Papers

As quantum computing continues to scale, quantum measurement and control (QMC) are increasingly constrained by calibration workflow complexity and by requirements for low-latency execution, robust exception handling, and traceable workflow governance. Existing frameworks for QMC are specialized and task-specific, while language-model-based agents for QMC suffer from excessive latency and cannot satisfy the strict timing and control-density demands of large-scale quantum systems. Here we propose QMClaw, a general, workflow-oriented framework for QMC built, featuring a local-first, tool-governed, robust architecture. At its core is a RuleEngine-centered control layer that processes structured context, performs rule-based state transitions, and generates execution plans for typical calibration workflows. Language models are used only for natural-language interaction, high-level task understanding, and exception support, keeping the critical fast path efficient. We implement a single qubit tune-up workflow as a demonstration and validation using real quantum device dataset. We also prove that the framework achieves quantitatively acceptable levels in terms of resource cost, LLM calling times and decision latency, enabling its practical deployment in large-scale quantum qubit measurement and control scenarios. This work presents a general workflow-oriented framework for QMC and provides evidence that rule-centered architectures are a promising design choice for scalable quantum-system calibration.

Dynamic polarization controllers are key devices with broad applications in many fields. However, most on-chip polarization controllers still rely on traditional blind-search methods, whereas analytical optical-computing approaches remain insufficiently explored, particularly with respect to calibration and endless polarization control. With the accurate relative phase of Mach-Zehnder interferometer (MZI) being fully controllable on an integrated photonics chip, we present an analytical polarization control (APC) method using four phase shifters and optical computing, eliminating the need for the traditional inefficient blind-search procedure. The basic structures and operations of APC are clarified. The proposed calibration method and endless control method enable continuous APC while compensating for phase differences within the MZI structures. We simulate the influence of the endless control unit on polarization control and quantify the effect of the fourth phase difference on the output extinction ratio. With the fourth phase shifter, the phase difference encountered during Stokes vector measurement can be effectively compensated, and rotations around all three axes on the Poincaré sphere can be realized. These results establish a practical APC architecture based on optical computing for photonics chips. The proposed APC methods, combined with a FPGA-based hardware acceleration, will enable high speed on-chip polarization controllers.

Selecting an effective encoding quantum circuit is a key challenge in quantum kernel methods because different feature maps can lead to different performance. Conventional methods require constructing and evaluating every circuit for each new dataset, making it computationally expensive. We present Qmes, an open-source Python package that automatically recommends circuits through meta-learning. Qmes characterizes a dataset using classical complexity measures and queries a pre-trained model to recommend circuits without quantum evaluation at inference time. The package provides modular components for meta-feature extraction, quantum-kernel evaluation, recommender training, model selection, and user-defined circuit extension. We validate Qmes on 105 classification and 86 regression benchmark datasets. Qmes reduces the mean recommendation regret by 2.2x and 4.2x for classification and regression, respectively, compared to a non-adaptive baseline, with statistical significance confirmed via a paired Wilcoxon signed-rank test ($p < 10^{-4}$). Qmes thus enables efficient and practical encoding-circuit selection for quantum kernel methods.

The laboratory-frame anti-Jaynes–Cummings (AJC) interaction retains a residual detuning $2f\lambda$ that is absent from the rotating-frame model. We map two proposed remedies—a Kerr shift $\chi(\hat a^\dagger\hat a)^2$ and collective Dicke coupling of $N$ two-level emitters—for a squeezed vacuum on that ladder ($r=1$, $\langle n\rangle=\sinh^2 r\simeq 1.38$). All quoted contrasts are the amplitude of the first turning point of the atomic ground-state population, which coincides with the two-level formula $\mathcal{C}=1/[1+(2f+\chi)^2]$ at $r=0$ to $10^{-9}$. Three results follow. (i)~A single Kerr strength never restores unit contrast at $r=1$; the $r=0$ $n$-dependent shift $\chi(2n+1)$ cannot cancel $2f\lambda$ on every occupied Fock component. (ii)~The exact $r=1$ contrast at $\chi=0$ is not reproduced by an incoherent sum $\sum_n P_n(r)\,\mathcal{C}_n$ built from the $r=0$ two-level formula; pointwise deviations are several tenths. (iii)~Collective coupling raises the contrast systematically. At $f=5$ one finds $\mathcal{C}=0.140$ ($N=1$) and $\mathcal{C}=0.575$ ($N=8$), above the unsqueezed value $8/[8+(2f)^2]=0.074$. The $N=16$ point at this $f$ remains truncation-limited and is not quoted to three digits. The same $N\sim(2f)^2$ estimate for $\mathcal{C}=1/2$ places trapped-ion values $f\sim 10^{2}$–$10^{3}$ outside the present construction. The relevant platform is ultrastrong circuit QED with $f\sim 1$–$10$. The calculation is a numerical control landscape, not a new solvable limit.

