Pith. sign in

REVIEW 5 major objections 5 minor 119 references

Viral Lattice Theory: A Biophysical Model for Virion Motion

T0 review · 5 major / 5 minor · reviewed 2026-08-11 · deepseek-v4-flash

Pith's one-line read This paper claims collective virion motion can be modeled as a viral lattice whose phonon modes obey an uncertainty-like bound linking capsid stiffness and vibrational frequency.

desk verdict The uncertainty relation is a definitional tautology, not a derivation; the paper is a competent but padded tutorial in operator lattice dynamics wearing viral vocabulary. read the letter →

arxiv 2501.05459 v2 pith:RMFFITXJ submitted 2024-12-25 physics.bio-ph

classification physics.bio-ph
keywords virallatticephononmodescapsidstiffnessuncertaintyrelationoperatortheoryviscoelasticdampingvirionself-organizationrespiratoryaerosoltransmission
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

This paper tries to establish that an ensemble of metabolically inert virions can be modeled as a viral lattice—nodes linked by effective springs arising from Coulombic and Lennard-Jones forces—whose collective vibrations are viral phonons. It then promotes self-stiffness (the restoring force felt by a virion's own deformation modes) and phononic frequency (the oscillation frequency of a lattice mode) to non-commuting operators on a Hilbert space, and derives an uncertainty-like relation $\sigma_\omega \sigma_S \ge \frac{1}{2}|\langle \hat{D}\rangle|$ whenever $[\hat{\omega}, \hat{S}] = i\hat{D}$. If the framework holds, it would establish a fundamental limit on simultaneously specifying capsid rigidity and vibrational response, reinterpret apparent stochasticity in virion motion as deterministic chaos from rapid viral-phonon mode transitions, and point toward antivirals that target specific vibrational modes. The paper also derives a complex-damped PDE for the displacement field and argues the system is well-posed and testable with imaging and spectroscopy.

What carries the argument

The central object is the viral lattice matrix $\Lambda_\Phi$, a block-structured dynamical matrix assembled from force-constant classes $\alpha$ (self), $\beta$ (nearest neighbor), $\gamma$ (next-nearest neighbor), $\Omega$ (peripheral), and $\psi$ (inter-cellular). Passing from discrete lattice sums to a continuum gives a complex-valued displacement field $u(r,t)$ governed by a viscoelastic PDE with complex damping $\eta = \eta_R + i\eta_I$; from that PDE the paper builds a Hilbert-space operator formalism in which $\hat{S}$ and $\hat{\omega}$ are defined via functional calculus and perturbation theory. The load-bearing non-commutativity $[\hat{\omega}, \hat{S}] \ne 0$ is the mechanism that produces the paper's headline uncertainty inequality.

What would settle it

A decisive check would be ultrafast scattering or high-resolution imaging of aerosolized respiratory virions: if no periodic or paracrystalline ordering appears on picosecond-to-nanosecond timescales, the lattice premise fails. A second decisive check is to measure capsid stiffness and vibrational frequency distributions independently and see whether the product of their standard deviations can fall below the paper's bound; if it can, the uncertainty relation is refuted.

Watch

Extended reading notes

Core claim

The central claim, stated on the paper's own terms, is that virions interacting through Coulombic and Lennard-Jones potentials form a periodic viral lattice; after a continuum limit the lattice is described by a complex-valued displacement field whose collective modes are viral phonons. Recasting the dynamics in a Hilbert space, the paper defines a self-stiffness operator $\hat{S}$ and a phononic frequency operator $\hat{\omega}$, shows they generically fail to commute, and uses a general uncertainty inequality for non-commuting observables to conclude $\sigma_\omega \sigma_S \ge \frac{1}{2}|\langle \hat{D}\rangle|$ when $[\hat{\omega}, \hat{S}] = i\hat{D}$. This is offered as a fundamental bound on how precisely capsid rigidity and vibrational frequency can be known together, with consequences for capsid stability, genome release, and antiviral design. The paper also claims that transient picosecond lattice states, driven by host-supplied energy and damped by a complex viscoelastic coefficient, can sustain infectivity in aerosolized droplets.

Load-bearing premise

The load-bearing premise is Axiom 3: that virions spontaneously self-organize into periodic, free-energy-minimizing lattices under sufficient energy input, and that the collective wavelengths of interest vastly exceed inter-virion spacing; if real virion populations do not form such lattices, the phonon and uncertainty results have no physical referent.

Editorial extensions

If this is right

  • If the model is right, capsid mutations that alter self-stiffness must shift the viral phonon spectrum in a constrained way, giving a mechanical route to phenotype changes.
  • The apparent randomness of aerosolized virion motion could be deterministic mode hopping, so high-speed tracking should reveal rapid transitions among a discrete set of vibrational modes.
  • The complex-damped PDE predicts damped resonances and shifted peak frequencies; spectroscopic or mechanical perturbation experiments should see those shifts rather than sharp undamped lines.
  • Antiviral strategies could target resonant vibrational modes to destabilize capsids or trigger genome release, and virus-like particles could serve as tunable testbeds.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • Inference: the uncertainty relation is a formal consequence of choosing non-commuting operators; its physical content in a classical lattice remains to be established by showing that $\hat{S}$ and $\hat{\omega}$ correspond to independently measurable experimental quantities.
  • Inference: the aerosol-transmission picture depends on an unstated short-range ordering assumption; a testable extension is to look for transient paracrystalline order in droplets with scattering or cryo-EM, and if none appears the phonon mechanism is likely irrelevant in that regime.
  • Inference: one could test the bound directly by pairing nanoindentation stiffness measurements with inelastic light scattering on single capsids or virus-like particles, then comparing the product of variances against $\frac{1}{2}|\langle \hat{D}\rangle|$.
Share X Bluesky LinkedIn Reddit HN

Signed reviews

No signed human review yet.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

5 major / 5 minor

Summary. The manuscript proposes 'Viral Lattice Theory,' a framework in which virions are treated as nodes of a simple cubic lattice interacting through Coulomb and Lennard-Jones potentials. The authors derive a continuum PDE for a complex displacement field, introduce a Hilbert-space operator formalism with displacement, momentum, stiffness, and frequency operators, and claim a derived uncertainty relation between a virion's self-stiffness operator and its phononic frequency operator. The paper also discusses complex viscoelastic damping, well-posedness, effective Hamiltonians, and potential experimental validation. The central advertised result is Corollary 3.4, which states that σ_ω σ_S ≥ ½ |⟨D̂⟩| whenever [ω̂, Ŝ] = iD̂, and this is presented as a fundamental limit on specifying capsid rigidity and vibrational response.

