Papers

We present a resource-efficient method based on repetitive weak measurements to directly measure the noise spectrum of a generic quantum environment that causes qubit phase decoherence. The weak measurement is induced by a Ramsey interferometry measurement (RIM) on the qubit and periodically applied during the free evolution of the environment. We prove that the measurement correlation of such repetitive RIMs approximately corresponds to a direct sampling of the noise correlation function, thus enabling direct noise spectroscopy of the environment. Compared to dynamical-decoupling-based noise spectroscopy, this method can efficiently measure the full noise spectrum with the detected frequency range not limited by qubit coherence time. This method is also more resource-efficient than the correlation spectroscopy, as for the same detection accuracy with $N$ sampling times, it takes total detection time $O(N)$ while the latter one takes time $O(N^2)$. We numerically demonstrate this method for both bosonic and spin baths.

Recently, Ai, Cruz, Garbrecht, and Tamarit (arXiv:2001.07152, arXiv:2404.16026, arXiv:2511.04216) claimed that the strong CP problem can be avoided by adopting a particular order of limits in the Euclidean path integral, in which the spacetime volume is taken to infinity before summing over all topological sectors. We critically examine this proposal using exactly solvable examples of one-dimensional quantum mechanics on a ring, namely the quantum rotor and the quantum pendulum. These systems provide fully controlled settings with known $\theta$-dependent spectra. We find that the ACGT procedure fails to reproduce the correct energy spectrum. Since the spectrum is a direct physical observable, this result demonstrates that the proposed order of limits cannot be justified and conclusions about CP conservation in QCD cannot be based on this prescription alone.

Approximating the permanent of a complex-valued matrix is a fundamental problem with applications in Boson sampling and probabilistic inference. In this paper, we extend factor-graph-based methods for approximating the permanent of non-negative-real-valued matrices that are based on running the sum-product algorithm (SPA) on standard normal factor graphs, to factor-graph-based methods for approximating the permanent of complex-valued matrices that are based on running the SPA on double-edge normal factor graphs. On the algorithmic side, we investigate the behavior of the SPA, in particular how the SPA fixed points change when transitioning from real-valued to complex-valued matrix ensembles. On the analytical side, we use graph covers to analyze the Bethe approximation of the permanent, i.e., the approximation of the permanent that is obtained with the help of the SPA. This combined algorithmic and analytical perspective provides new insight into the structure of Bethe approximations in complex-valued problems and clarifies when such approximations remain meaningful beyond the non-negative-real-valued settings.

The rapid growth of modern machine learning (ML) models presents fundamental challenges in parameter efficiency and computational resource requirements. This study introduces the Quantum Recurrent Unit (QRU), a novel quantum neural network (NN) architecture specifically designed to address these challenges while remaining compatible with Noisy Intermediate-Scale Quantum (NISQ) devices. QRU leverages quantum controlled-SWAP (C-SWAP; Fredkin) gates to implement an information selection mechanism inspired by classical Gated Recurrent Units (GRUs), enabling selective processing of temporal information via quantum operations. Through its innovative recurrent architecture featuring measurement results feedforward state propagation and shared parameters across time steps, QRU achieves constant circuit depth and constant parameter count regardless of input sequence length, effectively circumventing stringent NISQ hardware constraints. We systematically validate QRU through three progressive experiments: (1) oscillatory behavior prediction, where 72-parameter QRU matches 197-parameter classical GRU performance; (2) Wisconsin Diagnostic Breast Cancer classification, where 35 parameters achieve 96.13% accuracy comparable to 167-parameter artificial NNs; and (3) MNIST handwritten digit recognition, where 132 parameters reach 98.05% accuracy, outperforming a 27,265-parameter convolutional NN. These results demonstrate that QRU consistently achieves comparable or superior performance with significantly fewer parameters than classical NNs while maintaining constant quantum circuit depth. The architecture's quantum-native design, combining C-SWAP-based information selection with novel recurrent processing, suggests QRU's potential as a fundamental building block for next-generation ML systems, offering a promising pathway toward more efficient and scalable quantum ML architectures.

