# Features

i-PI includes a large number of sophisticated methods, that have been contributed over the years by many people. While the core of i-PI is focused on molecular dynamics simulations, and path integral methods in particular, several techniques have been implemented that benefit from the decoupling of force evaluation and nuclear positions evolution. Here you will find a comprehensive list, that we try to keep updated. Please get in touch if we are missing something or someone, and please format your contribution section following this template.

Developers receive too little recognition for their implementation efforts. For this reason, we list together with every feature not only the paper(s) that first introduced the methods, but also those that were connected with the implementation of the method in i-PI. Finding these features readily available is saving you weeks of work: reward the developers by spending 15 seconds to add one more citation to your manuscript!

- Thermodynamic integrations (dev)
- Finite-differences Suzuki-Chin PIMD (dev)
- Reweighting-based high-order PIMD (dev)
- Perturbed Path Integrals (dev)
- Geometry Optimization (dev)
- Finite-differences Vibrational Analysis (dev)
- Multiple Time Step integrators (dev)
- Ring-Polymer Contraction
- Direct Estimators for Isotope Fractionation (dev)
- Free-energy Perturbation Estimators for Isotope Fractionation (dev)
- Quantum Alchemical Transformation (dev)
- Langevin Sampling for Noisy or Dissipative Forces (dev)
- Path Integral GLEs
- Generalized Langevin Equation Thermostats
- Path-Integral Langevin Equation Thermostats
- Path Integrals at Constant Pressure
- Path Integral Molecular Dynamics

### Thermodynamic integrations

Thermodynamic integrations are made easy with i-PI, through the connection of different sockets and the different weights one can assign to different forces. It is possible to do harmonic (Debye model) to anharmonic integration, or integrations between different kinds of potentials. Also, quantum thermodynamic integrations relative to mass are easily done through the manual input of each atom’s masses.

**Main contributors:** Mariana Rossi, Michele Ceriotti

**Implementation:**

M. Rossi, P. Gasparotto, M.Ceriotti *“Anharmonic and Quantum Fluctuations in Molecular Crystals: A First-Principles Study of the Stability of Paracetamol”*, Phys. Rev. Lett. 117, 115702 (2016)

DOI: 10.1103/PhysRevLett.117.115702 — BIBTEX: fetch

### Finite-differences Suzuki-Chin PIMD

Suzuki-Chin PIMD gives better convergence w.r.t. the number of imaginary time slices as compared to the standard Trotter scheme. The implementation uses a symplectic and time-reversible finite-difference algorithm to compute high order corrections to traditional PIMD for any empirical or ab initio forcefield.

**Main contributors:** Venkat Kapil, Michele Ceriotti

**Implementation and Theory:**

V.Kapil, J.Behler, M.Ceriotti *“High order path interals made easy”*, J. Chem. Phys. 145, 234103 (2016)

DOI: 10.1063/1.4971438 — BIBTEX: fetch

**Theory:**

S.Jang, S.Jang, G.A.Voth *“Applications of higher order composite factorization schemes in imaginary time path integral simulations “*, J. Chem. Phys. 115, 7832 (2001)

DOI: 10.1063/1.1410117 — BIBTEX: fetch

S.A.Chin *“Symplectic integrators from composite operator factorizations”*, Phys. Lett. A 226, 344 (1997)

DOI: 10.1016/s0375-9601(97)00003-0 — BIBTEX: fetch

M.Suzuki *“Hybrid exponential product formulas for unbounded operators with possible applications to Monte Carlo simulations”*, Phys. Lett. A 201, 425 (1995)

DOI: 10.1016/0375-9601(95)00266-6 — BIBTEX: fetch

### Reweighting-based high-order PIMD

The Boltzmann weight assciated with the high order correction to standard PIMD is printed out as a property so that the high order estimate of an arbitrary position-dependent observable can be computed as a weighted average.