We ask when qubit controls can produce an effective generator that drives every initial state to the same pure state. Lie-algebra closure alone cannot answer this question because it loses the distinction between reversible control and irreversible dissipation. Lie wedges retain this distinction by enforcing nonnegative strengths for dissipative generators. For drift-free qubits with Hamiltonian controls available with either sign and at most one independently actuated dissipator generated by a traceless jump operator, we classify all nontrivial systems into thirteen structural types, or strata. Explicit tests assign each system to a stratum, and necessary and sufficient conditions determine whether its Lie wedge contains a stabilizing generator. These criteria distinguish stabilizable and non-stabilizable systems even when they share the same generated Lie algebra and stratum. In one exceptional stratum, a single dissipative orientation cannot stabilize a pure state even with the available Hamiltonian controls. Averaging two orientations of the same dissipative channel, related by those controls, produces a stabilizing generator.

This work provides a digital quantum simulation scheme for $1{+}1$-dimensional $SU(2)$ Yang–Mills theory with Dirac fermions. It takes the form of a quantum circuit, infinitely repeating across space and time with $\Delta_t=\Delta_x=\varepsilon$, whose wires follow lightlike propagation. The construction mirrors the logic of the standard quantum field theory approach, transposed to the discrete setting. Namely, we start from the Dirac quantum walk, restore $SU(2)$ gauge symmetry by introducing the gauge field, lift the walk to a multi-particle QCA while preserving fermionic anticommutation, and equip the gauge field with its own dynamics. Rather than relying on Clebsch–Gordan decompositions, we use the pointwise-product structure of gauge-link updates, which yields self-contained proofs of unitarity and gauge covariance in quantum-computing notation. The construction provides an explicit algorithmic formulation of the theory, whose continuum limit we discuss.

Von Neumann proposed two quantum entropies, one in 1927 and the other in 1929. He intended to define thermodynamic entropy for quantum states in both cases. The 1927 entropy is the well-known von Neumann entropy, which is zero for all pure states. The 1929 entropy, which is nonzero for almost all pure states, has largely been ignored. After reviewing the history and properties of both entropies, we argue that the 1927 entropy is not thermodynamic entropy and should be used simply as a measure of entanglement, whereas the 1929 entropy is the true thermodynamic entropy for quantum states.

Equivariant quantum networks encode symmetry as an inductive bias, which can improve generalization and may also favor optimization convergence. Equivariance alone, however, does not constrain the noncommuting closure of trainable generators, and this closure can still grow rapidly in symmetry-preserving variational circuits. We introduce a hierarchical ancilla-controlled architecture that addresses this Lie-algebra-growth mechanism. Commuting invariant-sector projectors on the data register select parameterized operations on a shared ancilla register, where the noncommuting trainable dynamics is confined. The trainable circuit decomposes into compatible joint sectors, giving a sector-probability-weighted ancilla response and an explicit view of parameter sharing across hierarchical paths. For an ancilla dimension $d_A=2^m$ and $K_\ell$ retained layer-wise control modes, we prove the group-independent bound $\dim(\mathfrak g)\le (d_A^2-1)\prod_{\ell=1}^{L}(K_\ell+1)$. The bound is polynomial in the number of data qubits when $m$ and $K_\ell$ remain constant along a logarithmic-depth hierarchy. Particle-number and parity projectors illustrate the general construction, while a fixed Clebsch–Gordan coupling tree supplies a concrete $SU(2)$ realization with rotation-invariant scalar outputs. Finite-size state-vector simulations exhibit slower gradient-variance decay and larger initialization gradients than generic and conventional rotationally equivariant circuits over the studied system sizes. The same realization fits sparse rotation-invariant classification tasks and geometry-dependent Heisenberg ground-state energies. These results support restricted trainable Lie-algebra growth as a structural strategy for initialization trainability in the regimes considered here.