Quantum annealing is a promising approach for solving combinatorial optimization problems. However, its performance is often limited by the overhead of additional qubits required for embedding logical QUBO models onto quantum annealers. This overhead becomes severe when logical QUBO models have dense connectivity. Such dense structures frequently arise when formulating equality and inequality constraints. To address this issue, we propose a method to construct a significantly sparser logical QUBO model for these constraints. By adding auxiliary variables based on specific network structures, our approach decomposes the original constraint into smaller, more manageable constraints. We demonstrate that this method reduces the number of edges (quadratic terms) from $O(N^2)$ to $O(N)$ for the one-hot constraint and to $O(N\log N)$ in the worst case for general equality constraints, where $N$ is the number of variables. Experimental results on D-Wave's hardware show that our formulation leads to substantial reductions in the number of qubits required for embedding, shorter average chain lengths, lower chain break rates, and higher feasible solution rates compared to conventional methods. This work provides a practical tool for efficiently solving constrained optimization problems on current and future quantum annealers.

We demonstrate that a two-polariton blockade (2PB) can occur under resonant single-polariton driving in an atom-cavity system operating in the ultrastrong coupling (USC) regime-a phenomenon qualitatively distinct from, and unattainable in, both the strong and weak coupling regimes. In the USC regime, where the ratio of the atom-cavity coupling strength to the cavity resonance frequency exceeds 0.1, hybrid light-matter quasiparticles known as polaritons emerge. By employing modified second- and third-order correlation functions appropriate for the USC regime, we predict the emergence of 2PB, characterized by pronounced two-polariton bunching accompanied by suppressed three-polariton coincidences. This Letter introduces a novel route to achieving 2PB, with promising implications for the realization of multiparticle quantum light sources in the USC regime.

Drug-drug interactions (DDIs) strongly affect the safety and efficacy of combination therapies. Despite the availability of large DDI databases, selecting optimal multi-drug combinations that balance safety, therapeutic benefit, and regimen size remains a challenging combinatorial optimization problem. Here, we present a quantum-control-based framework for DDI-aware drug combination optimization, in which known harmful and synergistic interactions are encoded into Ising Hamiltonians as penalties and rewards, respectively. The optimization is performed using the feedback-based quantum algorithm FALQON, a gradient-free variational approach. We study two clinically motivated tasks: the Maximum Safe Subset problem and the Synergy-Constrained Optimization problem. Numerical simulations using interaction data from Drugs.com and SYNERGxDB demonstrate efficient convergence and high-quality solutions for clinically relevant drug sets, including COVID-19 case studies.

Variational Quantum Algorithms are a vital part of quantum computing. It is a blend of quantum and classical methods for tackling tough problems in machine learning, chemistry, and combinatorial optimization. Yet as these algorithms scale up, they cannot escape the barren-plateau phenomenon. As systems grow, gradients can vanish so quickly that training deep or randomly initialized circuits becomes nearly impossible. To overcome the barren plateau problem, we introduce a two-stage optimization framework. First comes the convex initialization stage. Here, we shape the quantum energy landscape, the Hilmaton landscape, into a smooth, low-energy basin. This step makes gradients easier to spot and keeps noise from derailing the process. Once we have gotten a stable gradient flow, we move to the second stage: nonconvex refinement. In this phase, we let the algorithm wander through different energy minima, making the model more expressive. We show that our proposed algorithm theoretically reduces the dependence on the condition number of the underlying quantum least squares approximate matrix via Riemannian manifold optimization. Finally, we used our two-stage solution to perform quantum cryptanalysis of quantum key distribution protocol (i.e., BB84) to determine the optimal cloning strategies. The simulation results showed that our proposed two-stage solution outperforms its random initialization counterpart.