Significance. If the uncertainty relation and lattice model were genuinely derived from the underlying Coulomb/Lennard-Jones interactions, the framework could provide a useful bridge between soft-matter physics, continuum mechanics, and virology, and the proposed experimental protocol would give a concrete route to falsification. The manuscript is commendably explicit in stating axioms, definitions, and a proposed validation experiment, and it engages with a broad literature on capsid mechanics. However, as it stands, the central result is not a consequence of the viral-lattice dynamics: the non-commutativity of Ŝ and ω̂ is put in by definition rather than derived, the operators are not shown to satisfy the domain and self-adjointness hypotheses of Robertson–Schrödinger, and canonical commutation relations are imported into a classical system without physical justification. The biophysical premise of spontaneously forming periodic virion lattices in respiratory aerosols is also asserted rather than evidenced. For these reasons, the significance of the paper as a source of reliable physical predictions is currently low.

major comments (5)
  1. [§3.5.3, Theorem 3.9, Eq. (3.45)] The proof of non-commutativity is circular. Theorem 3.9 assumes that the action of Ŝ on an eigenmode |φ_n(k)⟩ produces a new mode |φ'_n(k)⟩ with a different frequency ω'_n(k) ≠ ω_n(k), and then computes [Ŝ, ω̂]|φ_n(k)⟩ = (ω'_n(k) − ω_n(k))|φ'_n(k)⟩ ≠ 0. But this is true for any operator that sends each eigenvector to a different eigenvector with a different eigenvalue; it is a property of the definition of Ŝ in Definition 6.5, not a physical derivation. No computation from the dynamical matrix D(k), from the Coulomb/Lennard-Jones Hessian, or from the lattice mechanics is given that establishes the mapping U_n ↦ U'_n or the inequality ω'_n ≠ ω_n. Thus the central non-commutativity claim is an assumption built into the definitions, and Corollary 3.4 inherits this circularity.
  2. [§6.2, Definition 6.6 and Corollary 3.4] The Robertson–Schrödinger inequality is applied to operators that are not shown to satisfy its hypotheses. The inequality requires two self-adjoint operators on a common dense domain. The frequency operator ω̂ is self-adjoint only in the idealized Hermitian limit stated in Definition 6.4, while the model elsewhere explicitly allows non-self-adjoint generators with complex damping. The stiffness operator Ŝ is defined only by its action on eigenmodes in Definition 6.5; no dense domain, no closure, and no self-adjointness are established. Moreover, the operator D̂ in [ω̂, Ŝ] = iD̂ is never computed from the model parameters. Consequently, Eq. (3.41) is a formal inequality applied to operators whose commutator and spectral properties are not established, rather than a derived relation.
  3. [§6.2, Eq. (6.24)] The canonical commutation relations [û_{n,i}, p̂_{m,j}] = iℏ δ_{n,m} δ_{i,j} are imported from quantum mechanics into a classical lattice without physical justification. Axiom 2 states that virion motion is governed by classical mechanics, and the displacement and momentum variables of a classical lattice commute. Asserting a nonzero commutator with ℏ imposes a quantum structure that is not derived from any limiting procedure, coarse-graining argument, or measurement protocol. This assumption is load-bearing because the uncertainty-like relation in Corollary 3.4 is presented as a consequence of non-commuting operators; if the commutation relations are merely postulated, the central result is not derived from the viral-lattice dynamics.
  4. [§2.2, Axiom 3, and Remark 3.4] The biophysical premise that virions 'can self-organize into periodic lattice structures' under 'sufficient energy input' in aerosolized droplets is unsupported. The observational evidence cited for paracrystalline arrays concerns viral factories inside host cells (e.g., Iridoviridae), not sparse, polydisperse virions in respiratory aerosols. The continuum limit further requires wavelengths much larger than inter-virion spacing, but for realistic aerosol concentrations the virion spacing is many particle diameters and there is no basis for a periodic lattice at all. Even if the operator derivation were repaired, the claimed biological implications for aerosolized respiratory virions would require explicit estimates of virion density, interaction strength, and lattice stability in the aerosol regime.
  5. [§6.1, Theorem 6.4 and Remark 6.5] The stability analysis uses an incorrect sign convention for complex eigenvalues. With the time dependence e^{−iλt} adopted in Eq. (6.7), writing λ_n = a_n + i b_n gives e^{−iλ_n t} = e^{−i a_n t} e^{b_n t}; hence the imaginary part b_n controls exponential growth or decay, and the real part a_n controls oscillation. The theorem instead assumes a_n < 0 for stability and Remark 6.5 states that Re(λ) determines exponential decay/growth and Im(λ) sets oscillation frequency. This inverts the roles of real and imaginary parts and, if taken literally, makes the stability criterion in Theorem 6.4 incorrect. This is a concrete technical error in a section that is used to assert mode stability and damped behavior.
minor comments (5)
  1. [§3.3, Theorems 3.4 and 3.5] The Gershgorin Circle Theorem is stated twice with two different numbers (Theorem 3.4 and Theorem 3.5), and the second statement includes a proof sketch that is mislabeled. The duplicate numbering should be corrected.
  2. [§4, Definition 4.1] The continuum mass density formula ϱ(r) = lim_{a→0} mN/|Ω| is ambiguous as written; the limit should specify how N and |Ω| scale with a so that ϱ remains finite and well-defined.
  3. [§2.2, Figure 1 caption] The scale bar for the paracrystalline array is given as '200 µm'; given the virion diameters of 120–350 nm, the inset scale bar is likely intended to be 200 nm. Please verify.
  4. [§6.1, Remark 6.5] The remark uses 'negative α' where it presumably means 'negative a' in the decomposition λ = a + ib; this typo should be fixed in addition to the substantive sign issue noted in the major comments.
  5. [§5.2, Eq. (5.21)] The definition Ĥ_eff(k) := iℏ Â(k) introduces a factor ℏ with no stated justification in a classical model; if ℏ is retained only as a bookkeeping constant, this should be stated explicitly when the Hilbert-space analogy is introduced.

Circularity Check

3 steps flagged · score 8.0 of 10

The stiffness–frequency uncertainty relation is built into Definition 6.5: S-hat is defined to send eigenmodes to modes with altered frequencies, making [omega-hat, S-hat] non-zero tautological; Theorem 3.9 assumes the eigenvalue shift it purports to prove.

  1. self definitional [Section 6.2, Definition 6.5 (Self-Stiffness Operator), Eq. (6.18)]
    "More concretely, if a small change in stiffness modifies λn(k) to λ′n(k) = a′n(k) +ib′n(k) and the corresponding eigenmode Un(k) to U′n(k), then: ˆSUn(k) := U′n(k). ... In generic, non-symmetric, and non-degenerate scenarios, the action of ˆS on eigenmodes alters the imaginary parts of the eigenvalues in a mode-dependent way. Consequently, ˆω and ˆS generally fail to commute: [ˆω, ˆS] ̸= 0."

    The noncommutativity is inserted by definition. The frequency operator ω-hat is defined to be diagonal on the eigenmodes, while S-hat is defined as the operator that maps each eigenmode to a different 'perturbed' eigenmode with an altered eigenvalue. Any such map fails to commute with a diagonal operator; the nonzero commutator is therefore not a derived consequence of the lattice mechanics. No computation from the Coulomb/Lennard-Jones potential, the dynamical matrix, or the generator A establishes this action or the size of the commutator.

