Papers

We investigate the imaginary-time relaxation critical dynamics of the two-dimensional transverse-field Ising model using infinite projected entangled pair states (iPEPS) with the full-update strategy. Simulating directly in the thermodynamic limit, we explore the relaxation process near the critical point with two types of initial states: a fully polarized state and a product state with a small magnetization. For the fully polarized state, the magnetization shows a power law scaling $M\propto \tau^{-\beta/(\nu z)}$ in the imaginary-time evolution, from which both the critical point and critical exponent can be determined with high accuracy. For the nearly paramagnetic state, the relaxation process exhibits a behavior of $M\propto \tau^\theta$ with $\theta=0.1958$ being the critical initial-slip exponent, which is in good agreement with that obtained from the dynamic scaling of the self-correlation in quantum Monte Carlo method. These universal features emerge well before the system converges to the ground state, demonstrating the efficiency of imaginary-time evolution for probing quantum criticality. Our results demonstrate that iPEPS can serve as a robust and scalable method for studying dynamical critical phenomena in two-dimensional quantum many-body systems.

Mid-circuit measurement (MCM) enables qubit reuse and dynamic control in quantum processors, underpinning resource-efficient algorithms and quantum error correction. However, MCM introduces non-negligible errors, including measurement-induced crosstalk, idling-qubit decoherence, and reset infidelity. Additionally, MCM error rates vary across qubits within the same processor, with some exhibiting substantially higher errors. Existing compilers, including Qiskit-compiler and QR-Map, ignore MCM error variations, leading to fidelity loss in circuits with frequent MCM operations. In this paper, we present MERA, an MCM-error-aware quantum compilation framework that integrates MCM error modeling into the layout, routing, and scheduling stages. We first use the lightweight profiling method to capture a per-qubit MCM error distribution that remains stable for over 24 hours. The distribution guides MERA in applying MCM-error-aware layout and routing, while MERA further incorporates context-aware dynamic decoupling to improve fidelity. In evaluation, MERA delivers 24.94% – 80.48% average fidelity gains over the Qiskit-compiler (optimization level 3) across different groups in selected benchmarks without additional SWAP overhead. It also boosts the fidelity of QR-Map-generated circuits by 29.26% on average (up to 122.58%), demonstrating its effectiveness for circuits with frequent MCM operations.

Spontaneous macroscopic quantum synchronization is an emergent phenomenon where an ensemble of quantum oscillators achieves global phase coherence through the interplay of interaction and dissipation. To illuminate this phenomenon, we study an ensemble of two-level systems (TLS) and establish its associated nonlinear quantum master equation, for which self-consistent analytical solutions of quantum synchronization can be obtained. The trajectories on the Bloch sphere vividly illustrate how dissipation and interaction drive the system toward a synchronized state. We present a phase diagram for macroscopic synchronization as a function of interaction strength and the gain-to-damping ratio. Furthermore, we demonstrate full synchronization and partial synchronization between two groups of TLS with different natural frequencies. This work establishes ensemble of TLS as a remarkable system for understanding spontaneous quantum synchronization.

Resonant parametric modulation is a major tool of studying magnetic systems. For a spin-1/2 chain in a strong magnetic field, the resulting excitations can be mapped on fermionic excitations in the Kitaev chain. We show that the response to turning on the modulation reveals dynamical bulk aspects of the nontrivial topology of the closed chain. In the topological regime, depending on the turn-on rate, the system displays an absence of frequency dispersion of the time-averaged magnetization and an absence or a suppression of its spatial correlations near resonance. The transition between the topological and trivial regimes is controlled by the modulation frequency.

Can particles at definite positions in real space, obeying Newton's equations under an ordinary interaction force, have a coarse-grained description that is the Schrödinger equation? We present a medium of companion particles on a line under a force of exactly that kind: each companion pays for the mismatch of the signed inverse gaps to its two neighbors. A binary polarity carried by each companion makes stationary states with nodes dynamically stable and supplies the quantization condition. Finite chains relax into the stationary densities of the box and the harmonic oscillator and develop double-slit fringes. In the smooth limit the Schrödinger equation emerges, with $\psi$ carrying two real fields rather than being fundamental.