Current quantum neural networks suffer from extreme sensitivity to both adversarial perturbations and hardware noise, creating a significant barrier to real-world deployment. Existing robustness techniques typically sacrifice clean accuracy or require prohibitive computational resources. We propose a hybrid quantum-classical Differentiable Quantum Architecture Search (DQAS) framework that addresses these limitations by jointly optimizing circuit structure and robustness through gradient-based methods. Our approach enhances traditional DQAS with a lightweight Classical Noise Layer applied before quantum processing, enabling simultaneous optimization of gate selection and noise parameters. This design preserves the quantum circuit's integrity while introducing trainable perturbations that enhance robustness without compromising standard performance. Experimental validation on MNIST, FashionMNIST, and CIFAR datasets shows consistent improvements in both clean and adversarial accuracy compared to existing quantum architecture search methods. Under various attack scenarios, including Fast Gradient Sign Method (FGSM), Projected Gradient Descent (PGD), Basic Iterative Method (BIM), and Momentum Iterative Method (MIM), and under realistic quantum noise conditions, our hybrid framework maintains superior performance. Testing on actual quantum hardware confirms the practical viability of discovered architectures. These results demonstrate that strategic classical preprocessing combined with differentiable quantum architecture optimization can significantly enhance quantum neural network robustness while maintaining computational efficiency.

We develop a first-order Feshbach-Villars (FV) Hamiltonian framework for spin-0 relativistic quantum dynamics in the presence of Planck-scale kinematic deformations described within generalized doubly special relativity (G-DSR). Starting from a generic nonlinear momentum-space map, we derive the corresponding modified dispersion relation (MDR) at leading order in the Planck length \(l_p\) and construct a consistent FV linearization of the deformed Klein-Gordon operator. The resulting two-component Hamiltonian remains \(\sigma_3\)-pseudo-Hermitian at \(\mathcal{O}(l_p)\), which guarantees conservation of the FV charge and current and provides a current-based definition of reflection and transmission in stationary scattering. As applications, we study two benchmark settings in which the FV metric structure is essential: (i) the one-dimensional Klein-Gordon oscillator and (ii) scattering from electrostatic step and barrier potentials. For the oscillator, we obtain controlled \(\mathcal{O}(l_p)\) branch-resolved spectral shifts and show how kinetic versus mass-shell deformations reshape the level spacing and the high-energy spectral compression. For step and barrier scattering, we compute reflection and transmission coefficients directly from the pseudo-Hermitian FV current and quantify the deformation-induced shift of the supercritical (pair-production) threshold. A comparative analysis of the Amelino-Camelia and Magueijo-Smolin realizations indicates that MS-type deformations generally delay the onset of the supercritical regime and reduce the magnitude of the negative transmitted flux within the validity domain \(l_p E \ll 1\).

We investigate periodically impulsive fractional relaxation as a minimal model of nonlocal dissipative dynamics under repeated external stimulation. The free relaxation law is classical, but the driven problem introduces an additional timescale whose competition with the intrinsic fractional-memory scale generates nontrivial accumulation and crossover behavior. We derive the exact Laplace-domain and time-domain responses, establish the sparse-forcing scaling of the long-time averaged response, and obtain an analytical crossover interval proportional to the inverse fractional power of the relaxation coefficient. To separate established properties of Mittag–Leffler relaxation from the new effects of forcing, we explicitly compare the unforced, impulsive, and periodically driven settings. Extended long-time simulations verify the algebraic tail, while an independent L1 discretization provides a numerical benchmark for the exact solution. We further connect the relaxation kernel to measurable frequency-domain quantities through the Cole–Cole complex susceptibility and discuss interpretations in dielectric and viscoelastic relaxation, anomalous transport, non-Markovian open systems, and intermittent reinforcement. The resulting framework supplies an analytically solvable reference model for memory accumulation under repeated driving. The present analytical framework therefore provides a bridge between fractional relaxation theory and experimentally accessible time- and frequency-domain observables.

We present a rigorous and complete security proof of the decoy-state BB84 quantum key distribution (QKD) protocol. Our analysis aims to achieve a high standard of mathematical rigour and completeness, thereby providing the necessary foundation for certification and standardization efforts. Beyond establishing the security of a specific protocol, this work develops a general and modular framework that can be readily adapted to a broad class of QKD protocols, including both prepare-and-measure and entanglement-based variants. Our framework unifies all major ingredients required for the analysis of realistic QKD protocols, including the analysis of classical authentication and classical processing, source-replacement schemes, finite-size analysis, source maps, squashing maps, and decoy-state techniques. In doing so, this work consolidates a diverse range of techniques scattered across the QKD literature into a unified formalism, representing a general and rigorous treatment of QKD security. Finally, it outlines a clear path towards incorporating practical imperfections within the same framework, thereby laying the groundwork for addressing implementation security in future analysis.