**Main contributors:** Michele Ceriotti , Guy A. R. Brian

**Implementation:**

M.Ceriotti, G.A.R.Brian, O.Riordan, D.E.Manolopolous *“The inefficiency of re-weighted sampling and the curse of system size in high-order path integration”*, Proc. R. Soc. A 468, 2-17 (2011)

DOI: 10.1098/rspa.2011.0413 — BIBTEX: fetch

**Theory:**

S.Jang, S.Jang, G.A.Voth *“Applications of higher order composite factorization schemes in imaginary time path integral simulations “*, J. Chem. Phys. 115, 7832 (2001)

DOI: 10.1063/1.1410117 — BIBTEX: fetch

S.A.Chin *“Symplectic integrators from composite operator factorizations”*, Phys. Lett. A 226, 344 (1997)

DOI: 10.1016/s0375-9601(97)00003-0 — BIBTEX: fetch

M.Suzuki *“Hybrid exponential product formulas for unbounded operators with possible applications to Monte Carlo simulations”*, Phys. Lett. A 201, 425 (1995)

DOI: 10.1016/0375-9601(95)00266-6 — BIBTEX: fetch

### Perturbed Path Integrals

Effectively a zeroth-order cumulant expansion of the high-order PI Hamiltonian, perturbed path integrals offer an attractive approach to compute thermochemistry of materials and molecules including quantum nuclei, as a post-processing of a Trotter trajectory.

**Main contributors:** Igor Poltavski

**Theory:**

I. Poltavsky and A. Tkatchenko, *“Modeling Quantum Nuclei with Perturbed Path Integral Molecular Dynamics”*, Chem. Sci. 7, 1368 (2016)

DOI: 10.1039/C5SC03443D — BibTeX: fetch

### Geometry Optimization

Several standard algorithms for geometry optimization have been implemented to give the convenience of static calculations that are fully compatible with (PI)MD and other advanced sampling techniques.

**Main contributors:** Benjamin Helfrecht, Sophie Mutzel, Riccardo Petraglia, Yair Litman, Mariana Rossi

**Implementation:**

M. Rossi, P. Gasparotto, and M. Ceriotti, *“Anharmonic and Quantum Fluctuations in Molecular Crystals: A First-Principles Study of the Stability of Paracetamol”*, Phys. Rev. Lett. 117, 115702 (2016)

DOI: 10.1103/PhysRevLett.117.115702 — BibTeX: fetch

**Theory:**

W. H. Press, *“Numerical Recipes: The Art of Scientific Computing”*, (Cambridge University Press, 2007)

### Finite-differences Vibrational Analysis

### Multiple Time Step integrators

A multiple time step integration scheme allows for integration of different components of forces with different time steps. It becomes advantageous when the total force can be decomposed into a slowly varying expensive part and a rapidly varying cheap part. A larger time step can be used to integrate the former, there by reducing the number of expensive computations.

**Main contributors:** Venkat Kapil

**Implementation:**

V.Kapil, J.VandeVondele, M.Ceriotti *“Accurate molecular dynamics and nuclear quantum effects at low cost by multiple steps in real and imaginary time: using density functional theory to accelerate wavefunction methods”*, J. Chem. Phys. 144, 054111 (2016)

DOI: 10.1063/1.4941091 — BibTeX: fetch

**Theory:**

M.Tuckerman, B.J.Berne *“Reversible multiple time scale molecular dynamics”*, J. Chem. Phys. 97, 1990 (1992)

DOI: 10.1063/1.463137 — BibTeX: fetch

### Ring-Polymer Contraction

A ring-polymer contraction makes it possible to compute different components of the forces on different number of imaginary time slices. In order to reap maximum benefits, the implementation is fully compatible with the multiple time step integrators.

**Main contributors:** Michele Ceriotti, Venkat Kapil

**Implementation:**

V.Kapil, J.VandeVondele, M.Ceriotti *“Accurate molecular dynamics and nuclear quantum effects at low cost by multiple steps in real and imaginary time: using density functional theory to accelerate wavefunction methods”*, J. Chem. Phys. 144, 054111 (2016) DOI: 10.1063/1.4941091 — BibTeX: fetch

**Theory:**

T.Markland, D.E.Manolopoulos *“An efficient ring polymer contraction scheme for imaginary time path integral simulations”*, J. Chem. Phys. 129, 024105 (2008)

DOI: 10.1063/1.2953308 — BibTeX: fetch

### Direct Estimators for Isotope Fractionation

A direct estimator to evaluate the isotope fractionation ratios using a single operation (and a single keyword in the input file), without the need for a thermodynamic integration with respect to the mass of the isotope.

**Main contributors:** Bingqing Cheng, Michele Ceriotti

**Implementation and Theory:**

B.Cheng, M.Ceriotti, “Direct path integral estimators for isotope fractionation ratios.” The Journal of chemical physics 141, 244112 (2015) DOI: 10.1063/1.4904293 — BibTeX: fetch

### Free-energy Perturbation Estimators for Isotope Fractionation

### Quantum Alchemical Transformation

An algorithm that performs Monte Carlo moves to change a chemical species into its isotopes.