It is known that the spacetime metric can be recovered from quantum-field correlators. We extend this programme by showing that the Einstein tensor can be directly written in terms of UV-regulated field correlations. The same correlation structure also directly determines the Ricci tensor, while higher coincidence derivatives recover the connection and Riemann tensor. We further show that the renormalized stress-energy tensor can be formulated within this framework, up to the standard finite renormalization freedom. These results provide a correlation-based organization of the semiclassical Einstein equations and advance the programme of formulating spacetime geometry in terms of quantum field correlations.

Universal scaling generated when a strongly interacting quantum many-body system is driven across a continuous phase transition provides a dynamical probe of equilibrium criticality. Accessing this regime numerically in two dimensions is challenging because it requires accurate real-time evolution of correlated many-body states over many system sizes and driving rates. We introduce a Neural Foundation-state Subspace (NFS) method for near-adiabatic dynamics. A foundation neural-network quantum state represents the ground-state manifold along the driving path, and a small fidelity-selected subset defines a fixed variational subspace. The many-body Schrödinger equation then reduces to the evolution of a few linear coefficients, with projected operators reusable across ramp times. We validate the method on the two-dimensional transverse-field Ising model, recovering the expected Kibble-Zurek scaling and critical exponents in quantitative agreement with ground-state quantum Monte Carlo estimates. Applied to the frustrated square-lattice $J_1$-$J_2$ Heisenberg model up to $16 \times 16$ clusters, our approach provides strong numerical evidence of Kibble-Zurek mechanism across the Néel-to-spin-liquid transition at $J_2/J_1=0.49$, yielding ${\nu=1.23(15)}$ and ${\eta=0.409(19)}$ at fixed $z=1$, consistent with static estimates and supporting the proposed continuous critical behavior.

Let $S$ be the common tensor-product and commuting-operator supremum of the $I_{3322}$ Bell functional in the Collins-Gisin normalization. Starting from a certified value window and Bellman/path equivalence, we prove that no finite-dimensional quantum strategy attains $S$, whereas a spatial strategy on $\ell^2(\mathbb{Z})\otimes\ell^2(\mathbb{Z})$ does. The finite-dimensional statement includes mixed states and binary POVMs. Consequently $C_q(3,3;2,2)$ is not closed and $C_{qs}(3,3;2,2)\setminus C_q(3,3;2,2)$ is nonempty. We also establish the dimension complexity $D(\epsilon)=\Theta(\log(1/\epsilon))$: approaching $S$ requires and suffices local dimension logarithmic in inverse error. The constructive upper bound is $D(\epsilon)\le 23.9010650\log(1/\epsilon)$ for all sufficiently small $\epsilon$, with natural logarithms; the lower constants are existential. The proofs use critical Bellman storage, spectral transport and normalizable orbit measures. A finite weighted-flow argument supplies the unrestricted quantitative lower bound without identifying distinct joint spectral components. This revision replaces an unsupported step in the earlier lower argument and records additional proof corrections. Prior numerical certification and independent concurrent attainment results are credited. Exact arithmetic and Lean 4 check specified numerical, scalar and finite accounting facts; the complete analytic proof is not formalized.

