restricted to near-resonant conditions, where standard averaging techniques remain valid. Here we investigate how detuning from resonance can be used to dynamically spin-lock a dipolar-coupled ensemble. We show that the combination of offset and pulse structure generates an effective Rabi field with sharply structured amplitude and tilt. This behavior - supported by a semi-analytical framework, numerical simulations and experiment - enables new approaches to many-body system control, here exemplified via offset-induced reversible interconversion of Zeeman and dipolar order, and heterospin polarization transfer away from rf-field matching conditions. Further, we leverage artificial-intelligence-assisted sequence design to explore regimes with long control cycles - where average Hamiltonian theory breaks down, but effective locking persists - opening pathways to rich offset-dependent responses. These findings position offset-enabled dynamic locking as a promising tool for quantum sensing, energy transfer, and spin-order manipulation beyond traditional approaches.

We develop an exact theory of coherence-selective stroboscopic resetting for quadratic open quantum systems within the single-particle density-matrix formalism. We focus on the survival of coherences and the associated thermodynamic cost at the stroboscopic fixed point. To this end, we introduce a one-parameter family of reset channels that continuously interpolates between complete coherence erasure and complete coherence preservation. This unifies the reset-map description, the repeated-interaction and evolving-correlation endpoint channels, and the thermodynamic cost of environmental reinitialization. For a single fermionic level coupled to a structured semi-infinite tight-binding bath, we derive the exact affine stroboscopic map, solve for its unique fixed point, and compute the retained coherence spectrum, the post-reset occupation, and the reset heat current. We find that retained coherence increases monotonically with the retention parameter, whereas the reset heat current is generically nonmonotonic and is maximized at an intermediate operating point. Thus the protocol that stores the most coherence is not the one that dissipates the most heat. Exact operating diagrams further show that coherence-optimal and coherence-per-cost-optimal protocols are both driven toward the coherence-preserving endpoint, while the heat-optimal protocol depends strongly on the reset interval. We also show that this coherence-cost geometry survives at nonzero chemical potential as a filling-biased deformation of the same fixed-point tradeoff, rather than as an independent particle-current optimization problem. These results establish coherence-selective resetting as a distinct control principle for structured-bath open quantum systems and provide an exactly solvable benchmark for memory engineering and thermodynamic optimization under repeated environmental reinitialization.

As physical systems, qubits must evolve from input to output state. We describe a simple scheme in which the effect of a quantum gate is described by the action of an effective Hamiltonian acting for some characteristic time. This model shows that the action of common unary gates is to induce Bloch sphere trajectories along lines of latitude relative to an eigenvector of the gate. Such trajectories would immediately move a `rebit', initially confined to a line of latitude, off this line and acquire a complex phase. The role of the complex phase in bringing about the entanglement of two qubits is also highlighted. It is then asked whether such dynamics could be modelled using real QM. It is shown that the continuous evolution required for such dynamics can only be provided by members of the special orthogonal group of the vector space. Since the matrices representing many quantum gates of interest have determinant -1, no real special orthogonal operators can model their evolution if the dimension of the real vector space is the same as that of the complex space. Next we look at the mapping from a complex vector space of dimension $N$ to a real space of dimension $2N$ that is often used to construct `real' QM. It is shown that this is just an isomorphic mapping from the scalar representation of complex numbers to their $2\times2$ matrix equivalents, so that the resulting matrices are actually represent complex matrices. Finally, we investigate the endomorphism of real vector spaces of dimension $N = 2^{n}$, where $n \in \mathbb{Z}^{+}$, suitable for the modelling of $n-1$ qubits. We confirm that the mapping from $\mathbb{C}^{2^{n-1}} \to \mathbb{R}^{2^{n}}$ only maps elements of $\mathrm{End}(\mathbb{C}^{2^{n-1}})$ to a restricted subspace of $\mathrm{End}(\mathbb{R}^{2^{n}})$ that reproduces the `real' representation of complex matrices.