  2. self definitional [Section 3.3, Theorem 3.9 (Non-Commutativity of Self-Stiffness and Frequency Operators), Eq. (3.45)]
    "ˆω ˆS|ϕn(k)⟩ = ˆω|ϕ′n(k)⟩ = ω′n(k)|ϕ′n(k)⟩, ˆS ˆω|ϕn(k)⟩ = ˆS(ωn(k)|ϕn(k)⟩) = ωn(k)|ϕ′n(k)⟩, where |ϕ′n(k)⟩ is the modified mode after ˆS acts. Since ω′n(k) ̸= ωn(k) generally holds when self-stiffness changes, it follows that: [ ˆS, ˆω]|ϕn(k)⟩ = (ω′n(k) − ωn(k))|ϕ′n(k)⟩ ̸= 0."

    The proof's only input is the assertion that S-hat changes the mode frequency. But that is exactly the noncommutativity being proved: an operator defined by altering the eigenvalues of a diagonal operator cannot commute with it. The inequality ω'_n ≠ ω_n is merely asserted to hold 'generally when self-stiffness changes,' not derived from the dynamical matrix, potential, or any physical equation of motion. Thus Theorem 3.9 restates Definition 6.5 rather than providing independent evidence for noncommutation.

1 more flagged steps
  1. other [Section 6.2, Definition 6.6 and Section 3.3, Corollary 3.4]
    "Let ˆω and ˆS be as defined above, and assume [ ˆω, ˆS] = i ˆD for some operator ˆD. For a state ψ ∈ D( ˆω) ∩ D( ˆS) ⊆ H, define ... By the Robertson-Schrödinger uncertainty principle [90]: σωσS ≥ 1/2 |⟨ψ| ˆD|ψ⟩|."

    The uncertainty inequality is conditional on an assumed commutator [ω-hat, S-hat] = iD-hat, but no candidate D-hat is ever computed from the viral-lattice dynamics. Moreover, S-hat is only defined by its action on a collection of eigenvectors and is not shown to be densely defined or self-adjoint, which Robertson–Schrödinger would require. The central 'derived' relation is therefore postulated in the same breath as the operator definitions, rather than following from the Coulombic/Lennard-Jones lattice model.

full rationale

The paper's central claimed result—an uncertainty-like relation coupling virion self-stiffness and phononic frequency—is not derived from independent lattice dynamics. Definition 6.5 constructs S-hat as the operator that sends each eigenmode to a perturbed eigenmode with a different eigenvalue, while Definition 6.4 makes ω-hat diagonal on the original eigenbasis. The nonzero commutator is then mathematically automatic: any map that moves every eigenvector to a different eigenvector of a diagonal operator fails to commute with it. Theorem 3.9 makes this explicit by assuming the frequency shift ω'_n ≠ ω_n and then 'proving' noncommutativity from that assumption. Corollary 3.4 and Definition 6.6 then apply Robertson–Schrödinger to a commutator iD-hat that is never computed or derived; it is simply assumed to exist. No physical input from the Coulomb and Lennard-Jones potentials, the dynamical matrix, or the continuum PDE is used to determine S-hat or D-hat. The uncertainty relation is thus equivalent to the definition of the operators, so the central claim reduces to its own input by construction. The paper is not primarily circular through self-citation; the circularity is internal to the operator definitions and proof strategy.

Assumptions & free parameters 6 free parameters · 6 assumptions · 3 invented entities

The central claims rest on several unvalidated modeling choices: periodic lattice self-assembly, a continuum approximation, an imported quantum operator algebra, and a set of symbolic force constants and damping coefficients. The 'derivation' of the uncertainty relation is largely built into the operator definitions.

free parameters (6)
  • lattice constant a
    Sets nearest-neighbor spacing and all Hessian entries; assumed, not measured (Def. 2.5, Eq. 3.4).
  • virion mass m
    Assumed identical for all virions; appears in dynamical matrix and frequencies (Def. 3.6).
  • Coulomb charges q_i and Lennard-Jones parameters epsilon, sigma
    Needed to compute V'' and spring constants; no values given (Def. 1.3).
  • complex damping coefficients eta_R, eta_I
    Introduced to model viscoelastic environment; no values or constitutive relations (Def. 4.5).
  • Hessian force constants alpha, beta, gamma, Omega, psi
    Effective spring constants from V''; treated symbolically, no numeric values (Eq. 3.47).
  • sound speed c_s and optical parameters omega0, alpha for density of states
    Assumed for phonon density of states (Eq. 3.67-3.71).
assumptions (6)
  • domain assumption Axiom 1: Virions are metabolically inert and do not use ATP outside host.
    Used to justify classical deterministic mechanics; reasonable biology but not derived.
  • domain assumption Axiom 3: Virions self-organize into periodic lattices minimizing free energy.
    Load-bearing: no evidence for ordered lattices in aerosol droplets; see Section 3.1.
  • domain assumption Axiom 4: Total energy of the viral lattice is conserved.
    Invoked for Hamiltonian/operator formalism; conflicts with later non-conservative damping unless restricted.
  • ad hoc to paper Canonical commutation relations [u-hat, p-hat] = i h-bar are imposed on a classical lattice.
    Section 6.2 Eq. (6.24): imports quantum CCR without physical justification for virions.
  • domain assumption Continuum limit validity: wavelengths much larger than lattice spacing.
    Remark 3.4; needed to replace discrete lattice by PDE, but no scale separation shown.
  • standard math Well-posedness conditions: positive damping, ellipticity, Lipschitz domain.
    Invoked via Lumer-Phillips/Hille-Yosida; standard but not verified for the specific operators.
invented entities (3)
  • Viral phonon wavefunction psi-tilde(r,t)
    purpose: Model quantized collective vibrational modes that store/redistribute host energy and sustain infectivity.
    No direct observation; only proposed spectroscopy/imaging validation (Section 3.5.3).
  • Self-stiffness operator S-hat and frequency operator omega-hat
    purpose: Define an uncertainty-like limit between capsid rigidity and vibrational response.
    Defined functionally so that they fail to commute; no experimental handle independent of the model (Definitions 6.4-6.5).
  • Effective mass operator M-hat and mass bands
    purpose: Capture spatial/temporal mass heterogeneity in the lattice.
    Speculative operator analog, no measurement proposed (Section 6.2).

how reviews work

0 comments
Cite this review

Pith. "Pith review of Viral Lattice Theory: A Biophysical Model for Virion Motion." pith.science (2026). https://pith.science/paper/RMFFITXJ

@misc{pith2026250105459,
  author       = {Pith},
  title        = {Pith review of: Viral Lattice Theory: A Biophysical Model for Virion Motion},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/RMFFITXJ}},
  note         = {Machine review of arXiv:2501.05459}
}
read the original abstract

We present a rigorously formulated, novel operator-based framework that merges ideas from condensed matter physics, continuum mechanics, and quantum-inspired theory to analyze collective virion behavior in complex environments. By modeling metabolically inert virions, whose main interactions are Coulombic and Lennard-Jones, as nodes in a viral lattice linked by effective springs, we obtain collective vibrational modes akin to phonons in solids. A coupled, complex-valued displacement field PDE underpins our approach, enabling wave mechanics and functional analysis to define key observables, ranging from stress fields and thermodynamic responses to effective Hamiltonians. We interpret the apparent stochasticity of virion motion as deterministic chaos arising from rapid transitions among 'viral phonon' modes that store and redistribute energy from the host. Short-lived lattice states (picoseconds) may thus help sustain infectivity in aerosolized droplets of respiratory virions. Extending our operator framework, we derive an uncertainty-like relation coupling a virion's self-stiffness operator with its phononic frequency operator, underscoring fundamental limits on specifying capsid rigidity and vibrational response. We also explore transient coherence effects, akin to entanglement witness operators, which may expose critical correlations affecting capsid resilience or genome release. Our approach invites experimental validation via advanced imaging, high-resolution spectroscopy, and mechanical perturbations. By integrating aspects of soft matter physics, crystallography, statistical mechanics, and wave-based modeling, this methodology suggests new antiviral strategies targeting specific vibrational modes and guides the rational design of virus-based vectors in therapeutic or diagnostic applications.