Quantum error-correction decoders are typically benchmarked against synthetic circuit-level noise, under the assumption that a decoder's ranking under such noise transfers to hardware and improves as the noise model becomes more realistic. The Willow processor, the first to operate below the surface-code threshold, allows us to test this assumption. We rank a panel of six decoders using a four-rung ladder of noise models with increasing fidelity, evaluated against real data across three code distances, two bases, and fifteen round counts. Rank agreement with hardware appears once the noise model gives each operation type its own error rate. Calibrating the model to the device improves absolute error rates but not rank agreement. We additionally provide the first independent evaluation of NVIDIA's Ising pre-decoder on hardware, at code distances below its training receptive field and via a mapping onto the lattice on which it was trained. Under these conditions, it holds no accuracy-latency advantage: another panel decoder matches or improves on it in both per-cycle error rate and decode latency in 278 of the 280 evaluations. We release the full pipeline and the per-shot outcome of every evaluation, so future decoders and devices can be compared.

Distributed quantum computing (DQC) offers a promising approach to scale quantum computing by overcoming the resource limitations of a single quantum processor. However, inter-node communication remains a major bottleneck of DQC due to inefficient and error-prone entanglement distribution. Optimizing inter-node communication can not only reduce the amount of entanglement resource needed to execute a quantum circuit but also improve execution speed and accuracy of the results. This paper proposes DPRQ, a qubit routing algorithm for minimizing inter-node communication in distributed quantum circuits divided into collective communication blocks. Unlike current approaches that utilize greedy block-level qubit routing strategies, DPRQ employs a dynamic programming-based technique focused on global circuit-level optimization, while capturing inter-block dependencies. We evaluated DPRQ on four sets of quantum circuits and a variety of DQC configurations. The results demonstrate that DPRQ's innovative routing strategy achieves an average of 24.40% reduction with a maximum of 85.06% reduction in inter-node communication, when compared to the state-of-the-art collective communication-based DQC compiler QuComm.

This work describes the calculation of spin-orbit spillage from a crystal structure. Spin-orbit spillage provides a measure of the likelihood that a material has topological character. The spillage also provides the reference quantity for the machine-learning classifier of Choudhary et al., which predicts whether the spillage exceeds a specified threshold rather than the calculation of its numerical value directly. The complete computation workflow was applied to the insulating compound BaMg2Bi2, yielding a spillage of 2.094 compared with the published VASP spillage of 2.075, corresponding to a difference of 0.9%. The calculation is described in terms of two Quantum ESPRESSO (QE) calculations of spillage performed with and without spin-orbit coupling, the role of relativistic pseudopotentials, and the subsequent wavefunction-overlap analysis. The limitations of the same calculation procedure for semimetals are also examined.

We introduce chameleon gates as a natural generalization of conventional quantum controlled-gates. Chameleon gates are state-based quantum controlled-operations that retain standard elements such as control and target systems, while introducing a new feature: the quantum knob. This knob is a quantum signal (state) that determines the operation performed by the gate. Consequently, the action and form of a chameleon gate depend dynamically on the quantum knob, allowing the gate to adapt its operation and implement transformations that are not necessarily unitary. This shapeshifting property is in stark contrast to conventional quantum controlled-gates, whose actions are fixed and cannot be modified. We also propose how chameleon gates can be realized using conventional quantum gates available in current quantum technologies. We then employ chameleon gates as a useful building block within the recently proposed state-based quantum computation (SBQC) framework. Using this approach, we demonstrate the simulation of state-dependent (nonlinear) quantum evolutions.