Block encodings of non-unitary matrix functions are central to quantum numerical linear algebra. Hamiltonian simulation is a natural input model for Hermitian matrices, but accurate block encodings often incur large subnormalization. We decouple the accuracy from the subnormalization by formulating the matrix-function block encoding as a Fourier-extension approximation problem, yielding a linear combination of unitaries for Hermitian matrix inputs. Fourier extensions approximate non-periodic functions by a Fourier series on a larger periodic domain, creating redundant coefficients that can be optimized for their absolute sum, and hence subnormalization. The coefficients may be chosen for optimal subnormalization with algebraic convergence, by tuning the subnormalization bound for increasing rates of exponential convergence, or by Sobolev-regularized fitting to accommodate more general spectral sets. Fourier-extension block encodings apply to eigenvalue transforms of Hermitian matrices, or to odd singular-value transforms of general matrices, including as a quantum linear systems algorithm.

We develop a dynamical framework for quantum measurement based on stochastic but unitary evolution in projective state space. Random Hamiltonians drawn from the Gaussian Unitary Ensemble generate stochastic unitary dynamics of the quantum state, while equivalence classes reflecting finite detector resolution define classical observables as well as classical configuration-space and phase-space submanifolds. When the evolution is constrained to the phase-space submanifold, free Schrödinger dynamics reduces to Newtonian motion, while stochastic motion constrained to the classical configuration-space submanifold yields ordinary Brownian motion in classical space. Transition probabilities under the stochastic dynamics satisfy the Born rule, whereas the constrained classical evolution produces the normal probability distributions characteristic of classical measurements. We show that, in this setting, measurement, state reduction, and the quantum-classical transition emerge from unitary dynamics alone, without invoking nonunitary collapse or additional postulates. Entanglement and EPR correlations arise geometrically from the evolution of joint states in composite state space, preserving locality in spacetime. The framework provides a unified dynamical account of measurement and classicality compatible with the structure of quantum mechanics.

Quantum Key Distribution (QKD) protocols rely on authenticated classical communication. Typical QKD security proofs are carried out in an idealized setting where authentication is assumed to behave honestly: it never aborts, and all classical messages are delivered faithfully with their original timing preserved. Authenticated channels that can be constructed in practice have different properties. Most critically, such channels may abort asymmetrically, such that only the receiving party may detect an authentication failure while the sending party remains unaware. Furthermore, an adversary may delay, reorder, or block classical messages. This discrepancy means that existing security proofs under honest authentication do not directly establish security in the practical authentication setting. We address this gap using an existing security definition from the literature that permits asymmetric aborts while retaining secrecy of any key produced and agreement of the keys whenever both parties accept. Our main result is a reduction theorem showing that, under mild and easily satisfied protocol conditions, any QKD protocol proven secure under the honest authentication setting, for the standard security definition with symmetric aborts, remains secure under a practical authentication setting, for the weaker security definition that allows for asymmetric aborts. This result allows all existing QKD proofs to be retroactively lifted to the practical authentication setting (with asymmetric aborts) with a minor protocol tweak.

The paper relates to a quantum radar deployment by the Born-Feynman path integrals approach based on quantum dots. The radar system comprises a quantum dot-based entangled photon generator, a transmission module, a delay line, a detection module, and a signal processing unit. The quantum dot-based entangled photon generator produces entangled photon pairs via spontaneous parametric down-conversion or stimulated emission. The signal transmission module, equipped with a microwave antenna and beamforming elements, directs the signal photon toward a target. The delay line module synchronizes the retained idler photon with the returning signal photon, preserving quantum coherence. The detection module collects the reflected signal photon and uses a cryogenically cooled superconducting nanowire single photon detector (SNSPD) for detection. Finally, the signal processing unit analyzes the quantum correlation between the scattered and idler photons to enable precise quantum state comparison.