Artificial intelligence (AI) is used in numerous fields of science, yet the initial research questions and targets are still almost always provided by human researchers. AI-generated creative ideas in science are rare and often vague, so that it remains a human task to execute them. Automating idea generation and implementation in one coherent system would significantly shift the role of humans in the scientific process. Here we present AI-Mandel, an LLM agent that can generate and implement ideas in quantum physics. AI-Mandel formulates ideas from the literature and uses a domain-specific AI tool to turn them into concrete experiment designs that can readily be implemented in laboratories. The generated ideas by AI-Mandel are often scientifically interesting - for two of them we have already written independent scientific follow-up papers. The ideas include new variations of quantum teleportation, primitives of quantum networks in indefinite causal orders, and new concepts of geometric phases based on closed loops of quantum information transfer. AI-Mandel is a prototypical demonstration of an AI physicist that can generate and implement concrete, actionable ideas. Building such a system is not only useful to accelerate science, but it also reveals concrete open challenges on the path to human-level artificial scientists.

Integer factorization is a computational problem of fundamental importance in cybersecurity and secure communications, as its difficulty form the basis of modern public-key cryptography. While Shor's algorithm can solve this problem efficiently on a universal quantum computer, near-term devices require alternative approaches. The Adiabatic Factorization Algorithm and its digitized counterparts offer a promising NISQ-era pathway but suffer from high-order many-body interactions that are difficult to implement. In this work, we propose a modified QAOA-based factorization protocol that simplifies the interacting Hamiltonian to include only two-body terms, significantly reducing its experimental complexity. Numerical simulations show that this method achieves comparable or higher fidelities than the standard protocol, while requiring fewer quantum resources and converging more rapidly for problem instances up to eight qubits. We analyze the characteristic fidelity behavior introduced by the Hamiltonian modification. Additionally, we report on simulations with alternative cost-function definitions that frequently yielded improved performance.

High-precision clock synchronization is essential for a wide range of network-distributed applications. In the quantum space, these applications include communication, sensing, and positioning. However, current synchronization techniques are vulnerable to attacks, such as intercept-resend attacks, spoofing, and delay attacks. Here, we propose and experimentally demonstrate a new quantum secure time transfer (QSTT) system, subsequently used for clock synchronization, that largely negates such attacks. Novel to our system is the optimal use of self-generated quantum keys within the QSTT to information-theoretically secure the maximum amount of timing data; as well as the introduction, within a hybrid quantum/post-quantum architecture, of an information-theoretic secure obfuscated encryption sequence of the remaining timing data. With these enhancements, we argue that our new system represents the most robust implementation of QSTT to date.

We present hybrid Gibbs sampling algorithms for the stabilizer code Hamiltonians of the rotated surface code and the toric code with only local quantum algorithms, using $\sim L/2$ quantum circuit depth to prepare the Gibbs state of the rotated surface code Hamiltonian, and $L$ quantum circuit depth to prepare the Gibbs state of the toric code Hamiltonian, being $L$ the side of the side of the square lattice. We further show that if we allow for non-local gates, the Gibbs state of the periodic 1D Ising model can be prepared in logarithmic depth and linearly many simultaneous measurements.

The goal of quantum channel discrimination and estimation is to determine the identity of an unknown channel from a discrete or continuous set, respectively. The query complexity of these tasks is equal to the minimum number of times one must call an unknown channel to identify it within a desired threshold on the error probability. In this paper, we establish lower bounds on the query complexities of channel discrimination and estimation, in both the parallel and adaptive access models. We do so by establishing new or applying known upper bounds on the squared Bures distance and symmetric logarithmic derivative Fisher information of channels. Phrasing our statements and proofs in terms of isometric extensions of quantum channels allows us to give conceptually simple proofs for both novel and known bounds. We also provide alternative proofs for several established results in an effort to present a consistent and unified framework for quantum channel discrimination and estimation, which we believe will be helpful in addressing future questions in the field.

Quantum kernel methods are a promising branch of quantum machine learning, but their per- formance across data types and encoding choices remains incompletely understood. To address this gap, we developed an algorithmic framework for variational quantum kernels utilizing resource- efficient ansätze for complex classification tasks and introduced a parameter scaling technique to accelerate convergence. We conducted a comprehensive benchmark of this framework on eight chal- lenging, real-world and high-dimensional datasets covering tabular, image, time series, and graph data. Our results show that the proposed quantum kernel demonstrated competitive classification accuracy compared to standard classical kernels in classical simulation, such as the radial basis function (RBF) kernel. This work demonstrates that properly designed quantum kernels can func- tion as versatile, high-performance tools, laying a foundation for quantum-enhanced applications in machine learning. Further research is needed to fully assess the practical performance of quantum methods.