We study the one-shot and concurrent hitting for the discrete-time Grover-coined quantum walk on cubelike graphs $G=\text{Cay}(\mathbb Z_2^d,\Omega)$ of degree $\Delta=|\Omega|$. Starting from the vertex labeled $0$, we identify $\sigma=\bigoplus_{\omega\in\Omega}\omega$ as a natural target vertex; for the hypercube, $\sigma$ is precisely the antipodal vertex. For families with $\Delta\to\infty$, let $T$ be an integer having the same parity as $\Delta$ and satisfying $ \left|T-\frac{\pi\Delta}{2}\right|\leq 1. $ We show that the probability $p_T(\sigma)$ of finding the walker at $\sigma$ when it is measured at time $T$ satisfies $$ p_T(\sigma)=1-O(\Delta^{-1/5}). $$ Thus the target is found with probability tending to one after $\Theta(\Delta)$ steps. For the concurrently measured walk, let $H_T^{\mathrm{Conc}}(\sigma)$ denote the probability that the target is detected at or before time $T$ when it is tested after every step. We prove $$ p_T(\sigma)\leq T H_T^{\mathrm{Conc}}(\sigma), $$ which implies $H_T^{\mathrm{Conc}}(\sigma)=\Omega(\Delta^{-1})$ over the same time scale. The proof uses the Walsh-Fourier decomposition, an exact two-dimensional reduction of each Fourier mode, and a universal second-moment identity for the associated character sums. Our results extend Kempe's hypercube hitting phenomenon (J. Kempe, Probab. Theory Relat. Fields 133, 215-235, 2005) to arbitrary cubelike generating sets and establish the conjectured asymptotic hitting behavior for cublelike and augmented cubes in Mulherkar, Rajdeepak and Sunitha (Int. J. Quantum Inf. 20,2250020, 2022)

In single-port non-Hermitian sensors the Petermann factor offsets susceptibility gains, imposing a strict resource bound on metrological precision. We test whether a multi-port geometry can evade this bound: a double-chain optomechanical ladder with opposing non-reciprocal hoppings spatially separates signal amplification from quantum-noise drainage, and gradient-based differentiable optimal control (DOC) maximizes the resource-normalized Fisher information $\Fnorm$ subject to a Hurwitz-stability constraint. Across system sizes $N\in\{\num{6},\dots,\num{16}\}$ the optimizer returns $\Fnorm>0$ in every case, with two coexisting solution classes whose selection is initialization-dependent: deep-stability configurations achieve $\Fnorm\in\numrange{0.937}{0.987}$ with attenuated transmission, while marginal-stability configurations deliver directional gain $\Gfwd\in\qtyrange{13.5}{15.5}{\dB}$ with isolation $\Iso\in\qtyrange{40}{64}{\dB}$. A multi-restart ensemble reveals these classes are the endpoints of a precision–gain frontier. All solutions remain Hurwitz-stable under \qty{5}{\percent} disorder (\qty{87.5}{\percent} recovery), and the deep-stability advantage survives realistic preamplifier noise at $\Fnormeff\approx\num{0.3}$–$\num{0.5}$. Mapped onto circuit-QED parameters, the architecture enables sub-attonewton force sensing and broadband axion searches across the \qtyrange{1}{10}{\giga\hertz} band.

The scalability of variational quantum algorithms is fundamentally limited by the barren plateau effect, where the cost-function variance vanishes with system size, rendering optimization impractical. Recent Lie-algebraic approaches for deep parameterized have enabled a unified analytical understanding of this challenge but require either the initial state or the measurement observable to belong to the dynamical Lie algebra generated by the circuit. Here, we introduce a representation-theoretic framework under $2$-design hypothesis showing that variational quantum landscapes admit a natural decomposition into irreducible representation channels. This yields exact expressions and analytical bounds for the cost-function variance applicable to arbitrary initial states and observables, with previous Lie-algebraic results emerging as a special case. We illustrate the framework by analyzing the energy landscape of the one-dimensional ANNNI model for several circuit architectures, revealing trainability regimes inaccessible to existing methods. Our results establish a general representation-theoretic framework for analyzing variational quantum landscapes, substantially extending the analytical theory of barren plateaus.