Figures

Figures reproduced from arXiv: 2501.05459 by the authors.

Figure 1
Figure 1. Transmission electron micrographs of iridovirus cultured from the liver of a naturally diseased [PITH_FULL_IMAGE:figures/full_fig_p003_1.png] view at source ↗
Figure 2
Figure 2. Illustration of a uniformly charged virion with idealized SARS-CoV-2 virion with spikes, repre [PITH_FULL_IMAGE:figures/full_fig_p006_2.png] view at source ↗
Figure 3
Figure 3. Schematic representation of two virions with net charges and their respective electric fields. [PITH_FULL_IMAGE:figures/full_fig_p007_3.png] view at source ↗
Figures from the paper (42 more)
Figure 4
Figure 4. Figure 4: Schematic of a single virion embedded in a conceptual simple cubic lattice of virions. Such [PITH_FULL_IMAGE:figures/full_fig_p008_4.png]
Figure 5
Figure 5. Figure 5: A conceptual depiction of a virion (with a non-spherical morphology and spike proteins) embed [PITH_FULL_IMAGE:figures/full_fig_p009_5.png]
Figure 6
Figure 6. Figure 6: Two Virions Under Compressive External Force. Schematic showing two spherical virions (α and β) experiencing an external force Fapplied (red arrow). The total interaction potential Φtot(a) = ΦCoulomb(a) + ΦLJ(a) is depicted as a combination of Coulombic (blue) and Lenn…
Figure 8
Figure 8. Figure 8: This visualization represents the Hamiltonian of a viral lattice, highlighting capsid self-stiffness [PITH_FULL_IMAGE:figures/full_fig_p019_8.png]
Figure 9
Figure 9. Figure 9: Visualization of a viral lattice highlighting the interaction framework across a 2 [PITH_FULL_IMAGE:figures/full_fig_p023_9.png]
Figure 10
Figure 10. Figure 10: Viral Lattice with Phonon Mode Operators at Equilibrium. Each lattice site (rep￾resenting a virion) is labeled with a shorthand symbol (α, β, γ, Ω, etc.). Blue arrows indicate the local phonon-mode vectors derived from the Hamiltonian expansion. In this equilibrium vi…
Figure 11
Figure 11. Figure 11: Time-Dependent Lattice Response and Mode Evolution. Shown here is a later time step, illustrating how each virion site (again labeled α, β, γ, Ω, . . .) shifts under the phonon operators. The vectors now evolve in direction or magnitude, reflecting changes in local st…
Figure 14
Figure 14. Figure 14: Visualization of the quantized viral phonon wave function [PITH_FULL_IMAGE:figures/full_fig_p032_14.png]
Figure 15
Figure 15. Figure 15: The blue spiral shows the trajectory of the wave in the complex plane with real (u) and [PITH_FULL_IMAGE:figures/full_fig_p035_15.png]
Figure 17
Figure 17. Figure 17: The shifted resonance frequencies ωres as a function of wave number k for various damping coefficients ηI . The equation ωres = qΛΦ ϱ k − ηI 2ϱ highlights the interplay between elastic moduli (ΛΦ), mass density (ϱ), and the imaginary part of the damping coefficient (η…
Figure 18
Figure 18. Figure 18: Visualization of the complex-valued displacement field [PITH_FULL_IMAGE:figures/full_fig_p040_18.png]
Figure 19
Figure 19. Figure 19: The ”base” viral lattice configuration depicted in Hilbert space. Each lattice point is labeled [PITH_FULL_IMAGE:figures/full_fig_p050_19.png]
Figure 20
Figure 20. Figure 20: Conceptual depiction of the viral lattice state |Ψ(t)⟩ evolving in H, indicating elastic (red), dissi￾pative (blue), and possible stochastic (green) influences. The real part often represents in-phase or conservative dynamics; the imaginary part captures out-of-phase …
Figure 21
Figure 21. Figure 21: This visualization illustrates the frequency operator applied to the viral lattice in Hilbert [PITH_FULL_IMAGE:figures/full_fig_p055_21.png]
Figure 22
Figure 22. Figure 22: Self-Stiffness Operator in Hilbert Space. [PITH_FULL_IMAGE:figures/full_fig_p056_22.png]
Figure 23
Figure 23. Figure 23: Red arrows indicate the conjugate momenta associated with each lattice point, calculated as [PITH_FULL_IMAGE:figures/full_fig_p057_23.png]
Figure 24
Figure 24. Figure 24: Blue arrows indicate the conjugate displacement associated with each lattice point, calculated [PITH_FULL_IMAGE:figures/full_fig_p058_24.png]
Figure 25
Figure 25. Figure 25: This visualization demonstrates the interaction between virion density and displacement fields. [PITH_FULL_IMAGE:figures/full_fig_p060_25.png]
Figure 26
Figure 26. Figure 26: Time Evolution of a Discretized Viral Lattice Under a Self-Adjoint Hamiltonian. Each sub-figure illustrates a distinct time step (0, 1, and 2) for a simplified discretized viral lattice, with circles denoting equilibrium positions in a 2D slice of the Hilbert space. R…
Figure 27
Figure 27. Figure 27: Comparison of Displacement Patterns along Rows vs. Columns in a Self-Adjoint Viral Lattice. Illustrated here is a discretized viral lattice undergoing unitary (undamped) oscilla￾tions. Each site’s displacement over time can be traced either across columns (vertical sl…
Figure 28
Figure 28. Figure 28: This visualization represents the stress (ˆσ) and elastic modulus (Eˆ) operators applied to the viral lattice. Stress Vectors: Blue arrows depict the directional stress forces acting at each lattice point, derived from local strain gradients. Elastic Modulus: Orange s…
Figure 29
Figure 29. Figure 29: This visualization represents the creation (ˆa [PITH_FULL_IMAGE:figures/full_fig_p063_29.png]
Figure 30
Figure 30. Figure 30: Visualization of the energy flux operator (Jˆ) applied to the viral lattice in Hilbert space. Red arrows depict energy flux vectors, calculated as the anticommutator of displacement and momentum￾like operators. This operator highlights channels of energy flow within t…
Figure 31
Figure 31. Figure 31: Visualization of the adjoint displacement field and intensity operator in the viral lattice. Blue [PITH_FULL_IMAGE:figures/full_fig_p067_31.png]
Figure 32
Figure 32. Figure 32: Visualization of the viral coherence operator (Kˆ ) applied to the viral lattice in Hilbert space. Blue arrows depict coherence vectors, capturing pairwise correlations between normal modes. This operator acts as a rank-one-plus extension that captures pairwise correl…
Figure 33
Figure 33. Figure 33: Wave Propagation Across a Defective Viral Lattice. Each colored column represents a distinct region of the lattice, possibly with different elastic or structural properties. At each time step, mechanical waves (arrows) propagate across columns, partially reflecting an…
Figure 34
Figure 34. Figure 34: The viral lattice demonstrating temperature dependent modes. [PITH_FULL_IMAGE:figures/full_fig_p072_34.png]
Figure 35
Figure 35. Figure 35: Visualization of the viral lattice in Hilbert space with combined dynamics from the [PITH_FULL_IMAGE:figures/full_fig_p074_35.png]
Figure 36
Figure 36. Figure 36: Visualization of the viral lattice in Hilbert space, where purple arrows display the helicity, [PITH_FULL_IMAGE:figures/full_fig_p075_36.png]
Figure 37
Figure 37. Figure 37: Schematic representation of the vibrational spectrum for an ideal viral lattice. Our theo [PITH_FULL_IMAGE:figures/full_fig_p077_37.png]
Figure 38
Figure 38. Figure 38: Visualization of the evolution semigroup operator [PITH_FULL_IMAGE:figures/full_fig_p079_38.png]
Figure 39
Figure 39. Figure 39: This graphic illustrates the two-parameter evolution family [PITH_FULL_IMAGE:figures/full_fig_p081_39.png]
Figure 40
Figure 40. Figure 40: The lattice points, represented as grey circles labeled with virion classes ( [PITH_FULL_IMAGE:figures/full_fig_p083_40.png]
Figure 41
Figure 41. Figure 41: This visualization represents noise-interpretation operators applied to the viral lattice in the [PITH_FULL_IMAGE:figures/full_fig_p085_41.png]
Figure 42
Figure 42. Figure 42: Visualization of the transformed probability density functional. The plot demonstrates the [PITH_FULL_IMAGE:figures/full_fig_p087_42.png]
Figure 43
Figure 43. Figure 43: Visualization of the application of the magnetic field operator [PITH_FULL_IMAGE:figures/full_fig_p088_43.png]
Figure 44
Figure 44. Figure 44: isualization of the polar decomposition components on a unit circle viral lattice. Lattice points [PITH_FULL_IMAGE:figures/full_fig_p089_44.png]
Figure 45
Figure 45. Figure 45: Spiral operator Pˆ transforms lattice points into a spiral configuration, illustrating structures relevant to viral packing. The transformation combines amplitude (Aˆ(r, t)) and phase (ϕˆ(r, t)) operators to model energy and phase dynamics in compactly packed geometri…
Figure 46
Figure 46. Figure 46: Combined Swirl and Radial Dispersion. The operator Vˆ(r, θ, t) applies both a rotational swirl (due to Rˆ(θ, t)) and an outward radial displacement (due to Dˆ(r, t)). Over time, this leads to a spiral expansion of the viral lattice, analogous to spreading or disassemb…
Figure 47
Figure 47. Figure 47: Illustration of the Viral Clustering Vortex Operator [PITH_FULL_IMAGE:figures/full_fig_p092_47.png]
Figure 48
Figure 48. Figure 48: Visualization of spectral projection operators via Riesz projections. The eigenvalues of the [PITH_FULL_IMAGE:figures/full_fig_p093_48.png]
Figure 49
Figure 49. Figure 49: Visualizing “Entanglement Zones” Within a Viral Lattice. Shown is a discretized viral lattice where nodes represent lattice sites (e.g., capsid protein coordinates) and green lines indicate “entanglement zones” as detected by an entanglement witness Wˆ . Regions with …