In the standard circuit model, elementary gates are defined relative to a chosen tensor factorization and are therefore extrinsic to the ambient group $U(2^n)$. Writing $N=2^n$, we introduce an intrinsic descriptor layer in $U(N)$ by declaring as primitive the motions inside faithful embedded copies of $SU(2)$ (phase-free), together with a phase-inclusive $U(2)$ variant. We describe the embedding landscape $\Emb(SU(2),U(N))$ as a finite union of $U(N)$-homogeneous strata indexed by isotypic multiplicities, with stabilizers given by centralizers, and we isolate a canonical two-level sector parameterized by $\Gr_2(\C^N)$ up to a $PSU(2)$ gauge. Equipping $U(N)$ with the Hilbert–Schmidt bi-invariant metric, each embedded subgroup is totally geodesic, yielding a variational characterization of elementary motions via minimal-norm logarithms. On the constructive side, we prove phase-free universality in $SU(N)$ from two-level primitives using QR/Givens factorizations together with explicit diagonal generation, and we obtain full universality in $U(N)$ by explicit abelian phase bookkeeping (equivalently, via the $U(2)$ two-level dictionary). Finally, we formalize a modular finite-alphabet compilation interface: any approximation routine in $SU(2)$ (e.g.\ Solovay–Kitaev) can be lifted through two-level embeddings to yield $U(N)$-level synthesis with global operator-norm error control.

We give a rigorous and self-contained analysis of the Grover–Rudolph quantum state-preparation algorithm, which encodes a probability distribution $\{p_k\}$ as an $n$-qubit amplitude state $\sum_k\sqrt{p_k}\ket{k}$ via a hierarchy of controlled $\RY$ rotations determined by a dyadic refinement of the target. We formalize the dyadic probability tree, derive the trigonometric factorization of conditional masses, and prove by induction that the circuit prepares exactly the desired measurement law. We further prove that perturbing each rotation angle by at most $\eta$ changes the output distribution by at most $\min(1,n\eta)$ in total variation, and combine this with a Hoeffding concentration bound to obtain an explicit design rule: $b\ge\log_2(2n\pi/\varepsilon)$ bits and $S\ge 2^{n+1}\log(2/\delta)/\varepsilon^2$ shots suffice to achieve accuracy $\varepsilon$ with confidence $1-\delta$. As a circuit-theoretic complement, we provide an ancilla-free transpilation of each stage into $\{\RY(\cdot),X,\CNOT\}$ via Gray-code ladders and a Walsh–Hadamard angle transform.

The entanglement entropy (EE) of any bipartition of a pure state can be approximately expressed as a sum of entanglement links (ELs). In this work, we introduce their exact extension, i.e. the entanglement hyperlinks (EHLs), a type of generalized mutual informations defined through the inclusion-exclusion principle, each of which captures contributions to the multipartite entanglement that are not reducible to lower-order terms. We show that any EHL crossing a factorized partition must vanish, and that the EHLs between any set of blocks can be expressed as a sum of all the EHLs that join all of them. This last result allows us to provide an exact representation of the EE of any block of a pure state, from the sum of the EHLs which cross its boundary. In order to illustrate their rich structure, we discuss some explicit numerical examples using ground states of local Hamiltonians. The EHLs thus provide a remarkable tool to characterize multipartite entanglement in quantum information theory and quantum many-body physics.

In the first part of the paper we study a perturbative model of the Rabi system of Quantum Optics. We are therefore able to describe, through Rellich's theory, an analytic expansion of finite families of eigenvalues, of arbitrary fixed length. In particular, we prove that for finite families of eigenvalues the Braak conjecture holds. In the second part we study the asymptotics of the Weyl spectral counting function of a class of systems that generalize the Quantum Rabi Model to an $N$-level atom ($N\geq3$) with $n=N-1$ cavity modes of the electromagnetic field, with particular interest in the case $N=3$ and $n=2$.

Colour centres in silicon have great potential as single photon sources for quantum technologies. Some of them - like the T centre - also possess optically-active spins that enable spin-photon interfaces for generating entangled photons and multi-spin registers. This paper explores the generation of several types of colour centres in silicon for mass-manufacturable silicon-on-insulator quantum devices. We investigate how different processes in the device development affect the presence of the quantum emitters, including thermal annealing and fabrication steps for optical nanostructures. The study reveals coupled formation dynamics between different colour centres, identifies optimal parameters for annealing processes, and reports on the sensitivity to annealing duration and nanofabrication procedures for photonic integrated circuits. Furthermore, we discern stable optical signals from colour centres in silicon which have not been identified before.