High-rate quantum low-density parity-check (qLDPC) codes can substantially reduce qubit overhead relative to surface codes, but their advantage depends on efficiently realizing nonlocal syndrome extraction. We study the \([[144,12,12]]\) bivariate bicycle code on a neutral-atom architecture with native three-dimensional (3D) geometry, comparing planar and 3D embeddings while holding the code fixed. We characterize spatial efficiency using the logical-qubit density, defined as the number of encoded logical qubits per unit spatial footprint. Because the optical controller's field of view limits the transverse extent of an array, this metric estimates the number of logical qubits that can be accommodated within a fixed optical field of view. The 3D embedding achieves approximately \(4\times\) greater areal logical-qubit density than the planar layout and \(42\times\) greater than a surface-code baseline. It also reduces the bivariate bicycle syndrome-extraction time by roughly \(2\times\) compared to a planar baseline, with fewer movement operations and substantially shorter atom-transport distance. Native 3D geometry can improve both the packing density and executable realization of nonlocal qLDPC codes, making practical performance depend jointly on code structure, optical geometry, transport scheduling, and hardware-level noise. This motivates further development of control techniques in 3D.

Interactions between a quantum system and its environment can inject ergotropy into the system, raising the question of the minimal dimensionality and physical resources required for such injection. We first show that ergotropy injection is impossible under thermal operations when both the system and environment are qubits, whereas it becomes possible when the environment is enlarged to a qutrit. We further show that already in the qubit-qubit setting, relaxing environmental thermality and allowing interactions between system and environment allows ergotropy increment under energy-conserving unitaries. To elucidate the role of interactions, we consider a two-qubit isotropic XY interaction Hamiltonian and identify its distinct degeneracy regimes. We show that, in the central-block regime, when both the initial system and environmental states are incoherent, no ergotropic gain is possible when the environment is initially thermal, irrespective of the interaction strength. In contrast, environmental athermality in the form of population inversion, while retaining incoherence, enables ergotropic injection. We derive the optimal ergotropic gain and show that environmental coherence can enhance it, while system coherence alone need not be beneficial and can even reduce the gain. We further consider the double-degenerate regime, characterized by a finite interaction strength, and demonstrate positive ergotropic gain even for a thermal environment.

Twin-field (TF) quantum key distribution (QKD) offers a promising approach to long-distance QKD networks due to its superior performance over large channel losses. Due to specialized hardware requirements, nearly all long-distance TFQKD demonstrations have only two users exchanging keys, rather than a network with three or more users. In this work, we experimentally demonstrate a proof-of-principle three-user-pair Sagnac TFQKD network spanning 127-km using single-photon avalanche detectors without any active phase stabilization or postcompensation. We implement efficient procedures for maintaining polarization stability and circumventing Rayleigh backscattering noise to achieve a stable Sagnac interference visibility of $93\pm1$% over one hour. A secure key rate of $1.398\times10^{-5}$ bits per pulse is achieved over an asymmetric communication channel with 102-km fiber and 45-dB overall loss. To our knowledge, this is the first TFQKD network without active phase stabilization or postcompensation achieved over long fibers. Our results represent a highly practical and cost-effective approach to long-distance QKD networks.

We prove a structure theorem for the dimension towers~$\{d_k(D)\}_{k\geq0}$ which arise in the number-theoretic formulation of Zauner's SIC-POVM conjecture over a real quadratic field~$K=\Q(\qD)$. If~$\eps$ denotes the first totally positive power of a fundamental unit of~$K$ and $t_k = \eps^k + \eps^{-k}$ the trace of its $k$-th power, then the SIC dimension tower~$\{d_k=1+t_k\}_{k\geq0}$ is the level~$m=3$ row of an infinite two-dimensional cyclotomic array~$\{\Psi_m(t_k)\}_{m\geq1,k\geq0}$ attached to~$K$, while the auxiliary factors~$(d_k+1)$ and $(d_k-3)$ are its ramified levels $m=2$ and $m=1$. Here~$\Psi_m$ denotes the minimal polynomial of~ $\zeta_m+\zeta_m^{-1} = 2\cos{2\pi/m}$. This construction arose initially from an attempt to formulate relations among SIC dimensions in $q$-algebraic terms. The central object is a single closed composite norm relation for the two-parameter family $c_{m,k}=1-\zeta_m\eps^k$ over the cyclotomic field tower $\{K(\mu_m)\}_{m\geq1}$. This framework sheds new light on the mod-$p$ analogue of Leopoldt's conjecture, by placing the central 3-symmetry of Zauner's conjecture within a broader arithmetic context. Away from the primes dividing~$2mD$, the valuations $v_p(\Psi_m(t_k))$ at every fixed level~$m$ are described exactly in terms of a single local unit valuation, which is then related, through the~$p$-adic class number formula, to the corresponding $p$-adic $L$-value.