Retarded support, upper-half-plane holomorphy, and Hardy boundary control are distinct properties of a memory kernel. We give sufficient conditions linking them for the Nakajima–Zwanzig kernel of an open system with finite-dimensional system Liouville space. If the projected kernel has an absolutely continuous real-axis representation with density w in L1 intersect Lp0, no singular part, and p0 > 1, its transform lies in the operator-valued Hardy class Hp(B) for 1 < p <= p0. A finite-dimensional componentwise argument yields the corresponding principal-value and once-subtracted Kramers–Kronig (KK) boundary formulas; the H1 endpoint is separate. Microscopic unitary evolution gives holomorphy and a trace-norm bound for reduced-state transforms for arbitrary trace-class initial states, without that spectral hypothesis. On a common analytic domain, a perturbative force-fit equation has a first-order quotient pole at a simple baseline state-transform zero zeta only when the first-order inhomogeneous numerator I_tilde^(1)(zeta) is nonzero; at finite perturbation the actual zero and numerator must be checked, while matrix reconstructions additionally require adjugate non-cancellation. For rational reconstructions, the printed local or global clearing and no-cancellation hypotheses convert a rational kernel pole into a genuine upper-half-plane propagator pole. Such a pole is incompatible with a uniformly bounded CPTP family when the transforms agree on an open set, with Vieta's formula giving the imaginary-part budget. We formalize these paper-specific implications in Lean 4 from named classical inputs. A finite Jaynes–Cummings calculation provides a shifted, distributional KK check with a 0.024 percent fixed-truncation residual.

Single photon emitters (SPEs) are integral parts of several quantum technology implementations. Over the past decade or so, monolayers of transition metal dichalcogenides (TMDCs) have emerged as one of the promising candidates for SPE platforms with attractive characteristics. To move ahead, it is necessary to understand the atomistic origin of SPEs in TMDCs - a topic which is highly debated with contradicting proposals. In this paper, we critically review these existing proposals to elucidate their origin. Further, we perform a critical trend analysis for different figures of merit of TMDC-based SPEs, and propose a characterization methodology to streamline the reporting process. Finally, we review several quantum technology implementations where solid state SPEs are being used, and identify the advancements required in TMDC-based SPEs for their successful adoption in these technologies.

In this work, we develop a theoretical description of the collective behavior of interacting dipolar planar rotors by using time independent perturbation theory and a small angle quadratic approximation. The ground state properties for both the ordered and disordered quantum phases of the system are directly calculated and analyzed. Time-independent perturbation theory is shown to be appropriate for the disordered phase. For the ordered phase, we construct a quadratic approximation based on the stable equilibrium configurations of the dipolar ordering; we show that the inclusion of the quartic terms from the expansion of the potential energy are essential to correct the shift in the energy spectrum due to quantization ambiguities. Numerical techniques such as Exact Diagonalization and Density Matrix Renormalization Group are used for the benchmark the quality of both approximations.

Recently, Pang et al reported a novel polarization transfer scheme applicable to three-spin systems, whereby a rotating-frame NMR analogue of the cross effect could transfer polarization between; e.g., two 13Cs and an 15N in a single crystal. The present work furthers this scheme to the case of powder NMR under magic angle spinning (MAS) conditions, as well as to solution NMR. It is found that in all such cases a second-order average Hamiltonian can transfer polarization between non-equivalent, coupled abundant spins (e.g., two 1Hs) prepared in anti-longitudinal magnetization states, and the spin-locked magnetization of a rare spins (e.g., one 13C). The average Hamiltonian for such three-spin (S1-S2) to I transfer was derived for both liquids and solids, and found in good quantitative agreement with numerical simulations and experiments. At an optimal transfer condition whereby an I-spin RF irradiation field matches the S1-S2 chemical-shift-difference, a maximum polarization enhancement equal to the ratio of gyromagnetic ratios is achieved; as explained and demonstrated in the study, ca. half of this can be effectively obtained for I = 13C in powdered solids and in multi-spin systems in solutions. All such processes display an oscillatory nature, meaning that the transverse spin-locked polarization of a rare spin can become anti-longitudinal magnetization of abundant spins -without ever pulsing on the latter. The roles played by many-body interactions, RF inhomogeneities, and interferences of other coherences during the execution of these novel forms of cross-polarization were investigated, and are exemplified with experiments and simulations.

Recent work investigated the use of Stimulated Brillouin Scattering (SBS) to measure changes in fiber parameters, thereby enhancing the security of a Quantum Key Distribution (QKD) system. In this work, we focus solely on the impact of quantum technology on the task of intrusion-detection. We derive an effective input-output model for the SBS interaction, and utilize it to compare three detection methods: First, the established state of the art. Second, a photon-counting based method which will likely be available in the near future and, finally, the ultimate quantum limit. We illustrate the potential benefit from modern quantum technology within two different mathematical frameworks: First by using the quantum error exponent of asymmetric hypothesis testing, and second in the context of parameter-estimation and quantum metrology.