arXiv subjects

David A. Mazziotti

Publications and source records attributed to David A. Mazziotti.

At least 19 recordsLinked to original sources

arXiv2026

Collective Excitonic Entanglement in Singlet Fission

Singlet fission, the conversion of one singlet exciton into two triplet excitons, has the potential to revolutionize solar energy production by boosting the efficiency of solar cells beyond the Shockley-Queisser limit. However, the practical realization of singlet fission remains an outstanding challenge, and its underlying mechanisms have long been debated. Here we show that singlet fission arises from a distinctive type of collective excitonic entanglement in which the excitons condense into a single particle-hole mode, the same principle that leads to the Bose-Einstein condensation of excitons. Quantitatively, this condensation appears as a large eigenvalue of the particle-hole reduced density matrix (RDM), representing multiple excitons occupying a collective mode. We utilize the particle-hole RDM to capture the intrinsic particle-hole correlations in singlet fission materials including acene crystals and covalently linked pentacene dimers, revealing how structural changes control singlet fission mechanisms and modulate the contributions of charge transfer states. The same characteristic enhancement of excitonic population in a single mode is common to the onset of exciton condensation and the mechanism of photosynthetic energy transfer. Together, our results establish a unifying framework for understanding the origins of singlet fission in terms of collective excitonic entanglement.

physics.chem-ph↗

arXiv2026

A differential derivation of the Obara-Saika relation for Gaussian electron repulsion integrals

The Obara-Saika (OS) method is one of the most widely used techniques in quantum chemistry for evaluating electron repulsion integrals (ERIs) via a set of recurrence relations that build higher angular momentum integrals from lower-order ones. The original derivation by Obara and Saika proceeded by directly relating integrals of differing angular momentum. In this work, we present a compact novel derivation of the OS vertical recurrence relation based solely on differential relations between Gaussian basis functions, expanding on a method suggested in earlier work. By explicitly deriving the required derivative expressions we identify all non-zero primitive terms contributing to the full ERI to develop a hierarchical formulation of the OS recursion relations. This approach has pedagogical value as a rigorous and self-contained derivation. Additionally, the resulting organization exposes independent primitive derivative quantities and may be useful for code generation and parallel implementations on modern GPU architectures.

physics.chem-ph↗

arXiv2026

Representability for Quantum Theory beyond Particle-Number Conservation

Representability determines when a two-particle reduced density matrix (2-RDM) corresponds to a physical quantum state, enabling many-particle quantum calculations with 2-RDMs rather than the wave function. In this Letter, we present a solution of the representability problem for quantum systems without particle-number conservation. The physically allowed set of 2-RDMs can be characterized from a geometrically `orthogonal' set, the polar cone. We derive explicit linear equations for the two-body operators in the polar cone -- the intersection of the $p$-positive cone with the two-body operator space -- to obtain a systematic hierarchy of representability conditions that do not depend on higher RDMs or the wave function. Moreover, by augmenting these conditions with the particle-number variance, we obtain a unified framework for treating both particle-number-conserving and nonconserving systems. We illustrate with a spin system and molecular H$_4$.

quant-ph↗

arXiv2026

Direct Variational Calculation of Two-Electron Reduced Density Matrices via Semidefinite Machine Learning

We introduce a data-driven framework for approximating the convex set of $N$-representable two-electron reduced density matrices (2-RDMs). Traditional approaches characterize this set through linear matrix inequalities that define its supporting hyperplanes. Here, we instead learn a vertex-based approximation to its boundary from molecular data and use this information to improve the set defined by low-order positivity constraints, without explicitly constructing higher-order conditions. The resulting semidefinite machine learning approach -- combining an input convex neural network with semidefinite programming -- drives a direct variational calculation of the 2-RDM with enhanced accuracy at computational cost comparable to two-positivity calculations. Applications to the potential energy curves of ${\rm C}_2^{2-}$, ${\rm N}_2$, and ${\rm O}_2^{2+}$ demonstrate these systematic improvements as well as close agreement with complete active space configuration interaction results. Overall, semidefinite machine learning interweaves data-driven boundary information with semidefinite positivity constraints to yield more accurate energies and 2-RDMs without explicit higher-order positivity conditions.