Discussion (0). Continue with ORCID to comment.

Reference graph

Works this paper leans on

119 extracted references · 79 canonical work pages

  1. [1]

    Mahan, G. D. (2010). Condensed Matter in a Nutshell . Princeton University Press. ISBN: 978- 0691140162

  2. [2]

    D., & Lifshitz, E

    Landau, L. D., & Lifshitz, E. M. (1986). Theory of Elasticity (3rd ed.). Butterworth-Heinemann. ISBN: 978-0750626330

  3. [3]

    Hall, B. C. (2015). Lie Groups, Lie Algebras, and Representations: An Elementary Introduction (2nd ed.). Springer. ISBN: 978-3319134666

  4. [4]

    Woit, P. (2023). Notes on Quantum Mechanics, Representation Theory and Number Theory . Re- trieved from https://www.math.columbia.edu/ woit/LieGroups-2023/qmnumbertheory.pdf

  5. [5]

    Shankar, R. (2017). Quantum Field Theory and Condensed Matter: An Introduction . Cambridge University Press. ISBN: 978-1107171473

  6. [6]

    N., Phan, A

    Dung, D. N., Phan, A. D., Nguyen, T. T., & Lam, V. D. (2021). Effects of surface charge and environmental factors on the electrostatic interaction of fiber with virus-like particle: A case of coronavirus. AIP Advances, 11(10), 105008. https://doi.org/10.1063/5.0065147

  7. [7]

    Li, S., Erdemci-Tandogan, G., Wagner, J., van der Schoot, P., & Zandi, R. (2017). Im- pact of a nonuniform charge distribution on virus assembly. Physical Review E , 96(2), 022401. https://doi.org/10.1103/PhysRevE.96.022401

  8. [8]

    D., Dobnikar, J., & Podgornik, R

    Farrell, J. D., Dobnikar, J., & Podgornik, R. (2023). Role of genome topol- ogy in the stability of viral capsids. Physical Review Research , 5(L012040). https://doi.org/10.1103/PhysRevResearch.5.L012040

Show all 119 references
  1. [9]

    L., Pavlova, A., Fan, Z., & Gumbart, J

    Lynch, D. L., Pavlova, A., Fan, Z., & Gumbart, J. C. (2023). Understanding virus structure and dynamics through molecular simulations. Journal of Chemical Theory and Computation , 19(11), 3025–3036. https://doi.org/10.1021/acs.jctc.3c00116

  2. [10]

    Kurebayashi, Y., et al. (2020). Live Imaging of Virus-Infected Cells by Using a Sialidase- Activated Fluorogenic Probe. In Methods in Molecular Biology (Vol. 2123, pp. 179–189). Springer. https://doi.org/10.1007/978-1-0716-1258-3 13

  3. [11]

    Gallo, A., et al. (2014). Influenza A virus propagation in MDCK: Intracellular virus repli- cation kinetics and cell density effect. Vaccine VI Conference Proceedings . Retrieved from https://dc.engconfintl.org/vaccine vi/91/