Building on the relativistic Hamiltonian of Sonnleitner and Barnett arXiv:1806.00234 and its post-Newtonian extensions by Schwartz and Giuilini arXiv:1908.06929, we investigate composite atomic systems in dynamical gravitational backgrounds. Using a local inertial frame and a perturbed Minkowski metric, we derive curvature-dependent corrections to both center-of-mass and internal Hamiltonians for atoms interacting with weak gravitational waves. The resulting Hamiltonian contains distinct curvature couplings modifying the internal potential and affecting the center-of-mass dynamics. These contributions imply that internal-energy variations do not always reduce to mass renormalization and can induce genuine forces due to changes in momentum. The initial research was motivated by anomalous friction-like forces emerging in quantum optics, and clarified that the anomalous forces are mere relativistic corrections from mass-energy equivalence. Our results suggest that, with increasingly sensitive detectors, additional forces from gravitational wave interactions may become visible in future experiments.

Quantum interferometers offer phase measurement capabilities that surpass the standard quantum limit (SQL), with phase sensitivity and quantum enhancement factor serving as key performance metrics. However, practical implementations face severe degradation of both metrics due to unavoidable losses, representing the foremost challenge in advancing quantum interferometry toward real-world applications. To address this challenge, we propose a coherent-amplifier-empowered quantum interferometer. The coherent amplifier dramatically suppresses the decay of both sensitivity and quantum enhancement under high-loss conditions, maintaining phase sensitivity beyond the original SQL even for losses exceeding 90%. Using an injected 4.2 dB squeezed-vacuum state in experimental demonstration, our scheme reduces the quantum enhancement degradation under 90% loss from 3.7 dB in a conventional quantum interferometer (CQI) to only 1.5 dB. More importantly, the phase sensitivity degradation under the same loss is limited to 4.0 dB, markedly outperforming the 11.2 dB degradation observed in a CQI. This improvement is enabled by the coherent amplifier's phase-sensitive photon amplification and its protection of the quantum state. This breakthrough in amplifier-empowered quantum interferometry overcomes the critical barrier to practical deployment, enabling robust quantum-enhanced measurements in lossy environments.

Quantum Machine Learning(QML) is developed by combining quantum mechanics principles with classical machine learning techniques in a hybrid framework that can give faster, exponential, more efficient power of quantum computing with the data driven intelligence. Quantum illumination(QI) is the quantum mechanical technique along with analysis of light matter interaction from source to detection end that connects quantum principle to hardware implementation. Superposition and entanglement control are deeply needed for the information-qubit processing in quantum computing. Improvement of measurement and performance are directly linked to detecting weak signal or intensity. This paper motivated that using quantum-enhanced technique how we can analysis previous superposition of qubit state which can clearly analyzed quantum interference diffraction patterns and its superposition using double slit experiment. Then constructed quantum neural network back propagation technique such that can give information of qubit position in any previous superposition state. Which is very import for any quantum optimization and search algorithm.

Quantum tunneling is analyzed within the Everettian interpretation, where decoherence generates distinct reflected and transmitted branches. The tunneling probability is obtained from relative branch weights via the Born rule without invoking collapse. Tunneling time \(\tau_T \) is reformulated as the branching duration \(\tau_T \sim N_B \tau_B\), where\(\ N_B \) is the number of environmental degrees of freedom and \(\tau_B\) is the decoherence time required to distinguish branches. Macroscopic tunneling in Josephson junctions is also analyzed.