physics.chem-ph↗

arXiv2025

Size-Consistent Quantum Chemistry on Quantum Computers

Hybrid quantum-classical algorithms have begun to leverage quantum devices to efficiently represent many-electron wavefunctions, enabling early demonstrations of molecular simulations on real hardware. A key prerequisite for scalable quantum chemistry, however, is size consistency: the energy of non-interacting subsystems must scale linearly with system size. While many algorithms are theoretically size-consistent, noise on quantum devices may couple nominally independent subsystems and degrade this fundamental property. Here, we systematically evaluate size consistency on quantum hardware by simulating systems composed of increasing numbers of non-interacting H$_{2}$ molecules using optimally shallow unitary circuits. We find that molecular energies remain size-consistent within chemical accuracy for an estimated 118 and 71 H$_{2}$ subsystems for one- and two-qubit unitary designs, respectively, demonstrating that current quantum devices preserve size consistency over chemically relevant system sizes and supporting the feasibility of scalable, noise-resilient simulation of strongly correlated molecules and materials.

quant-ph↗

arXiv2025

Witnessing Entanglement in Mixed-Particle Quantum Systems

We introduce an entanglement witness that identifies off-diagonal long-range order (ODLRO) -- a distinctive form of entanglement -- in systems containing both fermionic and bosonic particles. By analyzing the particle-hole reduced density matrices of each subsystem, the approach detects ODLRO independently in both fermionic and bosonic sectors and identifies when long-range order develops across the entire mixed-particle system. The witness also quantifies the magnitude of ODLRO within each particle type, revealing how fermionic and bosonic correlations combine to form the total entanglement of the system, including a bosonic condensation of particle-hole pairs driven by many-body correlations rather than particle statistics. Using the Lipkin-Meshkov-Glick spin model, we show how the transition from ODLRO localized to one particle type to ODLRO shared by both particle types captures the onset of collective entanglement in a mixed-particle environment, providing new insight into systems where fermionic and bosonic correlations coexist.

quant-ph↗

arXiv2025

Entanglement Witnesses of Condensation for Enhanced Quantum Sensing

Quantum phenomena such as entanglement provide powerful resources for enhancing classical sensing. Here, we theoretically show that collective entanglement of spin qubits, arising from a condensation of particle-hole pairs, can strongly amplify transitions between ground and excited spin states, potentially improving signal contrast in optically detected magnetic resonance. This collective state exhibits an $\mathcal{O}(\sqrt{N})$ enhancement of the transition amplitude with respect to an applied microwave field, where $N$ is the number of entangled spin qubits. We computationally realize this amplification using an ensemble of $N$ triplet spins with magnetic dipole interactions, where the largest transition amplitudes occur at geometries for which the condensation of particle-hole pairs is strongest. This effect, robust to noise, originates from the concentration of entanglement into a single collective mode, reflected in a large eigenvalue of the particle-hole reduced density matrix -- an entanglement witness of condensation analogous to off-diagonal long-range order, though realized here in a finite system. These results offer a design principle for quantum sensors that exploit condensation-inspired entanglement to boost sensitivity in spin-based platforms.

quant-ph↗

arXiv2025

Qumode-Based Variational Quantum Eigensolver for Molecular Excited States

We introduce the Qumode Subspace Variational Quantum Eigensolver (QSS-VQE), a hybrid quantum-classical algorithm for computing molecular excited states using the Fock basis of bosonic qumodes in circuit quantum electrodynamics (cQED) devices. This approach harnesses the native universal gate sets of qubit-qumode architectures to construct highly expressive variational ansatze, offering potential advantages over conventional qubit-based methods. In QSS-VQE, the electronic structure Hamiltonian is first mapped to a qubit representation and subsequently embedded into the Fock space of bosonic qumodes, enabling efficient state preparation and reduced quantum resource requirements. We demonstrate the performance of QSS-VQE through simulations of molecular excited states, including dihydrogen and a conical intersection in cytosine. Additionally, we explore a bosonic model Hamiltonian to assess the expressivity of qumode gates, identifying regimes where qumode-based implementations outperform purely qubit-based approaches. These results highlight the promise of leveraging bosonic degrees of freedom for enhanced quantum simulation of complex molecular systems.

quant-ph↗

arXiv2025

Many-Body Time Evolution from a Correlation-Efficient Quantum Algorithm

We introduce the correlation-efficient time-evolution (CETE) algorithm for simulating quantum many-body dynamics. CETE recasts each step of time evolution as a time-independent correlation problem: the ansatz begins from a mean-field single Slater determinant and is then correlated to capture the true time-evolved state. We derive this exact ansatz from a contraction of the time-dependent Schrödinger equation onto the space of two electrons. Unlike conventional evolution by sequential short-time propagators, which must both correlate and decorrelate the state as the degree of correlation fluctuates in time, CETE correlates only once. This substantially reduces circuit depth, extending accessible simulation times on near-term quantum devices. We demonstrate the approach by simulating the time evolution of the hydrogen molecule's electronic wavefunction, highlighting the potential for the CETE algorithm to simulate strongly correlated systems on near-term devices.