**Main contributors:** Bingqing Cheng, Michele Ceriotti

**Implementation:**

Cheng, Bingqing, J"{o}rg Behler, Michele Ceriotti, *“Nuclear Quantum Effects in Water at the Triple Point: Using Theory as a Link Between Experiments.”* J. Phys. Chem. Lett. 7(12), 2210-2215 (2016)

DOI: 10.1021/acs.jpclett.6b00729 — BibTeX: fetch

**Theory:**

Michael R. Shirts, David L. Mobley, John D. Chodera, *“Alchemical Free Energy Calculations: Ready for Prime Time?”*, Ann. Rep. Comp. Chem. 41-59 (2007)

DOI: 10.1016/S1574-1400(07)03004-6 — BibTeX: fetch

Jian Liu, Richard S Andino, Christina M Miller, Xin Chen, David M Wilkins, Michele Ceriotti, David E Manolopoulos, *“A surface-specific isotope effect in mixtures of light and heavy water”*, J. Phys. Chem. C 117(6), 2944-2951 (2013)

DOI: 10.1021/jp311986m — BibTeX: fetch

### Langevin Sampling for Noisy or Dissipative Forces

A modified Langevin thermostat that allows for constant-temperature dynamics with noisy or dissipative forces by applying additional damping or noise for compensation. The implementation contains a method to adjust the amount of compensation automatically.

**Main contributors:** Jan Kessler, Thomas D. Kühne

**Theory:**

T. D. Kühne, M. Krack, F. R. Mohamed, M. Parrinello, *“Efficient and Accurate Car-Parrinello-like Approach to Born-Oppenheimer Molecular Dynamics”*, Phys. Rev. Lett. 98, 066401 (2007)

DOI: 10.1103/PhysRevLett.98.066401 — BibTeX: fetch

F. R. Krajewski, M. Parrinello, *“Linear scaling electronic structure calculations and accurate statistical mechanics sampling with noisy forces”*, Phys. Rev. B 73, 041105 (2006)

DOI: 10.1103/PhysRevB.73.041105 — BibTeX: fetch

Y. Luo, A. Zen, S. Sorella, *“Ab initio molecular dynamics with noisy forces: Validating the quantum Monte Carlo approach with benchmark calculations of molecular vibrational properties “*, J. Chem. Phys. 141, 194112 (2014)

DOI: 10.1063/1.4901430 — BibTeX: fetch

### Path Integral GLEs

Generalized Langevin Equations can be combined with a PIMD framework to accelerate convergence of quantum observables while retaining systematic approach to the quantum limit. Parameters formatted for i-PI input can be obtained from the GLE4MD website.

**Main contributors:** Michele Ceriotti, Joshua More

**Implementation:**

M. Ceriotti, J. More, D. Manolopoulos, *“i-PI: A Python interface for ab initio path integral molecular dynamics simulations”*, Comp. Phys. Comm. 185(3), 1019 (2014)

DOI: 10.1016/j.cpc.2013.10.027 — BibTeX: fetch

**Theory:**

*PIGLET* — M. Ceriotti and D. E. Manolopoulos, *“Efficient First-Principles Calculation of the Quantum Kinetic Energy and Momentum Distribution of Nuclei”*, Phys. Rev. Lett. 109, 100604 (2012)

DOI: 10.1103/PhysRevLett.109.100604 — BibTeX: fetch

*PI+GLE* — M. Ceriotti, D. E. Manolopoulos, and M. Parrinello, *“Accelerating the Convergence of Path Integral Dynamics with a Generalized Langevin Equation”*, J. Chem. Phys. 134, 84104 (2011)

DOI: 10.1063/1.3556661 — BibTeX: fetch

### Generalized Langevin Equation Thermostats

The Generalized Langevin Equation provides a very flexible framework to manipulate the dynamics of a classical system, improving sampling efficiency and obtaining quasi-equilibrium ensembles that mimic quantum fluctuations. Parameters for the different modes of operation can be obtained from the GLE4MD website.

