The following important parameters (with these default values) were added:

relaxing/SDP/freq = 1	set this to -1 and lp/solvefreq to 1 to solve LP relaxations with eigenvector cuts
constraints/SDP/threads = 1	number of threads used for openblas; only available with OpenBLAS/OpenMP and compile option OMP=TRUE (default for SDPS=sdpa)
relaxing/SDP/sdpsolverthreads = -1	number of threads the SDP solver should use (-1 = number of cores); currently only supported for MOSEK
relaxing/SDP/displaystatistics = TRUE	Should statistics about SDP iterations and solver settings/success be printed after quitting SCIP-SDP ?
relaxing/SDP/slatercheck = 0	Should the Slater condition for the primal and dual problem be checked ahead of solving each SDP? [0: no, 1: yes and output statistics, 2: yes and print warning for every problem not satisfying primal and dual Slater condition]
relaxing/SDP/sdpinfo = FALSE	Should output of the SDP-Solver be printed to the console?
relaxing/SDP/sdpsolvergaptol = 1e-04	sets the tolerance for the duality gap in the SDP-Solver
relaxing/SDP/sdpsolverfeastol = 1e-06 (DSDP,SDPA) / 1e-07 (MOSEK)	feasibility tolerance for the SDP-Solver (should be less or equal to numerics/feastol)
relaxing/SDP/penaltyparam = -1	the starting value of the penalty parameter Gamma used for the penalty formulation if the SDP solver didn't converge; set this to a negative value to compute the parameter depending on the given problem
relaxing/SDP/lambdastar = -1	the parameter lambda star used by SDPA to set the initial point; set this to a negative value to compute the parameter depending on the given problem
branching/sdpinfobjective/priority = 2e+06	priority of combined infeasibility/objective branching rule; branching rule with highest priority is used
branching/sdpinfobjective/coupledvars = FALSE	If all branching candidates have objective zero, should we use the sum of the absolute objectives of all continuous variables coupled with the candidate through constraints?
branching/sdpinfobjective/singlecoupledvars = FALSE	If all branching candidates have objective zero, should we use the sum of the absolute objectives of all continuous variables coupled with the candidate through constraints in which no other candidate appears?
branching/sdpmostfrac/priority = 5e+05	priority of most fractional (largest fractional part) branching rule; branching rule with highest priority is used
branching/sdpmostinf/priority = 1e+06	priority of most infeasible (fractional part nearest to 0.5) branching rule; branching rule with highest priority is used
branching/sdpobjective/priority = 1.5e+06	priority of highest absolute objective branching rule; branching rule with highest priority is used
branching/sdpobjective/coupledvars = FALSE	If all branching candidates have objective zero, should we use the sum of the absolute objectives of all continuous variables coupled with the candidate through constraints?
branching/sdpobjective/singlecoupledvars = FALSE	If all branching candidates have objective zero, should we use the sum of the absolute objectives of all continuous variables coupled with the candidate through constraints in which no other candidate appears?
constraints/SDP/diaggezerocuts = TRUE	Should linear cuts enforcing the non-negativity of diagonal entries of SDP-matrices be added?
constraints/SDP/diagzeroimplcuts = TRUE	Should linear cuts enforcing the implications of diagonal entries of zero in SDP-matrices be added?
display/sdpfastsettings/active = 0	Should the percentage of SDP-relaxations solved with the fastest setting (SDPA) or the default formulation (DSDP) be displayed in the console? [0: off, 1: auto, 2:on]
display/sdppenalty/active = 0	Should the percentage of SDP-relaxations solved using a penalty formulation be displayed in the console? [0: off, 1: auto, 2:on]
display/sdpunsolved/active = 1	Should the percentage of SDP-relaxations that could not be solved be displayed in the console? [0: off, 1: auto, 2:on]
heuristics/sdpfracdiving/freq = -1	set this to 0 or more to enable a fractional diving heuristic for SDPs
heuristics/sdprand/freq = 1	set this to -1 to disable the randomized rounding heuristic
heuristics/sdprand/generalints = FALSE	Should randomized rounding also be applied if there are general integer variables and not only binary variables ?
heuristics/sdprand/nrounds = 2	number of rounding rounds
propagating/sdp-obbt/freq = -1	set this to 0 or more to enable optimization-based bound tightening using SDP-relaxations
propagating/sdp-obbt/propcont = TRUE	Should optimization-based bound tightening be performed for continuous variables ?
propagating/sdp-obbt/propbin = FALSE	Should optimization-based bound tightening be performed for binary variables ?
propagating/sdpredcost/freq = 1	set this to -1 to disable reduced cost fixing for SDPs
propagating/sdpredcost/forbins = TRUE	Should SDP reduced cost fixing be executed for binary variables?
propagating/sdpredcost/forintcons = TRUE	Should SDP reduced cost fixing be executed for integer and continuous variables?
relaxing/SDP/maxpenaltyparam = -1	the maximum value of the penalty parameter Gamma used for the penalty formulation if the SDP solver didn't converge; set this to a negative value to compute the parameter depending on the given problem
relaxing/SDP/npenaltyincr = -1	maximum number of times the penalty parameter will be increased if the penalty formulation failed
relaxing/SDP/objlimit = FALSE	Should an objective limit be given to the SDP-Solver?
relaxing/SDP/resolve = TRUE	Should the relaxation be resolved after bound-tightenings were found during propagation (outside of probing)?
relaxing/SDP/settingsresetfreq = -1	frequency for resetting parameters in SDP solver and trying again with fastest settings [-1: never, 0: only at depth settingsresetofs, n: all nodes with depth a multiple of n]; currently only supported for SDPA
relaxing/SDP/settingsresetofs = 0	frequency offset for resetting parameters in SDP solver and trying again with fastest settings; currently only supported for SDPA
relaxing/SDP/tightenvb = TRUE	Should Big-Ms in varbound-like constraints be tightened before giving them to the SDP-solver ?