We provide an operational interpretation of the multivariate Rényi divergence in terms of economic-theoretic tasks based on betting, risk aversion, and multiple lotteries. We show that the multivariate Rényi divergence $D_{\underline{\alpha}}(\vec{P}_X)$ of probability distributions $\vec{P}_X =(p^{(0)}_X,\dots,p^{(d)}_X)$ and real-valued orders $\underline{\alpha} = (\alpha_0, \dots, \alpha_d)$ quantifies the economic-theoretic value that a rational agent assigns to $d$ lotteries with odds $o^{(k)}_X \propto (p_X^{(k)})^{-1}$ ($k=1,\dots,d$) on a random event described by $p^{(0)}_X$. In particular, when the odds are fair and the rational agent maximises over all betting strategies, the economic-theoretic value (the isoelastic certainty equivalent) that the agent assigns to the lotteries is exactly given by $w^{\mathrm{ICE}}_{\underline{R}}=\exp[D_{\underline{\alpha}}(\vec{P}_X)]$, where $\underline{R}=(R_1,\dots,R_d)$ is a risk-aversion vector with $R_k = 1+\alpha_k/\alpha_0$ being the risk-aversion parameter for lottery $k$. Furthermore, we introduce a new conditional multivariate Rényi divergence that characterises a generalised scenario where the agent uses side information. We prove that this new quantity satisfies a data processing inequality which can be interpreted as the increment in the economic-theoretic value provided by side information; crucially, such a data processing inequality is a consequence of the agent's economic-theoretically consistent risk-averse attitude towards every lottery and vice versa. Finally, we apply these results to the resource theory of informative measurements in general probabilistic theories (GPTs). By establishing quantitative connections between information theory, physics, and economics, our framework provides a novel operational foundation for quantum state betting games with multiple lotteries in the realm of quantum resource theories.

Quantum cryptographic conferencing (QCC) allows multiple parties to establish common secure keys in quantum networks with information-theoretic security. However, the secure transmission distances of current QCC implementations are still limited to the metropolitan areas. Here, we experimentally demonstrate the three-intensity phase-matching (PM) QCC protocol considering finite-size effects by employing frequency-locking and phase-tracking techniques for three parties. The key distribution capability of the PM QCC protocol is demonstrated in the symmetric fiber channels with the distance from each party to the measurement site up to 100 km. The network adaptability of the PM QCC protocol is demonstrated in asymmetric fiber channels used to simulate fiber channel configurations in real networks. Thus, the feasibility of applying the PM QCC protocol to practical intercity quantum networks with both symmetric and asymmetric channels is verified.

We investigate the estimation of dephasing-induced decoherence in continuous-variable quantum systems using non-Gaussian probe states. By purifying the open system, we identify optimal probes, specifically squeezed cat and symmetric squeezed compass states, via quantum Fisher information. These results are in agreement with numerical simulation. In settings where the intra-cavity field is inaccessible and standard measurements are impractical, utilizing an ancilla approach where a qubit traverses or interacts with the cavity field, leading to measurement of the qubit, hence allowing estimation of the dephasing rate via Wigner function reconstruction or less costly marginal distribution.

The question of when the Kirkwood-Dirac quasiprobability serves as the most appropriate description for quantum measurements has remained unresolved, particularly across different measurement strengths. While known to generate anomalous weak values in the weak measurement regime and to reduce to classical probabilities under projective measurement, the physical mechanism governing its continuous transformation has been lacking. Here we demonstrate that the KD quasiprobability provides a general framework for all measurement regimes by identifying pointer-induced decoherence as the universal mechanism controlling this transition. We show that the decoherence factor F(t) simultaneously quantifies the loss of quantum coherence and interpolates the measurement strength from weak to strong. Within this framework, the KD quasiprobability naturally deforms from its full complex form-governing weak values-to the real, non-negative Wigner formula describing projective measurements, while maintaining informational completeness throughout the transition. Our work resolves the fundamental question of the KD distribution's applicability by establishing it as the universal framework that seamlessly connects all quantum measurement regimes through a physically transparent decoherence pathway.

The long-term security of public blockchains strictly depends on the hardness assumptions of the underlying digital signature schemes. In the current scenario, most deployed cryptocurrencies and blockchain platforms rely on elliptic-curve cryptography, which is vulnerable to quantum attacks due to Shor's algorithm. Therefore, it is important to understand how post-quantum (PQ) digital signatures behave when integrated into real blockchain systems. This report presents a blockchain prototype that supports multiple quantum-secure signature algorithms, focusing on CRYSTALS-Dilithium, Falcon and Hawk as lattice-based schemes. This report also describes the design of the prototype and discusses the performance metrics, which include key generation, signing, verification times, key sizes and signature sizes. This report covers the problem, background, and experimental methodology, also providing a detailed comparison of quantum-secure signatures in a blockchain context and extending the analysis to schemes such as HAETAE.