The problem of the effective excitations of a gauge theory in the nonperturbative regime remains not completely understood. Using the Refined Gribov-Zwanziger (RGZ) theory as effective model for pure gauge Yang-Mills theories, we revisit the quasiparticle (quadratic) excitations of the theory. A novel interpretation of such quasiparticles is proposed, in the case of real mass poles, taking into account the manifest ${\cal PT}-$symmetry of the RGZ Lagrangian.

There is an extensive body of research probing the potential of adiabatic quantum computation and quantum annealing to solve hard computational problems. This research endeavor is complicated by noise afflicting hardware during the computational process. An error-correcting approach called quantum annealing correction (QAC) was suggested to mitigate this noise. The QAC approach employs a centralized version of the repetition code in which the qubits are configured in a star-graph pattern with one special qubit playing the role of the hub. In this paper, we explore the thermal physics of the centralized repetition code, using a Lindblad equation framework to analyze its lifetime when coupled to a thermal bath. We show that its centralized configuration leads to thermal stability, enabling the robust storage of a logical bit of information, despite the fact that there is only 1 ferromagnetic Ising interaction per qubit like a 1-dimensional Ising chain.

Modern atomistic simulations increasingly employ localized orbitals to represent quantum operators, yielding sparse block matrices whose block shapes vary with chemical species and basis choice. Conventional scalar sparse formats store the entries of each block individually, obscuring this local structure and limiting the use of efficient block algorithms. We present VBCSR, a distributed sparse matrix library that preserves variable-size atomic blocks and accelerates the core linear algebra of large-scale atomistic simulations. A unified interface automatically maps scalar, uniform-basis, and multispecies operators to compressed sparse row (CSR), block sparse row (BSR), or variable-block compressed sparse row (VBCSR). Our advanced acceleration method groups blocks of equal shape and dispatches them to optimized dense kernels. In the reported benchmarks, VBCSR outperforms the tested Python-accessible reference implementations for several block-sparse benchmarks. We further demonstrate VBCSR in an InP nanoparticle application containing more than \(10^6\) atoms.

Quantum simulations of correlated many-body systems will inevitably operate with imperfect information: the prepared states may arise from incomplete or approximate ansatze, while their measured Hamiltonian and overlap matrix elements are additionally affected by hardware and statistical noise. Robust quantum algorithms will be those that can improve upon reliable lower-level descriptions in spite of these imperfections. We introduce a dual-space nonorthogonal configuration-interaction (DS-NOCI) framework built around this principle. Rather than replacing a classically accessible NOCI reference manifold with correlated quantum states, DS-NOCI retains both spaces and couples them variationally. The reference sector provides a stable many-body backbone, while the quantum states contribute whatever additional correlation directions they contain. With exact matrix elements, the enlarged dual space gives a ground-state energy no higher than either the reference-only NOCI or correlated-only quantum-NOCI spaces, ensuring that an incomplete correlation model cannot degrade the underlying variational description. The additional reference–correlated matrix elements require only one correlated state preparation and are therefore less demanding than the correlated–correlated block already required by quantum variant of NOCI. Molecular benchmarks further show enhanced resilience to imperfect amplitudes and noisy matrix elements. DS-NOCI thus provides a general strategy for building quantum many-body formulations that remain useful when both correlation models and quantum computations are necessarily incomplete and noisy.