  4. [12]

    J., Enquist, L

    Flint, S. J., Enquist, L. W., Racaniello, V. R., Rall, G. F., & Skalka, A. M. (2015). Principles of Virology (4th ed.). ASM Press. ISBN: 9781555819514. Retrieved from https://books.google.com/books/about/Principles of Virology.html?id=rEL2DwAAQBAJ

  5. [13]

    M., & Howley, P

    Knipe, D. M., & Howley, P. M. (Eds.). (2013). Fields Virology (6th ed.). Lippincott Williams & Wilkins. ISBN: 9781451105636. Retrieved from https://books.google.com/books/about/Fields Virology.html?id=dxIrrMrot3gC

  6. [14]

    Crick, F. H. C.; Watson, J. D. Structure of small viruses. Nature 1956, 177(4506), 473–475

  7. [15]

    Caspar, D. L. D.; Klug, A. Physical principles in the construction of regular viruses. Cold Spring Harbor Symposia on Quantitative Biology 1962, 27, 1–24

  8. [16]

    E.; Speir, J

    Johnson, J. E.; Speir, J. A. Quasi-equivalent viruses: a paradigm for protein assemblies. Journal of Molecular Biology 1997, 269(5), 665–675

  9. [17]

    G.; Johnson, J

    Rossmann, M. G.; Johnson, J. E. Icosahedral RNA virus structure. Annual Review of Biochemistry 2013, 82, 805–841

  10. [18]

    Theoretical aspects of virus capsid assembly

    Zlotnick, A. Theoretical aspects of virus capsid assembly. Journal of Molecular Recognition 2005, 18(6), 479–490. 100

  11. [19]

    C.; Shepherd, C

    Natarajan, P.; Lander, G. C.; Shepherd, C. M.; Reddy, V. S.; Brooks, C. L., III; Johnson, J. E. Structural analysis of T=1 and T=3 icosahedral viruses: Evidence of a common capsid protein lineage. Journal of Virology 2005, 79(23), 14967–14970

  12. [20]

    F.; Cong, Y.; Liu, X.; Jakana, J.; Gorchakov, R.; Baker, M

    Zhang, R.; Hryc, C. F.; Cong, Y.; Liu, X.; Jakana, J.; Gorchakov, R.; Baker, M. L.; Weaver, S. C.; Chiu, W. 3D characterization of viral genome organization at subnanometer resolution. Cell 2019, 176(2), 281–294

  13. [21]

    E.; Schwartz, C.; Rey, F

    Liu, C.; Miller, S. E.; Schwartz, C.; Rey, F. A.; Risco, C. Structures from Cryo-EM: A New Vision of the Infected Cell. Annual Review of Biophysics 2020, 49, 51–75

  14. [22]

    L.; et al

    Duran-Meza, A. L.; et al . Controlling the surface charge of simple viruses. Under review/preprint (2022)

  15. [23]

    K.; van der Schoot, P

    Kegel, W. K.; van der Schoot, P. Competing hydrophobic and screened-Coulomb interactions in hepatitis B virus capsid assembly. Biophysical Journal 2004, 86(6), 3905–3913

  16. [24]

    Bancroft, J. B. The self-assembly of spherical plant viruses. Advances in Virus Research 1970, 16, 99–134

  17. [25]

    G., Hick, P., Huang, J., Ince, I

    Chinchar, V. G., Hick, P., Huang, J., Ince, I. A., Jancovich, J. K., Marschang, R., Qin, Q., Subrama- niam, K., Waltzek, T. B., Whittington, R., Williams, T., & Zhang, Q.-Y. (2017). ICTV Virus Tax- onomy Profile: Iridoviridae. Journal of General Virology , 98(5), 890–891. doi1...

  18. [26]

    Risco, C., Fernandez de Castro, I., Sanz-Sanchez, L., & Narayan, K. (2012). Three-dimensional imaging of viral infections. Annual Review of Virology , 1, 453–473

  19. [27]

    Virus Factories

    Fernandez de Castro, I.; Tenorio, R.; Risco, C. Virus Factories. In Encyclopedia of Virology, Bam- ford, D. H.; Zuckerman, M., Eds.; Elsevier, 2021; pp 495–500

  20. [28]

    A., Hyatt, A., Green, D

    Daszak, P., Berger, L., Cunningham, A. A., Hyatt, A., Green, D. E., & Speare, R. (1999). Emerging infectious diseases and amphibian population declines. Emerging Infectious Diseases, 5(6), 735–748. doi10.3201/eid0506.990601

  21. [29]

    Lipid dynamics and interactions within virus replication organelles.Annual Review of Virology 2017, 4(1), 241–260

    Altan-Bonnet, N. Lipid dynamics and interactions within virus replication organelles.Annual Review of Virology 2017, 4(1), 241–260

  22. [30]

    Ke, F., & Zhang, Q.-Y. (2022). ADR V 12L: A Ranaviral Putative Rad2 Family Protein Involved in DNA Recombination and Repair. Viruses, 14(5), 908. doi10.3390/v14050908

  23. [31]

    Israelachvili, J. (2011). Intermolecular and Surface Forces (3rd ed.). Academic Press

  24. [32]

    Quantized Acoustic Phonons Map the Dynamics of a Single Virus

    Zhang, Y.; Wu, R.; Shahjahan, M.; Yang, C.; Pyeon, D.; Harel, E. Quantized Acoustic Phonons Map the Dynamics of a Single Virus. Preprint (2023)

  25. [33]

    A.; Wang, J

    Ma, X.; Hu, F.; Wei, X.; Su, Q.; Song, C.; Liu, Y.; Markus, M. A.; Wang, J. Vibrational spectroscopy reveals symmetry-breaking vibrational couplings in virus capsids. Nature Chemistry 2014, 6, 186– 192

  26. [34]

    Mempin, R., et al. (2013). Release of extracellular ATP by bacteria during growth . BMC Microbiol- ogy, 13(1), 1-10

  27. [35]

    M., & Deamer, D

    Becker, W. M., & Deamer, D. W. (1983). The World of the Cell . Benjamin/Cummings Publishing Company

  28. [36]

    Pavelin, J., & Wadhams, G. H. (2017). Bacterial Chemotaxis: A New Player in Bacterial–Host Interactions. Advances in Applied Microbiology, 100, 1-26

  29. [37]

    Giuliani, A., et al. (2007). Emergence of order in collective dynamics: transitions from local to global behavior in complex systems . Frontiers in Bioscience, 12, 2459-2471

  30. [38]

    Mirzadeh, M., & Kahrizi, D. (2008). Thermodynamic properties and phase transitions in viral cap- sids. Journal of Theoretical Biology, 251(3), 478-484

  31. [39]

    Tzlil, S., et al. (2004). A statistical-thermodynamic model of viral assembly . Biophysical Journal, 86(4), 2037-2048. 101

  32. [40]

    Noether, E. (1918). Invariante Variationsprobleme . Nachrichten von der Gesellschaft der Wis- senschaften zu G¨ ottingen, Mathematisch-Physikalische Klasse, 235-257

  33. [41]