We show that any Petz $f$-divergence (where $f$ is operator convex) between quantum states admits a universal $\chi^2$-mixture representation: the distinguishability of $\rho$ from $\sigma$ is obtained as a positive superposition of quadratic contrasts $\chi^2_\lambda$, with nonnegative weights $w_f(\lambda)$ determined explicitly from the Stieltjes representation of the generator $f$. This identifies $\chi^2_\lambda$ as atomic building blocks for quantum $f$-divergences and yields closed-form $w_f$ for canonical choices (relative entropy/KL, Hellinger/Bures, R'{e}nyi). By mapping $\chi^2_\lambda$ into a classical Pearson $\chi^2$, we leverage the Chapman-Robbins variational representation and obtain a tight and universal quantum thermodynamic uncertainty relation: any $f$-divergence is lower bounded by a function of the statistics of quantum observables (mean and variance), reproducing previous and novel results in quantum thermodynamics as applications.

Classical shadow tomography offers a scalable route to estimating properties of quantum states, but the resulting reduced density matrices (RDMs) often violate constraints that ensure they represent $N$-electron states – known as $N$-representability conditions – because of statistical and hardware noise. We present a correlated purification framework based on semidefinite programming to restore accuracy to these noisy, unphysical two-electron RDMs. The method performs a bi-objective optimization that minimizes both the many-electron energy and the nuclear norm of the change in the measured 2-RDM. The nuclear norm, often employed in matrix completion, promotes low-rank, physically meaningful corrections to the 2-RDM, while the energy term acts as a regularization term that can improve the purity of the ground state. While the method is particularly effective for the ground state, it can also be applied to excited and non-stationary states by decreasing the weight of the energy relative to the error norm. In an application to fermionic shadow tomography of large hydrogen chains, correlated purification yields substantial reductions in both energy and 2-RDM error, achieving chemical accuracy across dissociation curves. This framework provides a robust strategy for tomography in many-body quantum simulations.

High-dimensional entanglement offers significant advantages over its low-dimensional counterpart in various information-processing tasks. However, to harness these advantages, it is crucial that the quantum channels used to store or transmit the subsystems of an entangled system not only preserve entanglement but also maintain its dimensionality above a certain threshold. The maximum entanglement dimension that a channel can preserve is referred to as its effective dimensionality, since the channel cannot be used to transmit information of dimension greater than that in a single use. In this work, we present a method to certify whether a quantum channel can preserve entanglement dimension above a given threshold. Unlike existing approaches, our method is faithful, i.e., it can be applied to any channel, and avoids common assumptions such as preparation of entangled states, auxiliary side channels, or perfect measurement devices. Moreover, the method can be extended to faithfully certify other classes of non-resource-breaking channels, such as non-nonpositive-partial-transpose-breaking channels (non-NPT-breaking channels). Finally, we discuss possible experimental realizations of our certification scheme through explicit examples.

The Equivariant Quantum Circuit (EQC) for the Travelling Salesman Problem (TSP) has been shown to achieve near-optimal performance in solving small TSP problems (up to 20 nodes) using only two parameters at depth 1. However, extending EQCs to larger TSP problem sizes remains challenging due to the exponential time and memory for quantum circuit simulation, as well as increasing noise and decoherence when running on actual quantum hardware. In this work, we propose the Size-Invariant Grid Search (SIGS), an efficient training optimization for Quantum Reinforcement Learning (QRL), and use it to simulate the outputs of a trained Depth-1 EQC up to 350-node TSP instances - well beyond previously tractable limits. At TSP with 100 nodes, we reduce total simulation times by 96.4%, when comparing to RL simulations with the analytical expression (151 minutes using RL to under 6 minutes using SIGS on TSP-100), while achieving a mean optimality gap within 0.005 of the RL trained model on the test set. SIGS provides a practical benchmarking tool for the QRL community, allowing us to efficiently analyze the performance of QRL algorithms on larger problem sizes. We provide a theoretical explanation for SIGS called the Size-Invariant Properties that goes beyond the concept of equivariance discussed in prior literature.

Understanding the influence of atmospheric turbulence on the propagation of entangled biphoton states is essential for free-space quantum communication protocols. Using the extended Huygens-Fresnel principle and the Kolmogorov turbulence model, we derive an analytical expression for the combined density operator of the signal and idler fields generated via SPDC, following propagation through separate turbulent channels. By expressing this density operator in the continuous position basis, we show how the spatial correlations between signal and idler persist through turbulence despite the loss of state purity, as they transition from being quantum to classical in nature. We further identify a finite range of propagation distances over which the angle-OAM entanglement is maximized, which provides valuable insights for designing free-space quantum communication links operating over several kilometers through the turbulent atmosphere.