We present a unified theoretical analysis of three-photon quantum interference in a Six-Port Mach-Zehnder Interferometer (6p-MZI) constructed from two cascaded tritters, with two independent phase modulators placed between the tritter arms. We analytically derive the transfer matrix of the 6p-MZI and show how they organize into three symmetry classes, governed by the discrete Fourier transform (DFT) structure of the tritter and the conjugate relations. Furthermore, we analyze two input regimes: First, three indistinguishable single photons are injected into the tritter, and the output probability distributions $P_{[111]}$, $P_{[\{300\}]}$, and $P_{[\{210\}]}$ are derived as functions of the two relative phases $(\phi_1, \phi_2)$. At $\phi_2 = 0$, the single-phase limit is recovered, which confirms 100% visibility of the even-distribution fringe. Second, a hybrid coherent-Fock input $|\alpha\rangle_1|\alpha\rangle_2|1\rangle_3$ is analyzed via the density matrix formalism. The average photon number at each output port exhibits amplitude-dependent phase shifts. Our results establish the 6p-MZI as a programmable platform for tripartite quantum state manipulation and coherent amplitude sensing.

Jets are central to the physics programs of both current and future colliders, from precision Standard Model measurements and searches for new physics at the Large Hadron Collider to studies of nucleon structure at the future Electron-Ion Collider. Motivated by these applications, we explore quantum machine learning for jet classification and present a permutation-invariant Quantum Graph Neural Network (QGNN) applied to particle-cloud representations of jets. We apply the model to two such discrimination tasks: quark vs. gluon and up vs. down quark flavor tagging, with the latter being, to our knowledge, the first application of a quantum model to this problem. In the ideal simulation, the QGNN performs competitively against the Particle Flow Network and traditional QCD observables. We further deploy scaled-down models to IBM and IonQ quantum processing units (QPUs), where we train and evaluate them, obtaining promising results. Finally, we perform an interpretability analysis to characterize the observables learned by the quantum model, relating them to generalized angularities for the quark-gluon study and to jet charge for the flavor study.

We develop a quantum sensing framework for the phase independent detection of weak coherent optical displacements based on SU(1,1) interferometry. Unlike conventional quantum measurement protocols that require prior knowledge of the signal phase and coherent homodyne detection, the proposed approach estimates the displacement magnitude independently of its phase. We show that, under ideal lossless conditions, a conventional SU(1,1) interferometer employing only total intensity detection saturates the quantum Cramer Rao bound for displacement magnitude estimation. We further derive the analytical expression of the quantum Cramer Rao bound and the sensitivity of the conventional SU(1,1) interferometer with total intensity detection and systematically investigate its performance in the presence of optical loss. The proposed phase-independent intensity detection scheme achieves comparable performance over experimentally relevant operating regimes while eliminating the need for local oscillators, phase locking, and quadrature tracking. These results establish SU(1,1) based intensity detection as a practical platform for phase independent quantum sensing.

We introduce a new class of p-adic Dirac equations, formulated in the standard axiomatic framework of quantum mechanics, in which the ordinary spatial derivatives are replaced by non-local operators built from arbitrary integrable kernels. We diagonalize the resulting free Dirac Hamiltonian in momentum space, construct its plane-wave solutions, determine its spectrum, and establish a p-adic charge-conjugation symmetry relating particle and antiparticle sectors. We then discretize the free equation in two ways, both giving genuine continuous-time quantum walks rather than the discrete-time, coined walks that dominate the existing literature: a first construction on a countable covering of the underlying p-adic space, and a second, more explicit construction on a finite, tree-structured graph, for which we prove that the transition probabilities, once the internal (particle/antiparticle) components of the wavefunction are combined, form a genuine, properly normalized set of transition probabilities at every instant of time; in other words, ignoring the internal structure of the walk, it behaves exactly like an ordinary random walk on that graph. Building on this stochastic-matrix property, we discuss how the resulting construction can serve as the foundation of a quantum network with genuinely relativistic-type internal degrees of freedom, complementing earlier, non-relativistic p-adic quantum neural networks. To the best of our knowledge, this is the first continuous-time quantum walk whose free dynamics coincides exactly with a Dirac equation on a hierarchical graph. We close with a discussion of the open mathematical and computational problems raised by this construction.