quant-ph↗

arXiv2025

Correlated Purification for Restoring $N$-Representability in Quantum Simulation

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.

quant-ph↗

arXiv2025

Constrained Shadow Tomography for Molecular Simulation on Quantum Devices

Quantum state tomography is a fundamental task in quantum information science, enabling detailed characterization of correlations, entanglement, and electronic structure in quantum systems. However, its exponential measurement and computational demands limit scalability, motivating efficient alternatives such as classical shadows, which enable accurate prediction of many observables from randomized measurements. In this work, we introduce a bi-objective semidefinite programming approach for constrained shadow tomography, designed to reconstruct the two-particle reduced density matrix (2-RDM) from noisy or incomplete shadow data. By integrating $N$-representability constraints and nuclear-norm regularization into the optimization, the method builds an $N$-representable 2-RDM that balances fidelity to the shadow measurements with energy minimization. This unified framework mitigates noise and sampling errors while enforcing physical consistency in the reconstructed states. Numerical and hardware results demonstrate that the approach significantly improves accuracy, noise resilience, and scalability, providing a robust foundation for physically consistent fermionic state reconstruction in realistic quantum simulations.

quant-ph↗

arXiv2025

Entanglement Complexity in Many-body Systems from Positivity Scaling Laws

Area laws describe how entanglement entropy scales and thus provide important necessary conditions for efficient quantum many-body simulation, but they do not, by themselves, yield a direct measure of computational complexity. Here we introduce a complementary framework based on $p$-particle positivity conditions from reduced density matrix (RDM) theory. These conditions form a hierarchy of $N$-representability constraints for an RDM to correspond to a valid $N$-particle quantum system, becoming exact when the Hamiltonian can be expressed as a convex combination of positive semidefinite $p$-particle operators. We prove a general complexity bound: if a quantum system is solvable with level-$p$ positivity independent of its size, then its entanglement complexity scales polynomially with order $p$. This theorem connects structural constraints on RDMs with computational tractability and provides a rigorous framework for certifying when many-body methods including RDM methods can efficiently simulate correlated quantum matter and materials.

quant-ph↗

arXiv2025

Refining ensemble $N$-representability of one-body density matrices from partial information

The $N$-representability problem places fundamental constraints on reduced density matrices (RDMs) that originate from physical many-fermion quantum states. Motivated by recent developments in functional theories, we introduce a hierarchy of ensemble one-body $N$-representability problems that incorporate partial knowledge of the one-body reduced density matrices (1RDMs) within an ensemble of $N$-fermion states with fixed weights $w_i$. Specifically, we propose a systematic relaxation that reduces the refined problem -- where full 1RDMs are fixed for certain ensemble elements -- to a more tractable form involving only natural occupation number vectors. Remarkably, we show that this relaxed problem is related to a generalization of Horn's problem, enabling an explicit solution by combining its constraints with those of the weighted ensemble $N$-representability conditions. An additional convex relaxation yields a convex polytope that provides physically meaningful restrictions on lattice site occupations in ensemble density functional theory for excited states.

quant-ph↗

arXiv2025

Spin adaptation of the cumulant expansions of reduced density matrices

We develop a systematic framework for the spin adaptation of the cumulants of p-particle reduced density matrices (RDMs), with explicit constructions for p = 1 to 3. These spin-adapted cumulants enable rigorous treatment of both S_z and S^2 symmetries in quantum systems, providing a foundation for spin-resolved electronic structure methods. We show that complete spin adaptation -- referred to as complete S-representability -- can be enforced by constraining the variances of S_z and S^2, which require the 2-RDM and 4-RDM, respectively. Importantly, the cumulants of RDMs scale linearly with system size -- size-extensive -- making them a natural object for incorporating spin symmetries in scalable electronic structure theories. The developed formalism is applicable to density-based methods (DFT), one-particle RDM functional theories (RDMFT), and two-particle RDM methods. We further extend the approach to spin-orbit-coupled systems via total angular momentum adaptation. Beyond spin, the framework enables the adaptation of RDM theories to additional symmetries through the construction of suitable irreducible tensor operators.