Theories of gravity in which the metric is fundamentally classical predict stochastic fluctuations in the gravitational field. In this article, we study the stochastic Klein-Gordon equation as a starting point to understand the phenomenology of linearised classical-quantum hybrid gravity. In particular, we describe how to compute the non-equilibrium two point function of the scalar field, showing explicitly the role of the initial state in regulating divergences. To do so, we use a "mod-squared-retarded" pole-prescription and find that the covariance in the field is non-zero only outside the lightcone, scales inversely with the spatial distance of the spacetime points and grows linearly in time. The energy has a contact divergence similar to that found in the quantum case. We conclude by discussing possible implications of anomalous diffusion for hybrid theories of gravity, especially looking at the energy density in the predicted gravitational waves background, which can be inferred from the scalar covariances.

Distributed architecture is a promising route to scaling fault-tolerant quantum computing (FTQC) beyond the inherent limitations of single processors. For practical implementation of distributed FTQC, logical Bell pair preparation must be designed not only for efficient Bell pair consumption but also for the spacetime volume of the protocol; however, entanglement distillation protocols have primarily focused on minimizing the consumption of Bell pairs, often resulting in protocols that require a substantial number of local operations. To resolve this issue, we introduce a metric for characterizing the practical cost of preparing high-fidelity logical Bell pairs, link-limited volume (LLV), which is a circuit-volume metric incorporating both the cost of physical Bell pairs and the spacetime volume of local operations. Guided by this metric, we propose entanglement boosting protocol, which achieves efficient preparation of logical Bell pairs encoded in rotated surface code with LLV reduced by orders of magnitude compared to prior state-of-the-art methods. In this protocol, paralleling recent advances in magic state cultivation, we employ soft-information decoders and postselection to suppress the logical error rates of Bell pairs to practical levels in the order of $10^{-10}$ from 86 noisy physical Bell pairs at 1% error, while all local operations are implementable within a spatial region of a single surface code patch with 2D local connectivity. We also present a pipelined implementation of entanglement distillation using high-rate quantum error-correcting codes, enabling arbitrarily low logical error rates while also maintaining physically efficient implementations. These results pave the way for the practical implementation of distributed FTQC, reinforcing the benefits of fast interconnect technologies and serving as a guiding principle for the efficient design of protocols and devices.

We investigate the dynamics of key quantum correlations - Negativity (NG), Quantum Discord (QD), and Quantum-Memory-Assisted Entropic Uncertainty (QM-EUR) - in a bipartite two-qubit system under the influence of external pulses and various decoherence channels, including amplitude damping (gamma_amp), pure dephasing (gamma_deph), and pulse-induced dephasing (G), while different regimes of inter-qubit coupling (Jzz, Jxx), qubit energy splitting (epsilon), and pulse parameters (A_pulse, beta_pulse) are explored. Our results show that inter-qubit coupling and energy splitting epsilon significantly influence the dynamics, producing pronounced oscillations in the weak-coupling regime and protecting pre-existing entanglement in the strong-coupling regime. NG is the most sensitive, QD persists longer revealing nonclassical correlations independent of entanglement, and QM-EUR reflects residual quantum memory and entropic uncertainty, showing that quantum signatures survive even when NG and QD are weak. Pulse amplitude and width effectively control the generation and dissipation of correlations, while the intensity of pulse-induced dephasing modulates the balance between sustained oscillations and rapid decoherence. The initial state also plays a crucial role: a partially entangled initial state is more resilient to perturbations, preserving correlations over time, whereas a separable state exhibits cycles of entanglement creation and destruction. Thus, by adjusting system parameters, it is possible to control the stability and lifetime of correlations and coherence, providing a framework to optimize quantum systems for applications requiring both strong entanglement and long-lasting coherence, such as quantum computing and secure communication.

Machine learning models are used for pattern recognition analysis of big data, without direct human intervention. The task of unsupervised learning is to find the probability distribution that would best describe the available data, and then use it to make predictions for observables of interest. Classical models generally fit the data to Boltzmann distribution of Hamiltonians with a large number of tunable parameters. Quantum extensions of these models replace classical probability distributions with quantum density matrices. An advantage can be obtained only when features of density matrices that are absent in classical probability distributions are exploited. Such situations depend on the input data as well as the targeted observables. Explicit examples are discussed that bring out the constraints limiting possible quantum advantage. The problem-dependent extent of quantum advantage has implications for both data analysis and sensing applications.

