Organized by GPT-6-Astra. SPONGE 2.0 is under active, iterative development; features, parameters, and documentation may change. Consult the GitHub repository’s docs and skills for the latest version information.

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Enhanced Sampling Parameters

Collective Variables (CV)

Parameter	Type	Description
cv_in_file	string	Collective variable definition file path

CV definitions are loaded from the file pointed to by cv_in_file. New CV files should use TOML; the legacy block format remains supported for compatibility. See Collective Variables Guide for the supported CV types, virtual atoms, printing, and complete examples.

Bundled sponge.input.v2 protocols store CV virtual atoms as typed HDF5 objects below /cv/virtual_atom/<name>. Each object contains type, atom_indices, enabled_default, and, for a center, weight. A regular CV can use /cv/<name>/atom_refs to mix physical atom indices and virtual-atom names without embedding a large legacy configuration string.

Metadynamics

Configured via [META] or [meta] section:

Parameter	Type	Description
sink	string	Sink metadynamics mode

Detailed SinkMeta parameter list: sinkmeta.md

SITS

SITS parameters live under the [SITS] scope:

[SITS]
mode = "iteration"
atom_numbers = "ALL"
k_numbers = 40
T_low = 300.0
T_high = 600.0
record_interval = 1
update_interval = 100

Common Parameters

Parameter	Scope	Type	Default	Description
mode	SITS	string	required	SITS run mode
atom_in_file	SITS	string	-	File-based atom partition definition for selective enhancement
atom_numbers	SITS	int or string	required if atom_in_file is absent	Number of leading atoms in the selectively enhanced set, or "ALL" / "ITS"
cross_enhance_factor	SITS	float	0.5	Enhancement factor for the cross term
fb_interval	SITS	int	1	Feedback-bias update interval

Exactly one atom-selection method is required: atom_in_file or atom_numbers.

Iteration / Production Parameters

Parameter	Scope	Type	Default	Description
k_numbers	SITS	int	40	Number of temperature points
T_low	SITS	float	-	Lower temperature bound for generated ladder
T_high	SITS	float	-	Upper temperature bound for generated ladder
T	SITS	slash-separated string	-	Explicit temperature ladder used instead of T_low / T_high
record_interval	SITS	int	1	Energy record interval
update_interval	SITS	int	100	Parameter update interval
pe_a	SITS	float	1.0	Multiplicative energy scaling factor
pe_b	SITS	float	0.0	Additive energy offset
fb_bias	SITS	float	0.0	Additional bias applied to fb
nk_rest	SITS	bool	false in iteration, true otherwise	Whether to read restart Nk values
nk_in_file	SITS	string	required when nk_rest = true or in production mode	Input file for restarting Nk
nk_fix	SITS	bool	false in iteration, true otherwise	Freeze Nk during the run
nk_rest_file	SITS	string	auto-generated	Output file for restart Nk values when nk_fix = false
nk_traj_file	SITS	string	auto-generated	Output file for Nk history when nk_fix = false

mode options:

Value	Description
"observation"	Observation phase
"iteration"	Iteration phase
"production"	Production phase
"empirical"	Empirical mode
"amd"	AMD mode
"gamd"	GaMD mode

Empirical / AMD / GaMD Parameters

Parameter	Scope	Type	Default	Description
pe_a	SITS	float	required in amd / gamd, 1.0 in empirical	Bias strength parameter
pe_b	SITS	float	required in amd / gamd, 0.0 in empirical	Bias threshold parameter
T_low	SITS	float	required in empirical	Lower temperature bound
T_high	SITS	float	required in empirical	Upper temperature bound

Notes:

• amd, gamd, and empirical do not use the full k_numbers / Nk update workflow.
• The current source reads T as a slash-separated string rather than a TOML numeric array.