**Main contributors:** Michele Ceriotti

**Implementation:**

M. Ceriotti, G. Bussi, M. Parrinello, *“M. Colored-Noise Thermostats à la Carte”*, J. Chem. Theory Comput. 6, 1170–1180 (2010)

DOI: 10.1021/ct900563s — BibTeX: fetch

**Theory:**

*Optimal Sampling Efficiency* — M. Ceriotti, G. Bussi, and M. Parrinello, *“Langevin Equation with Colored Noise for Constant-Temperature Molecular Dynamics Simulations”*, Phys. Rev. Lett. 102, 20601 (2009)

DOI: 10.1103/PhysRevLett.102.020601 — BibTeX: fetch

*Quantum Thermostat* — M. Ceriotti, G. Bussi, and M. Parrinello, *“Nuclear Quantum Effects in Solids Using a Colored-Noise Thermostat”*, Phys. Rev. Lett. 103, 30603 (2009)

DOI: 10.1103/PhysRevLett.103.030603 — BibTeX: fetch

*Delta Thermostat* — M. Ceriotti and M. Parrinello, *“The δ-Thermostat: Selective Normal-Modes Excitation by Colored-Noise Langevin Dynamics”*, Procedia Comput. Sci. 1, 1607 (2010)

DOI: 10.1016/j.procs.2010.04.180 — BibTeX: fetch

*MTS Thermostat* — J. A. Morrone, T. E. Markland, M. Ceriotti, and B. J. Berne, *“Efficient Multiple Time Scale Molecular Dynamics: Using Colored Noise Thermostats to Stabilize Resonances”*, J. Chem. Phys. 134, 14103 (2011)

DOI: 10.1063/1.3518369 — BibTeX: fetch

*“Hot-spot”* — R. Dettori, M. Ceriotti, J. Hunger, C. Melis, L. Colombo, and D. Donadio, *“Simulating Energy Relaxation in Pump-Probe Vibrational Spectroscopy of Hydrogen-Bonded Liquids”*, J. Chem. Theory Comput. (2017)

DOI: 10.1021/acs.jctc.6b01108 — BibTeX: fetch

### Path-Integral Langevin Equation Thermostats

Simple yet efficient Langevin thermostat for PIMD, with normal-modes thermostats optimally coupled to the ideal ring polymer frequencies

**Main contributors:** Michele Ceriotti

**Implementation and Theory:**

M. Ceriotti, M. Parrinello, T. E. Markland, and D. E. Manolopoulos, *“Efficient stochastic thermostatting of path integral molecular dynamics”* J. Chem. Phys. 133, 124104 (2010).

DOI: 10.1063/1.3489925 — BibTeX: fetch

### Path Integrals at Constant Pressure

The constant-pressure implementation allows for arbitrary thermostats to be applied to the cell degrees of freedom, and work in both constant-shape and variable-cell mode.

**Main contributors:** Michele Ceriotti, Joshua More, Mariana Rossi

**Implementation:**

M. Ceriotti, J. More, D. Manolopoulos, *“i-PI: A Python interface for ab initio path integral molecular dynamics simulations”*, Comp. Phys. Comm. 185(3), 1019 (2014)

DOI: 10.1016/j.cpc.2013.10.027 — BibTeX: fetch

**Theory:**

G. J. Martyna, A. Hughes, M. Tuckerman, *“Molecular dynamics algorithms for path integrals at constant pressure”*, J. Chem. Phys. 110(7), 3275 (1999)

DOI: 10.1063/1.478193 — BibTeX: fetch

G. Bussi, T. Zykova-Timan, M. Parrinello, *“Isothermal-isobaric molecular dynamics using stochastic velocity rescaling”*, J. Chem. Phys. 130(7), 074101 (2009)

DOI: 10.1063/1.3073889 — BibTeX: fetch

P. Raiteri, J. D. Gale, G. Bussi, *“Reactive force field simulation of proton diffusion in BaZrO _{3} using an empirical valence bond approach”*, J. Phys. Cond. Matt. 23(33), 334213 (2011)

DOI: 10.1088/0953-8984/23/33/334213 — BibTeX: fetch

### Path Integral Molecular Dynamics

The basic PIMD implementation in i-PI relies on a normal-modes integrator, and allows setting non-physical masses, so that both RPMD and CMD can be easily realized.

**Main contributors:** Michele Ceriotti, Joshua More

**Implementation:**

M. Ceriotti, J. More, D. Manolopoulos, *“i-PI: A Python interface for ab initio path integral molecular dynamics simulations”*, Comp. Phys. Comm. 185(3), 1019 (2014) DOI: 10.1016/j.cpc.2013.10.027 — BibTeX: fetch

**Theory:**

R. Feynman, A. Hibbs, *“Quantum Mechanics and Path Integrals”*, McGraw-Hill (1964)

M. Tuckerman, *“Statistical Mechanics and Molecular Simulations”*, Oxford Univ. Press (2008)