    Goldstein, H., Poole, C., & Safko, J. (2002). Classical Mechanics (3rd ed.). Addison-Wesley

  34. [42]

    M., & Simon, M

    Vogt, V. M., & Simon, M. N. (1999). Mass Determination of Rous Sarcoma Virus Viri- ons by Scanning Transmission Electron Microscopy. Journal of Virology , 73(8), 7050-7055. https://doi.org/10.1128/JVI.73.8.7050-7055.1999

  35. [43]

    J., Kettleson, E., Ramaswami, B., Chen, D

    Hogan, C. J., Kettleson, E., Ramaswami, B., Chen, D. R., & Biswas, P. (2006). Charge reduced elec- trospray size spectrometry of mega- and gigadalton complexes: whole viruses and virus fragments. Analytical Chemistry, 78(3), 844-852. https://doi.org/10.1021/ac051571i

  36. [44]

    Katz, G., Benkarroum, Y., Wei, H., Rice, W., Bucher, D., Alimova, A., Katz, A., Klukowska, J., Herman, G., & Gottlieb, P. (2014). Morphology of Influenza B/Lee/40 Determined by Cryo-Electron Microscopy. PLoS ONE, 9, e88288. https://doi.org/10.1371/journal.pone.0088288

  37. [45]

    Kittel, C. (2005). Introduction to Solid State Physics (8th ed.). Wiley

  38. [46]

    Frenkel, D., & Smit, B. (2002). Understanding Molecular Simulation: From Algorithms to Applica- tions (2nd ed.). Academic Press

  39. [47]

    P., & Tildesley, D

    Allen, M. P., & Tildesley, D. J. (1987). Computer Simulation of Liquids . Oxford University Press

  40. [49]

    Ciarlet, P. G. (1988). Mathematical Elasticity: Volume I: Three-Dimensional Elasticity . North- Holland

  41. [50]

    Born, M., & Huang, K. (1998). Dynamical Theory of Crystal Lattices . Oxford University Press

  42. [51]

    Evans, L. C. (2010). Partial Differential Equations (2nd ed.). American Mathematical Society

  43. [52]

    G., Hyatt, A., Miyazaki, T., & Williams, T

    Chinchar, V. G., Hyatt, A., Miyazaki, T., & Williams, T. (2009). Family Iridoviridae: Poor viral relations no longer. Current Topics in Microbiology and Immunology , 328, 123–170

  44. [53]

    L., et al

    Ivanovska, I. L., et al. (2004). Bacteriophage capsids: Tough nanoshells with complex elastic prop- erties. PNAS, 101(20), 7600–7605

  45. [54]

    H., & Wuite, G

    Roos, W. H., & Wuite, G. J. (2010). Nano-indentations of viral capsids: probing the mechanical function of an infectious organelle. Biophysical Journal, 99(4), 1175–1181

  46. [55]

    Wuite, G. J. L. et al., ”Single-molecule studies of viral DNA packaging and ejection,” Curr. Opin. Virol. 2, 68–74 (2008)

  47. [56]

    et al., ”Mechanical processes in biochemistry,” Annu

    Bustamante, C. et al., ”Mechanical processes in biochemistry,” Annu. Rev. Biochem. 83, 523–547 (2014)

  48. [57]

    Kato, T. (1995). Perturbation Theory for Linear Operators . Springer

  49. [58]

    Condensed Matter Field Theory, 2nd ed.; Cambridge University Press, 2010

    Altland, A.; Simons, B. Condensed Matter Field Theory, 2nd ed.; Cambridge University Press, 2010

  50. [59]

    Electronic Transport in Mesoscopic Systems ; Cambridge University Press, 1995

    Datta, S. Electronic Transport in Mesoscopic Systems ; Cambridge University Press, 1995

  51. [60]

    Luzzati, V.; Vachette, P.; Sackett, D. L. Is the gel to liquid-crystal transition of phospholipid bilayers coupled to a general mechanism of pressure sensing in membranes?Biophysical Journal 2004, 86(4), 2547–2550

  52. [61]

    Many-Body Quantum Theory in Condensed Matter Physics: An Introduc- tion; Oxford University Press, 2004

    Bruus, H.; Flensberg, K. Many-Body Quantum Theory in Condensed Matter Physics: An Introduc- tion; Oxford University Press, 2004

  53. [62]

    Mahan, G. D. Many-Particle Physics , 3rd ed.; Springer, 2000

  54. [63]

    K.; Beale, P

    Pathria, R. K.; Beale, P. D. Statistical Mechanics, 3rd ed.; Academic Press, 2011

  55. [64]

    Molecular Biology of the Cell , 6th ed.; Garland Science, 2015

    Alberts, B.; Johnson, A.; Lewis, J.; Morgan, D.; Raff, M.; Roberts, K.; Walter, P. Molecular Biology of the Cell , 6th ed.; Garland Science, 2015. 102

  56. [65]

    A., Jr.; Travers, P.; Walport, M.; Shlomchik, M

    Janeway, C. A., Jr.; Travers, P.; Walport, M.; Shlomchik, M. J. Immunobiology, 5th ed.; Garland Science, 2001

  57. [66]

    L.; Cox, M

    Nelson, D. L.; Cox, M. M. Lehninger Principles of Biochemistry , 5th ed.; W. H. Freeman, 2008

  58. [67]

    K¨ onig, R., & Stertz, S. (2015). Recent strategies and progress in identifying host factors involved in virus replication. Current Opinion in Microbiology , 26, 79-88. https://doi.org/10.1016/j.mib.2015.06.001

  59. [68]

    Fischer, M. G. (2020). Virophages go viral: the astonishing worldwide ubiquity of virophage se- quences. New Microbes and New Infections, 34, 100622

  60. [70]

    Initial-Boundary Value Problems and the Navier-Stokes Equations ; Aca- demic Press, 1989

    Kreiss, H.-O.; Lorenz, J. Initial-Boundary Value Problems and the Navier-Stokes Equations ; Aca- demic Press, 1989

  61. [73]

    Hagan, M. F. (2008). Controlling viral capsid assembly with templating. Phys. Rev. E, 77, 051904

  62. [74]

    Zlotnick, A., & Mukhopadhyay, S. (2011). Virus assembly, allostery and antivirals. Trends Micro- biol., 19(1), 14–23

  63. [75]

    Lakes, R. S. (2009). Viscoelastic Materials. Cambridge University Press

  64. [76]

    Harvey, S. C. (2015). The Mechanics of Viral Shell Assembly. Biophys. J., 109(1), 1–2

  65. [77]

    J., & Pincet, F

    Bustamante, C., Bryer, A. J., & Pincet, F. (2021). Single-molecule studies of nucleic acid motors reveal structural dynamics and mechanochemical coupling. Nat. Rev. Mol. Cell Biol., 22, 529–547

  66. [78]

    Mateu, M. G. (2013). Mechanical properties of viruses analyzed by atomic force microscopy: A virological perspective. Virus Research, 168, 1–22

  67. [79]

    Reed, M., & Simon, B. (1975). Methods of Modern Mathematical Physics II: Fourier Analysis, Self-Adjointness. Academic Press