In addition to topological lattice defects such as dislocations and disclinations, crystals are also accompanied by unavoidable ordinary defects, devoid of any non-trivial geometry or topology, among which vacancies, Schottky defects, substitutions, interstitials, and Frenkel pairs are the most common. In this work, we demonstrate that these ubiquitous ordinary lattice defects, although geometrically trivial, can nonetheless serve as universal probes of the non-trivial topology of electronic Bloch bands, and any change in the local topological environment in an otherwise normal insulator in terms of mid-gap bound states in their vicinity. We theoretically establish these generic findings by implementing a minimal model Hamiltonian describing time-reversal symmetry breaking topological and normal insulators on a square lattice, fostering such point defects. The defect-bound mid-gap modes are also shown to be robust against sufficiently weak random point-like charge impurities. Furthermore, we showcase experimental observation of such bound states by embedding ordinary crystal defects in two-dimensional acoustic Chern lattices, where precision-controlled hopping amplitudes are implemented via active meta-atoms and Green's-function-based spectroscopy is used to reconstruct spectra and eigenstates. Our combined theory-experiment study establishes ordinary lattice defects as probes of topology that should be germane in crystals of any symmetry and dimension, raising the possibility of arresting localized Majorana modes near such defects in the bulk of topological superconductors and to emulate ordinary-defect-engineered topological devices.

Quantum theory of geometrically frustrated systems is usually approached as a gauge theory where the local conservation law becomes the Gauss law. Here we show that it can do something fundamentally different: enforce a global conserved quantity via a non-perturbative tiling invariant, rigorously linking microscopic geometry to a new macroscopically phase-coherent state. In a frustrated bosonic model on the honeycomb lattice in the cluster-charging regime at fractional filling, this mechanism protects a conserved global quantum number, the sublattice polarization $\tilde{N} = N_A - N_B$. Quantum fluctuation drives the spontaneous symmetry breaking of this global U(1) symmetry to result in a supernematic (SN) phase – an incompressible yet phase-coherent quantum state that breaks rotational symmetry without forming a superfluid or realizing topological order. This establishes a route to a novel quantum many-body state driven by combinatorial constraints.

Spontaneous collective decay in incoherently driven atomic ensembles can generate macroscopic coherence in the steady state, as exemplified by steady-state superradiance in single-mode cavities. Whether spontaneous order persists beyond the Dicke limit, where competing collective decay channels and light propagation might preclude an ordered phase, remains an open question. We address it by analyzing incoherently pumped atoms coupled to one-dimensional electromagnetic baths through two models: a ring cavity with two bright decay channels, and a bidirectional waveguide where propagation additionally induces Hamiltonian dipole-dipole interactions. We find that both systems sustain steady-state phase order with intensity scaling as $N^2$, but that the order takes two qualitatively distinct forms, neither described by a single macroscopic dipole. In the ring cavity, individual trajectories spontaneously break mirror symmetry, locking the atomic phases and the emitted field to one of two chiral orders. In the waveguide, coherent interactions instead enforce a phase-separated steady state in which the two chiral orders coexist, each dominating one end of the array. Our results show how competition and propagation shape emergent order beyond the Dicke limit.

The speed of a fault-tolerant quantum computer depends in large part on the reaction time of its classical electronics, that is, the total time required by decoders and controllers to determine the outcome of a logical measurement and execute subsequent conditional logical operations. Despite its importance, the reaction time and its impact on the design of a logical microarchitecture of a quantum computer are not well understood. In this work, we perform a detailed system-level analysis of the classical and quantum resource requirements of a surface code based architecture. To this end, we construct a model of the reaction time in which the decoder latency is based on parallel space- and time-window decoding methods. In addition, we draw communication latencies from our envisioned quantum execution environment, which comprises a high-speed network of quantum processing units, controllers, decoders, and high-performance computing nodes. We use this model to estimate the increase in the logical error rate of magic state injections as a function of the reaction time. We then show how the microarchitecture can be optimized with respect to the reaction time, and present full-system quantum resource estimates based on realistic hardware noise parameters for executing utility-scale quantum circuits of the Fermi-Hubbard model (2562 logical qubits and $4$$\times$$10^6$ $T$ gates) and NMR spectral prediction (241 logical qubits and $5.11$$\times$$10^{11}$ $T$ gates). We numerically determine the impact of improving reaction time on the code distance required for the core processor and on the size of the resource state factory. Moreover, we analyze how decoder speeds constrain the size of practically executable circuits, and show that state-of-the-art decoders will require a performance improvement of at least an order of magnitude to execute utility-scale quantum algorithms within days.