physics.chem-ph↗

arXiv2025

Quantum Many-body Simulations from a Reinforcement-Learned Exponential Ansatz

Solving for the many-body wavefunction represents a significant challenge on both classical and quantum devices because of the exponential scaling of the Hilbert space with system size. While the complexity of the wavefunction can be reduced through conventional ansätze (e.g., the coupled cluster ansatz), it can still grow rapidly with system size even on quantum devices. An exact, universal two-body exponential ansatz for the many-body wavefunction has been shown to be generated from the solution of the contracted Schrödinger equation (CSE), and recently, this ansatz has been implemented without classical approximation on quantum simulators and devices for the scalable simulation of many-body quantum systems. Here we combine the solution of the CSE with a form of artificial intelligence known as reinforcement learning (RL) to generate highly compact circuits that implement this ansatz without sacrificing accuracy. As a natural extension of CSE, we reformulate the wavefunction update as a Markovian decision process and train the agent to select the optimal actions at each iteration based upon only the current CSE residual. Compact circuits with high accuracy are achieved for H3 and H4 molecules over a range of molecular geometries.

quant-ph↗

arXiv2025

Bootstrapping the Electronic Structure of Quantum Materials

The last several decades have seen significant advances in the theoretical modeling of materials within the fields of solid-state physics and materials science, but many methods commonly applied to this problem struggle to capture strong electron correlation accurately. Recent widespread interest in quantum materials -- where strong correlation plays a crucial role in the quantum effects governing their behavior -- further highlights the need for theoretical methods capable of rigorously treating such correlation. Here, we present a periodic generalization of variational two-electron reduced density matrix (2-RDM) theory, a bootstrapping-type method that minimizes the ground-state energy as a functional of the 2-RDM without relying on the wavefunction. The 2-RDM is computed directly by semidefinite programming with $N$-representability conditions, ensuring accurate treatment of strongly correlated electronic systems. By exploiting translational symmetry, we significantly reduce computational scaling, enabling applications to realistic materials-scale systems. Additionally, we introduce an alternative to conventional energy band structures: natural-orbital occupation-number bands, which, being independent of mean-field assumptions, offer deeper insights into electron correlation effects. We demonstrate the effectiveness of this approach by applying the theory to hydrogen chains, molybdenum disulfide, and nickel oxide, showing that natural-orbital occupation bands correctly capture electronic character in regimes where density functional theory fails. This work represents a major step toward accurately describing the electronic structure of quantum materials using reduced density matrices rather than wavefunctions.

cond-mat.str-el↗

arXiv2025

Unitary Dilation Strategy Towards Efficient and Exact Simulation of Non-Unitary Quantum Evolutions

Simulating quantum systems with their environments often requires non-unitary operations, and mapping these to quantum devices often involves expensive dilations or prohibitive measurement costs to achieve desired precisions. Building on prior work with a finite-differences strategy, we introduce an efficient and exact single-ancilla unitary decomposition technique that addresses these challenges. Our approach is based on Lagrange-Sylvester interpolation, akin to analytical differentiation techniques for functional interpolation. As a result, we can exactly express any arbitrary non-unitary operator with no finite approximation error using an easily computable decomposition. This can lead to several orders of magnitude reduction in the measurement cost, which is highly desirable for practical quantum computations of open systems.

quant-ph↗

arXiv2024

A Molecular Perspective of Exciton Condensation from Particle-hole Reduced Density Matrices

Exciton condensation, the Bose-Einstein-like condensation of quasibosonic particle-hole pairs, has been the subject of much theoretical and experimental interest and holds promise for ultra-energy-efficient technologies. Recent advances in bilayer systems, such as transition metal dichalcogenide heterostructures, have brought us closer to the experimental realization of exciton condensation without the need for high magnetic fields. In this perspective, we explore progress towards understanding and realizing exciton condensation, with a particular focus on the characteristic theoretical signature of exciton condensation: an eigenvalue greater than one in the particle-hole reduced density matrix, which signifies off-diagonal long-range order. This metric bridges the gap between theoretical predictions and experimental realizations by providing a unifying framework that connects exciton condensation to related phenomena, such as Bose-Einstein condensation and superconductivity. Furthermore, our molecular approach integrates exciton condensation with broader excitonic phenomena, including exciton-related entanglement and correlation, unlocking potential advancements in fields like quantum materials and energy transport. We discuss connections between recent experimental and theoretical work and highlight the discoveries that may arise from approaching exciton condensation from a molecular perspective.

cond-mat.mtrl-sci↗