  68. [80]

    Sakurai, J. J. (1995). Modern Quantum Mechanics (Revised ed.). Addison-Wesley

  69. [81]

    Dirac, P. A. M. (1981). The Principles of Quantum Mechanics (4th ed.). Oxford University Press

  70. [82]

    Reed, M., & Simon, B. (1972). Methods of Modern Mathematical Physics I: Functional Analysis . Academic Press

  71. [83]

    Teschl, G. (2014). Mathematical Methods in Quantum Mechanics . American Mathematical Society

  72. [84]

    Reed, M., & Simon, B. (1979). Methods of Modern Mathematical Physics III: Scattering Theory . Academic Press

  73. [85]

    Pazy, A. (1983). Semigroups of Linear Operators and Applications to Partial Differential Equations . Springer

  74. [86]

    Davies, E. B. (2007). Linear Operators and their Spectra . Cambridge University Press

  75. [87]

    Da Prato, G., & Zabczyk, J. (1992). Stochastic Equations in Infinite Dimensions . Cambridge Uni- versity Press

  76. [88]

    Connes, A. (1994). Noncommutative Geometry. Academic Press

  77. [89]

    J., & Nagel, R

    Engel, K. J., & Nagel, R. (2000). One-Parameter Semigroups for Linear Evolution Equations . Springer

  78. [90]

    The Uncertainty Principle,

    H. P. Robertson, “The Uncertainty Principle,” Phys. Rev. 34 (1929), 163–164. 103

  79. [91]

    Zlotnick, A. (2003). Are weak protein–protein interactions the general rule in capsid assembly? Virology, 315(2), 269–274

  80. [92]

    Frank, J. (2014). Molecular Machines in Biology . Cambridge University Press

  81. [93]

    Hall, B. C. (2013). Quantum Theory for Mathematicians . Springer

  82. [94]

    Olver, P. J. (1993). Applications of Lie Groups to Differential Equations (2nd ed.). Springer

  83. [95]

    Lakadamyali, M., & Cosma, M. P. (2014). Advanced imaging techniques for the study of chromatin and nuclear organization. Genome Biology, 15, 458

  84. [96]

    J., Kaiser, C

    Bustamante, C. J., Kaiser, C. M., Maillard, R. A., Goldman, D. H., & Wilson, C. A. (2021). Single- molecule studies of protein folding with optical tweezers. Chemical Reviews, 121(9), 5198–5261

  85. [97]

    Mahan, G. D. (2000). Many-Particle Physics (3rd ed.). Kluwer Academic/Plenum Publishers

  86. [98]

    L., & Magenes, E

    Lions, J. L., & Magenes, E. (1972). Non-Homogeneous Boundary Value Problems and Applications , Vol. I. Springer

  87. [99]

    Reed, M., & Simon, B. (1978). Methods of Modern Mathematical Physics IV: Analysis of Operators . Academic Press

  88. [100]

    Conway, J. B. (2000). A Course in Operator Theory . American Mathematical Society

  89. [101]

    Bratteli, O., & Robinson, D. W. (1987). Operator Algebras and Quantum Statistical Mechanics 1 . Springer

  90. [102]

    W., & Mermin, N

    Ashcroft, N. W., & Mermin, N. D. (1976). Solid State Physics . Saunders College Publishing

  91. [103]

    Da Prato, G., & Zabczyk, J. (1992). Stochastic Equations in Infinite Dimensions . Cambridge University Press

  92. [104]

    C. L. Brooks III, M. Karplus, and B. M. Pettitt, Proteins: A Theoretical Perspective of Dynamics, Structure, and Thermodynamics , Adv. Chem. Phys. 71, 1 (1983)

  93. [105]

    Conformational Change of Proteins Arising from Normal Mode Calculations,

    F. Tama and Y.-H. Sanejouand, “Conformational Change of Proteins Arising from Normal Mode Calculations,” Protein Eng. 14, 1–6 (2002)

  94. [106]

    L. N. Trefethen, M. Embree, Spectra and Pseudospectra: The Behavior of Nonnormal Matrices and Operators, Princeton University Press, 2005

  95. [107]

    Temam, R. (1995). Navier-Stokes Equations and Nonlinear Functional Analysis

  96. [108]

    Sakurai, J. J. (1994). Modern Quantum Mechanics . Addison-Wesley

  97. [109]

    D., & Lifshitz, E

    Landau, L. D., & Lifshitz, E. M. (1980). Statistical Physics (3rd ed.). Pergamon Press

  98. [110]

    Zwanzig, R. (2001). Nonequilibrium Statistical Mechanics. Oxford University Press

  99. [111]

    Latushkin, Y., & Shvydkoy, R. (2014). Dichotomies in Random Evolution Equations: Nonau- tonomous Case. Israel Journal of Mathematics , 199(1), 297–327

  100. [112]

    N., & Embree, M

    Trefethen, L. N., & Embree, M. (2005). Spectra and Pseudospectra: The Behavior of Nonnormal Matrices and Operators. Princeton University Press

  101. [113]

    Bender, C. M. (2007). Making sense of non-Hermitian Hamiltonians. Reports on Progress in Physics, 70(6), 947–1018

  102. [114]

    Heiss, W. D. (2012). The physics of exceptional points. Journal of Physics A: Mathematical and Theoretical, 45(44), 444016

  103. [116]

    Mateu, M. G. (2012). Mechanical properties of viruses analyzed by atomic force microscopy: a virological perspective. Virus Research, 168(1), 1–22. 104

  104. [117]

    Horodecki, R., Horodecki, P., Horodecki, M., & Horodecki, K. (2009). Quantum entanglement. Reviews of Modern Physics, 81 (2), 865

  105. [118]

    M., & Torell, L

    Mullins, W. M., & Torell, L. M. (2018). Brillouin scattering: Characterization of living matter. Annual Review of Physical Chemistry , 69, 331–353

  106. [119]

    Jacrot, B. (1976). The study of biological structures by neutron scattering from solution. Reports on Progress in Physics , 39(10), 911–953

  107. [120]

    Amini, S., et al. (2020). High-frequency micromechanical resonances in viral capsids. Nature Physics, 16, 219–225

  108. [121]

    F., et al

    Garmann, R. F., et al. (2019). Physical principles in the self-assembly of a simple spherical virus. Biophysical Journal,

  109. [122]

    Wuite, G. J. L., et al. (2019). Studying mechanical properties of viruses using optical tweezers. Current Opinion in Virology , 36, 32–37

  110. [123]

    H., Baker, M

    Zhou, Z. H., Baker, M. L., Jiang, W., Rixon, F. J., & Chiu, W. (2000). Arrangement of VP26 and the Triplex Proteins in Herpes Simplex Virus-1 Capsids. Journal of Virology , 74(3), 1663–1673

  111. [124]

    Zlotnick, A. (2015). Theoretical aspects of virus capsid assembly. Journal of Molecular Biology , 428(5), 821–837. 105

Pith tools

Reviewed August 11, 2026 · model on record in the stance chip above.