The development of quantum computation has resulted in many quantum algorithms for a wide array of tasks. Recently, there is a growing interest in using quantum computing techniques to estimate or compute quantum information-theoretic quantities such as Renyi entropy, Von Neumann entropy, matrix means, etc. Motivated by these results, we present quantum algorithms for computing the maximal quantum $f$-divergences and the operator-theoretic matrix Kubo–Ando means. Both of them involve Renyi entropies, matrix means as special cases, thus implying the universality of our framework.

The projected ensemble – an ensemble of pure states on a subsystem conditioned on projective measurement outcomes on its complement – provides a finer probe of ergodicity and information structure than the reduced density matrix of the subsystem in bipartite quantum states. This framework can be generalised to partial projected ensembles in tripartite settings, where outcomes from part of the measured subsystem are discarded, leading to ensembles of mixed states. We show that information measures defined for such ensembles, in particular the Holevo information, yield a more detailed characterisation of how quantum information is distributed between subsystems compared to conventional entanglement measures. Using exact analytical results supported by numerical results, we uncover a qualitative change in the scaling of the Holevo information with system size in partial projected ensembles generated by Haar-random states, as the relative sizes of the subsystem are varied. In one phase, the Holevo information decays exponentially with system size, while in the other it grows linearly, thereby defining distinct information phases separated by sharp transitions signalled by non-analyticities in the Holevo information. The exponentially decaying phase rigorously establishes the existence of a measurement-invisible quantum-correlated phase – a manifestation of many-body information scrambling with no bipartite analogue. We contrast this information-phase diagram with the entanglement-phase structure of tripartite Haar-random states obtained from logarithmic negativity, and show that the Holevo information reveals additional fine structure beyond conventional entanglement measures. Finally, we show that these information phases, as characterised by the Holevo information, emerge in the dynamics of chaotic quantum circuits and discuss the associated timescales.

Finite-size general security proofs for quantum key distribution based on Rényi entropies have recently been introduced. These approaches are more flexible and provide tighter bounds on the secret key rate than traditional formulations based on the von Neumann entropy. However, deploying them requires minimizing the conditional Rényi entropy, a difficult optimization problem that has hitherto been tackled using ad-hoc techniques based on the Frank-Wolfe algorithm, which are unstable and can only handle particular cases. In this work, we introduce a method based on non-symmetric conic optimization for solving this problem. Our technique is fast, reliable, and completely general. We illustrate its performance on several protocols, whose results represent an improvement over the state of the art.

We study the interplay between crossing symmetry and entanglement in $2 \to 2$ scattering within local quantum field theories that possess an $SU(N)$ global symmetry. In particular, we recast scattering amplitudes of fixed helicity as quantum operations on the Hilbert space of internal quantum numbers, where the external states play the role of qudits. The entire space of $SU(N)$-invariant scattering operators between qudits is spanned by a minimal set of three quantum gates. Recoupling relations among quantum gates are shown to follow directly from the crossing properties of the underlying amplitudes and reveal that entanglement generated from separable states in one channel is necessarily intertwined with another. Consequently, we argue any interacting quantum field theory that realizes an $SU(N)$ global symmetry must generate entanglement in at least one scattering channel.

Quantum fluctuation plays a key role in the parametric down-conversion in the Langevin regime. In this paper, we report the experimental realization of optical parametric down-conversion in the Langevin regime on a chip. By precisely controlling the loss inherently tied to fluctuation, we observe the asymmetric Hong-Ou-Mandel dip - a hallmark of quantum fluctuation in the fluctuation-driven PDC, and the fluctuation-induced compression of single photons by nearly one order of magnitude. These findings pave the way for the manipulation of quantum fluctuation, quantum states, and system-reservoir interaction.

We study scattering of particles which obey an $SU(N)$ global symmetry through the lens of quantum computation and quantum algorithms. We show that for scattering between particles which transform in the fundamental or anti-fundamental representations, i.e. qudits, all 2-2 scattering amplitudes can be constructed from only three quantum gates. Further, for any $N$, all 2-2 scattering channels are shown to emerge from the span of a $\mathbb{Z}_{2}$ algebra, suggesting that scattering in this context is fundamentally governed by the action of “bit flips” on the internal quantum numbers. We frame these findings in terms of quantum algorithms constructed from Linear Combinations of Unitaries and block encoding.